1. SOCW 671 # 8 Single Subject/System Designs Intro to Sampling

2. Single-Subject Designs  Evaluation designs that involve arrangements in which repeated observations are taken before, during, and/or after an intervention.  These observations are compared to monitor the progress and assess the outcome of that service.

3. Logic of Single Subject/System Designs Unlike experimental designs that involve experimental and control groups, single system designs have one identified client/system This identified client/system may be an individual or group These designs are based on a time- series

4. Use on the Micro Level of Social Work Practice If you are practicing at the micro level, this likely will be the most common method to use. Directly related to client progress

5. Measurement Issues Need to specify targets of intervention by having an operational definition of target behavior Triangulation - the use of two or more indicators or measurement strategies when confronted with a multiplicity of measurement options Self-report scales often used, these have plusses and minuses

6. Unobtrusive Measurement Preferred Will want to reduce bias and reactivity through the use of unobtrusive measurement (means observing and recording behavioral data in ways that by and large are not noticeable to the person being observed).

7. First Need Baseline (control phase) Measures Pattern should not reflect a trend of dramatic improvement to the degree that it suggests the problem is nearing resolution Should have many measurement points Chronologically graphed data should be stable

8. Alternative Designs AB ABAB Multiple Baseline & Successive Interventions Multiple Component

9. AB: Basic Single-Subject Design  Collect data during baseline period  Collect data during intervention  Problems is that it does not control well for history

10. ABAB: Withdrawal/Reversal Design  Two problems  Improvement in target behavior may not be reversible even when intervention is withdrawn  Practitioner may be unwilling to withdraw something that appears to be working

11. Multiple Baseline-Design (Successive Interventions) Consists of several different interventions The interventions are staggered. Each intervention is applied one after another in separate phases. The application of the intervention is provided to different target problems, settings, or individuals

12. Multiple-Component Design Combines elements of the experimental replication and successive intervention designs. Can be used with or without baselines/ Purpose is to compare the relative effectiveness of two different interventions Problems with being able to infer that only one component resulted in target behavior

13. Data Analysis Two-standard deviation-band approach (Sheward Chart) Chi-square t-test & ANOVA

14. Shewart Chart Mean level of baseline data is identified Two standard deviation levels (bands) are constructed above and below the mean line These bands are extended into the intervention phase If two successive observations during intervention, there is a significant change

15. Complicating Factors Carryover – occurs when the effects obtained in one phase appear to carry over into the next phase Contrast – when the subject reacts to the difference in the two interventions or phases Order of presentation – when the order of the phases by themselves may be part of a causal impact Incomplete data – when a subject of client does not “fit” nicely into the phase time frame Training Phase – client may not have the prerequisite skills for full participation in the intervention when it begins

16. Causality Criteria in Single Subject (System) Designs temporal arrangement co-presence of the intervention & desired change in target behavior repeated co-presence of the intervention and the manifestations of the desired change consistency over time conceptually and practically grounded in scientific/professional knowledge.

17. Design Validity & Reliability Replication is very useful Statistical Conclusion Validity: Did Change Occur? Internal Validity: Was change Caused by Intervention? Construct Validity: Was Intervention and Measurement of Outcomes Accurately Conducted?

18. Intro to Sampling Non-probability Probability

19. Non-probability Reliance on available subjects Quota sampling Snowball sampling Selecting informants

20. Probability Simple random Systematic Stratified Cluster

21. Issues in Program Evaluation Evaluation as Representation  Program evaluation is not the program, only a snap shot of it  Organizations are complex, therefore evaluations often focus on select services  Evaluations can go beyond consumer focus, may review staff, community relations, continuing education, etc.

22. Common Characteristics Program models Resource constraints Evaluation tools Politics and ethics Cultural considerations Presentation of evaluation findings

23. Common Characteristics (continued) Program models  Need blueprint as expressed by logic model  Program survival requires that evaluation be performed to maintain contracts  Outputs and outcomes monitored Outputs are non-client related objectives Outcomes are client related objectives  Infrastructure related objectives serve program maintenance function

24. Common Characteristics (continued) Resource constraints  Insufficient time, staff, money, or evaluation know- how  Typical implementation time Needs assessment 3 to 6 months Evaluability assessment 3 to 6 months Process evaluation 12 to 18 months Outcome evaluation 6 to 12 months Cost-benefit analysis 1 to 2 months