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PAST PAPERS: RESEARCH METHODS: AQA A-LEVEL PSYCHOLOGY RESOURCES

Psychology aqa  a-level (7182)  unit 2: 7182/2.

Full model answers for all of these questions are  available here

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THE SYLLABUS

METHODS, TECHNIQUES & DESIGN

  • Primary and secondary data, and meta-analysis. Quantitative and qualitative data
  • Aims, operationalising variables, IV’s and DV’s
  • Hypotheses - directional and non-directional
  • Experimental design - independent groups, repeated measures, matched pairs
  • Validity – internal and external; extraneous and confounding variables; types of validity and improving validity
  • Control – random allocation, randomisation, standardisation
  • Demand characteristics and investigator effects
  • Reliability; types of reliability and improving reliability
  • Pilot studies
  • Correlation analysis – covariables and hypotheses, positive/negative correlations
  • Observational techniques – use of behavioural categories
  • Self-report techniques – design of questionnaires and interviews
  • Case studies
  • Content analysis & thematic analysis

PARTICIPANTS; ETHICS; FEATURES OF SCIENCE & SCIENTIFIC METHOD; THE ECONOMY

  • Selecting participants and sampling techniques
  • The British Psychological Society (BPS) code of ethics and ways of dealing with ethical issues
  • Forms and instructions
  • Peer review
  • Features of science: objectivity, empirical method, replicability and falsifiability, paradigms and paradigm shifts
  • Reporting psychological investigations
  • The implications of psychological research for the economy

DESCRIPTIVE STATISTICS

  • Analysis and interpretation of quantitative data. Measures of central tendency - median, mean, mode. Calculating %’s. Measures of dispersion – range and standard deviation (SD)
  • Presentation and interpretation of quantitative data – graphs, histograms, bar charts, scattergrams and tables
  • Analysis and interpretation of correlational data; positive and negative correlations and the interpretation of correlation coefficients
  • Distributions: normal and skewed

INFERENTIAL STATISTICS

  • Introduction
  • Factors affecting choice of statistics test: Spearman’s rho, Pearson’s r, Wilcoxon, Mann-Whitney, related t-test, unrelated t-test, Chi-Squared test
  • Levels of measurement – nominal, ordinal, interval
  • Procedures for statistics tests
  • Probability and significance: use of statistical tables and critical values in interpretation of significance; Type I and Type II errors
  • Introduction to statistical testing: the sign test

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SPECIMEN PAPER 1 ( Psychology A-level revision)

Read the item and then answer the questions that follow.

A psychologist wanted to see if verbal fluency is affected by whether people think they are presenting information to a small group of people or to a large group of people.

The psychologist needed a stratified sample of 20 people. She obtained the sample from a company employing 60 men and 40 women.

The participants were told that they would be placed in a booth where they would read out an article about the life of a famous author to an audience. Participants were also told that the audience would not be present, but would only be able to hear them and would not be able to interact with them.

There were two conditions in the study, Condition A and Condition B.

Condition A: 10 participants were told the audience consisted of 5 listeners.

Condition B: the other 10 participants were told the audience consisted of 100 listeners.

Each participant completed the study individually. The psychologist recorded each presentation and then counted the number of verbal errors made by each participant.

(a) Identify the dependent variable in this study. (2 marks)

(b) Write a suitable hypothesis for this study. (3 marks)

(c)  Identify one extraneous variable that the psychologist should have controlled in the study and explain why it should have been controlled. (3 marks)

(d) Explain one advantage of using a stratified sample of participants in this study. (2 marks)

(e) Explain how the psychologist would have obtained the male participants for her stratified sample. Show your calculations. (3 marks)

(f) The psychologist wanted to randomly allocate the 20 people in her stratified sample to the two conditions. She needed an equal number of males in each condition and an equal number of females in each condition. Explain how she would have done this. (4 marks)

Mean number of verbal errors and standard deviations for both conditions

AQA PSYCHOLOGY A LEVEL RESEARCH METHODS 14

(g)  What conclusions might the psychologist draw from the data in the table? Refer to the means and standard deviations in your answer. (6 marks)

(h) Read the item and then answer the question that follows.

The psychologist had initially intended to use the range as a measure of dispersion in this study but found that one person in Condition A had made an exceptionally low number of verbal errors.

Explain how using the standard deviation rather than the range in this situation, would improve the study. [3 marks]

(i) Name an appropriate statistical test that could be used to analyse the number of verbal errors in Table 1. Explain why the test you have chosen would be a suitable test in this case. [4 marks]

(j) The psychologist found the results were significant at p<0.05. What is meant by ‘the results were significant at p<0.05’? [2 marks]

(k) Briefly explain one method the psychologist could use to check the validity of the data she collected in this study. [2 marks]

(l)  Briefly explain one reason why it is important for research to undergo a peer review process. [2 marks]

(m) Read the item and then answer the question that follows.

The psychologist focused on fluency in spoken communication in her study. Other research has investigated sex differences in non-verbal behaviours such as body language and gestures

Design an observation study to investigate sex differences in non-verbal behaviour of males and females when they are giving a presentation to an audience.

In your answer you should provide details of:

  • The task for the participants
  • The behavioural categories to be used and how the data will be recorded
  • How reliability of the data collection might be established
  • Ethical issues to be considered.

(Total 12 marks)

SPECIMEN PAPER 2 ( A-level Psychology revision)

Researchers were interested in the spatial awareness skills of motorists. They decided to investigate a possible relationship between different aspects of spatial awareness. Motorists who had between ten and twelve years of driving experience and held a clean driving licence with no penalty points were asked to complete two sets of tasks.

Set 1: To follow a series of instructions and using a map, to identify various locations correctly. This provided a map reading score for each motorist with a maximum score of 20.

Set 2: To complete a series of practical driving tasks accurately. This involved tasks such as driving between cones, driving within lines and parking inside designated spaces. Each motorist was observed completing the Set 2 tasks by a single trained observer who rated each performance by giving the driver a rating out of 10.

The following results were obtained.

Table 1: The map reading scores and driver ratings of motorists

AQA PSYCHOLOGY A LEVEL RESEARCH METHODS

(a) Should the hypothesis be directional? Explain your answer. (2 marks)

(b) Write a suitable hypothesis for this investigation. (3 marks)

(c) Identify a suitable graphical display for the data in Table 1 and briefly explain why this display would be appropriate. (2 marks)

(d) Using the data in Table 1, comment on the relationship between the map reading scores and the driver rating scores of the participants. [3 marks]

AQA PSYCHOLOGY A LEVEL RESEARCH METHODS 1

(e) Briefly outline one problem of using a single trained observer to rate the participants’ driving skills in the practical task. Briefly discuss how this data collection method could be modified to improve the reliability of the data collected. (6 marks)

(f) The researchers decided to analyse the data using a Spearman’s rho test. Explain why this is a suitable choice of test for this investigation. (3 marks)

(g) After analysis of the data the researchers obtained a calculated value of r s = 0.808. Using the information in Table 2 above, what conclusion can the researchers draw about the relationship between the map reading and driving skills of the motorists? Explain your answer. [4 marks]

(h) Distinguish between a Type I error and a Type II error. (4 marks)

When the researchers looked at the data collected more closely they noticed possible gender differences in the results.

AQA PSYCHOLOGY A LEVEL RESEARCH METHODS 2

(i) What do the mean and standard deviation values suggest about the male and female performances in the investigation? (4 marks)

In a replication of the part of the study in which map reading skills were investigated, 20 men and 20 women completed the original map reading task and the researchers obtained the following data:

AQA PSYCHOLOGY A LEVEL RESEARCH METHODS 3

(j) The mean map reading score for both groups together was 12.23. What percentage of the male group scored above the mean score and what percentage of the female group scored above the mean score? Show your calculations. (4 marks)

(k) Using your answers to both 2 previous questions, comment on the performances of the male and the female participants in this study. (2 marks)

(l) Briefly explain one reason why it is important for research to be replicated. (2 marks)

(m) Imagine you have been asked to design a study to investigate possible gender differences in card sorting behaviours. You decide you will ask participants to sort a shuffled pack of playing cards into their suits of hearts, clubs, diamonds and spades. You decide you will time the participants as they do this using a stop watch.

Discuss the following aspects of this investigation:

  • with reference to the card sorting task, explain how you would ensure that this is made the same task for all participants
  • one methodological issue you should take into account when obtaining suitable participants for this study and explain how you would deal with this issue
  • how you would ensure that the experience of your participants is ethical.

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SPECIMEN PAPER 3 ( AQA A-level Psychology revision)

Following previous research indicating the social benefits of green space in urban areas, two psychology students decided to observe social behaviour in public spaces. They focused on two neighbouring towns, Greensville where most public spaces were planted with flowers and vegetables, and Brownton where most public spaces were paved with concrete.

The students compared the instances of considerate behaviours in the two towns.

Considerate behaviour categories included putting litter in the bin, having a dog on a lead and riding a bike with care.

The observations were carried out in four different areas of a similar size in each town on weekdays between the hours of 4.30pm and 6.00pm. The students worked together to ensure inter-observer reliability, recording each target behaviour whenever it occurred.

(a) Should the hypothesis for this research be directional or non-directional? Explain your answer. (2 marks)

(b) Before the observation could begin, the students needed to operationalise the behaviour category ‘riding a bike with care’.

Explain what is meant by operationalisation and suggest two ways in which ‘riding a bike with care’ could have been operationalised. (4 marks)

(c) The students thought that having a dog on a lead was a useful measure of considerate behaviour because it had face validity. Explain what is meant by face validity in this context. (3 marks)

(d) Identify and briefly outline two other types of validity in psychological research. (4 mark

(e) Identify the behaviour sampling method used by the students. Shade one box only.

  • Time sampling
  • Pair sampling
  • Event sampling
  • Target sampling

(f) Explain how inter-observer reliability could be ensured by working as a pair. (3 marks)

AQA PSYCHOLOGY A LEVEL RESEARCH METHODS 4

The students noted that overall more considerate behaviours occurred in Greensville than in Brownton.

(g) Calculate the ratio of considerate behaviours observed in Greensville to considerate behaviours observed in Brownton. Show your workings and present your answer in the simplest form. (3 marks)

(h) The students carried out a Chi-square test on their data.  Explain why the Chi-square test was an appropriate test to use in this case. (3 marks)

(i) In order to interpret the results of the Chi-square test the students first needed to work out the degrees of freedom. They used the following formula.

Degrees of freedom (df) = (r–1) x (c–1)

r = number of rows and c = number of columns

Calculate the degrees of freedom for the data in Table 1. Show your workings.

(j) The calculated value of Chi-square was 6.20. Referring to Table 2 below, state whether or not the result of the Chi-square test is significant at the 0.05 level of significance. Justify your answer. (3 marks)

To be significant at the level shown the calculated value of Chi Square must be equal to or greater than the critical/table value

(k) In the discussion section of their report of the investigation the students wanted to further discuss their results in relation to levels of significance.

Write a short paragraph the students could use to do this. (4 marks)

(l) As a follow-up to their observation the students decided to interview some of their peers about inconsiderate behaviours in their 6th Form Centre. The interviews were recorded.

Explain how the students could develop their interview findings by carrying out a content analysis and why content analysis would be appropriate in this case. (3 marks

(m) Suggest one inconsiderate behaviour that the students might focus on in their content analysis. (1 mark)

(n) Design an experiment to investigate the effect of indoor plants on mood in office workers. For your measure of mood, you should devise a measure that would give data suitable for testing at the ordinal level of measurement.

  • Design – include reference to the experimental design, variables and controls
  • Materials/Apparatus – describe any special materials required
  • Data analysis that could be used – include reference to descriptive and inferential analysis.

Justify your choices. (12 marks)

2017 ( AQA A-level Psychology revision guide)

A psychologist wanted to test whether listening to music improves running performance.

The psychologist conducted a study using 10 volunteers from a local gym. The psychologist used a repeated measures design. Half of the participants were assigned to condition A (without music) and half to condition B (with music).

All participants were asked to run 400 metres as fast as they could on a treadmill in the psychology department. All participants were given standardised instruction. All participants wore headphones in both conditions. The psychologist recorded their running time in seconds. The participants returned to the psychology department the following week and repeated the test in the other condition.

(a) Identify the type of experiment used in this study.

(b) Identify the operationalised dependent variable in the study. (2 marks)

The results of the study are given in Table 1 below.

Table 1. Mean number of second taken to complete the 400m run and the standard deviation for both conditions.

(c) Explain why a histogram would not be an appropriate way of displaying the means shown in Table 1. (2 marks)

(d) Name a more appropriate graph to display the means shown in Table 1. Suggest appropriate X (Horizontal) and Y (vertical) axis labels for your graph choice. (3 marks)

Name of graph

X axis label

Y axis label

(e) What do the mean and standard deviation values in Table 1 suggest about the participants’ performances with and without music? Justify your answer. (4 marks)

(f) Calculate the percentage decrease in the mean time it took participants to run 400 metres when listening to music. Show your workings. Give your answer to three significant figures. (4 marks)

The researcher used a directional hypothesis and analysed the data using a related t-test. The calculated value of t where degrees of freedom (df) = 9 was 1.4377. He decided to use the 5% level of significance.

Table 2. Table of critical values of t

Calculated value of t must be equal to or greater than the critical value in this table for significance to be shown.

(g) Give three reasons why the researcher used a related t-test in this study and, using Table 2, explain whether or not the results are significant (5 marks)

(h) What is meant by a Type II error? Explain why psychologists normally use the 5% level of significance in their research. (3 marks)

(i) Identify one extraneous variable that could have affected the results of this study. Suggest why it would have been important to control this extraneous variable and how it could have been controlled in this study. (3 marks)

(j) The report was submitted for peer review and a number of recommendations were advised.

Describe the process and purposes of peer review. (6 marks)

People’s perception of how they spent their time at the gym is often not very accurate. Some spent more time chatting than on the treadmill. A psychologist decides to observe the actual behaviour of an opportunity sample of gym users at a local gym.

(k) Explain why it is more appropriate for the psychologist to use an observation than a questionnaire in this case. (3 marks)

(l) Design an observational study to investigate how people spent their time at the gym.

In your answer you will be awarded credit for providing appropriate details of

  • Type of observation with justification
  • Operationalised behaviour categories
  • Use of time and/or event sampling with justification
  • How reliability of data collection could be assessed.

2018 ( A-level Psychology resources)

A psychologist was reading an article about typical dream themes in adults.

Figure 2 shows the main dream themes identified in the article.

Figure 2 Main dream themes

AQA PSYCHOLOGY A LEVEL RESEARCH METHODS 5

(a) Using Figure 2, estimate the percentage of dreams that were reported to be about being chased. Shade one box only. [1 mark]

A           4%

B           12%

C           27%

D           42%

The psychologist was interested in finding out whether dream themes differed between box males and females, particularly in terms of social interaction. She decided to conduct a pilot study. Twenty undergraduate students (8 male and 12 female) volunteered for the study. For a six-week period the students were interviewed at 9 am each morning when they arrived at university. Interviewers, who did not know the purpose of the study, carried out and recorded the dream interviews.

(a) What is meant by a pilot study? Explain one possible reason why the psychologist decided to conduct a pilot study for this investigation. [3 marks]

(b) The interviews produced qualitative data. What is meant by qualitative data? Give one strength of collecting qualitative data in this study. [2 marks]

(c) What are investigator effects? Suggest one way in which they could have been minimised during the dream interviews. [3 marks]

Another researcher, who did not know the purpose of the study, carried out a content analysis of the interview data.

(d) Explain how this content analysis could have been conducted. [4 marks]

The psychologist wanted to assess the reliability of the content analysis.

(e) Explain how the reliability of the content analysis could be assessed. [4 marks]

When comparing the data for males and females, the psychologist found that there was a difference in the proportion of friendly and aggressive social interactions. This is shown in Table 2.

Table 2: Percentage of friendly and aggressive social interactions in dreams reported by males and females

A total of 375 dreams reported by males included social interaction.

(f) Use the data in Table 2 to calculate how many of these dreams reported by males were classified as aggressive. Show your workings. [2 marks]

(g) Draw a suitable graphical display to represent the data in Table 2 box. Label your graph appropriately. [4 marks]

The psychologist decided to conduct an experiment to investigate the effect of watching box horror films before going to bed.

A volunteer sample of 50 university students consented to take part in the experiment.

The 50 students were randomly split into two groups. Group 1 watched a horror film before going to bed each night for the first week then a romantic comedy before going to bed each night for the second week. Group 2 watched the romantic comedy in the first week and the horror film in the second week.

When the students woke up each morning, each student received a text message that asked if they had had a nightmare during the night. They could respond ‘yes’ or ‘no’.

(h) Write a brief consent form that would have been suitable for use in this experiment. The consent form should:

  • include some detail of what participants might expect to happen
  • refer to ethical issues
  • be in an appropriate format/style

(i) The psychologist proposed a directional hypothesis.

Write a directional hypothesis for this experiment. [3 marks]

The psychologist used a repeated measures design in this experiment.

(j) Explain why it was important to use a repeated measures design in this case.  [2 marks]

The psychologist used counterbalancing in this experiment.

(k) Explain why it was appropriate to use counterbalancing in this experiment. [2 marks]

(l) Explain how the box psychologist could have randomly split the sample of 50 students into the two groups. [3 marks]

The psychologist collated the responses of all the participants over the two-week period and calculated the mean and standard deviation for each condition.

Table 3: Mean number of nightmares reported and the standard deviation for each condition

(m) What do the mean and standard deviation values in Table 3 suggest about the effect of the type of film watched on the occurrence of nightmares? Justify your answer. [4 marks]

The psychologist found that the difference in the number of nightmares reported in the two conditions was significant at p<0.05.

(n) Explain what is meant by ‘significant at p<0.05’ in the context of this experiment. [2 marks]

(o) The psychologist was concerned about the validity of the experiment.

Suggest one possible modification to the design of the experiment and explain how this might improve validity. [3 marks]

2019 ( AQA A-level Psychology resources)

(a) Which of the following does reliability refer to?

Shade one circle only. [1 mark]

A           The accuracy of the data

B           The consistency of the data

C           The levels of the data

D           The validity of the data

(b) Which of the following is not a role of peer review in the scientific process?

A           To determine whether to award research funding

B           To ensure only significant results are published

C           To make sure research has high validity and reliability

D           To retain the integrity of psychological research

(c) Give one reason why it is important for scientific reports to include a referencing section? [1 mark]

It was recently reported in a newspaper that time spent playing team sports increases happiness levels. A researcher was keen to find out whether this was due to participating in a team activity or due to participating in physical activity, as he could not find any published research on this.

The researcher used a matched-pairs design. He went into the student café and selected the first 20 students he met. Each student was assigned to one of two groups.

Participants in Group A were requested to carry out 3 hours of team sports per week. Participants in Group B were requested to carry out 3 hours of exercise independently in a gym each week. All participants were told not to take part in any other type of exercise for the 4-week duration of the study.

All participants completed a happiness questionnaire at the start and end of the study. The researcher then calculated the improvement in happiness score for each participant.

(d) Which of the following is correct?

A           Groups A and B are conditions of the dependent variable and happiness is the independent variable.

B           Groups A and B are conditions of the independent variable and happiness is the dependent variable.

C           Groups A and B are the controls and happiness is the experimental condition.

D           Groups A and B are the experimental conditions and happiness is the control.

(e) Would a directional or non-directional hypothesis be more suitable for the researcher to use? Explain your answer. 2 marks]

(f) Write a suitable hypothesis for this experiment. [3 marks]

(g) Identify the type of sampling method used in this experiment. Explain one limitation of using this sampling method in this study. [3 marks]

(h) Identify one variable on which participants should be matched in this matched-pairs design. Explain how the researcher could assign matched participants to either Group A or Group B. [4 marks]

(i) Explain one strength of using a matched-pairs design rather than a repeated-measures design. [2 marks]

The results of the study are given in Table 2 below.

               Table 2 Improvement in happiness scores

AQA PSYCHOLOGY A LEVEL RESEARCH METHODS 6

The researcher decided to use the Sign Test to see whether there was a significant difference in the improvement in the scores between the two groups at the 5% level of significance.

(j) Calculate the value of S in this study. Show your workings. [2 marks]

AQA PSYCHOLOGY A LEVEL RESEARCH METHODS 7

Significance is shown if the calculated value of S is equal to or less than the critical value.

(k) Explain whether or not there was a significant difference in the improvement in the scores between the two groups. Use your answer to Question 22 and Table 3. [2 marks]

The validity of the data was questioned when the researcher presented his results. The researcher explained that he chose to use the happiness questionnaire because it had high concurrent validity.

(l) Explain what it means for a test to have high concurrent validity. [2 marks]

The questionnaire had high concurrent validity.

Validity was still a concern because the researcher knew which participants were in each experimental group.

(m) Explain how this could have affected the validity of the study. [4 marks]

(n) Using your answer to Question m, suggest one way in which the researcher could modify the study to improve the internal validity of the study? Justify your answer. [4 marks]

A psychology teacher read the researcher’s study on sport and happiness. She considered whether setting group tasks could improve her students’ level of happiness. She decided to conduct an independent groups experiment with 30 students taking A-level Psychology using the same happiness questionnaire.

(o) Suggest an appropriate statistical test the psychology teacher could use to analyse the data. Justify your choice of test. [4 marks]

(p) Design an independent groups experiment that the psychology teacher could conduct.

  • the aim of the experiment
  • identification and manipulation of variables including details of the task
  • controls to minimise the effects of extraneous variables
  • data handling and analysis – use of descriptive statistics and/or data presentation.

Justify your design choices. [12 marks]

2020 ( A-level Psychology notes)

A study into the relationship between recreational screen time and academic achievement was conducted. Students were asked to self-report the number of hours spent watching TV, playing on their mobile phones or video games (daily recreational screen time) and their end-of-year test performances (academic performance).

The results of the study are shown in Figure 2.

