UID:
almahu_9949641809502882
Format:
1 online resource (xxii, 212 pages).
Edition:
First edition.
ISBN:
9781003453079
,
1003453074
,
9781003830115
,
1003830110
,
9781003830061
,
1003830064
Content:
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, and points the reader to sources with more in-depth information. This book is intended for those with little or no background in statistics, to give them the confidence to approach statistics in published literature with a more critical eye, recognise when more specialist advice is needed, and give them the ability to communicate more effectively with statisticians. Key Features: Strong focus on quantitative research methods Complements more technical introductions to statistics Provides a good explanation of how quantitative studies are designed, and what biases and pitfalls they can involve
Note:
1. Introduction2. Why observational studies can be misleading3. How to select an outcome measure4. Improvement due to nonspecific effects of intervention5. Limitations of the pre-post design: biases related to systematic change6. Estimating unwanted effects with a control group7. Controlling for selection bias: randomized assignment to intervention8. The researcher as a source of bias 9. Further potential for bias: volunteers, dropouts, and missing data10. The randomized controlled trial as a method for controlling biases11. The importance of variation12. Analysis of a two-group RCT13. How big a sample do I need? Statistical power and type II errors 14. False positives, p-hacking and multiple comparisons15. Drawbacks of the two-arm RCT16. Moderators and mediators of intervention effects17. Adaptive Designs18. Cluster Randomized Controlled Trials19. Cross-over designs 20. Single case designs21. Can you trust the published literature?22. Pre-registration and Registered Reports23. Reviewing the literature before you start 24. Putting it all together25. Comments on exercises26. References
Language:
English
DOI:
10.1201/9781003453079
URL:
https://www.taylorfrancis.com/books/9781003453079
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