Description

Book Synopsis

Those who work in allied health professions and education aim to make people's lives better. Often, however, it is hard to know how effective this work has been: would change have occurred if there was no intervention? Is it possible we are doing more harm than good? To answer these questions and develop a body of knowledge about what works, we need to evaluate interventions. Objective intervention research is vital to improve outcomes, but this is a complex area, where it is all too easy to misinterpret evidence. This book uses practical examples to increase awareness of the numerous sources of bias that can lead to mistaken conclusions when evaluating interventions. The focus is on quantitative research methods, and exploration of the reasons why those both receiving and implementing intervention behave in the ways they do. Evaluating What Works: Intuitive Guide to Intervention Research for Practitioners illustrates how different research designs can overcome these issues

Table of Contents

1. Introduction 2. Why observational studies can be misleading 3. How to select an outcome measure 4. Improvement due to nonspecific effects of intervention 5. Limitations of the pre-post design: biases related to systematic change 6. Estimating unwanted effects with a control group 7. Controlling for selection bias: randomized assignment to intervention 8. The researcher as a source of bias 9. Further potential for bias: volunteers, dropouts, and missing data 10. The randomized controlled trial as a method for controlling biases 11. The importance of variation 12. Analysis of a two-group RCT 13. How big a sample do I need? Statistical power and type II errors 14. False positives, p-hacking and multiple comparisons 15. Drawbacks of the two-arm RCT 16. Moderators and mediators of intervention effects 17. Adaptive Designs 18. Cluster Randomized Controlled Trials 19. Cross-over designs 20. Single case designs 21. Can you trust the published literature? 22. Pre-registration and Registered Reports 23. Reviewing the literature before you start 24. Putting it all together 25. Comments on exercises 26. References

Evaluating What Works

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    £43.69

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    Order before 4pm today for delivery by Thu 25 Jun 2026.

    A Paperback by Dorothy V. M. Bishop, Paul Thompson

    15 in stock


      View other formats and editions of Evaluating What Works by Dorothy V. M. Bishop

      Publisher: Taylor & Francis Ltd
      Publication Date: 1/7/2023 12:12:00 AM
      ISBN13: 9781032590615, 978-1032590615
      ISBN10: 1032590610

      Description

      Book Synopsis

      Those who work in allied health professions and education aim to make people's lives better. Often, however, it is hard to know how effective this work has been: would change have occurred if there was no intervention? Is it possible we are doing more harm than good? To answer these questions and develop a body of knowledge about what works, we need to evaluate interventions. Objective intervention research is vital to improve outcomes, but this is a complex area, where it is all too easy to misinterpret evidence. This book uses practical examples to increase awareness of the numerous sources of bias that can lead to mistaken conclusions when evaluating interventions. The focus is on quantitative research methods, and exploration of the reasons why those both receiving and implementing intervention behave in the ways they do. Evaluating What Works: Intuitive Guide to Intervention Research for Practitioners illustrates how different research designs can overcome these issues

      Table of Contents

      1. Introduction 2. Why observational studies can be misleading 3. How to select an outcome measure 4. Improvement due to nonspecific effects of intervention 5. Limitations of the pre-post design: biases related to systematic change 6. Estimating unwanted effects with a control group 7. Controlling for selection bias: randomized assignment to intervention 8. The researcher as a source of bias 9. Further potential for bias: volunteers, dropouts, and missing data 10. The randomized controlled trial as a method for controlling biases 11. The importance of variation 12. Analysis of a two-group RCT 13. How big a sample do I need? Statistical power and type II errors 14. False positives, p-hacking and multiple comparisons 15. Drawbacks of the two-arm RCT 16. Moderators and mediators of intervention effects 17. Adaptive Designs 18. Cluster Randomized Controlled Trials 19. Cross-over designs 20. Single case designs 21. Can you trust the published literature? 22. Pre-registration and Registered Reports 23. Reviewing the literature before you start 24. Putting it all together 25. Comments on exercises 26. References

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