AQA PSYCHOLOGY A LEVEL RESEARCH METHODS 8

(a) In which section(s) of a scientific report would you expect to find reference to the results/findings of the investigation?

A           The abstract and the results sections only

B           The abstract, the discussion and the results sections only

C           The results and the discussion sections only

D           The results section only

(b) Which of the following correlation co-efficients best describes the data represented in Figure 2?

A           –0.80

B           –0.25

C           +0.25

D           +0.80

(c) Identify the type of graph shown in Figure 2 and explain why this is an appropriate graph to use for the data collected. [3 marks]

(d) Explain why it would not be appropriate for the researchers to conclude that increased recreational screen time reduces academic performance. [2 marks]

A psychologist reads a review of a meta-analysis confirming the relationship between recreational screen time and academic performance.

(e) What is meant by the term meta-analysis? [2 marks]

The psychologist decided to design an experiment to test the effects of recreational screen time on children’s academic performance.

The psychologist randomly selected four schools from all the primary schools in her county to take part in the experiment involving Year 5 pupils. Three of the four schools agreed to take part. In total, there were 58 pupils whose parents consented for them to participate. The 58 pupils were then randomly allocated to Group A or Group B.

For the two-week period of the experiment, pupils in Group A had no recreational screen time. Pupils in Group B were allowed unrestricted recreational screen time. At the end of the experiment all pupils completed a 45-minute class test, to achieve a test score.

(f) Complete Table 1 by ticking the statement that best describes the population and the sample in the psychologist’s experiment.

Place one tick in each column. [2 marks]

AQA PSYCHOLOGY A LEVEL RESEARCH METHODS 9

(g) Briefly explain why a directional hypothesis would be most suitable for this experiment. [1 mark]

(h) Write an appropriate hypothesis for this experiment. [3 marks]

The results obtained from the experiment are summarised in Table 2.

Table 2  Descriptive statistics for the test performance scores for Group A and Group B

AQA PSYCHOLOGY A LEVEL RESEARCH METHODS 10

(i) Using the data in Table 2, explain how the distribution of scores in Group A differs from the distribution of scores in Group B. [4 marks]

(j) What do the mean and standard deviation values in Table 2 suggest about the effect of the recreational screen time on test performance? Justify your answer. [4 marks]

(k) The psychologist wanted to test the statistical significance of the data.

Identify the most appropriate choice of statistical test for analysing the data collected and explain three reasons for your choice in the context of this study. [7 marks]

One criticism of the study is that the pupils were not matched on their typical recreational screen time.

(l) Explain how the psychologist could have matched pupils on their typical recreational screen time across the experimental conditions. [4 marks]

(m) Identify one other variable for which the psychologist could have matched the pupils. Explain how this might have affected the test performance if it was not controlled. [2 marks]

The feedback from one of the schools was that recreational screen time affected pupils’ social interactions. The psychologist decided to investigate this further by using an observation of social interaction during playtime at the school.

(n) Design the observation to investigate pupils’ social interaction in the playground.

In your answer you will be awarded credit for providing appropriate details of:

  • type of observation, with justification
  • choice of time sampling or event sampling, with justification
  • dealing with one relevant ethical issue
  • assessing reliability of the data through inter-observer reliability.

2021 ( AQA A-level Psychology notes)

A researcher placed an advert in a university psychology department asking for third year students to participate in a sleep experiment.

Each student had a sleep tracker watch to wear at home for the two-week study. Each morning they were asked to open the sleep tracker app to view their sleep quality data on their mobile phones. The students were unaware that the sleep data they could see on their phones had been manipulated by the researcher. Over the two weeks of the study, each student saw that he or she had had poor sleep quality for seven random nights of the experiment and good sleep quality for the remaining nights.

Every morning, after viewing the sleep data, each student completed a questionnaire about the previous night’s sleep. One of the questions asked the students to rate how well rested they felt, on a scale from 1–10, after the previous night’s sleep. Apart from this, students were asked to continue their normal everyday activities.

(a) Which of the following best describes the experimental method used in this study?

Shade one box only. [1 mark]

A           Field experiment

B           Laboratory experiment

C           Natural experiment

D           Quasi-experiment

(b) Write a directional hypothesis the researcher might use for this study. [3 marks]

(c) Which of the following best describes the sampling method used in this study?

A           Opportunity sampling

B           Stratified sampling

C           Systematic sampling

D           Volunteer sampling

(d) Explain one strength and one limitation of using this sampling method in this study. [4 marks]

The researcher collected quantitative data about how well rested the students felt.

(e) Explain one strength of collecting quantitative data in this study. [2 marks]

One ethical issue in this study is deception, as the students were unaware that the sleep data they could see on their phones had been manipulated by the researcher.

(f) Explain one way in which the researcher might deal with the deception in this study. [2 marks]

Apart from the question about how well rested the students felt, the researcher’s questionnaire contained nine other questions. The responses to these questions were not analysed.

(g) Explain one reason why the researcher decided to include these additional questions on the questionnaire. [2 marks]

(h) Explain one limitation of assessing sleep quality using a rating scale of 1–10. [2 marks]

The researcher believed that the actual number of hours slept by the students could have affected the results of the study.

(i) Suggest one other extraneous variable that could have affected the results of this study. Explain why it would have been important to control this extraneous variable and how it could have been controlled in this study. [4 marks]

In a follow-up study, the researcher investigated whether there was a correlation between the number of hours slept and how well rested the students felt.

The researcher randomly selected 18 participants from first-year students at the university.

On the day of the study, each student participant was asked, ‘How many hours did you sleep last night?’ They then had to rate on a scale of 1 to 5 how well rested they felt.

The researcher hypothesised that there would be a positive correlation between the two co-variables.

(j) Outline one reason why it was appropriate to conduct a correlation rather than an experiment in this case. [2 marks]

(k) Describe how the researcher could have used random sampling to obtain the students for this study. [3 marks]

The researcher used Spearman’s rho statistical test to analyse the data from this study.

(l) Explain why Spearman’s rho was a suitable test for this study. Refer to the description of the study in your answer. [4 marks]

The researcher chose to use the 5% level of significance and the calculated correlation coefficient for the Spearman’s rho test was 0.395

AQA PSYCHOLOGY A LEVEL RESEARCH METHODS 11

(m) Identify the appropriate critical value from Table 1. Explain your choice. [4 marks]

(n) Explain whether the researcher’s hypothesis should be accepted. Refer to the critical value identified in Question 21 in your answer. [2 marks]

(o) Explain why the researcher decided to use the 5% level of significance rather than the 1% level in this study. [2 marks]

When the researcher compared the calculated and critical values of rho, he began to wonder if he might have made a Type II error.

(p) Explain what is meant by a Type II error in the context of this study. [2 marks]

(q) Discuss features of science. Refer to one or more examples of psychological research in your answer. [8 marks]

2022 ( A-level Psychology revision notes)

A controlled observation was designed to compare the social behaviours of pre-school children of working parents and pre-school children of stay-at-home parents. The sample consisted of 100 children aged three, who were observed separately. Half of the children had working parents and the other half had stay-at-home parents.

The observation took place in a room which looked like a nursery, with a variety of toys available. In the room, there were four children and one supervising adult. Their behaviour was not recorded.

Each child participant was brought into the room and settled by their parent. The parent then left to sit outside. Each child participant’s behaviour was observed covertly for five minutes while they played in the room.

The observation was conducted in a controlled environment and a standardised script was used when the children and their parents arrived.

(a) Explain why the researcher used a controlled observation and a standardised script in this study. [4 marks] 

(b) Identify one limitation of controlled observations. [1 mark]

The researcher used two trained observers to record the social behaviours of each child during the observation.

(c) Give two behavioural categories that the observers could have used in the observation to assess the pre-school children’s social behaviour. Explain why your chosen categories are appropriate. [4 marks]

(d) Describe how the observers could use time sampling to record the social behaviour of each child during the five-minute period. [4 marks]

(e) Explain one strength and one limitation of using time sampling for this observation. [4 marks]

(f) Explain how the reliability of the controlled observation could be assessed through inter-observer reliability. [4 marks]

The data from the observation was summarised by converting the number of agreed observations into a total social behaviour score for each child.

The researcher then conducted a statistical test to identify whether there was a significant difference between the social behaviour scores for the children of stay-at-home parents and those of working parents.

(g) Identify an appropriate statistical test that the researcher could use to analyse the social behaviour scores in this study. Explain three reasons for your choice in the context of this study. [7 marks]

(h) Explain one reason why collecting quantitative data could reduce the validity of this study. [2 marks]

The findings of this study might have implications for the economy.

(i) Explain one or more possible implications of this study for the economy. [3 marks]

This study was written up as a scientific report.

(j) Describe features of the abstract section in a scientific report. [3 marks]

A new TV programme has been developed to increase positive social behaviours in pre-school children.

There is a proposal to carry out an experiment to compare the effects of the new TV programme and an existing TV programme, on positive social behaviours in pre-school children.

A sample of 500 pre-school children and their parents is available for the experiment. The parents have given consent for their children to take part in this experiment.

The experiment will take place over an 8-week period. Data on the children’s social behaviours will be gathered from the parents using a self-report method.

(j) Design the experiment to investigate whether watching the new TV programme leads to an increase in positive social behaviours in the children, compared with watching the existing TV programme.

In your answer you will gain credit for providing appropriate details of the following:

  • the type of experimental design, with justification
  • a self-report method of data collection, with justification
  • how to control one extraneous variable, with justification as to why this would need to be controlled.

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Psychology A Level

Overview – Research Methods

Research methods are how psychologists and scientists come up with and test their theories. The A level psychology syllabus covers several different types of studies and experiments used in psychology as well as how these studies are conducted and reported:

  • Types of psychological studies (including experiments , observations , self-reporting , and case studies )
  • Scientific processes (including the features of a study , how findings are reported , and the features of science in general )
  • Data handling and analysis (including descriptive statistics and different ways of presenting data ) and inferential testing

Note: Unlike all other sections across the 3 exam papers, research methods is worth 48 marks instead of 24. Not only that, the other sections often include a few research methods questions, so this topic is the most important on the syllabus!

research methods psychology paper 1

Example question: Design a matched pairs experiment the researchers could conduct to investigate differences in toy preferences between boys and girls. [12 marks]

Types of study

There are several different ways a psychologist can research the mind, including:

  • Experiments
  • Observation
  • Self-reporting

Case studies

Each of these methods has its strengths and weaknesses. Different methods may be better suited to different research studies.

Experimental method

The experimental method looks at how variables affect outcomes. A variable is anything that changes between two situations ( see below for the different types of variables ). For example, Bandura’s Bobo the doll experiment looked at how changing the variable of the role model’s behaviour affected how the child played.

Experimental designs

Experiments can be designed in different ways, such as:

  • Independent groups: Participants are divided into two groups. One group does the experiment with variable 1, the other group does the experiment with variable 2. Results are compared.
  • Repeated measures: Participants are not divided into groups. Instead, all participants do the experiment with variable 1, then afterwards the same participants do the experiment with variable 2. Results are compared.

A matched pairs design is another form of independent groups design. Participants are selected. Then, the researchers recruit another group of participants one-by-one to match the characteristics of each member of the original group. This provides two groups that are relevantly similar and controls for differences between groups that might skew results. The experiment is then conducted as a normal independent groups design.

Types of experiment

Laboratory vs. field experiment.

Experiments are carried out in two different types of settings:

  • E.g. Bandura’s Bobo the doll experiment or Asch’s conformity experiments
  • E.g. Bickman’s study of the effects of uniforms on obedience

Strengths of laboratory experiment over field experiment:

The controlled environment of a laboratory experiment minimises the risk of other variables outside the researchers’ control skewing the results of the trial, making it more clear what (if any) the causal effects of a variable are. Because the environment is tightly controlled, any changes in outcome must be a result of a change in the variable.

Weaknesses of laboratory experiment over field experiment:

However, the controlled nature of a laboratory experiment might reduce its ecological validity . Results obtained in an artificial environment might not translate to real-life. Further, participants may be influenced by demand characteristics : They know they are taking part in a test, and so behave how they think they’re expected to behave rather than how they would naturally behave.

Natural and quasi experiment

Natural experiments are where variables vary naturally. In other words, the researcher can’t or doesn’t manipulate the variables . There are two types of natural experiment:

  • E.g. studying the effect a change in drug laws (variable) has on addiction
  • E.g. studying differences between men (variable) and women (variable)

Observational method

The observational method looks at and examines behaviour. For example, Zimbardo’s prison study observed how participants behaved when given certain social roles.

Observational design

Behavioural categories.

An observational study will use behavioural categories to prioritise which behaviours are recorded and ensure the different observers are consistent in what they are looking for.

For example, a study of the effects of age and sex on stranger anxiety in infants might use the following behavioural categories to organise observational data:

Rather than writing complete descriptions of behaviours, the behaviours can be coded into categories. For example, IS = interacted with stranger, and AS = avoided stranger. Researchers can also create numerical ratings to categorise behaviour, like the anxiety rating example above.

Inter-observer reliability : In order for observations to produce reliable findings, it is important that observers all code behaviour in the same way. For example, researchers would have to make it very clear to the observers what the difference between a ‘3’ on the anxiety scale above would be compared to a ‘7’. This inter-observer reliability avoids subjective interpretations of the different observers skewing the findings.

Event and time sampling

Because behaviour is constant and varied, it may not be possible to record every single behaviour during the observation period. So, in addition to categorising behaviour , study designers will also decide when to record a behaviour:

  • Event sampling: Counting how many times the participant behaves in a certain way.
  • Time sampling: Recording participant behaviour at regular time intervals. For example, making notes of the participant’s behaviour after every 1 minute has passed.

Note: Don’t get event and time sampling confused with participant sampling , which is how researchers select participants to study from a population.

Types of observation

Naturalistic vs. controlled.

Observations can be made in either a naturalistic or a controlled setting:

  • E.g. setting up cameras in an office or school to observe how people interact in those environments
  • E.g. Ainsworth’s strange situation or Zimbardo’s prison study

Covert vs. overt

Observations can be either covert or overt :

  • E.g. setting up hidden cameras in an office
  • E.g. Zimbardo’s prison study

Participant vs. non-participant

In observational studies, the researcher/observer may or may not participate in the situation being observed:

  • E.g. in Zimbardo’s prison study , Zimbardo played the role of prison superintendent himself
  • E.g. in Bandura’s Bobo the doll experiment and Ainsworth’s strange situation , the observers did not interact with the children being observed

Self-report method

Self-report methods get participants to provide information about themselves. Information can be obtained via questionnaires or interviews .

Types of self-report

Questionnaires.

A questionnaire is a standardised list of questions that all participants in a study answer. For example, Hazan and Shaver used questionnaires to collate self-reported data from participants in order to identify correlations between attachment as infants and romantic attachment as adults.

Questions in a questionnaire can be either open or closed :

  • >8 hours
  • E.g. “How did you feel when you thought you were administering a lethal shock?” or “What do you look for in a romantic partner and why?”

Strengths of questionnaires:

  • Quantifiable: Closed questions provide quantifiable data in a consistent format, which enables to statistically analyse information in an objective way.
  • Replicability: Because questionnaires are standardised (i.e. pre-set, all participants answer the same questions), studies involving them can be easily replicated . This means the results can be confirmed by other researchers, strengthening certainty in the findings.

Weaknesses of questionnaires:

  • Biased samples: Questionnaires handed out to people at random will select for participants who actually have the time and are willing to complete the questionnaire. As such, the responses may be biased towards those of people who e.g. have a lot of spare time.
  • Dishonest answers: Participants may lie in their responses – particularly if the true answer is something they are embarrassed or ashamed of (e.g. on controversial topics or taboo topics like sex)
  • Misunderstanding/differences in interpretation: Different participants may interpret the same question differently. For example, the “are you religious?” example above could be interpreted by one person to mean they go to church every Sunday and pray daily, whereas another person may interpret religious to mean a vague belief in the supernatural.
  • Less detail: Interviews may be better suited for detailed information – especially on sensitive topics – than questionnaires. For example, participants are unlikely to write detailed descriptions of private experiences in a questionnaire handed to them on the street.

In an interview , participants are asked questions in person. For example, Bowlby interviewed 44 children when studying the effects of maternal deprivation.

Interviews can be either structured or unstructured :

  • Structured interview: Questions are standardised and pre-set. The interviewer asks all participants the same questions in the same order.
  • Unstructured interview: The interviewer discusses a topic with the participant in a less structured and more spontaneous way, pursuing avenues of discussion as they come up.

Interviews can also be a cross between the two – these are called semi-structured interviews .

Strengths of interviews:

  • More detail: Interviews – particularly unstructured interviews conducted by a skilled interviewer – enable researchers to delve deeper into topics of interest, for example by asking follow-up questions. Further, the personal touch of an interviewer may make participants more open to discussing personal or sensitive issues.
  • Replicability: Structured interviews are easily replicated because participants are all asked the same pre-set list of questions. This replicability means the results can be confirmed by other researchers, strengthening certainty in the findings.

Weaknesses of interviews:

  • Lack of quantifiable data: Although unstructured interviews enable researchers to delve deeper into interesting topics, this lack of structure may produce difficulties in comparing data between participants. For example, one interview may go down one avenue of discussion and another interview down a different avenue. This qualitative data may make objective or statistical analysis difficult.
  • Interviewer effects : The interviewer’s appearance or character may bias the participant’s answers. For example, a female participant may be less comfortable answering questions on sex asked by a male interviewer and and thus give different answers than if she were asked by a female interviewer.

Note: This topic is A level only, you don’t need to learn about case studies if you are taking the AS exam only.

Case studies are detailed investigations into an individual, a group of people, or an event. For example, the biopsychology page describes a case study of a young boy who had the left hemisphere of his brain removed and the effects this had on his language skills.

In a case study, researchers use many of the methods described above – observation , questionnaires , interviews – to gather data on a subject. However, because case studies are studies of a single subject, the data they provide is primarily qualitative rather than quantitative . This data is then used to build a case history of the subject. Researchers then interpret this case history to draw their conclusions.

Types of case study

Typical vs. unusual cases.

Most case studies focus on unusual individuals, groups, and events.

Longitudinal

Many case studies are longitudinal . This means they take place over an extended time period, with researchers checking in with the subject at various intervals. For example, the case study of the boy who had his left hemisphere removed collected data on the boy’s language skills at ages 2.5, 4, and 14 to see how he progressed.

Strengths of case studies:

  • Provides detailed qualitative data: Rather than focusing on one or two aspects of behaviour at a single point in time (e.g. in an experiment ), case studies produce detailed qualitative data.
  • Allows for investigation into issues that may be impractical or unethical to study otherwise. For example, it would be unethical to remove half a toddler’s brain just to experiment , but if such a procedure is medically necessary then researchers can use this opportunity to learn more about the brain.

Weaknesses of case studies:

  • Lack of scientific rigour: Because case studies are often single examples that cannot be replicated , the results may not be valid when applied to the general population.
  • Researcher bias: The small sample size of case studies also means researchers need to apply their own subjective interpretation when drawing conclusions from them. As such, these conclusions may be skewed by the researcher’s own bias and not be valid when applied more generally. This criticism is often directed at Freud’s psychoanalytic theory because it draws heavily on isolated case studies of individuals.

Scientific processes

This section looks at how science works more generally – in particular how scientific studies are organised and reported . It also covers ways of evaluating a scientific study.

Study features and design

Studies will usually have an aim . The aim of a study is a description of what the researchers are investigating and why . For example, “to investigate the effect of SSRIs on symptoms of depression” or “to understand the effect uniforms have on obedience to authority”.

Studies seek to test a hypothesis . The experimental/alternate hypothesis of a study is a testable prediction of what the researchers expect to happen.

  • E.g. “That SSRIs will reduce symptoms of depression” or “subjects are more likely to comply when orders are issued by someone wearing a uniform”.
  • E.g. “That SSRIs have no effect on symptoms on depression” or “subject conformity will be the same when orders are issued by someone wearing a uniform as when orders are issued by someone bot wearing a uniform”

Either the experimental/alternate hypothesis or the null hypothesis will be supported by the results of the experiment.

It’s often not possible or practical to conduct research on everyone your study is supposed to apply to. So, researchers use sampling to select participants for their study.

  • E.g. all humans, all women, all men, all children, etc.
  • E.g. 10,000 humans, 200 women from the USA, children at a certain school

For example, the target population (i.e. who the results apply to) of Asch’s conformity experiments is all humans – but Asch didn’t conduct the experiment on that many people! Instead, Asch recruited 123 males and generalised the findings from this sample to the rest of the population.

Researchers choose from different sampling techniques – each has strengths and weaknesses.

Sampling techniques

Random sampling.

The random sampling method involves selecting participants from a target population at random – such as by drawing names from a hat or using a computer program to select them. This method means each member of the population has an equal chance of being selected and thus is not subject to any bias.

Strengths of random sampling:

  • Unbiased: Selecting participants by random chance reduces the likelihood that researcher bias will skew the results of the study.
  • Representative: If participants are selected at random – particularly if the sample size is large – it is likely that the sample will be representative of the population as a whole. For example, if the ratio of men:women in a population is 50:50 and participants are selected at random, it is likely that the sample will also have a ratio of men to women that is 50:50.

Weaknesses of random sampling:

  • Impractical: It’s often impractical/impossible to include all members of a target population for selection. For example, it wouldn’t be feasible for a study on women to include the name of every woman on the planet for selection. But even if this was done, the randomly selected women may not agree to take part in the study anyway.

Systematic sampling

The systematic sampling method involves selecting participants from a target population by selecting them at pre-set intervals. For example, selecting every 50th person from a list, or every 7th, or whatever the interval is.

Strengths of systematic sampling:

  • Unbiased and representative: Like random sampling , selecting participants according to a numerical interval provides an objective means of selecting participants that prevents researcher bias being able to skew the sample. Further, because the sampling method is independent of any particular characteristic (besides the arbitrary characteristic of the participant’s order in the list) this sample is likely to be representative of the population as a whole.

