Differential attrition in health behaviour change trials: A systematic review and meta-analysis

Psychology and Health

Volumn 30, Issue 1, 2015, Pages 122-134

  Crutzen, Rik ^a   Viechtbauer, Wolfgang ^b   Spigt, Mark ^a,c   Kotz, Daniel ^a,d  

^a MAASTRICHT UNIVERSITY   (Netherlands)

^b MAASTRICHT UNIVERSITY   (Netherlands)

^c UNIVERSITY OF TROMSØ   (Norway)

^d UNIVERSITY COLLEGE LONDON   (United Kingdom)

Author keywords

bias; differential attrition; health behaviour change; internal validity; RCT

Indexed keywords

HEALTH BEHAVIOR; HUMAN; META ANALYSIS; PATIENT DROPOUTS; RANDOMIZED CONTROLLED TRIAL (TOPIC); STATISTICAL BIAS; STATISTICS AND NUMERICAL DATA;

BIAS (EPIDEMIOLOGY); HEALTH BEHAVIOR; HUMANS; PATIENT DROPOUTS; RANDOMIZED CONTROLLED TRIALS AS TOPIC;

EID: 84918561575     PISSN: 08870446     EISSN: 14768321     Source Type: Journal    
DOI: 10.1080/08870446.2014.953526     Document Type: Article

References (36)

