1. Psy2005: Applied Research Methods & Ethics in Psychology Lab Week 7: Using Simple Effects to investigate the effects of type of session and type of therapy on self-reported drug use 1

2. SPSS data files Open Psy2005 folder Open Week 7 Double click on ‘drug treatments3.sav’ Fundamental principle ◦ Each participant has their own row ◦ Each different bit of data must go in a separate column / variable Data view vs. Variable View ◦ Change via ‘tabs’ at bottom of window  or keyboard combination ⌘ T ◦ Data view for viewing / editing data ◦ Variable view for details of variables Tutor Led

3. Aims & Outcomes Provide an overview of research focusing on drug treatments Conduct a Simple Effects analysis on an independent groups factorial ANOVA ◦ Session when treatment is held constant ◦ Treatment when session is held constant Explain the key features of Simple Effects 3

4. Work on your own, in groups, whatever you feel is best for you! 4

5. Drug Treatments in Current Study Treatments (Weekly Sessions) ◦ 12-Step programme ◦ A Cognitive–Behavioural Motivational Intervention ◦ Standard care Type of session ◦ Group therapy ◦ Individual therapy Outcome Measures (1, 6, & 12 months) ◦ Self-monitored logbooks: drugs taken ◦ Recordings taken over a 28 day period prior to measurement 5

6. Participants & Therapists Participants: ◦ Prolific and other Priority Offender status and tested positive for cocaine or heroin during their arrest. ◦ Randomly allocated to one of the three groups. Therapists: Twelve therapists ran the sessions. ◦ All were qualified to degree standard and had a minimum of three years experience 6

7. Procedure Participants took part as part of a voluntary rehabilitation procedure Participants had either: ◦ 90 minute weekly closed (nobody was allowed to join after the first session) meetings in groups of 4-8 people with two Counsellors. ◦ 45 minute weekly individual sessions with one Counsellor Participants attended the sessions for 1 year. Treatment outcomes were measured at 1 month, 6 months & 12 months. 7

8. About the Experiment! Teasing apart the design ◦ Independent variables:  Type of drug treatment : 12 Step, CBT/MI, Standard Care  Type of session: group, individual ◦ Dependent variable  Self-reported drug use 8

9. Factorial ANOVA Total Variability Variance Explained by the Experiment Variance explained by treatment Variance explained by session Variance Explained by interaction between treatment and session Unexplained Variance 9

10. 10 Self-reported drug use at time: 1 month Self-reported drug use at time: 6 months Self-reported drug use at time: 1 Year Type of session: Group Vs Individual therapy Situation. More on this later! Type of therapy: 12 Step CBT with MI Standard care.

11. Conducting a factorial ANOVA 11 Student Led

12. 12 Student Led

13. The Output: The ANOVA Session (F(1,136)=10.352, MSe=1.650, p=0.002) Therapy (F(2,136)=13.550, MSe=1.650, p<0.001) Session x Therapy (F(2,136)=4.402, MSe=1.650 p=0.014) 13 Tutor Led

14. The Output: The interaction effect (F(2,136)=4.402, MSe=1.650, p=0.014) 14 Tutor Led

15. Conclusions: This is your first Summative Assessment Following a Factorial ANOVA on Drug Use (1 month) the following findings were observed ◦ Main effect for Session Factor ◦ Main effect for Treatment Factor ◦ Interaction effect for Session x Therapy What does this mean? ◦ You will have to wait until Week 8 to get a better understanding of the interaction. ◦ Before then, look at the graph and try to make sense of it yourself ◦ You need to understand this as it forms an integral part of your first summative assessment 15 Tutor Led

16. Evaluating the interaction effect: Simple Effects Interpreting main effects: Does the factor have a similar effect at all levels of the other factor Are the lines parallel? Interpreting interaction effects: A statistical interaction occurs when the effect of one independent variable on the dependent variable changes depending on the level of another independent variable. Simple Effect analysis is the examination of the effect of one factor at all levels of the other factor For our example there are two simple effects for type of treatment (more if they are significant!) and three simple effects for type of session. We will use the error term from the main ANOVA as our denominator as this is the most accurate measure of unexplained variance (MSe=1.650, df=136) 16 Tutor Led

17. Simple Effects for type of Session: Plotting the analyses 17 1. 2. 3. Session: 1.group vs individual at 12 Step 2.group vs individual at CBT/MI 3.group vs individual at Stan. Care Tutor Led

18. Back to SPSS: Select Cases for 12-step participants 18 Student Led

19. Select Cases for 12-step participants 19 Student Led

20. Independent Groups ANOVA Independent Groups ANOVA 20 Student Led

21. Output for Session at 12-Step Apply a Bonferroni correction as we are carrying out a family of tests (0.05/3=0.0167) Session at 12-Step (F(1,136)=14.596, MSe=1.650, p<0.001) These findings show that there is a significant reduction in self-reported drug use when the 12-step was presented in group sessions as opposed to individual sessions 21 This is replaced With MSe=1.650 This is replaced With MSe=1.650 This is replaced With df=136 This is replaced With df=136 This becomes 14.596 Student Led

22. Back to SPSS: Select Cases for CBT/MI participants 22 Student Led

23. Select Cases for CBT/MI participants 23 Student Led

24. Intependent Groups ANOVA 24 Student Led

25. Output for Session at CBT/MI Apply a Bonferroni correction as we are carrying out a family of tests (0.05/3=0.0167) Session at CBT/MI(F(1,136)=4.584, MSe=1.650, p=0.034) These show that the group session is more effective at CBT/MI but the correction means we cannot accept these findings as significant 25 This is replaced With MSe=1.650 This is replaced With MSe=1.650 This is replaced With df=136 This is replaced With df=136 This becomes 4.584 Student Led

26. Back to SPSS: Select Cases for Standard Care participants 26 Student Led

27. Select Cases for Standard Care participants 27 Student Led

28. Intependent Groups ANOVA 28 Student Led

29. Output for Session at Standard Care Apply a Bonferroni correction as we are carrying out a family of tests (0.05/3=0.0167) Session at CBT/MI(F(1,136)=0.135, MSe=1.650, p=0.714) These show no significant differences between the two types of session at Standard Care 29 This is replaced With MSe=1.650 This is replaced With MSe=1.650 This is replaced With df=136 This is replaced With df=136 This becomes 0.135 Student Led

30. Simple Effects for type of Session: Plotting the analyses 30 1. 2. 3. Session: 1.group vs individual at 12 (F(1,136)=14.596, MSe=1.650, p<0.001) 2.group vs individual at CBT/MI (F(1,136)=4.584, MSe=1.650, p=0.034 NS) 3.group vs individual at Stan. Care (F(1,136)=0.135, MSe=1.650, p=0.714 NS) Tutor Led

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32. Workbook 1 (Week 7) 32 There is no Workbook 1 (week 7) but please make sure you take a copy of the PPT files as they contain all of the information you need to write your lab report.