Weaknesses of systematic sampling:

  • Unexpected bias: Some characteristics could occur more or less frequently at certain intervals, making a sample that is selected based on that interval biased. For example, houses tend to be have even numbers on one side of a road and odd numbers on the other. If one side of the road is more expensive than the other and you select every 4th house, say, then you will only select even numbers from one side of the road – and this sample may not be representative of the road as a whole.

Stratified sampling

The stratified sampling method involves dividing the population into relevant groups for study, working out what percentage of the population is in each group, and then randomly sampling the population according to these percentages.

For example, let’s say 20% of the population is aged 0-18, and 50% of the population is aged 19-65, and 30% of the population is aged >65. A stratified sample of 100 participants would randomly select 20x 0-18 year olds, 50x 19-65 year olds, and 30x people over 65.

Strengths of stratified sampling:

  • Representative: The stratification is deliberately designed to yield a sample that is representative of the population as a whole. You won’t get people with certain characteristics being over- or under-represented within the sample.
  • Unbiased: Because participants within each group are selected randomly , researcher bias is unable to skew who is included in the study.

Weaknesses of stratified sampling:

  • Requires knowledge of population breakdown: Researchers need to accurately gauge what percentage of the population falls into what group. If the researchers get these percentages wrong, the sample will be biased and some groups will be over- or under-represented.

Opportunity and volunteer sampling

The opportunity and volunteer sampling methods:

  • E.g. Approaching people in the street and asking them to complete a questionnaire.
  • E.g. Placing an advert online inviting people to complete a questionnaire.

Strengths of opportunity and volunteer sampling:

  • Quick and easy: Approaching participants ( opportunity sampling) or inviting participants ( volunteer sampling) is quick and straightforward. You don’t have to spend time compiling details of the target population (like in e.g. random or systematic sampling ), nor do you have to spend time dividing participants according to relevant categories (like in stratified sampling ).
  • May be the only option: With natural experiments – where a variable changes as a result of something outside the researchers’ control – opportunity sampling may be the only viable sampling method. For example, researchers couldn’t randomly sample 10 cities from all the cities in the world and change the drug laws in those cities to see the effects – they don’t have that kind of power. However, if a city is naturally changing its drug laws anyway, researchers could use opportunity sampling to study that city for research.

Weaknesses of opportunity and volunteer sampling:

  • Unrepresentative: The pool of participants will likely be biased towards certain kinds of people. For example, if you conduct opportunity sampling on a weekday at 10am, this sample will likely exclude people who are at work. Similarly, volunteer sampling is likely to exclude people who are too busy to take part in the study.

Independent vs. dependent variables

If the study involves an experiment , the researchers will alter an independent variable to measure its effects on a dependent variable :

  • E.g. In Bickman’s study of the effects of uniforms on obedience , the independent variable was the uniform of the person giving orders.
  • E.g. In Bickman’s study of the effects of uniforms on obedience , the dependent variable was how many people followed the orders.

Extraneous and confounding variables

In addition to the variables actually being investigated ( independent and dependent ), there may be additional (unwanted) variables in the experiment. These additional variables are called extraneous variables .

Researchers must control for extraneous variables to prevent them from skewing the results and leading to false conclusions. When extraneous variables are not properly controlled for they are known as confounding variables .

For example, if you’re studying the effect of caffeine on reaction times, it might make sense to conduct all experiments at the same time of day to prevent this extraneous variable from confounding the results. Reaction times change throughout the day and so if you test one group of subjects at 3pm and another group right before they go to bed, you may falsely conclude that the second group had slower reaction times.

Operationalisation of variables

Operationalisation of variables is where researchers clearly and measurably define the variables in their study.

For example, an experiment on the effects of sleep ( independent variable ) on anxiety ( dependent variable ) would need to clearly operationalise each variable. Sleep could be defined by number of hours spent in bed, but anxiety is a bit more abstract and so researchers would need to operationalise (i.e. define) anxiety such that it can be quantified in a measurable and objective way.

If variables are not properly operationalised, the experiment cannot be properly replicated , experimenters’ subjective interpretations may skew results, and the findings may not be valid .

Pilot studies

A pilot study is basically a practice run of the proposed research project. Researchers will use a small number of participants and run through the procedure with them. The purpose of this is to identify any problems or areas for improvement in the study design before conducting the research in full. A pilot study may also give an early indication of whether the results will be statistically significant .

For example, if a task is too easy for participants, or it’s too obvious what the real purpose of an experiment is, or questions in a questionnaire are ambiguous, then the results may not be valid . Conducting a pilot study first may save time and money as it enables researchers to identify and address such issues before conducting the full study on thousands of participants.

Study reporting

Features of a psychological report.

The report of a psychological study (research paper) typically contains the following sections in the following order:

  • Title: A short and clear description of the research.
  • Abstract: A summary of the research. This typically includes the aim and hypothesis , methods, results, and conclusion.
  • Introduction: Funnel technique: Broad overview of the context (e.g. current theories, previous studies, etc.) before focusing in on this particular study, why it was conducted, its aims and hypothesis .
  • Study design: This will explain what method was used (e.g. experiment or observation ), how the study was designed (e.g. independent groups or repeated measures ), and identification and operationalisation of variables .
  • Participants: A description of the target population to be studied, the sampling method , how many participants were included.
  • Equipment used: A description of any special equipment used in the study and how it was used.
  • Standardised procedure: A detailed step-by-step description of how the study was conducted. This allows for the study to be replicated by other researchers.
  • Controls : An explanation of how extraneous variables were controlled for so as to generate accurate results.
  • Results: A presentation of the key findings from the data collected. This is typically written summaries of the raw data ( descriptive statistics ), which may also be presented in tables , charts, graphs , etc. The raw data itself is typically included in appendices.
  • Discussion: An explanation of what the results mean and how they relate to the experimental hypothesis (supporting or contradicting it), any issues with how results were generated, how the results fit with other research, and suggestions for future research.
  • Conclusion: A short summary of the key findings from the study.
  • Book: Milgram, S., 2010. Obedience to Authority . 1st ed. Pinter & Martin.
  • Journal article: Bandura, A., Ross, D. and Ross, S., 1961. Transmission of Aggression through Imitation of Aggressive Models . The Journal of Abnormal and Social Psychology, 63(3), pp.575-582.
  • Appendices: This is where you put any supporting materials that are too detailed or long to include in the main report. For example, the raw data collected from a study, or the complete list of questions in a questionnaire .

Peer review

Peer review is a way of assessing the scientific credibility of a research paper before it is published in a scientific journal. The idea with peer review is to prevent false ideas and bad research from being accepted as fact.

It typically works as follows: The researchers submit their paper to the journal they want it to be published in, and the editor of that journal sends the paper to expert reviewers (i.e. psychologists who are experts in that area – the researchers’ ‘peers’) who evaluate the paper’s scientific validity. The reviewers may accept the paper as it is, accept it with a few changes, reject it and suggest revisions and resubmission at a later date, or reject it completely.

There are several different methods of peer review:

  • Open review: The researchers and the reviewers are known to each other.
  • Single-blind: The researchers do not know the names of the reviewers. This prevents the researchers from being able to influence the reviewer. This is the most common form of peer review.
  • Double-blind: The researchers do not know the names of the reviewers, and the reviewers do not know the names of the researchers. This additionally prevents the reviewer’s bias towards the researcher from influencing their decision whether to accept their paper or not.

Criticisms of peer review:

  • Bias: There are several ways peer review can be subject to bias. For example, academic research (particularly in niche areas) takes place among a fairly small circle of people who know each other and so these relationships may affect publication decisions. Further, many academics are funded by organisations and companies that may prefer certain ideas to be accepted as scientifically legitimate, and so this funding may produce conflicts of interest.
  • Doesn’t always prevent fraudulent/bad research from being published: There are many examples of fraudulent research passing peer review and being published (see this Wikipedia page for examples).
  • Prevents progress of new ideas: Reviewers of papers are typically older and established academics who have made their careers within the current scientific paradigm. As such, they may reject new or controversial ideas simply because they go against the current paradigm rather than because they are unscientific.
  • Plagiarism: In single-blind and double-blind peer reviews, the reviewer may use their anonymity to reject or delay a paper’s publication and steal the good ideas for themself.
  • Slow: Peer review can mean it takes months or even years between the researcher submitting a paper and its publication.

Study evaluation

In psychological studies, ethical issues are questions of what is morally right and wrong. An ethically-conducted study will protect the health and safety of the participants involved and uphold their dignity, privacy, and rights.

To provide guidance on this, the British Psychological Association has published a code of human research ethics :

  • Participants are told the project’s aims , the data being collected, and any risks associated with participation.
  • Participants have the right to withdraw or modify their consent at any time.
  • Researchers can use incentives (e.g. money) to encourage participation, but these incentives can’t be so big that they would compromise a participant’s freedom of choice.
  • Researchers must consider the participant’s ability to consent (e.g. age, mental ability, etc.)
  • Prior (general) consent: Informing participants that they will be deceived without telling them the nature of the deception. However, this may affect their behaviour as they try to guess the real nature of the study.
  • Retrospective consent: Informing participants that they were deceived after the study is completed and asking for their consent. The problem with this is that if they don’t consent then it’s too late.
  • Presumptive consent: Asking people who aren’t participating in the study if they would be willing to participate in the study. If these people would be willing to give consent, then it may be reasonable to assume that those taking part in the study would also give consent.
  • Confidentiality: Personal data obtained about participants should not be disclosed (unless the participant agreed to this in advance). Any data that is published will not be publicly identifiable as the participant’s.
  • Debriefing: Once data gathering is complete, researchers must explain all relevant details of the study to participants – especially if deception was involved. If a study might have harmed the individual (e.g. its purpose was to induce a negative mood), it is ethical for the debrief to address this harm (e.g. by inducing a happy mood) so that the participant does not leave the study in a worse state than when they entered.

Reliability

Study results are reliable if the same results can be consistently replicated under the same circumstances. If results are inconsistent then the study is unreliable.

Note: Just because a study is reliable, its results are not automatically valid . A broken tape measure may reliably (i.e. consistently) record a person’s height as 200m, but that doesn’t mean this measurement is accurate.

There are several ways researchers can assess a study’s reliability:

Test-retest

Test-retest is when you give the same test to the same person on two different occasions. If the results are the same or similar both times, this suggests they are reliable.

For example, if your study used scales to measure participants’ weight, you would expect the scales to record the same (or a very similar) weight for the same person in the morning as in the evening. If the scales said the person weighed 100kg more later that same day, the scales (and therefore the results of the study) would be unreliable.

Inter-observer

Inter-observer reliability is a way to test the reliability of observational studies .

For example, if your study required observers to assess participants’ anxiety levels, you would expect different observers to grade the same behaviour in the same way. If one observer rated a participant’s behaviour a 3 for anxiety, and another observer rated the exact same behaviour an 8, the results would be unreliable.

Inter-observer reliability can be assessed mathematically by looking for correlation between observers’ scores. Inter-observer reliability can be improved by setting clearly defined behavioural categories .

Study results are valid if they accurately measure what they are supposed to. There are several ways researchers can assess a study’s validity:

  • E.g. let’s say you come up with a new test to measure participants’ intelligence levels. If participants scoring highly on your test also scored highly on a standardised IQ test and vice versa, that would suggest your test has concurrent validity because participants’ scores are correlated with a known accurate test.
  • E.g. a study that measures participants’ intelligence levels by asking them when their birthday is would not have face validity. Getting participants to complete a standardised IQ test would have greater face validity.
  • E.g. let’s say your study was supposed to measure aggression levels in response to someone annoying. If the study was conducted in a lab and the participant knew they were taking part in a study, the results probably wouldn’t have much ecological validity because of the unrealistic environment.
  • E.g. a study conducted in 1920 that measured participants’ attitudes towards social issues may have low temporal validity because societal attitudes have changed since then.

Control of extraneous variables

There are several different types of extraneous variables that can reduce the validity of a study. A well-conducted psychological study will control for these extraneous variables so that they do not skew the results.

Demand characteristics

Demand characteristics are extraneous variables where the demands of a study make participants behave in ways they wouldn’t behave outside of the study. This reduces the study’s ecological validity .

For example, if a participant guesses the purpose of an experiment they are taking part in, they may try to please the researcher by behaving in the ‘right’ way rather than the way they would naturally. Alternatively, the participant might rebel against the study and deliberately try to sabotage it (e.g. by deliberately giving wrong answers).

In some study designs, researchers can control for demand characteristics using single- blind methods. For example, a drug trial could give half the participants the actual drug and the other half a placebo but not tell participants which treatment they received. This way, both groups will have equal demand characteristics and so any differences between them should be down to the drug itself.

Investigator effects

Investigator effects are another extraneous variable where the characteristics of the researcher affect the participant’s behaviour. Again, this reduces the study’s ecological validity .

Many characteristics – e.g. the researcher’s age, gender, accent, what they’re wearing – could potentially influence the participant’s responses. For example, in an interview about sex, females may feel less comfortable answering questions asked by a male interviewer and thus give different answers than if they were asked by a female. The researcher’s biases may also come across in their body language or tone of voice, affecting the participant’s responses.

In some study designs, researchers can control for demand characteristics using double- blind methods. In a double-blind drug trial, for example, neither the participants nor the researchers know which participants get the actual drug and which get the placebo. This way, the researcher is unable to give any clues (consciously or unconsciously) to participants that would affect their behaviour.

Participant variables

Participant variables are differences between participants. These can be controlled for by random allocation .

For example, in an experiment on the effect of caffeine on reaction times, participants would be randomly allocated into either the caffeine group or the non-caffeine group. A non -random allocation method, such as allocating caffeine to men and placebo to women, could mean variables in the allocation method (in this case gender) skew the results. When participants are randomly allocated, any extraneous variables (e.g. gender in this case) will be allocated evenly between each group and so not skew the results of one group more than the other.

Situational variables

Situational variables are the environment the experiment is conducted in. These can be controlled for by standardisation .

For example, all the tests of caffeine on reaction times would be conducted in the same room, at the same time of day, using the same equipment, and so on to prevent these features of the environment from skewing the results.

In a repeated measures experiment, researchers may use counterbalancing to control for the order in which tasks are completed.

For example, half of participants would do task A followed by task B, and the other half would do task B followed by task A.

Implications of psychological research for the economy

Psychological research often has practical applications in real life. The following are some examples of how psychological findings may affect the economy:

  • Attachment : Bowlby’s maternal deprivation hypothesis suggests that periods of extended separation between mother and child before age 3 are harmful to the child’s psychological development. And if mothers stay at home during this period, they can’t go out to work. However, some more recent research challenges Bowlby’s conclusions, suggesting that substitutes (e.g. the father , or nursery care) can care for the child, allowing the mother to go back to work sooner and remain economically active.
  • Depression : Psychological research has found effective therapies for treating depression, such as cognitive behavioural therapy and SSRIs. The benefits of such therapies – if they are effective – are likely to outweigh the costs because they enable the person to return to work and pay taxes, as well avoiding long-term costs to the health service.
  • OCD : Similar to above: Drug therapies (e.g. SSRIs) and behavioural approaches (e.g. CBT) may alleviate OCD symptoms, enabling OCD sufferers to return to work, pay taxes, and avoid reliance on healthcare services.
  • Memory : Public money is required to fund police investigations. Psychological tools, such as the cognitive interview , have improved the accuracy of eyewitness testimonies, which equates to more efficient use of police time and resources.

Features of science

Theory construction and hypothesis testing.

Science works by making empirical observations of the world, formulating hypotheses /theories that explain these observations, and repeatedly testing these hypotheses /theories via experimentation.

  • E.g. A tape measure provides a more objective measurement of something compared to a researcher’s guess. Similarly, a set of scales is a more objective way of determining which of two objects is heavier than a researcher lifting each up and giving their opinion.
  • E.g. Burger (2009) replicated Milgram’s experiments with similar results.
  • E.g. The hypothesis that “water boils at 100°c” could be falsified by an experiment where you heated water to 999°c and it didn’t boil. In contrast, “everything doubles in size every 10 seconds” could not be falsified by any experiment because whatever equipment you used to measure everything would also double in size.
  • Freud’s psychodynamic theories are often criticised for being unfalsifiable: There’s not really any observations that could disprove them because every possible behaviour (e.g. crying or not crying) could be explained as the result of some unconscious thought process.

Paradigm shifts

Philosopher Thomas Kuhn argues that science is not as unbiased and objective as it seems. Instead, the majority of scientists just accept the existing scientific theories (i.e. the existing paradigm) as true and then find data that supports these theories while ignoring/rejecting data that refutes them.

Rarely, though, minority voices are able to successfully challenge the existing paradigm and replace it with a new one. When this happens it is a paradigm shift . An example of a paradigm shift in science is that from Newtonian gravity to Einstein’s theory of general relativity.

Data handling and analysis

Types of data, quantitative vs. qualitative.

Data from studies can be quantitative or qualitative :

  • Quantitative: Numerical
  • Qualitative: Non-numerical

For example, some quantitative data in the Milgram experiment would be how many subjects delivered a lethal shock. In contrast, some qualitative data would be asking the subjects afterwards how they felt about delivering the lethal shock.

Strengths of quantitative data / weaknesses of qualitative data:

  • Can be compared mathematically and scientifically: Quantitative data enables researchers to mathematically and objectively analyse data. For example, mood ratings of 7 and 6 can be compared objectively, whereas qualitative assessments such as ‘sad’ and ‘unhappy’ are hard to compare scientifically.

Weaknesses of quantitative data / strengths of qualitative data:

  • Less detailed: In reducing data to numbers and narrow definitions, quantitative data may miss important details and context.

Content analysis

Although the detail of qualitative data may be valuable, this level of detail can also make it hard to objectively or mathematically analyse. Content analysis is a way of analysing qualitative data. The process is as follows:

  • E.g. A bunch of unstructured interviews on the topic of childhood
  • E.g. Discussion of traumatic events, happy memories, births, and deaths
  • E.g. Researchers listen to the unstructured interviews and count how often traumatic events are mentioned
  • Statistical analysis is carried out on this data

Primary vs. secondary

Researchers can produce primary data or use secondary data to achieve the research aims of their study:

  • Primary data: Original data collected for the study
  • Secondary data: Data from another study previously conducted

Meta-analysis

A meta-analysis is a study of studies. It involves taking several smaller studies within a certain research area and using statistics to identify similarities and trends within those studies to create a larger study.

We have looked at some examples of meta-analyses elsewhere in the course such as Van Ijzendoorn’s meta-analysis of several strange situation studies and Grootheest et al’s meta-analysis of twin studies on OCD .

A good meta-analysis is often more reliable than a regular study because it is based on a larger data set, and any issues with one single study will be balanced out by the other studies.

Descriptive statistics

Measures of central tendency: mean, median, mode.

Mean , median , and mode are measures of central tendency . In other words, they are ways of reducing large data sets into averages .

The mean is calculated by adding all the numbers in a set together and dividing the total by the number of numbers.

  • Example set: 22, 78, 3, 33, 90
  • 22+78+3+33+90=226
  • The mean is 45.2
  • Uses all data in the set.
  • Accurate: Provides a precise number based on all the data in a set.

Weaknesses:

  • E.g.: 1, 3, 2, 5, 9, 4, 913 <- the mean is 133.9, but the 913 could be a measurement error or something and thus the mean is not representative of the data set

The median is calculated by arranging all the numbers in a set from smallest to biggest and then finding the number in the middle. Note: If the total number of numbers is odd, you just pick the middle one. But if the total number of numbers is even, you take the mid-point between the two numbers in the middle.

  • Example set: 20, 66, 85, 45, 18, 13, 90, 28, 9
  • 9, 13, 18, 20, 28 , 45, 66, 85, 90
  • The median is 28
  • Won’t be skewed by freak scores (unlike the mean).
  • E.g.: 1, 1, 3 , 9865, 67914 <- 3 is not really representative of the larger numbers in the set.
  • Less accurate/sensitive than the mean.

The mode is calculated by counting which is the most commonly occurring number in a set.

  • Example set: 7, 7, 20 , 16, 1, 20 , 25, 16, 20 , 9
  • There are two 7’s, but three 20’s
  • The mode is 20
  • Makes more sense for presenting the central tendency in data sets with whole numbers. For example, the average number of limbs for a human being will have a mean of something like 3.99, but a mode of 4.
  • Does not use all the data in a set.
  • A data set may have more than one mode.

Measures of dispersion: Range and standard deviation

Range and standard deviation are measures of dispersion . In other words, they quantify how much scores in a data set vary .

The range is calculated by subtracting the smallest number in the data set from the largest number.

  • Example set: 59, 8, 7, 84, 9, 49, 14, 75, 88, 11
  • The largest number is 88
  • The smallest number is 7
  • The range is 81
  • Easy and quick to calculate: You just subtract one number from another
  • Accounts for freak scores (highest and lowest)
  • Can be skewed by freak scores: The difference between the biggest and smallest numbers can be skewed by a single anomalous result or error, which may give an exaggerated impression of the data distribution compared to standard deviation .
  • 4, 4, 5, 5, 5, 6, 6, 7, 19
  • 4, 16, 16, 17, 17, 17, 18, 19 19

Standard deviation

The standard deviation (σ) is a measure of how much numbers in a data set deviate from the mean (average). It is calculated as follows:

  • Example data set: 59, 79, 43, 42, 81, 100, 38, 54, 92, 62
  • Calculate the mean (65)
  • -6, 14, -22, -23, 16, 35, -27, -11, 27, -3
  • 36, 196, 484, 529, 256, 1225, 729, 121, 729, 9
  • 36+196+484+529+256+1225+729+121+729+9=4314
  • 4314/10=431.4
  • √431.4=20.77
  • The standard deviation is 20.77

Note: This method of standard deviation is based on the entire population. There is a slightly different method for calculating based on a sample where instead of dividing by the number of numbers in the second to last step, you divide by the number of numbers-1 (in this case 4314/9=479.333). This gives a standard deviation of 21.89.