1. Ayling, K., Brierley, S., Johnson, B., Heller, S., & Eiser, C. (2015). How standard is standard care? Exploring control group outcomes in behaviour change interventions for young people with type 1 diabetes. Psychology & Health, 30(1), 85–103.
2. Blom, M., Georgiades, A., Janszky, I., Alinaghizadeh, H., Lindvall, B., & Ahnve, S. (2009). Daily stress and social support among women with CAD: Results from a 1-year randomized controlled stress management intervention study. International Journal of Behavioral Medicine, 16, 227–235.10.1007/s12529-009-9031-y
3. Boutron, I., Guittet, L., Estellat, C., Moher, D., Hróbjartsson, A., & Ravaud, P. (2007). Reporting methods of blinding in randomized trials assessing nonpharmacological treatments. PLoS Medicine, 4, e61.10.1371/journal.pmed.0040061
4. Boutron, I., Tubach, F., Giraudeau, B., & Ravaud, P. (2003). Methodological differences in clinical trials evaluating nonpharmacological and pharmacological treatments of hip and knee osteoarthritis. The Journal of the American Medical Association, 290, 1062–1070.
5. Boutron, I., Tubach, F., Giraudeau, B., & Ravaud, P. (2004). Blinding was judged more difficult to achieve and maintain in nonpharmacologic than pharmacologic trials. Journal of Clinical Epidemiology, 57, 543–550.10.1016/j.jclinepi.2003.12.010
6. Crocetti, M. T., Amin, D. D., & Scherer, R. (2010). Assessment of risk of bias among pediatric randomized controlled trials. Pediatrics, 126, 298–305.10.1542/peds.2009-3121
7. Crutzen, R., Peters, G.-J. Y., & Abraham, C. (2012). What about trialists sharing other study materials? British Medical Journal, 345, e8352.10.1136/bmj.e8352
8. Crutzen, R., Viechtbauer, W., Kotz, D., & Spigt, M. (2013). No differential attrition was found in randomized controlled trials published in general medical journals: A meta-analysis. Journal of Clinical Epidemiology, 66, 948–954.10.1016/j.jclinepi.2013.03.019
9. David, M. C., Alati, R., Ware, R. S., & Kinner, S. A. (2013). Attrition in a longitudinal study with hard-to-reach participants was reduced by ongoing contact. Journal of Clinical Epidemiology, 66, 575–581.10.1016/j.jclinepi.2012.12.002
10. de Bruin, M., McCambridge, J., & Prins, J. M. (2015). Reducing the risk of bias in health behaviour change trials: Improving trial design, reporting, or bias assessment criteria? A review and case study. Psychology & Health, 30(1), 8–34.
11. Dumville, J. C., Torgerson, D. J., & Hewitt, C. E. (2006). Reporting attrition in randomised controlled trials. British Medical Journal, 332, 969. Retrieved from http://www.bmj.com/content/332/7547/969
12. Duval, S. J., & Tweedie, R. L. (2000a). A nonparametric ‘trim and fill’ method of accounting for publication bias in meta-analysis. Journal of the American Statistical Association, 95, 89–98.
13. Duval, S. J., & Tweedie, R. L. (2000b). Trim and fill: A simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics, 56, 455–463.10.1111/j.0006-341X.2000.00455.x
14. Fleiss, J. L., & Berlin, J. A. (2009). Effect sizes for dichotomous data. In H. Cooper, L. V. Hedges, & J. C. Valentine (Eds.), The handbook of research synthesis and meta-analysis (2nd ed., pp. 237–253). New York, NY: Russell Sage Foundation.
15. Glasgow, R. E., Estabrooks, P. A., Marcus, A. C., Smith, T. L., Gaglio, B., Levinson, A. H., & Tong, S. (2008). Evaluating initial reach and robustness of a practical randomized trial of smoking reduction. Health Psychology, 27, 780–788.10.1037/0278-6133.27.6.780
16. Heneghan, C., Perera, R., Ward, A. A., Fitzmaurice, D., Meats, E., & Glasziou, P. (2007). Assessing differential attrition in clinical trials: Self-monitoring of oral anticoagulation and type II diabetes. BMC Medical Research Methodology, 7, 18.10.1186/1471-2288-7-18
17. Hewitt, C. E., Kumaravel, B., Dumville, J. C., & Torgerson, D. J. (2010). Assessing the impact of attrition in randomized controlled trials. Journal of Clinical Epidemiology, 63, 1264–1270.10.1016/j.jclinepi.2010.01.010
18. Higgins, J. P. T., & Green, S. (2008). Cochrane handbook for systematic reviews of interventions. Chichester: Wiley.10.1002/9780470712184
19. Kohl, L., Crutzen, R., & de Vries, N. K. (2013). Online prevention aimed at lifestyle behaviours: A systematic review of reviews. Journal of Medical Internet Research, 15, e146.10.2196/jmir.2665
20. Lurie, I., & Levine, S. Z. (2010). Meta-analysis of dropout rates in SSRIs versus placebo in randomized clinical trials of PTSD. The Journal of Nervous and Mental Disease, 198, 116–124.10.1097/NMD.0b013e3181cc41b6
21. Molenberghs, G., & Kenward, M. G. (2007). Missing data in clinical studies. Chichester: Wiley.10.1002/9780470510445
22. Noguchi, K., Albarracín, D., Durantini, M. R., & Glasman, L. R. (2007). Who participates in which health promotion programs? A meta-analysis of motivations underlying enrollment and retention in HIV-prevention interventions. Psychological Bulletin, 133, 955–975.10.1037/0033-2909.133.6.955
23. Peters, G.-J. Y., Abraham, C., & Crutzen, R. (2012). Full disclosure: Doing behavioural science necessitates sharing. The European Health Psychologist, 14, 77–84.
24. Peters, J. L., Sutton, A. J., Jones, D. R., Abrams, K. R., & Rushton, L. (2008). Contour-enhanced meta-analysis funnel plots help distinguish publication bias from other causes of asymmetry. Journal of Clinical Epidemiology, 61, 991–996.10.1016/j.jclinepi.2007.11.010
25. Prochaska, J. O., Velicer, W. F., Rossi, J. S., Redding, C. A., Greene, G. W., Rossi, S. R., … Plummer, B. A. (2004). Multiple risk expert systems interventions: Impact of simultaneous stage-matched expert system interventions for smoking, high-fat diet, and sun exposure in a population of parents. Health Psychology, 23, 503–516.10.1037/0278-6133.23.5.503
26. R Development Core Team. (2010). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing.
27. Rabinowitz, J., Levine, S. Z., Barkai, O., & Davidov, O. (2009). Dropout rates in randomized clinical trials of antipsychotics: A meta-analysis comparing first- and second-generation drugs and an examination of the role of trial design features. Schizophrenia Bulletin, 35, 775–788.10.1093/schbul/sbn005
28. Raudenbush, S. W. (2009). Analyzing effect sizes: Random-effects models. In H. Cooper, L. V. Hedges, & J. C. Valentine (Eds.), The handbook of research synthesis and meta-analysis (2nd ed., pp. 295–315). New York, NY: Russell Sage Foundation.
29. Schulz, K. F., & Grimes, D. A. (2002). Sample size slippages in randomised trials: Exclusions and the lost and wayward. The Lancet, 359, 781–785.10.1016/S0140-6736(02)07882-0
30. Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimental designs for generalized causal inference. Boston, MA: Houghton-Mifflin.
31. Stein, D. J., Ipser, J. C., & Seedat, S. (2006). Pharmacotherapy for post traumatic stress disorder (PTSD). Cochrane Database of Systematic Reviews, Art. No.: CD002795. Retrieved from http://www.thecochranelibrary.com/userfiles/ccoch/file/PTSD/CD002795.pdf
32. Sterne, J. A. C., & Egger, M. (2005). Regression methods to detect publication and other bias in meta-analysis. In H. R. Rothstein, A. J. Sutton, & M. Borenstein (Eds.), Publication bias in meta-analysis: Prevention, assessment and adjustment (pp. 99–110). Chichester: Wiley.
33. Toobert, D. J., Strycker, L. A., Glasgow, R. E., Barrera, M., Jr., & Angell, K. (2005). Effects of the mediterranean lifestyle program on multiple risk behaviors and psychosocial outcomes among women at risk for heart disease. Annals of Behavioral Medicine, 29, 128–137.10.1207/s15324796abm2902_7
34. Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor package. Journal of Statistical Software, 36, 1–48.
35. Viechtbauer, W., & Cheung, M. W.-L. (2010). Outlier and influence diagnostics for meta-analysis. Research Synthesis Methods, 1, 112–125.10.1002/jrsm.v1:2
36. Wortman, P. M. (1978). Differential attrition: Another hazard of follow-up research. American Psychologist, 33, 1145–1146.10.1037/0003-066X.33.12.1145