Who says yes? Identifying selection biases in a psychosocial intervention study of multiple sclerosis

The purpose of this work is to examine whether patients' sociodemographic and medical characteristics are associated with participation in a randomized controlled trial of two psychosocial interventions. After elimination of basic ineligibles from a registry of multiple sclerosis patients, 325...

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Veröffentlicht in:Social science & medicine (1982) 1995-02, Vol.40 (3), p.359-370
Hauptverfasser: Schwartz, Carolyn E., Fox, Bernard H.
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Sprache:eng
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Zusammenfassung:The purpose of this work is to examine whether patients' sociodemographic and medical characteristics are associated with participation in a randomized controlled trial of two psychosocial interventions. After elimination of basic ineligibles from a registry of multiple sclerosis patients, 325 patients were sent a letter inviting participation in the randomized trial. Among those invited, 29% expressed an interest in participating, 19% scheduled an intake interview and 13% were actually randomized. x 2 and logistic regression analyses were used to determine what factors were associated with successive stages of participation or non-participation in the study. Differential referral and participation rates could be traced in part to physician factors. With respect to patient factors, people were more likely to participate in the successive stages of recruitment if they had a higher median family income, lived a moderate distance from the hospital, and were disabled from working. Multivariate analyses of patient factors revealed that having a higher income and being disabled from work were the strongest predictors of participation, after adjusting for the effects of course of disease, disability status, and other sociodemographic predictors. Implications of these findings are discussed in terms of potential sources of bias in the selection of eligible patients, as well as the role the investigator may play in highlighting or underplaying this selection bias. Suggestions are made to minimize the bias-generating barriers.
ISSN:0277-9536
1873-5347
DOI:10.1016/0277-9536(94)E0092-7