  • Is less skewed by freak scores: Standard deviation measures the average difference from the mean and so is less likely to be skewed by a single freak score (compared to the range ).
  • Takes longer to calculate than the range .

Percentages

A percentage (%) describes how much out of 100 something occurs. It is calculated as follows:

  • Example: 63 out of a total of 82 participants passed the test
  • 63/82=0.768
  • 0.768*100=76.8
  • 76.8% of participants passed the test

Percentage change

To calculate a percentage change, work out the difference between the original number and the after number, divide that difference by the original number, then multiply the result by 100:

  • Example: He got 80 marks on the test but after studying he got 88 marks on the test
  • His test score increased by 10% after studying

Normal and skewed distributions

Normal distribution.

A data set that has a normal distribution will have the majority of scores on or near the mean average. A normal distribution is also symmetrical: There are an equal number of scores above the mean as below it. In a normal distribution, scores become rarer and rarer the more they deviate from the mean.

An example of a normal distribution is IQ scores. As you can see from the histogram below, there are as many IQ scores below the mean as there are above the mean :

statistical infrequency bell curve

When plotted on a histogram , data that follows a normal distribution will form a bell-shaped curve like the one above.

Skewed distribution

positive skew and negative skew histograms

Skewed distributions are caused by outliers: Freak scores that throw off the mean . Skewed distributions can be positive or negative :

  • Mean > Median > Mode
  • Mean < Median < Mode

Correlation

Correlation refers to how closely related two (or more) things are related. For example, hot weather and ice cream sales may be positively correlated: When hot weather goes up, so do ice cream sales.

Correlations are measured mathematically using correlation coefficients (r). A correlation coefficient will be anywhere between +1 and -1:

  • r=+1 means two things are perfectly positively correlated: When one goes up , so does the other by the same amount
  • r=-1 means two things perfectly negatively correlated: When one goes up , the other goes down by the same amount
  • r=0 means two things are not correlated at all: A change in one is totally independent of a change in the other

The following scattergrams illustrate various correlation coefficients:

correlation coefficient scatter graph examples

Presentation of data

table example

For example, the behavioural categories table above presents the raw data of each student in this made-up study. But in the results section, researchers might include another table that compares average anxiety rating scores for males and females.

Scattergrams

scattergram example

For example, each dot on the correlation scattergram opposite could represent a student. The x-axis could represent the number of hours the student studied, and the y-axis could represent the student’s test score.

eyewitness testimony loftus and palmer

For example, the results of Loftus and Palmer’s study into the effects of different leading questions on memory could be presented using the bar chart above. It’s not like there are categories in-between ‘contacted’ and ‘hit’, so the bars have gaps between them (unlike a histogram ).

A histogram is a bit like a bar chart but is used to illustrate continuous or interval data (rather than discrete data or whole numbers).

histogram example

Because the data on the x axis is continuous, there are no gaps between the bars.

line graph example

For example, the line graph above illustrates 3 different people’s progression in a strength training program over time.

pie chart example

For example, the frequency with which different attachment styles occurred in Ainsworth’s strange situation could be represented by the pie chart opposite.

Inferential testing

Probability and significance.

The point of inferential testing is to see whether a study’s results are statistically significant , i.e. whether any observed effects are as a result of whatever is being studied rather than just random chance.

For example, let’s say you are studying whether flipping a coin outdoors increases the likelihood of getting heads. You flip the coin 100 times and get 52 heads and 48 tails. Assuming a baseline expectation of 50:50, you might take these results to mean that flipping the coin outdoors does increase the likelihood of getting heads. However, from 100 coin flips, a ratio of 52:48 between heads and tails is not very significant and could have occurred due to luck. So, the probability that this difference in heads and tails is because you flipped the coin outside (rather than just luck) is low.

Probability is denoted by the symbol p . The lower the p value, the more statistically significant your results are. You can never get a p value of 0, though, so researchers will set a threshold at which point the results are considered statistically significant enough to reject the null hypothesis . In psychology, this threshold is usually <0.05, which means there is a less than 5% chance the observed effect is due to luck and a >95% chance it is a real effect.

Type 1 and type 2 errors

When interpreting statistical significance, there are two types of errors:

  • E.g. The p threshold is <0.05, but the researchers’ results are among the 5% of fluke outcomes that look significant but are just due to luck
  • E.g. The p threshold is set too low (e.g. <0.01), and the data falls short (e.g. p=<0.02)

Increasing the sample size reduces the likelihood of type 1 and type 2 errors.

Key maths skills made easy!

psychology research methods maths skills revision guide

Types of statistical test

Note: The inferential tests below are needed for A level only, if you are taking the AS exam , you only need to know the sign test .

There are several different types of inferential test in addition to the sign test . Which inferential test is best for a study will depend on the following three criteria:

  • Whether you are looking for a difference or a correlation
  • E.g. at the competition there were 8 runners, 12 swimmers, and 6 long jumpers (it’s not like there are in-between measurements between ‘swimmer’ and ‘runner’)
  • E.g. First, second, and third place in a race
  • E.g. Ranking your mood on a scale of 1-10
  • E.g. Weights in kg
  • E.g. Heights in cm
  • E.g. Times in seconds
  • Whether the experimental design is related (i.e. repeated measures ) or unrelated (i.e. independent groups )

The following table shows which inferential test is appropriate according to these criteria:

Note: You won’t have to work out all these tests from scratch, but you may need to:

  • Say which of the statistical tests is appropriate (i.e. based on whether it’s a difference or correlation; whether the data is nominal, ordinal, or interval; and whether the data is related or unrelated).
  • Identify the critical value from a critical values table and use this to say whether a result (which will be given to you in the exam) is statistically significant.

The sign test

The sign test is a way to calculate the statistical significance of differences between related pairs (e.g. before and after in a repeated measures experiment ) of nominal data. If the observed value (s) is equal or less than the critical value (cv), the results are statistically significant.

Example: Let’s say we ran an experiment on 10 participants to see whether they prefer movie A or movie B .

  • n = 9 (because even though there are 10 participants, one participant had no change so we exclude them from our calculation)
  • In this case our experimental hypothesis is two-tailed: Participants may prefer movie A or movie B
  • (The null hypothesis is that participants like both movies equally)
  • In this case, let’s say it’s 0.1
  • The experimental hypothesis is two-tailed
  • So, in this example, our critical value (cv) is 1
  • In this example, there are 2 As, so our observed value (s) is 2
  • In this example, the observed value (2) is greater than the critical value (1) and so the results are not statistically significant. This means we must accept the null hypothesis and reject the experimental hypothesis .

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The Use of Research Methods in Psychological Research: A Systematised Review

Salomé elizabeth scholtz.

1 Community Psychosocial Research (COMPRES), School of Psychosocial Health, North-West University, Potchefstroom, South Africa

Werner de Klerk

Leon t. de beer.

2 WorkWell Research Institute, North-West University, Potchefstroom, South Africa

Research methods play an imperative role in research quality as well as educating young researchers, however, the application thereof is unclear which can be detrimental to the field of psychology. Therefore, this systematised review aimed to determine what research methods are being used, how these methods are being used and for what topics in the field. Our review of 999 articles from five journals over a period of 5 years indicated that psychology research is conducted in 10 topics via predominantly quantitative research methods. Of these 10 topics, social psychology was the most popular. The remainder of the conducted methodology is described. It was also found that articles lacked rigour and transparency in the used methodology which has implications for replicability. In conclusion this article, provides an overview of all reported methodologies used in a sample of psychology journals. It highlights the popularity and application of methods and designs throughout the article sample as well as an unexpected lack of rigour with regard to most aspects of methodology. Possible sample bias should be considered when interpreting the results of this study. It is recommended that future research should utilise the results of this study to determine the possible impact on the field of psychology as a science and to further investigation into the use of research methods. Results should prompt the following future research into: a lack or rigour and its implication on replication, the use of certain methods above others, publication bias and choice of sampling method.

Introduction

Psychology is an ever-growing and popular field (Gough and Lyons, 2016 ; Clay, 2017 ). Due to this growth and the need for science-based research to base health decisions on (Perestelo-Pérez, 2013 ), the use of research methods in the broad field of psychology is an essential point of investigation (Stangor, 2011 ; Aanstoos, 2014 ). Research methods are therefore viewed as important tools used by researchers to collect data (Nieuwenhuis, 2016 ) and include the following: quantitative, qualitative, mixed method and multi method (Maree, 2016 ). Additionally, researchers also employ various types of literature reviews to address research questions (Grant and Booth, 2009 ). According to literature, what research method is used and why a certain research method is used is complex as it depends on various factors that may include paradigm (O'Neil and Koekemoer, 2016 ), research question (Grix, 2002 ), or the skill and exposure of the researcher (Nind et al., 2015 ). How these research methods are employed is also difficult to discern as research methods are often depicted as having fixed boundaries that are continuously crossed in research (Johnson et al., 2001 ; Sandelowski, 2011 ). Examples of this crossing include adding quantitative aspects to qualitative studies (Sandelowski et al., 2009 ), or stating that a study used a mixed-method design without the study having any characteristics of this design (Truscott et al., 2010 ).

The inappropriate use of research methods affects how students and researchers improve and utilise their research skills (Scott Jones and Goldring, 2015 ), how theories are developed (Ngulube, 2013 ), and the credibility of research results (Levitt et al., 2017 ). This, in turn, can be detrimental to the field (Nind et al., 2015 ), journal publication (Ketchen et al., 2008 ; Ezeh et al., 2010 ), and attempts to address public social issues through psychological research (Dweck, 2017 ). This is especially important given the now well-known replication crisis the field is facing (Earp and Trafimow, 2015 ; Hengartner, 2018 ).

Due to this lack of clarity on method use and the potential impact of inept use of research methods, the aim of this study was to explore the use of research methods in the field of psychology through a review of journal publications. Chaichanasakul et al. ( 2011 ) identify reviewing articles as the opportunity to examine the development, growth and progress of a research area and overall quality of a journal. Studies such as Lee et al. ( 1999 ) as well as Bluhm et al. ( 2011 ) review of qualitative methods has attempted to synthesis the use of research methods and indicated the growth of qualitative research in American and European journals. Research has also focused on the use of research methods in specific sub-disciplines of psychology, for example, in the field of Industrial and Organisational psychology Coetzee and Van Zyl ( 2014 ) found that South African publications tend to consist of cross-sectional quantitative research methods with underrepresented longitudinal studies. Qualitative studies were found to make up 21% of the articles published from 1995 to 2015 in a similar study by O'Neil and Koekemoer ( 2016 ). Other methods in health psychology, such as Mixed methods research have also been reportedly growing in popularity (O'Cathain, 2009 ).

A broad overview of the use of research methods in the field of psychology as a whole is however, not available in the literature. Therefore, our research focused on answering what research methods are being used, how these methods are being used and for what topics in practice (i.e., journal publications) in order to provide a general perspective of method used in psychology publication. We synthesised the collected data into the following format: research topic [areas of scientific discourse in a field or the current needs of a population (Bittermann and Fischer, 2018 )], method [data-gathering tools (Nieuwenhuis, 2016 )], sampling [elements chosen from a population to partake in research (Ritchie et al., 2009 )], data collection [techniques and research strategy (Maree, 2016 )], and data analysis [discovering information by examining bodies of data (Ktepi, 2016 )]. A systematised review of recent articles (2013 to 2017) collected from five different journals in the field of psychological research was conducted.

Grant and Booth ( 2009 ) describe systematised reviews as the review of choice for post-graduate studies, which is employed using some elements of a systematic review and seldom more than one or two databases to catalogue studies after a comprehensive literature search. The aspects used in this systematised review that are similar to that of a systematic review were a full search within the chosen database and data produced in tabular form (Grant and Booth, 2009 ).

Sample sizes and timelines vary in systematised reviews (see Lowe and Moore, 2014 ; Pericall and Taylor, 2014 ; Barr-Walker, 2017 ). With no clear parameters identified in the literature (see Grant and Booth, 2009 ), the sample size of this study was determined by the purpose of the sample (Strydom, 2011 ), and time and cost constraints (Maree and Pietersen, 2016 ). Thus, a non-probability purposive sample (Ritchie et al., 2009 ) of the top five psychology journals from 2013 to 2017 was included in this research study. Per Lee ( 2015 ) American Psychological Association (APA) recommends the use of the most up-to-date sources for data collection with consideration of the context of the research study. As this research study focused on the most recent trends in research methods used in the broad field of psychology, the identified time frame was deemed appropriate.

Psychology journals were only included if they formed part of the top five English journals in the miscellaneous psychology domain of the Scimago Journal and Country Rank (Scimago Journal & Country Rank, 2017 ). The Scimago Journal and Country Rank provides a yearly updated list of publicly accessible journal and country-specific indicators derived from the Scopus® database (Scopus, 2017b ) by means of the Scimago Journal Rank (SJR) indicator developed by Scimago from the algorithm Google PageRank™ (Scimago Journal & Country Rank, 2017 ). Scopus is the largest global database of abstracts and citations from peer-reviewed journals (Scopus, 2017a ). Reasons for the development of the Scimago Journal and Country Rank list was to allow researchers to assess scientific domains, compare country rankings, and compare and analyse journals (Scimago Journal & Country Rank, 2017 ), which supported the aim of this research study. Additionally, the goals of the journals had to focus on topics in psychology in general with no preference to specific research methods and have full-text access to articles.

The following list of top five journals in 2018 fell within the abovementioned inclusion criteria (1) Australian Journal of Psychology, (2) British Journal of Psychology, (3) Europe's Journal of Psychology, (4) International Journal of Psychology and lastly the (5) Journal of Psychology Applied and Interdisciplinary.

Journals were excluded from this systematised review if no full-text versions of their articles were available, if journals explicitly stated a publication preference for certain research methods, or if the journal only published articles in a specific discipline of psychological research (for example, industrial psychology, clinical psychology etc.).

The researchers followed a procedure (see Figure 1 ) adapted from that of Ferreira et al. ( 2016 ) for systematised reviews. Data collection and categorisation commenced on 4 December 2017 and continued until 30 June 2019. All the data was systematically collected and coded manually (Grant and Booth, 2009 ) with an independent person acting as co-coder. Codes of interest included the research topic, method used, the design used, sampling method, and methodology (the method used for data collection and data analysis). These codes were derived from the wording in each article. Themes were created based on the derived codes and checked by the co-coder. Lastly, these themes were catalogued into a table as per the systematised review design.

An external file that holds a picture, illustration, etc.
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Systematised review procedure.

According to Johnston et al. ( 2019 ), “literature screening, selection, and data extraction/analyses” (p. 7) are specifically tailored to the aim of a review. Therefore, the steps followed in a systematic review must be reported in a comprehensive and transparent manner. The chosen systematised design adhered to the rigour expected from systematic reviews with regard to full search and data produced in tabular form (Grant and Booth, 2009 ). The rigorous application of the systematic review is, therefore discussed in relation to these two elements.

Firstly, to ensure a comprehensive search, this research study promoted review transparency by following a clear protocol outlined according to each review stage before collecting data (Johnston et al., 2019 ). This protocol was similar to that of Ferreira et al. ( 2016 ) and approved by three research committees/stakeholders and the researchers (Johnston et al., 2019 ). The eligibility criteria for article inclusion was based on the research question and clearly stated, and the process of inclusion was recorded on an electronic spreadsheet to create an evidence trail (Bandara et al., 2015 ; Johnston et al., 2019 ). Microsoft Excel spreadsheets are a popular tool for review studies and can increase the rigour of the review process (Bandara et al., 2015 ). Screening for appropriate articles for inclusion forms an integral part of a systematic review process (Johnston et al., 2019 ). This step was applied to two aspects of this research study: the choice of eligible journals and articles to be included. Suitable journals were selected by the first author and reviewed by the second and third authors. Initially, all articles from the chosen journals were included. Then, by process of elimination, those irrelevant to the research aim, i.e., interview articles or discussions etc., were excluded.

To ensure rigourous data extraction, data was first extracted by one reviewer, and an independent person verified the results for completeness and accuracy (Johnston et al., 2019 ). The research question served as a guide for efficient, organised data extraction (Johnston et al., 2019 ). Data was categorised according to the codes of interest, along with article identifiers for audit trails such as authors, title and aims of articles. The categorised data was based on the aim of the review (Johnston et al., 2019 ) and synthesised in tabular form under methods used, how these methods were used, and for what topics in the field of psychology.

The initial search produced a total of 1,145 articles from the 5 journals identified. Inclusion and exclusion criteria resulted in a final sample of 999 articles ( Figure 2 ). Articles were co-coded into 84 codes, from which 10 themes were derived ( Table 1 ).

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Journal article frequency.

Codes used to form themes (research topics).

These 10 themes represent the topic section of our research question ( Figure 3 ). All these topics except, for the final one, psychological practice , were found to concur with the research areas in psychology as identified by Weiten ( 2010 ). These research areas were chosen to represent the derived codes as they provided broad definitions that allowed for clear, concise categorisation of the vast amount of data. Article codes were categorised under particular themes/topics if they adhered to the research area definitions created by Weiten ( 2010 ). It is important to note that these areas of research do not refer to specific disciplines in psychology, such as industrial psychology; but to broader fields that may encompass sub-interests of these disciplines.

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Topic frequency (international sample).

In the case of developmental psychology , researchers conduct research into human development from childhood to old age. Social psychology includes research on behaviour governed by social drivers. Researchers in the field of educational psychology study how people learn and the best way to teach them. Health psychology aims to determine the effect of psychological factors on physiological health. Physiological psychology , on the other hand, looks at the influence of physiological aspects on behaviour. Experimental psychology is not the only theme that uses experimental research and focuses on the traditional core topics of psychology (for example, sensation). Cognitive psychology studies the higher mental processes. Psychometrics is concerned with measuring capacity or behaviour. Personality research aims to assess and describe consistency in human behaviour (Weiten, 2010 ). The final theme of psychological practice refers to the experiences, techniques, and interventions employed by practitioners, researchers, and academia in the field of psychology.

Articles under these themes were further subdivided into methodologies: method, sampling, design, data collection, and data analysis. The categorisation was based on information stated in the articles and not inferred by the researchers. Data were compiled into two sets of results presented in this article. The first set addresses the aim of this study from the perspective of the topics identified. The second set of results represents a broad overview of the results from the perspective of the methodology employed. The second set of results are discussed in this article, while the first set is presented in table format. The discussion thus provides a broad overview of methods use in psychology (across all themes), while the table format provides readers with in-depth insight into methods used in the individual themes identified. We believe that presenting the data from both perspectives allow readers a broad understanding of the results. Due a large amount of information that made up our results, we followed Cichocka and Jost ( 2014 ) in simplifying our results. Please note that the numbers indicated in the table in terms of methodology differ from the total number of articles. Some articles employed more than one method/sampling technique/design/data collection method/data analysis in their studies.

What follows is the results for what methods are used, how these methods are used, and which topics in psychology they are applied to . Percentages are reported to the second decimal in order to highlight small differences in the occurrence of methodology.

Firstly, with regard to the research methods used, our results show that researchers are more likely to use quantitative research methods (90.22%) compared to all other research methods. Qualitative research was the second most common research method but only made up about 4.79% of the general method usage. Reviews occurred almost as much as qualitative studies (3.91%), as the third most popular method. Mixed-methods research studies (0.98%) occurred across most themes, whereas multi-method research was indicated in only one study and amounted to 0.10% of the methods identified. The specific use of each method in the topics identified is shown in Table 2 and Figure 4 .

Research methods in psychology.

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Research method frequency in topics.

Secondly, in the case of how these research methods are employed , our study indicated the following.

Sampling −78.34% of the studies in the collected articles did not specify a sampling method. From the remainder of the studies, 13 types of sampling methods were identified. These sampling methods included broad categorisation of a sample as, for example, a probability or non-probability sample. General samples of convenience were the methods most likely to be applied (10.34%), followed by random sampling (3.51%), snowball sampling (2.73%), and purposive (1.37%) and cluster sampling (1.27%). The remainder of the sampling methods occurred to a more limited extent (0–1.0%). See Table 3 and Figure 5 for sampling methods employed in each topic.

Sampling use in the field of psychology.

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Sampling method frequency in topics.

Designs were categorised based on the articles' statement thereof. Therefore, it is important to note that, in the case of quantitative studies, non-experimental designs (25.55%) were often indicated due to a lack of experiments and any other indication of design, which, according to Laher ( 2016 ), is a reasonable categorisation. Non-experimental designs should thus be compared with experimental designs only in the description of data, as it could include the use of correlational/cross-sectional designs, which were not overtly stated by the authors. For the remainder of the research methods, “not stated” (7.12%) was assigned to articles without design types indicated.

From the 36 identified designs the most popular designs were cross-sectional (23.17%) and experimental (25.64%), which concurred with the high number of quantitative studies. Longitudinal studies (3.80%), the third most popular design, was used in both quantitative and qualitative studies. Qualitative designs consisted of ethnography (0.38%), interpretative phenomenological designs/phenomenology (0.28%), as well as narrative designs (0.28%). Studies that employed the review method were mostly categorised as “not stated,” with the most often stated review designs being systematic reviews (0.57%). The few mixed method studies employed exploratory, explanatory (0.09%), and concurrent designs (0.19%), with some studies referring to separate designs for the qualitative and quantitative methods. The one study that identified itself as a multi-method study used a longitudinal design. Please see how these designs were employed in each specific topic in Table 4 , Figure 6 .

Design use in the field of psychology.

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Design frequency in topics.

Data collection and analysis —data collection included 30 methods, with the data collection method most often employed being questionnaires (57.84%). The experimental task (16.56%) was the second most preferred collection method, which included established or unique tasks designed by the researchers. Cognitive ability tests (6.84%) were also regularly used along with various forms of interviewing (7.66%). Table 5 and Figure 7 represent data collection use in the various topics. Data analysis consisted of 3,857 occurrences of data analysis categorised into ±188 various data analysis techniques shown in Table 6 and Figures 1 – 7 . Descriptive statistics were the most commonly used (23.49%) along with correlational analysis (17.19%). When using a qualitative method, researchers generally employed thematic analysis (0.52%) or different forms of analysis that led to coding and the creation of themes. Review studies presented few data analysis methods, with most studies categorising their results. Mixed method and multi-method studies followed the analysis methods identified for the qualitative and quantitative studies included.

