Intervention Design & Analysis Report
The Intervention Design & Analysis Report tests your learning of the research methods and statistical techniques related to intervention design and analysis covered in the course. It includes three questions, each containing multiple parts, and the questions cover learning of
(i) Intervention design & development
(ii) Tests of difference to assess impact of intervention
(iii) Tests of association to see what predicts intervention outcomes
The first question focuses on research methodology, while the second and third questions focus on performing analyses. All analyses should be performed using SPSS. A dataset containing the information needed to perform analyses for the second and third question has been uploaded to Blackboard. A paper has also been made available to help you to answer Q3a. In addition to successfully performing and reporting the analyses, you must be clear in how you interpret the results of your analysis, so state what the results mean.
Assessment information
• The answer for the first question should be no more than 1000 words.
• The answer for the second question should be no more than 1500 words
• The answer for the third question should be no more than 1500 words.
• To complete the report you will have to run analyses in SPSS.
(i) Intervention design & development (30%)
A local education authority official (Mr Turnip) approaches you to help create an effective intervention to promote eating five portions of fruit and vegetables among schoolchildren (aged 6-7) in Birmingham, UK. Use Intervention Mapping to outline the steps you would need to follow in the design and development of this intervention and describe the intervention content you would propose to use, based on existing evidence. Also, report how the intervention would be delivered and how you would assess the success of the intervention. Remember to explain your decisions.
MAXIMUM WORD LIMIT = 1000.
(ii) Tests of difference {35%}
(a) Prof Burger wants to test the hypothesis that schoolchildren eat more unhealthily at the weekend than on weekdays. He collects data that supports his hypothesis and wants to know why schoolchildren eat more unhealthily at the weekend than on weekdays. To answer this question he measures attitudes (beliefs about unhealthy eating) and intentions (goals/plans) to eat unhealthily on three nights (Thursday, Friday or Saturday), to see if values differ. Test the hypothesis that ‘Night’ affects (i) attitudes to eat unhealthily and (ii) intentions to eat unhealthily. Report if variances are equal or unequal and then report and interpret the results (15 marks).
(b) Prof Burger also wants to know if there are differences in intentions to eat unhealthily in two different locations (school or home). Compare the impact of ‘Location’ on intentions to eat unhealthily. Report if the variances are equal or unequal then report and interpret the results (10 marks).
(c) Compare the impact of gender on intentions controlling for attitudes. Report and interpret the results (10 marks).
(iii) Tests of association {35%}
Dr Snack wants to test the idea that psychological variables from the Theory of Planned Behaviour (TPB; Ajzen, 1991) predict undergraduates’ snack intentions and behaviour.
(a) Use McEachan et al.’s (2011) Health Psychology Review meta-analysis to report the average correlations for TPB variables for Dietary Behaviours and comment on which variables have the strongest relationships with intentions (10 marks).
(b) Dr Hemingway collects data from a sample of undergraduates. Participants complete TPB measures and also measures of anticipated regret (anticipating regret at snacking) and past snacking behaviour (snacking over the course of the last week). Conduct and report the correlations between each predictor variable and intentions, then state the direction, significance and size of these relationships. Also, conduct and report the correlations between predictor variables and comment on the independence of these variables from other predictors. Display all correlations in a table (15 marks)
(c) Perform a linear regression to predict snack intentions. Enter all variables that correlate with intentions into the regression. Summarise the results using a table. State which variables are significant predictors of snacking and interpret these results. (10 marks)