Data collection in the field of psychology.

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Data collection frequency in topics.

Data analysis in the field of psychology.

Results of the topics researched in psychology can be seen in the tables, as previously stated in this article. It is noteworthy that, of the 10 topics, social psychology accounted for 43.54% of the studies, with cognitive psychology the second most popular research topic at 16.92%. The remainder of the topics only occurred in 4.0–7.0% of the articles considered. A list of the included 999 articles is available under the section “View Articles” on the following website: https://methodgarden.xtrapolate.io/ . This website was created by Scholtz et al. ( 2019 ) to visually present a research framework based on this Article's results.

This systematised review categorised full-length articles from five international journals across the span of 5 years to provide insight into the use of research methods in the field of psychology. Results indicated what methods are used how these methods are being used and for what topics (why) in the included sample of articles. The results should be seen as providing insight into method use and by no means a comprehensive representation of the aforementioned aim due to the limited sample. To our knowledge, this is the first research study to address this topic in this manner. Our discussion attempts to promote a productive way forward in terms of the key results for method use in psychology, especially in the field of academia (Holloway, 2008 ).

With regard to the methods used, our data stayed true to literature, finding only common research methods (Grant and Booth, 2009 ; Maree, 2016 ) that varied in the degree to which they were employed. Quantitative research was found to be the most popular method, as indicated by literature (Breen and Darlaston-Jones, 2010 ; Counsell and Harlow, 2017 ) and previous studies in specific areas of psychology (see Coetzee and Van Zyl, 2014 ). Its long history as the first research method (Leech et al., 2007 ) in the field of psychology as well as researchers' current application of mathematical approaches in their studies (Toomela, 2010 ) might contribute to its popularity today. Whatever the case may be, our results show that, despite the growth in qualitative research (Demuth, 2015 ; Smith and McGannon, 2018 ), quantitative research remains the first choice for article publication in these journals. Despite the included journals indicating openness to articles that apply any research methods. This finding may be due to qualitative research still being seen as a new method (Burman and Whelan, 2011 ) or reviewers' standards being higher for qualitative studies (Bluhm et al., 2011 ). Future research is encouraged into the possible biasness in publication of research methods, additionally further investigation with a different sample into the proclaimed growth of qualitative research may also provide different results.

Review studies were found to surpass that of multi-method and mixed method studies. To this effect Grant and Booth ( 2009 ), state that the increased awareness, journal contribution calls as well as its efficiency in procuring research funds all promote the popularity of reviews. The low frequency of mixed method studies contradicts the view in literature that it's the third most utilised research method (Tashakkori and Teddlie's, 2003 ). Its' low occurrence in this sample could be due to opposing views on mixing methods (Gunasekare, 2015 ) or that authors prefer publishing in mixed method journals, when using this method, or its relative novelty (Ivankova et al., 2016 ). Despite its low occurrence, the application of the mixed methods design in articles was methodologically clear in all cases which were not the case for the remainder of research methods.

Additionally, a substantial number of studies used a combination of methodologies that are not mixed or multi-method studies. Perceived fixed boundaries are according to literature often set aside, as confirmed by this result, in order to investigate the aim of a study, which could create a new and helpful way of understanding the world (Gunasekare, 2015 ). According to Toomela ( 2010 ), this is not unheard of and could be considered a form of “structural systemic science,” as in the case of qualitative methodology (observation) applied in quantitative studies (experimental design) for example. Based on this result, further research into this phenomenon as well as its implications for research methods such as multi and mixed methods is recommended.

Discerning how these research methods were applied, presented some difficulty. In the case of sampling, most studies—regardless of method—did mention some form of inclusion and exclusion criteria, but no definite sampling method. This result, along with the fact that samples often consisted of students from the researchers' own academic institutions, can contribute to literature and debates among academics (Peterson and Merunka, 2014 ; Laher, 2016 ). Samples of convenience and students as participants especially raise questions about the generalisability and applicability of results (Peterson and Merunka, 2014 ). This is because attention to sampling is important as inappropriate sampling can debilitate the legitimacy of interpretations (Onwuegbuzie and Collins, 2017 ). Future investigation into the possible implications of this reported popular use of convenience samples for the field of psychology as well as the reason for this use could provide interesting insight, and is encouraged by this study.

Additionally, and this is indicated in Table 6 , articles seldom report the research designs used, which highlights the pressing aspect of the lack of rigour in the included sample. Rigour with regards to the applied empirical method is imperative in promoting psychology as a science (American Psychological Association, 2020 ). Omitting parts of the research process in publication when it could have been used to inform others' research skills should be questioned, and the influence on the process of replicating results should be considered. Publications are often rejected due to a lack of rigour in the applied method and designs (Fonseca, 2013 ; Laher, 2016 ), calling for increased clarity and knowledge of method application. Replication is a critical part of any field of scientific research and requires the “complete articulation” of the study methods used (Drotar, 2010 , p. 804). The lack of thorough description could be explained by the requirements of certain journals to only report on certain aspects of a research process, especially with regard to the applied design (Laher, 20). However, naming aspects such as sampling and designs, is a requirement according to the APA's Journal Article Reporting Standards (JARS-Quant) (Appelbaum et al., 2018 ). With very little information on how a study was conducted, authors lose a valuable opportunity to enhance research validity, enrich the knowledge of others, and contribute to the growth of psychology and methodology as a whole. In the case of this research study, it also restricted our results to only reported samples and designs, which indicated a preference for certain designs, such as cross-sectional designs for quantitative studies.

Data collection and analysis were for the most part clearly stated. A key result was the versatile use of questionnaires. Researchers would apply a questionnaire in various ways, for example in questionnaire interviews, online surveys, and written questionnaires across most research methods. This may highlight a trend for future research.

With regard to the topics these methods were employed for, our research study found a new field named “psychological practice.” This result may show the growing consciousness of researchers as part of the research process (Denzin and Lincoln, 2003 ), psychological practice, and knowledge generation. The most popular of these topics was social psychology, which is generously covered in journals and by learning societies, as testaments of the institutional support and richness social psychology has in the field of psychology (Chryssochoou, 2015 ). The APA's perspective on 2018 trends in psychology also identifies an increased amount of psychology focus on how social determinants are influencing people's health (Deangelis, 2017 ).

This study was not without limitations and the following should be taken into account. Firstly, this study used a sample of five specific journals to address the aim of the research study, despite general journal aims (as stated on journal websites), this inclusion signified a bias towards the research methods published in these specific journals only and limited generalisability. A broader sample of journals over a different period of time, or a single journal over a longer period of time might provide different results. A second limitation is the use of Excel spreadsheets and an electronic system to log articles, which was a manual process and therefore left room for error (Bandara et al., 2015 ). To address this potential issue, co-coding was performed to reduce error. Lastly, this article categorised data based on the information presented in the article sample; there was no interpretation of what methodology could have been applied or whether the methods stated adhered to the criteria for the methods used. Thus, a large number of articles that did not clearly indicate a research method or design could influence the results of this review. However, this in itself was also a noteworthy result. Future research could review research methods of a broader sample of journals with an interpretive review tool that increases rigour. Additionally, the authors also encourage the future use of systematised review designs as a way to promote a concise procedure in applying this design.

Our research study presented the use of research methods for published articles in the field of psychology as well as recommendations for future research based on these results. Insight into the complex questions identified in literature, regarding what methods are used how these methods are being used and for what topics (why) was gained. This sample preferred quantitative methods, used convenience sampling and presented a lack of rigorous accounts for the remaining methodologies. All methodologies that were clearly indicated in the sample were tabulated to allow researchers insight into the general use of methods and not only the most frequently used methods. The lack of rigorous account of research methods in articles was represented in-depth for each step in the research process and can be of vital importance to address the current replication crisis within the field of psychology. Recommendations for future research aimed to motivate research into the practical implications of the results for psychology, for example, publication bias and the use of convenience samples.

Ethics Statement

This study was cleared by the North-West University Health Research Ethics Committee: NWU-00115-17-S1.

Author Contributions

All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Writing Research Papers

  • Research Paper Structure

Whether you are writing a B.S. Degree Research Paper or completing a research report for a Psychology course, it is highly likely that you will need to organize your research paper in accordance with American Psychological Association (APA) guidelines.  Here we discuss the structure of research papers according to APA style.

Major Sections of a Research Paper in APA Style

A complete research paper in APA style that is reporting on experimental research will typically contain a Title page, Abstract, Introduction, Methods, Results, Discussion, and References sections. 1  Many will also contain Figures and Tables and some will have an Appendix or Appendices.  These sections are detailed as follows (for a more in-depth guide, please refer to " How to Write a Research Paper in APA Style ”, a comprehensive guide developed by Prof. Emma Geller). 2

What is this paper called and who wrote it? – the first page of the paper; this includes the name of the paper, a “running head”, authors, and institutional affiliation of the authors.  The institutional affiliation is usually listed in an Author Note that is placed towards the bottom of the title page.  In some cases, the Author Note also contains an acknowledgment of any funding support and of any individuals that assisted with the research project.

One-paragraph summary of the entire study – typically no more than 250 words in length (and in many cases it is well shorter than that), the Abstract provides an overview of the study.

Introduction

What is the topic and why is it worth studying? – the first major section of text in the paper, the Introduction commonly describes the topic under investigation, summarizes or discusses relevant prior research (for related details, please see the Writing Literature Reviews section of this website), identifies unresolved issues that the current research will address, and provides an overview of the research that is to be described in greater detail in the sections to follow.

What did you do? – a section which details how the research was performed.  It typically features a description of the participants/subjects that were involved, the study design, the materials that were used, and the study procedure.  If there were multiple experiments, then each experiment may require a separate Methods section.  A rule of thumb is that the Methods section should be sufficiently detailed for another researcher to duplicate your research.

What did you find? – a section which describes the data that was collected and the results of any statistical tests that were performed.  It may also be prefaced by a description of the analysis procedure that was used. If there were multiple experiments, then each experiment may require a separate Results section.

What is the significance of your results? – the final major section of text in the paper.  The Discussion commonly features a summary of the results that were obtained in the study, describes how those results address the topic under investigation and/or the issues that the research was designed to address, and may expand upon the implications of those findings.  Limitations and directions for future research are also commonly addressed.

List of articles and any books cited – an alphabetized list of the sources that are cited in the paper (by last name of the first author of each source).  Each reference should follow specific APA guidelines regarding author names, dates, article titles, journal titles, journal volume numbers, page numbers, book publishers, publisher locations, websites, and so on (for more information, please see the Citing References in APA Style page of this website).

Tables and Figures

Graphs and data (optional in some cases) – depending on the type of research being performed, there may be Tables and/or Figures (however, in some cases, there may be neither).  In APA style, each Table and each Figure is placed on a separate page and all Tables and Figures are included after the References.   Tables are included first, followed by Figures.   However, for some journals and undergraduate research papers (such as the B.S. Research Paper or Honors Thesis), Tables and Figures may be embedded in the text (depending on the instructor’s or editor’s policies; for more details, see "Deviations from APA Style" below).

Supplementary information (optional) – in some cases, additional information that is not critical to understanding the research paper, such as a list of experiment stimuli, details of a secondary analysis, or programming code, is provided.  This is often placed in an Appendix.

Variations of Research Papers in APA Style

Although the major sections described above are common to most research papers written in APA style, there are variations on that pattern.  These variations include: 

  • Literature reviews – when a paper is reviewing prior published research and not presenting new empirical research itself (such as in a review article, and particularly a qualitative review), then the authors may forgo any Methods and Results sections. Instead, there is a different structure such as an Introduction section followed by sections for each of the different aspects of the body of research being reviewed, and then perhaps a Discussion section. 
  • Multi-experiment papers – when there are multiple experiments, it is common to follow the Introduction with an Experiment 1 section, itself containing Methods, Results, and Discussion subsections. Then there is an Experiment 2 section with a similar structure, an Experiment 3 section with a similar structure, and so on until all experiments are covered.  Towards the end of the paper there is a General Discussion section followed by References.  Additionally, in multi-experiment papers, it is common for the Results and Discussion subsections for individual experiments to be combined into single “Results and Discussion” sections.

Departures from APA Style

In some cases, official APA style might not be followed (however, be sure to check with your editor, instructor, or other sources before deviating from standards of the Publication Manual of the American Psychological Association).  Such deviations may include:

  • Placement of Tables and Figures  – in some cases, to make reading through the paper easier, Tables and/or Figures are embedded in the text (for example, having a bar graph placed in the relevant Results section). The embedding of Tables and/or Figures in the text is one of the most common deviations from APA style (and is commonly allowed in B.S. Degree Research Papers and Honors Theses; however you should check with your instructor, supervisor, or editor first). 
  • Incomplete research – sometimes a B.S. Degree Research Paper in this department is written about research that is currently being planned or is in progress. In those circumstances, sometimes only an Introduction and Methods section, followed by References, is included (that is, in cases where the research itself has not formally begun).  In other cases, preliminary results are presented and noted as such in the Results section (such as in cases where the study is underway but not complete), and the Discussion section includes caveats about the in-progress nature of the research.  Again, you should check with your instructor, supervisor, or editor first.
  • Class assignments – in some classes in this department, an assignment must be written in APA style but is not exactly a traditional research paper (for instance, a student asked to write about an article that they read, and to write that report in APA style). In that case, the structure of the paper might approximate the typical sections of a research paper in APA style, but not entirely.  You should check with your instructor for further guidelines.

Workshops and Downloadable Resources

  • For in-person discussion of the process of writing research papers, please consider attending this department’s “Writing Research Papers” workshop (for dates and times, please check the undergraduate workshops calendar).

Downloadable Resources

  • How to Write APA Style Research Papers (a comprehensive guide) [ PDF ]
  • Tips for Writing APA Style Research Papers (a brief summary) [ PDF ]
  • Example APA Style Research Paper (for B.S. Degree – empirical research) [ PDF ]
  • Example APA Style Research Paper (for B.S. Degree – literature review) [ PDF ]

Further Resources

How-To Videos     

  • Writing Research Paper Videos

APA Journal Article Reporting Guidelines

  • Appelbaum, M., Cooper, H., Kline, R. B., Mayo-Wilson, E., Nezu, A. M., & Rao, S. M. (2018). Journal article reporting standards for quantitative research in psychology: The APA Publications and Communications Board task force report . American Psychologist , 73 (1), 3.
  • Levitt, H. M., Bamberg, M., Creswell, J. W., Frost, D. M., Josselson, R., & Suárez-Orozco, C. (2018). Journal article reporting standards for qualitative primary, qualitative meta-analytic, and mixed methods research in psychology: The APA Publications and Communications Board task force report . American Psychologist , 73 (1), 26.  

External Resources

  • Formatting APA Style Papers in Microsoft Word
  • How to Write an APA Style Research Paper from Hamilton University
  • WikiHow Guide to Writing APA Research Papers
  • Sample APA Formatted Paper with Comments
  • Sample APA Formatted Paper
  • Tips for Writing a Paper in APA Style

1 VandenBos, G. R. (Ed). (2010). Publication manual of the American Psychological Association (6th ed.) (pp. 41-60).  Washington, DC: American Psychological Association.

2 geller, e. (2018).  how to write an apa-style research report . [instructional materials]. , prepared by s. c. pan for ucsd psychology.

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  • What Types of References Are Appropriate?
  • Evaluating References and Taking Notes
  • Citing References
  • Writing a Literature Review
  • Writing Process and Revising
  • Improving Scientific Writing
  • Academic Integrity and Avoiding Plagiarism
  • Writing Research Papers Videos

Assignment 1 Types of Research Methods - An Nguyen

STUDY PROTOCOL article

A quasi-experimental mixed-method pilot study to check the efficacy of the “sound” active and passive music-based intervention on mental wellbeing and residual cognition of older people with dementia and dementia professionals’ burnout: a research protocol.

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  • 1 Centre for Socio-Economic Research on Aging, IRCCS INRCA-National Institute of Health and Science on Aging, Ancona, Italy
  • 2 Asociatia Habilitas – Centru de Resurse si Formare Profesionala, Bucharest, Romania
  • 3 Associação-Sons do Estaminé, Trofa, Portugal
  • 4 Associazione Centro Musicale Alessandro Orlandini-ACMO, Ancona, Italy
  • 5 Scoala de Pian by Lena Napradean, Bucharest, Romania
  • 6 Centre for Biostatistics and Applied Geriatric Clinical Epidemiology, IRCCS INRCA-National Institute of Health and Science on Ageing, Ancona, Italy

Purpose: The SOUND method offers an innovative blended intervention based on music circle-activities and cognitive stimulation approaches which was co-designed by musicians, health professionals, older people with dementia, family caregivers and researchers, for its application in dementia settings. The purpose of the paper is to describe the detailed procedure of the quasi-experimental pilot study.

Method: The experimental phase of SOUND uses a mixed-method design encompassing qualitative and quantitative observations, cognitive testing, self-report and interviewer-assisted questionnaires to investigate the effectiveness of the intervention for 45 people with dementia and 45 professionals (15 in every study country: Italy, Portugal, Romania).

Results: The pilot study will be the first implementation of the SOUND intervention aiming to investigate the feasibility and preliminary effects of the method.

Conclusion: The novelty of SOUND is its multicomponent method, including the most evidenced features for improving the wellbeing of participants.

1 Introduction

Dementia is an umbrella term to describe a set of cognitive, psychological and behavioral symptoms caused by brain diseases or conditions which are often progressive and non-reversible. The most common form of dementia, 60–70% of cases, is Alzheimer’s disease. Dementia is mostly prevalent in older age, with a significant increase over time as it almost doubles every 5 years after the age of 65 ( World Health Organization, 2021 ). It is estimated that over 55 million of people live with dementia worldwide of which 9.780.678 in Europe ( Alzheimer Europe, 2019 ; World Health Organization, 2021 ). This global epidemic is expected to almost triple by 2050 because of population ageing particularly in low and middle-income countries ( World Health Organization, 2021 ).

There is no cure for dementia, although certain pharmacological treatments may slow down the progression of the disease. Nevertheless, evidence shows that pharmacological therapies for treating the psychological and behavioral symptoms of dementia (BPSD) have limited efficacy, severe adverse effects and increased mortality. Consequently, it is recommended to use non-pharmacological treatments (NPT) as a first-choice intervention ( Magierski et al., 2020 ; Carrarini et al., 2021 ). In fact, NPT can be complementary treatments as, with a minimal risk for adverse effects, they can prevent and reduce BPSD, endorse quality of life, improve or maintain cognition and positively change brain activity ( Dyer et al., 2017 ; Chalfont et al., 2018 ; Shigihara et al., 2020 ). A range of NPT are available, such as socio and psycho-educational approaches, cognitive and emotion interventions, physical exercise and sensorial activities (e.g., music, art and massage therapies). Other psychoeducational interventions are linked to training professionals and informal caregivers in order to reduce their stress/burnout and to improve their knowledge on dementia care ( Barbosa et al., 2014 ; Briones-Peralta et al., 2020 ). Among all, music interventions targeted to older people with dementia seem to be the most effective NPT to manage BPSD ( Abraha et al., 2017 ; Dyer et al., 2017 ). Indeed, music is associated to mental wellbeing, quality of life, self-awareness and coping in people with diagnosed health conditions and to reduced risk of depression in older people ( Daykin et al., 2017 ). Moreover, music training looks like a powerful means for preventing the neurocognitive degeneration, since music enhances cerebral plasticity and induces the creation of new connections in the brain ( Hyde et al., 2009 ; Habibi et al., 2017 ).

Musical leisure activities seem to have a positive effect on the cognitive, emotional, and neural function of older people both during normal aging ( Klimova et al., 2017 ; Särkämö, 2018 ) and with dementia ( Särkämö, 2018 ). Considering the latter, music can improve various aspects of their health and well-being: (a) cognition, especially verbal fluency and attention; (b) psychological aspects, such as mood, sense of self and identity; (c) mobility and coordination; (d) and behavior by reducing agitation, buffering isolation and strengthening communication ( Brancatisano et al., 2019 ). Some studies show that music interventions can improve the cognitive state ( Moreno-Morales et al., 2020 ), attention, immediate and delayed memory, executive function and gait speed (e.g., Domínguez-Chávez et al., 2019 ).

There is a great variety of music interventions including for instance, listening to music, playing instruments, and singing in chorus, but it is still not clear which is the most effective type of intervention and what are the factors determining their effectiveness. A relatively recent systematic review ( Moreno-Morales et al., 2020 ) underlines that interventions involving listening to music have a greater positive effect on cognitive functions compared to active musical activities, such as singing or playing an instrument. In fact, listening to music implies a wide cortical activation by requiring the integration of perception of sounds, rhythms, and lyrics, alongside the simultaneous attention to the environment ( Gaser and Schlaug, 2003 ; Soria-Urios et al., 2011 ; McDermott et al., 2012 ).

Many interventions, for example, are based on music therapy, i.e., an evidence-based practice carried out by trained and certified music therapists. Music therapy treatments can improve cognition ( Bruer et al., 2007 ; Chu et al., 2013 ) and verbal fluency ( Brotons and Koger, 2000 ; Lyu et al., 2018 ) whilst they can reduce associated symptoms of dementia such as depression ( Chu et al., 2013 ) and agitation ( Lin et al., 2010 ; Raglio et al., 2010 ; Vink et al., 2012 ; Tsoi et al., 2018 ). Music therapy can also have positive effects on clinical parameters by decreasing the systolic blood pressure of older people living in nursing home ( Uğur et al., 2016 ).

Furthermore, group music-based treatments, i.e., based on passive and active music making exercises, not necessarily music therapy driven, can also reduce apathy ( Tang et al., 2018 ), agitation ( Choi et al., 2009 ; Ho et al., 2018 ) and depression ( Ashida, 2000 ) and improve overall cognition ( Cheung et al., 2016 ; Tang et al., 2018 ), verbal fluency and memory ( Cheung et al., 2016 ). Thomas et al. (2017) demonstrated that individualized music treatments, such as personalized playlists, can have a positive effect on individuals’ mental health by reducing the use of antipsychotic medication with people with dementia.

Nevertheless, there is no agreement in the literature around the effectiveness of music-based intervention in different realms among older people with dementia, as research is still in initial stages. For example, Van der Steen et al. (2017) underlines that there is no evidence that music-based therapeutic interventions have effects on agitation or aggression, on emotional well-being or quality of life, nor on behavioral problems. Conversely, Moreno-Morales et al. (2020) conclude that there is evidence that music therapy can improve cognitive function in people living with dementia, that it can have a positive effect in the treatment of long-term depression and it can improve quality of life of people with dementia in the short-term.

The lack of evidence around the effectiveness of music interventions with OPDs, may depend on the studies small sample size, unclear assessment methods, the variety of music interventions ( Van der Steen et al., 2017 ) and of tests used for the outcomes assessment ( Moreno-Morales et al., 2020 ) and the absolute dearth of longitudinal studies that can demonstrate the long-term effect of music interventions on OPDs’ mood, cognitive and physical function ( Moreno-Morales et al., 2020 ).

Non-pharmacological treatments, including music-based intervention, can have a positive effect also on healthcare workers ( Cabrera et al., 2015 ). A qualitative study on music and dance interventions in dementia care found that healthcare staff had increased positive interactions, relationships, communication, sense of confidence, empathy, and an improved understanding of residents’ emotional state and experience of limitations ( Melhuish et al., 2016 ). Such aspects, together with the team cohesion, work engagement and job satisfaction, contribute to preventing stress and burnout of healthcare staff ( Maslach and Leiter, 1999 ; Öhman et al., 2017 ; Costello et al., 2018 ). However, there are few music-based treatments targeted to care professionals and none, to the best of our knowledge, involving both dementia care professionals and older patients.

Thus, even if the practice and part of the scientific literature, confirm the power of music in improving OPDs’ functions and care professionals’ well-being at the work place, the quality of evidence is low and so further research is needed ( Dyer et al., 2017 ).

Considering the above, further studies should include emotional well-being and social outcomes to improve the knowledge about the effects of music on older people with dementia and dementia care professionals to support the implementation of music interventions as a care strategy.

This protocol has been designed to cover this knowledge gap by testing an intervention based on active and passive music activities delivered in circle with older people with mild cognitive impairment and mild to moderate dementia, and dementia care professionals. Particularly, the study aims to investigate two principal factors: 1) the efficacy of the SOUND intervention on OPDs; and 2) the impact of implementing the SOUND intervention on the DCPs who are delivering it as a novel group. Overall, the pilot study aims to assess the feasibility and preliminary outcomes of the protocol. The study is part of the SOUND project, funded by the Erasmus + program (contract 2021-1-IT02-KA220-ADU-000033494) and aimed at designing an original music-based curriculum for dementia care professionals and testing a pilot music-based intervention with OPDs in Italy, Portugal and Romania. At the time of writing this manuscript, we were about ending the training for dementia care professionals and planning the intervention that will be concluded in the three countries in early 2024.

2 Materials and methods

2.1 study design.

The pilot study will adopt a mixed-method approach encompassing quantitative and qualitative analysis of data gathered from video recording and from psychometric and idiosyncratic tools during specific times of the trial (pre-post and longitudinal). This design was chosen in preparation of a future full-scale study that will be a non-randomized larger trial. The latter seems to be in line with the features of the intervention and with the target population. In fact, the intervention is based on the SOUND methodology that can be carried out in groups including seven or eight OPDs coupled by the same number of care professionals, according to the guidelines for music-based interventions for people with dementia recommending the involvement of few persons in every group for ensuring the effectiveness of the intervention ( Janus et al., 2020 ).

Moreover, being aware that quantitative measures alone would not be able to fully capture the possible effect of a non-pharmacological treatment on older people with a degenerative disease such as dementia, the study design also included the collection of qualitative variables e.g., through biographies and live and ex post observations. This very time-consuming methodology would not be feasible in a randomized controlled trial that would pre-suppose a very large sample of subjects.

In light of the above, this pilot study, as well as the full-scale study, will adopt a sampling for meaning procedure ( Luborsky and Rubinstein, 1995 ): people will be selected who can provide knowledge and meanings useful for understanding of individuals’ experience by taking the insider’s perspective. The latter is meaningful and informative, because has, in itself, individuals’ key symbols, values and ideas that shape and inform their experience with dementia in the role of professionals and older people with dementia ( Luborsky and Rubinstein, 1995 ). Accordingly, the sample size considered the six sampling-based considerations by Onwuegbuzie and Collins (2017) for sampling by meaning.

This pilot study will also assess the feasibility of data collection methods and intervention implementation (recruitment, retention, intervention fidelity, acceptability, adherence to the intervention, and engagement) not only for the larger scale study but also in the view of the application of the intervention with people with more severe dementia or in rehabilitative units ( Teresi et al., 2022 ). The feasibility assessment will be carried out by a senior researcher in the role of supervisor who will analyze the data collection method and the intervention implementation according to the guidelines provided by Teresi et al. (2022) .

The study includes dementia care professionals (DCPs) (e.g., neuropsychologists, physicians, educators, nurses, professional caregivers), and older people with dementia (OPDs) that will be monitored in different phases, depending on the type of variable and instrument used. Some data will be analyzed by a pre-post group comparison. The data will be collected in three moments: one week before the start of the intervention (T0), at its end (T1), and 2 weeks after the end of the intervention (T2). Data will be also collected during the intervention phase and analyzed longitudinally depending on the time frame of the collection (daily from T0 to T2 versus at each SOUND session). The Figure 1 below shows the progression of the data collection and experimental phase within the Research design.

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Figure 1. Research design.

2.2 Conditions

2.2.1 participants.

In every study country, 15 OPDs and 15 DCPs will be recruited and participate to the experimentation, for a total of 45 OPDs and 45 DCPs (90 people overall). OPDs and DCPs’ inclusion and exclusion criteria are summarized below ( Table 1 ).

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Table 1. Participants’ selection criteria.

Older people with dementias will be recruited from the study organizations, health care dementia services and community services such as diagnostic centers, dementia day care centers, residential care facilities and charities. Individuals will already have a formal diagnosis of MCI or dementia. Their level of cognitive impairment is routinely assessed by the health professionals of the organization to which they belong. Therefore, these health professionals will support the recruitment and selection processes. Ethical approval has been obtained depending on the national legal requirements. OPDs retention will be empowered by collaborating with their professional caregivers who will present the SOUND activities as a pleasant novelty and as a gift.

DCPs will be selected among those who have successfully completed the SOUND training i.e., a 22-h training based on an original SOUND curriculum 1 co-designed with OPDs, DCPs and family caregivers in Summer 2022. The training was implemented in Spring 2023 in the three study countries, by means of an e-learning platform, called Virtual Music Circle (VMC), specifically developed within the SOUND project, and of face-to face lessons, to train the professionals who will be involved in the intervention. The SOUND training concept and learning outcomes are deepened in a dedicated paper (Quattrini et al., under review) 2 . The training was open to entire teams of participating organizations. Selected DCPs will include permanent staff and trainees who may or may not have an established relationship with OPDs. DCPs will be required to study OPDs biographies to properly relate to OPDs during the intervention considering their needs and characteristics. None of the selected DCPs used the SOUND intervention prior to the trial, therefore all of them will apply it for the first time. The total number of people per every SOUND activities group will be of about 15, including both OPDs and DCPs. For example, one group may include eight OPDs, five DCPs, the facilitator and the co-facilitator. The other group may be made of seven OPDs, four DCPs, the facilitator and the co-facilitator. This will be made to guarantee the correct delivery of the intervention and provide the conditions to enhance its potentials. In fact, small-sized units of 5–15 people can positively impact older people’s well-being, behavior, functioning, and activity engagement ( Verbeek et al., 2009 ) and doing activities in small groups can hinder the participants’ cognitive decline ( Kok et al., 2016 ) and favor social connection ( Van Zadelhoff et al., 2011 ) more than in large groups.

An attendance sheet will be used to monitor participation, whereby absence from half or more of the sessions will result in a drop-out.

2.2.2 The SOUND intervention

The intervention will be implemented in Italy, in an Alzheimer day-care center, and in Portugal and Romania, in older people care facilities hosting people with dementia, where the DCPs who will be involved would regularly work. It includes 12 sessions delivered twice a week, for a 6-week period. Although there is no consensus regarding the frequency required for music-based interventions ( Moreno-Morales et al., 2020 ), past research suggests that a higher occurrence may be more impactful ( Carr et al., 2013 ).

During the intervention, OPDs and DCPs are positioned in a circle and everyone plays a specific role within the circle. OPDs will be the participants to whom the intervention is delivered. DCPs will implement the intervention by undertaking specific roles, i.e., the roles of facilitator, co-facilitator or internal observer. The role of facilitator will be assigned to a musician or a DCP with music skills, previously trained in the SOUND method. During the sessions, the facilitator proposes the activities to the participants in a responsorial style, holds the circle, welcomes and repeats any spontaneous and unexpected activity coming from the participants and proposes it to the whole circle. A DCP will be the co-facilitator, who is responsible for supporting the facilitator during the session. The role of internal observers, generally four per SOUND session, will be assigned to the rest of recruited DCPs: their task is to support the OPDs during the intervention in a non-intrusive and facilitating way while taking part in the activity. Facilitator, co-facilitator and internal observers take mental notes of their observations for reporting them in writing at the end of each session by using the live monitoring tools reported in Table 2 . Four researchers (for covering all the sections of the circle circumference) will be the external observers: they will focus on OPDs’ emotional and behavioral responses to the proposed activities and take notes through dedicated tools ( Table 2 ).

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Table 2. Live monitoring outcomes tools.

Each SOUND session lasts about 45 min and it is divided in four different phases: (1) welcoming; (2) opening activity; (3) three to five main activities depending on the length and intensity of each one; (4) closing activity. To every phase, except for phase 3, an exercise corresponds.

The intervention foresees both active (vocal and rhythmic production) and passive (listening to pieces of music) music-based activities. Additionally, narrative activities may be linked to the music, such as creating or telling stories, talking about pictures, describing an object and so on. All activities have the general objective of enhancing participants’ wellbeing. Additionally, each activity aims to stimulate specific cognitive abilities. The goal is not to complete an exercise correctly, on the opposite the facilitator has the task to adapt activities to the group participants and use what is generally considered as a mistake as a resource to creatively change the activity. Therefore, the focus is on inclusion rather than on performance.

All the activities are chosen based on: (a) OPDs’ personal music preferences identified by means of a biographical sheet, as detailed below; (b) OPDs’ level of impairment; (c) the objective of the stimulation activities e.g., verbal fluency, memory, coordination. Activities are also organized taking into account particular fears and triggering factors of OPDs based on their personal stories and current situations, checked through the biographical sheet.

The activities proposed are personalized based on the OPDs’ preferences and on their actual mental and physical condition, thus they may need to be adapted from time to time and from person to person. For an example of activities, see Annex 1 .

2.2.3 The environment

The literature shows that there is a connection between certain characteristics of the environment and OPDs’ physical functioning, emotional well-being and social interaction ( Calkins, 1988 , 2001 ; Day and Calkins, 2002 ; Marcus, 2007 ; Marquardt and Schmieg, 2009 ; Chaudhury and Cooke, 2014 ). Chaudhury et al. (2016) underlines the need for creating physical environments appropriate and responsive to cognitive abilities and functioning of OPDs living in residential facilities and day care centers.

It is well-known that since neurological disorders can alter OPDs’ senses, i.e., their perception of reality, especially the sight, well-designed environments can promote wayfinding and orientation ( Marquardt and Schmieg, 2009 ), improve activities of daily living function ( Reimer et al., 2004 ), autonomy and meaningful activity ( Kane et al., 2007 ), and reduce anxiety, agitation, aggression ( Schwarz et al., 2004 ).

Homelike environments (i.e., open-plan lounge/dining areas, residential furniture and flooring) displayed reduced verbal and overall aggression, verbal agitation and anxiety ( Zeisel et al., 2003 ; Wilkes et al., 2005 ), are associated with fewer walking/pacing episodes, ( Yao and Algase, 2006 ) and enhance engagement in daily activities, social interaction ( Campo and Chaudhury, 2011 ) and autonomy ( Chaudhury et al., 2016 ).

High noise levels, such as for example alarms, rings and staff conversations not including older users, are associated with the latter’s reduced social interaction, increased agitation and aggression, disruptive behavior and wandering ( Campo and Chaudhury, 2011 ; Garcia et al., 2012 ; Garre-Olmo et al., 2012 ; Joosse, 2012 ).

The intensity of the light is also important for creating a welcoming environment for OPDs. In fact, the exposure to a bright light can decrease agitation and disruptive behavior and improve cognition and mood, albeit modestly ( Nowak and Davis, 2010 ).

This is the reason why it is very important that the room hosting the SOUND activities is homelike displayed, welcoming, with soft light and that the level of noise is very low, for favoring concentration and cognition. The room will need to be large enough to allow participants movement, tidy with as little distracting objects as possible, with a suitable level of light which is not too dark and not too bright, and with small sound reverberation. The chairs need to be arranged in a circle with assigned seats (placing a sheet on each chair, where the name of each participant is written) taking into account specific aspects for interacting with the OPDs: (a) interpersonal dynamics; (b) visual/auditory difficulties; (c) need for proximity to the healthcare staff; (d) definition of roles. Considering the space of the circle as inside a square, one chair for each corner needs to be positioned outside the circle for the external observers.

2.3 Outcome measures and data collection tools

2.3.1 outcome measures.

The primary outcome variable for OPDs is the level of their mental wellbeing, while the primary outcome variable for care professionals is the level of burnout. Secondary outcomes variables for DCPs are (a) level of stress, (b) level of work cooperation and of (c) emotional well-being and, for OPDs, they are levels of (a) cognitive abilities, (b) neuropsychiatric symptoms, (c) mood and (d) emotional well-being.

Pre, post and longitudinal-intervention outcome ( Table 3 ) as well as live monitoring tools ( Table 2 ) were developed for assessing the impact of the SOUND intervention on DCPs and OPDs.

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Table 3. Pre, post and longitudinal-intervention outcome tools.

2.3.2 Pre-post and longitudinal tools

Concerning DCPs, an ad hoc questionnaire has been developed to investigate the level of stress and cooperation of professionals before and after the intervention. Beyond the demographic questions (i.e., age, gender, nationality, marital status, education), the pre-intervention questionnaire includes ad hoc questions on: (a) work condition (e.g., position, role, activities); (b) music attitudes; (c) well-being, motivation, satisfaction and self-realization at work (d) teamwork, (e) relationship with patients and family caregivers. Additionally, the Burnout Assessment Tool (BAT) will be administered for evaluating the work-related stress. Respondents can answer all the questions (i.e., both ad hoc questions and the BAT battery) through a five-point Likert scale, where 1 represents the lower and 5 the higher score/frequency. The post-intervention questionnaire for DCPs follows the same structure of the pre-intervention ones, except for quantitative and qualitative questions asking to what extent and how the intervention has improved every area e.g., well-being, team work, relationship with OPDs.

The Burnout Assessment Tool (BAT) is a self-assessment questionnaire that measures parameters associated with burnout ( De Beer et al., 2020 ; Schaufeli et al., 2020 ) validated in Italy ( Angelini et al., 2021 ; Borrelli et al., 2022 ), in Romania ( Oprea et al., 2021 ), in Portugal ( Sinval et al., 2022 ) and with European cut-off scores ( Schaufeli et al., 2023 ). The BAT contains four different subscales: exhaustion, mental distance, loss of emotional control and loss of cognitive control. In addition, there are two sub-dimensions: psychological disorders and psychosomatic disorders. In total, the questionnaire consists of 33 items (23 for the reduced version), each with a 5-point scale (1 = never, 2 = rarely, 3 = sometimes, 4 = often and 5 = always). The total score is obtained by summing the points. A difference of ± 10 points with a 95% confidence interval shows significance in the variation of burnout ( Daniels et al., 2022 ). The BAT will be the tool to assess the primary outcome for DCPs.

For the OPDs, demographic and baseline data will include age, gender, nationality, marital status, education, living condition, dementia service they attend, type of diagnosis, time of diagnosis, level of verbal expression and comprehension. As outcome tools, the following psychometric and standardized measures will be used.

The Neuropsychiatric Inventory (NPI) is a tool to assess dementia-related behavioral symptoms by examining 12 sub-domains of behavioral issues: delusions, hallucinations, agitation/aggression, dysphoria, anxiety, euphoria, apathy, disinhibition, irritability/lability, aberrant motor activity, night-time behavioral disturbances and appetite and eating abnormalities ( Cummings et al., 1994 ; Cummings, 1997 , 2020 ). The inventory is administered by a health professional to the primary family (if the older person lives in the community) or professional caregivers (if the older person lives in a care home). Each sub-domain includes a screening question followed by a sub-list of questions to answer if the behavior is present, which rate the frequency (4-point scale) and severity (3-point scale) of symptoms plus the level of distress caused to the caregiver (5-point scale). The measure provides a total score for BPSD ranging 0–144 and for caregiver’s stress from 0 to 60. The validity and reliability of the tool is well established even across translations ( Farina et al., 2009 ; Ferreira et al., 2015 ).

The Montreal Cognitive Assessment (MoCA) is a brief screening tool for detecting mild cognitive impairment and dementia, which is divided in seven domains and sub-scores: orientation (6 points); attention (6 points); memory (5 points for delayed recall); visuospatial/executive (5 points); naming (3 points); language (3 points); abstraction (2 points); if the person has ≤ 12 years of education a further point will be added ( Nasreddine et al., 2005 ). The test has been shown to have good validity, internal consistency, test–retest and inter-observer reliability (e.g., Freitas et al., 2013 ) and it is used worldwide.

The Frontal Assessment Battery (FAB) is a short neuropsychological tool aiming to assess executive functions or functions related to the frontal lobes and correlated with frontal metabolism ( Sarazin et al., 1998 ). It includes 6 subtests one for each investigated cognitive function: similarities test (conceptualization and abstract reasoning); verbal fluency test (mental flexibility); Luria motor sequences (motor programming and executive control of action); conflicting instructions (sensitivity to interference); go–no go test (inhibitory control); prehension behavior (environmental autonomy). The scoring for each subtest is from 0 to 3, for a maximum total score of 18 (highest performance). The battery has good validity (correlation of ρ = 0.82 with the Mattis Dementia Rating Scale) and interrater reliability (κ = 0.87) ( Dubois et al., 2000 ).

The Hospital Anxiety and Depression Scale (HADS) is a 14-item self-report measure for screening anxiety (7 questions) and depression (7 questions) states. The Likert-scale ranges from 0–3 for a maximum total score of 21, with higher scores indicating greater anxiety and depression, and with a cut-off > 10 ( Zigmond and Snaith, 1983 ). It has shown high concurrent validity with other widespread anxiety and depression assessments and has proved a 20-day test-retest reliability of0.94 ( Michopoulos et al., 2008 ). It is widely used in the field of dementia as it is brief, measures both anxiety and depression and is suitable for people with physical comorbidities (e.g., Clare et al., 2012 ).

The WHO Wellbeing Index (WHO-5) is a self-assessment tool to measure the subjective mental well-being of individuals which is validated for older people ( Heun et al., 1999 ). It includes five items each scored from 0 to 5. The total score ranges from 0 to 25, with higher scores indicating greater mental well-being. Scores < 13 indicate poor well-being and suggest depression according to the criteria of the International Statistical Classification ( Tiganov et al., 1997 ). It is recommended to transform the raw scores to percentage scores, by multiplying it by 4, for data analysis when investigating change over time ( Topp et al., 2015 ). Low mood may be suggested by a percentage score of ≤ 50 whilst a score of ≤ 28 may indicates depression. Similar to Kikuchi et al. (2023) , a variation of ± 10 points of the percentage score with 95% confidence intervals will be considered significant. The reliability and validity of the WHO-5 is well established (e.g., Bech, 2012 ; Takai et al., 2013 ). The WHO-5 will be the tool to assess the primary outcome for OPDs.

The SOUND consortium developed the Longitudinal Emotional Well-being Thermometer (LEWT), an idiosyncratic tool for monitoring the emotional well-being of DCPs and OPDs from T0 to T2 on a daily basis for the overall duration of the intervention. This is a self-report tool for the professionals and an observation-based tool for primary family or professional caregivers to record OPDs’ emotional state. Both versions include the picture of a colored thermometer, with each color indicating an emotional range and corresponding to a score. The color and the scoring have been assigned on the basis of the quality and level of neurophysiological arousal (i.e., parasympathetic and sympathetic systems): green indicates a homeostatic state of peace and calm (score = 0); darker green is joy/satisfaction whilst yellow indicates confidence/hope (score = 1); light blue means worried/anxious versus orange is annoyed/frustrated (score = 2); dark blue indicates sad/depressed whilst red means angry/disgusted (score = 3). The higher the score the greater the emotional distress. DCPs will be asked to rate their prevalent emotional wellbeing state every day, at the end of the day, for 63 days. Likewise, primary family or professional caregivers, who have a pre-existing relationship with the OPD and are able to observe them daily, will be asked to report their cared for mood. The following mean range can be obtained from the total sum divided by the total days: scores from 0 to 1 indicate well-being, scores from 1 to 2 indicate mild emotional discomfort, and scores from 2 to 3 indicate emotional distress. Each emotional state will also have a code 1–7 to identify the type of emotion and calculate its prevalence throughout the intervention. Additionally, both versions include a final column in order to: (a) rate (on a 1–5 scale ranging from “not at all” to “completely”) how much the recorded emotion may be linked to SOUND sessions for health professionals; (b) record meaningful events in the daily life of OPDs which may be related to their emotional state. The results from the scoring can be summarized in a graph showing the daily trend of the emotional arousal, the frequency of each emotional group and their relationship to the SOUND intervention. The minimum detectable change and the threshold of clinical improvement will be calculated.

2.3.3 Live monitoring tools

The live monitoring of the observed OPDs’ emotional and behavioral reactions is very important because the deficit in the short-term memory of OPDs does not allow to gather reliable data about their emotions and thoughts, even if asked at the end of the intervention session. Thus, the use of further tools for monitoring the effects of the intervention during the delivery of the SOUND activities is included ( Table 2 ).

DCPs and OPDs, who will have provided their written or audio recorded verbal consent, will be video recorded by two cameras (for having two points of view and minimize blind points) during the delivery of the SOUND sessions. The recordings will be watched by the researchers who will analyze and interpret participants’ behaviors with the aim to evaluate the method and improve it.

Collecting information on OPDs and DCPs’ emotions is important to understand if there is an emotional synchronization between the two types of beneficiaries, that may contribute to overcome the professional-patient asymmetry and so increase the chances for a successful intervention. Such observations can be collected from the analysis of the video recordings. Furthermore, the research protocol includes an ad hoc instrument for this purpose, the Live Session Emotions Thermometer (LSET) 3 . LSET is an idiosyncratic tool for monitoring the emotions of both DCPs and OPDs during the activities which includes two forms, one for recording the OPDs observed emotional reaction and one for noting the professionals’ own reaction and how they handled the situation. This form encompasses quantitative and qualitative data. The tool includes the image of a thermometer with 10 degrees, where 1 indicates the lowest and 10 the highest intensity of the emotion. In the first form, the observer (DCP) identifies and writes down the prevalent emotion of the observed person (OPD) e.g., happiness or sadness, scores its intensity by crossing the corresponding degree in the thermometer, and describes the observed behavioral reaction and the activity that took place in that moment. In the second form, DCPs will report their own emotion, scored by intensity, their thoughts, their behavioral reaction (strategy adopted to handle the situation) and their sense of efficacy regarding the occurred episode. DCPs are requested to fill the LSET immediately after every SOUND session.

In addition, the external observers (i.e., the researchers), will be focused on each OPD and will fill-in the Apparent Affect Rating Scale (AARS; Lawton et al., 1999 ). The AARS is an observational tool designed for research purposes in the dementia field. The scale aims to rate five emotions, two of which positive (pleasure and interest) and three negative (fear/anxiety, anger and sadness), and their duration on a scale from 0 to 5 (0 = can’t tell; 1 = never; 2 = less than 16 secs; 3 = 16–59 secs; 4 = 1–2 mins; 5 = more than 2 mins) by observing the person for 5 min.

2.4 Data analysis

The analysis plan includes, for quantitative data, outcomes description. Normality in distribution of continuous variables will be assessed via Shapiro-Wilk test and the following measures will be reported: mean and standard deviation for normally distributed variables or median and interquartile range for non-normally distributed variables. Absolute frequency and percentage will be reported for categorical variables. Comparisons between outcomes and exposures will be made using the Chi Square test, (in the case of categorical variables) or t -test or F-Anova (in the case of comparisons between normally distributed continuous variables and the groups), or by non-parametric tests such as Wilcoxon rank-sum test or Kruskal-Wallis test (in the case of comparisons between non-normally distributed continuous variables and the groups). Through Pearson’s or Spearman’s correlation we are going to study the relationship between continuous variables as appropriate according to variables’ distribution. Temporal comparisons (T0 vs. T1, T0 vs. T2, or T1 vs. T2) will be conducted by T -test for paired samples. Possible multivariate models will be assumed in case of significant differences in outcomes at the univariate level: coefficients and standard errors or odds ratios and 95% confidence intervals will be reported according to the typology of outcomes (continuous or binary). Goodness of fit will be determined by R-squared of pseudo R-squared as appropriate. Subjects withdrawing from the study will not be replaced, according to the intention to treat (ITT) principle. Sequential imputation using chained equations method will be applied in case of missing values in covariates. Statistical analyses will be conducted by a statistician, who will be blind to group allocation prior to analysis. The significance threshold will always be set at p < 0.05. The software used for the analyses will be SPSS for Win V24.0 (SPSS Inc., Chicago, IL, USA).

Qualitative data from the open-ended questions, included in the ad hoc questionnaire for professionals, in the LEWT and in the LEST, will be analyzed thematically ( Braun and Clarke, 2006 ). The textual data will be analyzed by two independent researchers and checked by a third one (add reference). The notes taken by researchers during the watching of the SOUND sessions’ video recordings will be reported into a narrative ( Kutsche, 1998 ) and all narratives will be summarized cross-nationally. Then the narratives will be coded to select and emphasize relevant information answering the research questions and the codes will be merged in themes ( De Munck and Sobo, 1998 ). The textual data will be analyzed by two independent researchers and checked by a third one for minimizing the bias of subjectivity ( Golafshani, 2003 ).

The datasets that will be generated and/or analyzed during the pilot study will be available from the corresponding author on reasonable request.

This protocol and the template informed consent forms have been reviewed and approved by the responsible local Institutional Ethical Committees, as required in each participating country with respect to scientific content and compliance with applicable research and human subjects’ regulations. Any modifications to the protocol which may impact on the conduct of the study, potential benefit of the patient or may affect patient safety, including changes of study objectives, study design, patient population, sample sizes, study procedures, or significant administrative aspects will require a formal amendment to the protocol. Any amendment to the protocol will be approved by the Ethics Committees.

Each type of subject involved will be duly and comprehensively informed about the objectives of the study and the modalities of the music-type intervention, through an information sheet but also through an interview with the scientific supervisor (Dr. SS) when requested. Older people with dementia will be provided with the informed consent and will be asked to sign it in the presence of the family caregiver and the same sheet will be given to the latter. In the information sheet, as well as during the interview, it will be emphasized that adherence to the study is completely voluntary and that it can be quit at any time without having to give any explanation. The type of intervention will be explained to both the person with mild-to-moderate dementia and their family caregivers according to a capacity approach and with full respect for the older person’s residual capacities. For the same principle, where possible, informed consent will be signed by the person with dementia and their family caregiver/legal guardian. The intervention does not anticipate any risk, discomfort or intrusion of privacy. The professionals involved will be registered healthcare practitioners with extensive experience in working with OPDs or musicians trained in dementia care and have the skills to identify and address any discomfort experienced by participants during the intervention. The participation will not require the suspension of concomitant care or interventions.

All study-related information will be stored securely at the study site. All participant information will be stored in locked file cabinets in areas with limited access. All reports, data collection, process, and administrative forms will be identified by a coded ID [identification] number only to maintain participant confidentiality. All records that contain names or other personal identifiers, such as informed consent forms, will be stored separately from study records identified by code number. All local databases will be secured with password-protected access systems. Forms, lists, logbooks, appointment books, and any other listings that link participant ID numbers to other identifying information will be stored in a separate, locked file in an area with limited access.

The scientific integrity of the study requires that the data from all SOUND sites (i.e., Italy, Portugal and Romania) be analyzed study-wide and reported as such. All results coming from the data collected through this protocol are expected to protect the integrity of the major objective of the study at the time of their dissemination through scientific papers and oral presentations, that will be agreed in the Steering Committee (made of the Authors).

The primary outcome papers of SOUND i.e., those reporting the effects of the intervention on OPDs’ wellbeing and DCPs’ burnout will be presented by the first author to the Steering Committee for approval as well as secondary outcome papers and presentations (e.g., on DCPs’ cooperation or OPDs’ reduction of neuropsychiatric symptoms). The study results will be released to the participating DCPs, OPDs, informal caregivers and the general medical community.

The activities and music are carefully chosen in order to elicit in participants only feelings of peace and well-being, as previous similar experiments have shown ( Caldini et al., 2019 ). In compliance with the Declaration of Helsinki (stating that “the protocol should describe arrangements for post-study access by study participants to interventions identified as beneficial in the study or access to other appropriate care or benefits”), should this study provide evidence of the effectiveness of SOUND, the SOUND activities will be included in the routine of the dementia care centers. This goal is probable and achievable because a total of 63 professionals have been trained on the SOUND method, 29 in Italy, 17 in Portugal and 17 in Romania; moreover, the Virtual Music Circle training platform is predisposed to train further professionals (Quattrini et al., under review, see text footnote 2).

3 Discussion

To the best of our knowledge, SOUND is one of the few studies focusing on the impact of a music-based intervention on both dementia care professionals and older people with dementia, since the available studies are targeted to older people mainly (e.g., Hyde et al., 2009 ; Daykin et al., 2017 ; Habibi et al., 2017 ; Brancatisano et al., 2019 ; Domínguez-Chávez et al., 2019 ). Conversely, in this study, the former and the latter, are conceived by the protocol as distinct but also intertwined targets. They build together a unique care ecosystem that can be well-represented and interpreted by the circle, that is a democratic setting able to overcome the care asymmetry between care professionals and patients.

The intervention is innovative, because it is delivered in circle, it is led by facilitators with the support of other care professionals, all trained on the method through an original curriculum, and it includes different types of music activities both passive and active, highly personalized as based on the beneficiaries’ preferences and attitudes collected before the intervention finalization.

The protocol has been designed based on the recommendations of Moreno-Morales et al. (2020) by including well-focused outcome measures and discussing how the findings may improve the well-being of OPDs and DCPs.

Since the effects of music are not immediate ( Moreno-Morales et al., 2020 ), SOUND was conceived as a progressive and continuous intervention to obtain successful results ( Leubner and Hinterberger, 2017 ) and it foresaw both pre-post evaluation and medium-term follow-up.

In light of the above, with regard to OPDs we expect: (a) an increase of ± 10 points with 95% confidence interval in the WHO-5 percentage scores regarding wellbeing; (b) no decrease in MoCa and FAB scores regarding cognition; (c) a 50% reduction of the HADS score or absence of depression and anxiety concerning mood; (d) a decrease of 2 points corresponding to the median value for the BPSD symptoms and caregivers distress in the NPI; (e) a negative variation, e.g., of 0.5–1 points toward 0, in the LEWT as an index of improved emotional wellbeing.

Concerning the impact of the intervention on DCPs, we expect that: (a) the BAT scores will decrease by ± 10 points with a 95% confidence interval; (b) well-being at work, teamwork cooperation and communication with the OPDs will improve of one point on the five-point Likert scale for at least half of the items in each area. For example, to the question “How do you rate the quality of your relationship with older people with dementia?” we expect a minimal change from “Fair” to “Quite good”; (c) the LEWT scores will show a trend toward 0.

It is methodologically worth mentioning that this protocol was designed for DCPs daily working in a dementia care facility. However, the methodology may be applied even by external professionals who have an external collaboration with service providers. In this case, the impact of the caregiver stress, that may be influenced by working in a new workplace, could be measured by adding a question such as “In what way the delivery of the SOUND method in an unusual workplace have influenced your levels of work-related stress?”

One strength of the protocol lies in the use of both quantitative and qualitative data collection tools, and in a multi-method approach that will allow to gather written and visual data that will generate numerical, textual and narrative results. Another strength is the cross-national nature of the study that can provide interesting culture-based tips, since every team will use popular and traditional songs belonging to their context.

One limitation of the study may concern the small sample size at national level that will not allow a generalization of the results. Moreover, the protocol does not foresee the monitoring of clinical parameters such as cortisol, blood pressure as recommended by Uğur et al. (2016) . In fact, although it would have been interesting to check the impact of the intervention on these realms, the study did not receive enough funding to cover the expenses for a biochemical investigation.

Another limitation of the protocol, may be the missing inclusion of family caregivers as a target of the study. In fact, it would have been interesting to investigate the effect of the intervention on the dyad relationship family caregiver-cared for e.g., on communication and empathy. The SOUND project is currently training a group of family caregivers for adapting music activities to the home context, through mini animated videos. However, the effectiveness of this approach will need a separate evaluation.

Additionally, the OPDs-DCPs relationship was not included as a variable to investigate. The protocol could be amended for a further study to investigate primarily the effects of the intervention on the quality of the patient-caregiver relationship.

Finally, methodologically, the data on OPDs collected through the observation of DCPs as internal observers and researchers as external observers may entail the risk of subjectivity. Observation may in fact, be influenced by factors like mood, the personal experience (e.g., having a relative with dementia), the desire that the intervention has an impact on participants and so on. Therefore, to ensure the study confirmability (objectivity) and also its credibility, transferability, dependability according to Lincoln and Guba (1985) , Shenton (2004) and Golafshani (2003) , several expedients should be adopted by the research team e.g., (a) the admission of personal predispositions by the observers and the awareness that they can influence their data perception and interpretation; (b) the use of specific tools that try to translate qualitative data in categories and quantitative data/scores e.g., the AARS and the LSET; (c) the triangulation i.e., the presence of more than one researcher observing the same person, and the analysis of the recorded videos of the sessions helping making a synthesis of different points of observation; (d) frequent debriefing sessions in the team; (e) the examination of previous research findings referring to the same issue; (f) the description of the research design and its realization, and details of data collection and analysis processes.

The main study challenge may lie on the need of a multidisciplinary team, made of researchers, dementia care professionals and trained musicians for properly applying the intervention and monitoring its impact on the target groups. Since the presence of researchers and musicians is not common in the older people care facilities, this may limit the replicability of the study. Conversely, the SOUND curriculum is available online as an open-access resource, through the Virtual Music Circle e-learning platform and it will be open access at the end of the project for any care professional or musician who wanted to learn the method and deliver the activities with OPDs.

Finally, the pilot study can provide useful insights for future studies and contribute to improve the knowledge about the effectiveness of the music in dementia care facilities for both professionals and older patients.

Ethics statement

The study was approved by the IRCCS INRCA Ethic Committee on 26th May 2023 with General Director Communication number 234 provided on 9th June 2023.

Author contributions

SS: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing−original draft, Writing−review and editing. AM: Conceptualization, Data curation, Investigation, Methodology, Writing−original draft, Writing−review and editing. IC: Conceptualization, Data curation, Investigation, Methodology, Writing−review and editing. MA: Conceptualization, Data curation, Investigation, Methodology, Writing−review and editing. AH: Conceptualization, Methodology, Supervision, Validation, Writing−review and editing. LN: Data curation, Investigation, Writing−review and editing. MD: Formal analysis, Software, Writing−review and editing. SQ: Conceptualization, Data curation, Investigation, Methodology, Project administration, Writing−review and editing.

The author(s) declare financial support was received for the research, authorship, and/or publication of the article. The development of this protocol was supported by the Erasmus + program under the contract number 2021-1-IT02-KA220-ADU-000033494 and by Ricerca Corrente funding from the Italian Ministry of Health to IRCCS INRCA. These funding sources had no role in the design of this study and will not have any role during its execution, analyses, interpretation of the data, or decision to submit results.

Acknowledgments

We want to acknowledge the whole SOUND consortium: ACMO (Italy): AH, Giorgia Caldini, Claudia Bernardi, Claudia Carletti, Chiara Soccetti; HABILITAS (Romania): IC, Rodica Caciula; Scoala de Pian (Romania): LN, Maria Ionel; Sons do Estaminé (Portugal): MA, Pedro João, Sandra Costa, André NO; Eurocarers (Belgium): Svetlana Atanasova, Olivier Jacqmain, Stecy Yghemonos; Anziani e Non-Solo (Italy): Licia Boccaletti, Rita Seneca, Rebecca Vellani, Laura Stanzani; IRCSS-INRCA (Italy): SS (Principal investigator), SQ, AM.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

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Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg.2024.1327272/full#supplementary-material

  • ^ https://soundeuproject.eu/results/
  • ^ Quattrini, S., Merizzi, A., Caciula, I., Napradean, L., João Azevedo, M., Costa, S., et al. (under review). The design and implementation of a novel music-based curriculum for dementia care professionals. The experience of SOUND in Italy, Portugal and Romania .
  • ^ The Live Session Emotions Thermometer (LSET) was developed by Giorgia Caldini et al. during the first experimentation of Circleactivities at the day-care center Civica di Trento in 2018 ( Caldini et al., 2019 ).

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Keywords : music, dementia, non-pharmacological intervention, well-being, cognitive function

Citation: Santini S, Merizzi A, Caciula I, Azevedo MJ, Hera A, Napradean L, Di Rosa M and Quattrini S (2024) A quasi-experimental mixed-method pilot study to check the efficacy of the “SOUND” active and passive music-based intervention on mental wellbeing and residual cognition of older people with dementia and dementia professionals’ burnout: a research protocol. Front. Psychol. 15:1327272. doi: 10.3389/fpsyg.2024.1327272

Received: 24 October 2023; Accepted: 30 January 2024; Published: 14 February 2024.

Reviewed by:

Copyright © 2024 Santini, Merizzi, Caciula, Azevedo, Hera, Napradean, Di Rosa and Quattrini. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Alessandra Merizzi, [email protected]

† These authors have contributed equally to this work and share first authorship

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

A-level Sociology (AQA) Revision Notes

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On This Page:

Revision guide for AQA A-Level (7192) and AS-Level Sociology (7191), including straightforward study notes, independent study booklets, and past paper questions and answers. Fully updated for the summer 2021 term.

Download Past Paper Questions With Answers

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Paper 1: Education with Methods in Context

  • Study Booklet Part 1
  • Study Booklet Part 2
  • Study Booklet Part 3
  • Complete Revision Notes
  • Short Questions and Answers
  • the role and functions of the education system, including its relationship to the economy and to class structure
  • differential educational achievement of social groups by social class, gender and ethnicity in contemporary society
  • relationships and processes within schools, with particular reference to teacher/pupil relationships, pupil identities and subcultures, the hidden curriculum, and the organisation of teaching and learning
  • the significance of educational policies, including policies of selection, marketisation and privatisation, and policies to achieve greater equality of opportunity or outcome, for an understanding of the structure, role, impact and experience of and access to education; the impact of globalisation on educational policy.

Methods in Context

  • Students must be able to apply sociological research methods to the study of education.

Paper 2: Research Methods and Topics in Sociology

Research methods, topic 2: families and households, topic 5: beliefs in society, topic 6: global development.

  • Revision Notes
  • Knowledge Organiser
  • quantitative and qualitative methods of research; research design
  • sources of data, including questionnaires, interviews, participant and non-participant observation, experiments, documents and official statistics
  • the distinction between primary and secondary data, and between quantitative and qualitative data
  • the relationship between positivism, interpretivism and sociological methods; the nature of ‘social facts’
  • the theoretical, practical and ethical considerations influencing choice of topic, choice of method(s) and the conduct of research
  • the relationship of the family to the social structure and social change, with particular reference to the economy and to state policies
  • changing patterns of marriage, cohabitation, separation, divorce, childbearing and the life course, including the sociology of personal life, and the diversity of contemporary family and household structures
  • gender roles, domestic labour and power relationships within the family in contemporary society
  • the nature of childhood, and changes in the status of children in the family and society
  • demographic trends in the United Kingdom since 1900: birth rates, death rates, family size, life expectancy, ageing population, and migration and globalisation
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This paper is in the following e-collection/theme issue:

Published on 19.2.2024 in Vol 26 (2024)

Reliability of Telepsychiatry Assessments Using the Attention-Deficit/Hyperactivity Disorder Rating Scale-IV for Children With Neurodevelopmental Disorders and Their Caregivers: Randomized Feasibility Study

Authors of this article:

Author Orcid Image

Original Paper

  • Shunya Kurokawa 1 , MD, PhD   ; 
  • Kensuke Nomura 1, 2 , MD, PhD   ; 
  • Nana Hosogane 3 , MD   ; 
  • Takashi Nagasawa 4 , MD   ; 
  • Yuko Kawade 2, 5 , MD   ; 
  • Yu Matsumoto 2 , MD   ; 
  • Shuichi Morinaga 1, 6 , MD   ; 
  • Yuriko Kaise 1 , MA   ; 
  • Ayana Higuchi 1 , MA   ; 
  • Akiko Goto 5 , MD, PhD   ; 
  • Naoko Inada 7 , MA, PhD   ; 
  • Masaki Kodaira 3 , MD, PhD   ; 
  • Taishiro Kishimoto 8 , MD, PhD  

1 Department of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan

2 Department of Child Psychiatry, Shimada Ryoiku Medical Center for Challenged Children, Tokyo, Japan

3 Department of Child and Adolescent Mental Health, Aiiku Clinic, Tokyo, Japan

4 Department of Child and Adolescent Psychiatry, Tokyo Metropolitan Children's Medical Center, Tokyo, Japan

5 Tsurugaoka Garden Hospital, Tokyo, Japan

6 Hiratsuka City Hospital, Kanagawa, Japan

7 Department of Clinical Psychology, Taisho University, Tokyo, Japan

8 Hills Joint Research Laboratory for Future Preventive Medicine and Wellness, Keio University School of Medicine, Tokyo, Japan

Corresponding Author:

Taishiro Kishimoto, MD, PhD

Hills Joint Research Laboratory for Future Preventive Medicine and Wellness

Keio University School of Medicine

Mori JP Tower F7

1-3-1, Azabudai, Minato-ku

Tokyo, 106-0041

Phone: 81 3 5363 3219

Email: [email protected]

Background: Given the global shortage of child psychiatrists and barriers to specialized care, remote assessment is a promising alternative for diagnosing and managing attention-deficit/hyperactivity disorder (ADHD). However, only a few studies have validated the accuracy and acceptability of these remote methods.

Objective: This study aimed to test the agreement between remote and face-to-face assessments.

Methods: Patients aged between 6 and 17 years with confirmed Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition diagnoses of ADHD or autism spectrum disorder (ASD) were recruited from multiple institutions. In a randomized order, participants underwent 2 evaluations, face-to-face and remotely, with distinct evaluators administering the ADHD Rating Scale-IV (ADHD-RS-IV). Intraclass correlation coefficient (ICC) was used to assess the reliability of face-to-face and remote assessments.

Results: The participants included 74 Japanese children aged between 6 and 16 years who were primarily diagnosed with ADHD (43/74, 58%) or ASD (31/74, 42%). A total of 22 (30%) children were diagnosed with both conditions. The ADHD-RS-IV ICCs between face-to-face and remote assessments showed “substantial” agreement in the total ADHD-RS-IV score (ICC=0.769, 95% CI 0.654-0.849; P <.001) according to the Landis and Koch criteria. The ICC in patients with ADHD showed “almost perfect” agreement (ICC=0.816, 95% CI 0.683-0.897; P <.001), whereas in patients with ASD, it showed “substantial” agreement (ICC=0.674, 95% CI 0.420-0.831; P <.001), indicating the high reliability of both methods across both conditions.

Conclusions: Our study validated the feasibility and reliability of remote ADHD testing, which has potential benefits such as reduced hospital visits and time-saving effects. Our results highlight the potential of telemedicine in resource-limited areas, clinical trials, and treatment evaluations, necessitating further studies to explore its broader application.

Trial Registration: UMIN Clinical Trials Registry UMIN000039860; http://tinyurl.com/yp34x6kh

Introduction

Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are caused by genetic and environmental factors. Children with ADHD or ASD are recognized to be at risk for emotional and behavioral difficulties during adolescence, young adulthood, and beyond, owing to social adjustment difficulties. Hence, early detection and intervention are crucial to prevent the development of additional comorbidities [ 1 - 3 ].

The most recent US epidemiological study reported a prevalence of 9.5% for ADHD and 2.5% for ASD [ 4 ], making ADHD the most common neurodevelopmental disorder. In Japan, although epidemiological studies on ADHD in children are lacking, the prevalence rate in adults has been reported to be 1.65% [ 5 ]. However, children with ADHD or ASD face many obstacles in accessing specialized medical care. One of the biggest challenges is the global shortage of child psychiatrists, leading to long waiting times for diagnosis. For example, in Canada and the United States, the average wait times are 7 and 13 months, respectively [ 6 , 7 ]. This is particularly concerning in rural or isolated areas without access to specialized medical facilities.

In addition, these children may have difficulties leaving their homes and engaging in social interactions (ie, social withdrawal). Even when they have access to specialized medical facilities, some may find it extremely difficult to see a doctor in person. Moreover, it has been reported that these children have trouble with the time management associated with ADHD, resulting in high dropout rates during treatment [ 8 , 9 ].

Moreover, accurate diagnosis requires close observation by medical staff and a thorough interview with caregivers regarding the child’s developmental history [ 10 , 11 ]. However, a lack of trained evaluators can lead to difficulty in accurate assessment. Children’s evaluations are susceptible to being influenced by the halo effect (the distortion of evaluations about other characteristics due to the salient features they possess) and the contrast effect (a greater perception of difference than the actual difference) [ 12 , 13 ].

One possible approach to solving these problems is remote diagnosis and evaluation. In recent years, because a large part of psychiatric treatment and assessment has consisted of conversations with patients, remote evaluation and treatment using remote digital tools can be effective, particularly in clinical trials.

Therefore, the US Food and Drug Administration and the European Medicines Agency are promoting remote central evaluation using videoconferencing systems in psychiatric trials [ 14 ] and physician-led clinical trials [ 15 ], which are becoming increasingly common. To remotely perform a severity diagnosis in clinical trials, it is necessary to verify the degree of agreement with the usual face-to-face assessment.

Only a few studies have validated the agreement of remote assessment tests for developmental disorders with the usual face-to-face assessment [ 16 - 18 ]. A study reported that the Autism Diagnostic Interview–Revised Edition score from face-to-face interviews with caregivers of 20 children with ASD was equivalent to the Autism Diagnostic Interview–Revised Edition score from telephone interviews ( r =0.73-0.90) [ 16 ]. The Autism Diagnostic Observation Schedule–2, considered the gold standard for ASD observation ratings, was administered to 23 adults with ASD and showed an intraclass correlation coefficient (ICC) of 0.92 between face-to-face and remote assessments [ 17 ], with the limitation that the ratings were made by the same rater. One study used a mobile app to video record scenes in which parents were concerned about their child’s development at home [ 18 ]. Among the 40 children with ASD and 11 children with typical development, 88.2% of diagnoses agreed with the face-to-face diagnosis using the Autism Diagnostic Observation Schedule and other tools (κ=0.75; sensitivity=84.9%; specificity=94.4%).

However, research on the remote assessment of ADHD ratings is limited. The ADHD Rating Scale-IV (ADHD-RS-IV) [ 19 , 20 ] is the gold standard tool used to support the diagnosis and severity assessment of ADHD, and it has been used in practice in many clinical trials [ 21 , 22 ]. It has been reported that the sensitivity and specificity of ADHD-RS-IV in Japan above the 90th percentile were 89.13% and 94.07%, respectively [ 23 ]. This study aimed to test whether the remote method is equivalent to the face-to-face method for children with ADHD and ASD and their caregivers by administering ADHD-RS-IV and determining the ICC and to verify the validity and feasibility of remote assessment.

Participants

Patients were recruited at Keio University Hospital and 4 collaborating institutions (Shimada Ryoiku Medical Center for Challenged Children, Aiiku Clinic, Tokyo Metropolitan Children’s Medical Center, and Tsurugaoka Garden Hospital). The inclusion criteria were as follows: (1) confirmation of Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) [ 24 ] diagnoses of ADHD or ASD; (2) aged between 6 and 17 years at the time of obtaining consent; and (3) if receiving pharmacotherapy, the treatment was stable for at least 3 months before obtaining consent.

The exclusion criteria were as follows: (1) either the child or caregiver had a hearing or visual impairment that made it difficult to use remote tools, even with corrective devices, such as glasses or hearing aids; (2) there were no caregivers with information related to the participants’ early childhood; (3) individuals had comorbid symptoms, such as hallucinations and delusions, which made it challenging to engage in the study, as determined by the clinician; and (4) there were plans to initiate new treatments, such as pharmacotherapy or psychotherapy, during the observation period.

Baseline Assessments

Background information and data, such as age, sex, diagnosis, medication, duration of illness, and intelligence test results, were collected from medical records. For the baseline evaluation, the Autism-Spectrum Quotient–Japanese version for children, the Conners 3 Japanese version to evaluate ADHD symptoms by caregivers, the Strengths and Difficulties Questionnaire to assess social adaptation, and the Short Sensory Profile to assess sensory characteristics were administered.

Study Procedure

The ADHD-RS-IV and Childhood Autism Rating Scale–2 scores were used as primary outcomes to compare face-to-face and remote developmental evaluations.

After the baseline assessments, the participants underwent evaluations twice, either face-to-face or remotely. Recall bias could have occurred if the same evaluator had conducted both assessments. Therefore, the order of the face-to-face and remote evaluations was randomized for each participant, and different evaluators conducted the evaluations. To reduce the burden on the participants, minimize the practice effect, and avoid temporal changes, the interval between face-to-face and remote evaluations was set at least 2 weeks and no more than 3 months apart.

After completing the 2 assessments, the participants were given a questionnaire to report their satisfaction with the remote assessment. Additionally, given that previous studies showed long waiting periods for accessing child psychiatry specialists, we gathered background information on the waiting period at a specialist’s initial meeting. We also considered cases where specialized hospitals and clinics were not within one’s living area and collected data on the average travel time for outpatient visits and waiting time for their usual visit.

The 3 evaluators were licensed psychologists in developmental testing who had undergone sufficient training and had confirmed their agreement rates before conducting the evaluations. Evaluators rotated as needed for both in-person and remote assessments, rather than having specific evaluators for each. None of them was involved in the participants’ assessments or treatment during their usual visits.

As preliminary training before starting the research, 3 examiners administered the ADHD-RS-IV to 5 patients.

The remote smartphone assessment tool “Curon” by MICIN Co Ltd was used for the telemedicine evaluation. The participants were seated in front of a smartphone in their homes and were introduced to a remote evaluator. Remote evaluators administered their evaluations in a room at the Keio University Hospital using a PC. Although it was assumed that a download and upload environment of 50 Mbps or higher would be perfect for remote video applications, stable communication was achieved at approximately 5 Mbps, which, in most cases, fulfilled the Japanese standard 4G network. The assessments began after confirming that there were no interruptions in the video or audio environment.

Statistical Analysis

Test-retest reliability was assessed using the ICC for continuous variables, with the following standard performance parameters: almost perfect (0.81-1.00); substantial (0.61-0.80); moderate (0.41-0.60); fair (0.21-0.40); and slight (0.0-0.20) [ 25 ]. The ICC within the same rater when testing the same patient multiple times was assumed to be 0.90. Assuming that the ICC between the remote and face-to-face tests was 0.8, and to achieve a 95% CI width of 0.3 with a probability of >80%, a sample size of 31 was required. It was also assumed that the analysis would be conducted by dividing the participants into 2 groups: ASD and ADHD. Therefore, the required sample size was set at 62 [ 26 ]. Normally distributed data are described as mean (SD). Categorical variables are presented as numbers and percentages. All variables were inspected using histograms, q-q plots, and Kolmogorov-Smirnov tests before statistical analyses were conducted to test the distribution. All analyses were 2-sided with an α value of .05. Statistical analyses were conducted using the SPSS software (version 25.0; SPSS Inc).

Ethical Considerations

The study protocol was approved by the ethics committee of Keio University School of Medicine (20190301). The study was registered in the UMIN Clinical Trial Registry (UMIN000039860). Informed consent was obtained from all caregivers. For the children, an informed assent form was used, tailored to their age and understanding, and written confirmation of their consent was obtained after careful explanation. The personal information collected in this study was securely stored in a locked cabinet located within a lockable room belonging to the corresponding author. The information obtained through this study was anonymized by removing personal identifiers and assigning research numbers at each institution and then was stringently managed and preserved under the supervision of the corresponding author. In the event of an exacerbation of psychiatric symptoms as a result of this study, appropriate treatment was to be administered. No financial compensation was provided.

The demographic characteristics of the participants are shown in Table 1 . A total of 75 patients consented to participate in the study. Overall, 2 participants were from Keio University Hospital, 44 were from Shimada Ryoiku Medical Center for Challenged Children, 13 were from Aiiku Clinic, 10 were from Tokyo Metropolitan Children’s Medical Center, and 6 were from Tsurugaoka Garden Hospital. Of these, 1 participant from Shimada Ryoiku Medical Center for Challenged Children dropped out owing to time limitation. Among the 74 remaining participants, 17 (23%) were girls and 57 (77%) were boys. All patients were Asian (Japanese). Their ages ranged from 6 to 16 years, with an average of 10.4 (SD 2.5) years. The primary clinical diagnoses were as follows: 31 (42%) individuals were diagnosed with ASD, 43 (58%) were diagnosed with ADHD, and 22 (30%) had comorbid ASD and ADHD. Of the 61 caregivers, 47 (77%) had previous experience with remote video calls, whereas 14 (23%) did not.

a ADHD: attention-deficit/hyperactivity disorder.

b ASD: autism spectrum disorder.

c SDQ: Strength and Difficulties Questionnaire.

d AQ: Autism-Spectrum Quotient.

e SSP: Short Sensory Profile.

f CARS-2: Childhood Autism Rating Scale-2.

g ADHD-RS-IV, Attention-deficit/Hyperactivity Disorder Rating Scale-IV.

Participants were asked how long the waiting period was until the first visit for a child psychiatrist appointment, and the average was found to be 79.0 (SD 57.1; range 1-200) days. Regarding their usual visits, it took 36.8 (SD 20.7; range 5-100) minutes from leaving home to arriving at the hospital. The average waiting time for a usual appointment was 24.0 (SD 14.6; range 5-60) minutes. The potential time that could be saved using remote visits (by adding visiting time × 2 and waiting time) was 97.7 (SD 42.5; range 40-260) minutes.

ICCs of ADHD-RS-IV Between Face-to-Face and Remote Assessments

The ICCs obtained after preliminary training were as follows: 0.987 (95% CI 0.934-0.999; P <.001) for the total score; 0.991 (95% CI 0.957-0.999; P <.001) for the hyperactivity/impulsivity subscore; and 0.807 (95% CI 0.022-0.978; P =.02) for the inattention subscore.

The ICCs are shown in Figures 1 - 3 . The ICC of the total ADHD-RS-IV was 0.769 (95% CI 0.654-0.849; P <.001), which was “substantial,” according to the Landis and Koch criteria [ 25 ]. The ICC of the ADHD-RS-IV hyperactivity/impulsiveness and inattention subscores were 0.779 (95% CI 0.669-0.856; P <.001) and 0.667 (95% CI 0.515-0.778; P <.001), respectively, indicating “substantial” agreement. In patients with ADHD as their primary diagnosis, the ICC for total score was 0.816 (95% CI 0.683-0.897; P <.001), indicating “almost perfect” agreement; the ICC for hyperactivity/impulsiveness was 0.861 (95% CI 0.756-0.923; P <.001), indicating “almost perfect” agreement; and the ICC for inattention score was 0.642 (95% CI 0.423-0.790; P <.001), indicating “substantial” agreement. In patients with ASD as their primary diagnosis, the ICC for total score was 0.674 (95% CI 0.420-0.831; P <.001), indicating “substantial” agreement; the ICC for hyperactivity/impulsiveness was 0.591 (95% CI 0.299-0.782; P <.001), indicating “moderate” agreement; and ICC for inattention score was 0.733 (95% CI 0.511-0.863; P <.001), indicating “substantial” agreement.

research methods psychology paper 1

There were no clear sex differences in the ICCs. In regard to age, comparing the older age group (≥11 years; n=37) and the younger age group (≤10 years; n=37), the ICC for total score was 0.675 (95% CI 0.464-0.814; P <.001) in the younger age group and 0.757 (95% CI 0.558-0.873; P <.001) in the older age group. The ICC for hyperactivity/impulsiveness was 0.706 (95% CI 0.509-0.833; P <.001) in the younger age group and 0.730 (95% CI 0.515-0.858; P <.001) in the older age group. The ICC for inattention score was 0.599 (95% CI 0.357-0.766; P <.001) in the younger age group and 0.659 (95% CI 0.408-0.818; P <.001) in the older age group.

Principal Findings

This is the largest study to date on the validation and feasibility of remote ADHD testing. We found good agreement between the remote- and face-to-face–administered ADHD-RS-IV. This study also showed significant potential benefits for children and their caregivers in terms of reducing hospital visits and waiting times.

Additionally, as many as 14 (23%) out of the 61 caregivers who participated in the study had no previous experience with remote video calls; however, this did not pose a significant problem. This can be partly attributed to the staff providing detailed instructions. However, it is also possible that children who had attended internet-based classes at school because of the COVID-19 pandemic were able to provide guidance on the operation of the technology.

The results showed that the agreement rate between the face-to-face and remote assessments was lower in patients with ASD than in those with ADHD, according to the ADHD-RS-IV. One possible reason for the difference in results between patients with ADHD and ASD is the variability in interpretation among caregivers and evaluators. For example, when asked, “Does it seem like the child is not listening when spoken to?” caregivers of children with ASD, who may already have limited social interaction, may readily answer “yes” or “always.” In contrast, they may consider it a symptom of autism rather than inattentiveness related to ADHD and answer “no.” The wide range of interpretations provided by caregivers and evaluators may be a contributing factor [ 27 ].

The ADHD-RS-IV results indicated that the inattention ICC scores were numerically lower than the hyperactivity scores. This may be due to the remote assessment environment. At the time of enrollment, a quiet environment was recommended for remote assessments. However, because of the space and density of patients’ homes, situations often arose where there were numerous stimuli, such as the presence of toys or the assessment interview being conducted while other siblings were nearby or in the same room. These circumstances, compared with a controlled hospital consultation room, may have influenced the raters’ impressions of the participants in remote assessments. Moreover, when assessments take place at home, caregivers may feel uncomfortable explaining the severe or negative condition of their children in the presence of their child or other family members. It would be desirable to confirm in advance whether a space can be secured or a time when no other siblings are present can be arranged for remote assessment.

Our results have shown higher agreement rates in the older age group (≥11 years) compared to the younger age group (≤10 years). Symptoms such as hyperactivity and inattention in younger children may be more apparent in their home environment than in controlled settings due to familiarity and less stimulation control, resulting in a slight decrease in agreement with the assessment. Although there may be a benefit to internet-based assessment in regard to observing how the child typically behaves in relaxed homes, older children may be better suited for remote assessment in terms of agreement with face-to-face evaluation.

The potential time-saving effect, considering the time for visits to the hospital and waiting time at the hospital, was found to be 97.7 (SD 42.5; range 40-260) minutes. Given the increase in dual-income households in Japan, which has resulted in less time being spent with children, it would be highly meaningful if we could save this amount of time using remote assessments without reducing quality.

In addition, this research was conducted during the COVID-19 pandemic (the state of emergency was first declared on March 13, 2020, and was removed from the special measures law on May 8, 2023), which may have influenced the results. Although telemedicine was introduced in Japan, it was not widely adopted because of reluctance from the perspective of medical fees. Therefore, in many cases, people had to go to the hospital, facing the risk and anxiety of infection. The importance of having such tools ready to prepare for future outbreaks cannot be overlooked. While the demand for and evidence of telemedicine are expanding, there are also challenges. Issues such as the digital divide, which refers to the disparity that arises between people who can use the internet and computers and those who cannot, and in Japan specifically, the difficulty in widespread adoption due to regulations preventing billing for such services, are notable.

Based on the results of our study, telemedicine may be used under the following conditions: (1) in areas where there is a shortage of medical resources, such as public health and developmental support centers, by collaborating with child psychiatrists, clinical psychologists, and other medical professionals; (2) in central evaluations in clinical trials; and (3) to evaluate treatment effectiveness by combining and complementing face-to-face visits. Although further studies are needed, it may be used to screen children and their parents who are unsure whether to see a specialist and to provide assessment support for clinics without developmental testing capabilities.

Nevertheless, a careful balance must be maintained, as direct in-person assessment provides advantages such as observing nonverbal cues and behaviors, which may be important for a comprehensive understanding of the child’s condition.

Limitations

This study had several limitations. First, it was limited to children who had already been diagnosed and had received medical care and treatment. Therefore, these results do not apply to undiagnosed neurotypes. This study aimed to explore whether remote assessment tools could be helpful when children with developmental issues and their caregivers seek medical assistance. Therefore, the study design did not encompass typically developing children. Nonetheless, ICC, which usually tends to exhibit higher values when there is a diverse range of patient scores, manifested a relatively high degree of agreement, specifically in the group of children affected in this study. This can be interpreted as endorsing the validity of remote assessment procedures in this context. Second, although our study effectively indicated the potential for high-accuracy remote assessments, this does not necessarily guarantee a remote diagnosis. However, considering the frequent use of the ADHD-RS-IV in the diagnostic process for ADHD, the fact that we have demonstrated its robustness in the context of remote assessment may suggest its utility for future diagnoses. Even if remote ADHD-RS-IV assessments do not replace diagnosis during the first visit, they can be used to identify individuals who should be prioritized for early assessment by conducting severity evaluations and triages, thus expediting their initial consultation. To compensate for the weaknesses of this study, future studies should focus on examining the congruence between severity assessments and diagnoses conducted remotely in comparison with in-person evaluations, in addition to evaluating the efficacy of remote methods across diverse subpopulations.

Comparison With Previous Work

There have been few studies comparing ADHD assessment scales in face-to-face and remote settings. In previous research in the field of neurodevelopmental disorders, there is a report on the usability and reliability of the Autism Diagnostic Observation Schedule conducted face-to-face and remotely with 23 adults with ASD [ 16 ]. The ICC between face-to-face and remote was high at 0.92. In their report, technicians were present in the room during the remote assessment to provide assistance with technical operations, whereas in this study, we made it possible for participants to operate the equipment themselves at home without the help of technicians. Additionally, in that study, the same examiner conducted the tests in both face-to-face and remote settings for all cases. In contrast, in our study, different examiners conducted the tests in face-to-face and remote settings. Although it is difficult to compare because the disorder and assessment tools are different, considering these factors, the ICC value of our results is comparable, indicating a new finding in this field.

Conclusions

The results of this study showed that developmental assessments can be conducted with the same level of accuracy using remote tools as compared to face-to-face assessments. This means that even medical institutions where specialized assessments are not available, as well as health care centers, can benefit from these assessments, thereby improving the convenience for children who require early detection and intervention. Future research is needed to investigate the consistency of remote assessments and diagnoses compared with the initial face-to-face examination as well as the effectiveness of remote examinations in various subpopulations.

Acknowledgments

This study was supported in part by the Japan Science and Technology Agency Program on Open Innovation Platform With Enterprises, Research Institute, and Academia (JST-OPERA; grant JPMJOP1842; Principal Investigator Hiroaki Miyata) and by MICIN Inc, Tokyo, Japan.

Conflicts of Interest

KN has received speaker’s honoraria from Takeda, Janssen, Eli Lilly, Eisai, MSD, Otsuka, and Shionogi. MK has received honoraria from Takeda and Shionogi. TK has received consultant fees from Dainippon Sumitomo, Novartis, and Otsuka; speaker’s honoraria from Banyu, Eli Lilly, Dainippon Sumitomo, Janssen, MSD, Novartis, Otsuka, and Pfizer; and grant support from Takeda, Dainippon-Sumitomo, and Otsuka. The remaining authors have no conflicts of interest to declare.

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Abbreviations

Edited by T de Azevedo Cardoso, Y Hong; submitted 10.08.23; peer-reviewed by T Ewais, J Hamid, E Ikefuama; comments to author 30.11.23; revised version received 13.12.23; accepted 14.12.23; published 19.02.24.

©Shunya Kurokawa, Kensuke Nomura, Nana Hosogane, Takashi Nagasawa, Yuko Kawade, Yu Matsumoto, Shuichi Morinaga, Yuriko Kaise, Ayana Higuchi, Akiko Goto, Naoko Inada, Masaki Kodaira, Taishiro Kishimoto. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 19.02.2024.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.

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