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Erschienen in:
01.12.2013 | Review Article
Optimal patient education for cancer pain: a systematic review and theory-based meta-analysis
Erschienen in: Supportive Care in Cancer | Ausgabe 12/2013
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Purpose
Previous systematic reviews have found patient education to be moderately efficacious in decreasing the intensity of cancer pain, but variation in results warrants analysis aimed at identifying which strategies are optimal.
Methods
A systematic review and meta-analysis was undertaken using a theory-based approach to classifying and comparing educational interventions for cancer pain. The reference lists of previous reviews and MEDLINE, PsycINFO, and CENTRAL were searched in May 2012. Studies had to be published in a peer-reviewed English language journal and compare the effect on cancer pain intensity of education with usual care. Meta-analyses used standardized effect sizes (ES) and a random effects model. Subgroup analyses compared intervention components categorized using the Michie et al. (Implement Sci 6:42, 2011) capability, opportunity, and motivation behavior (COM-B) model.
Results
Fifteen randomized controlled trials met the criteria. As expected, meta-analysis identified a small-moderate ES favoring education versus usual care (ES, 0.27 [−0.47, −0.07]; P = 0.007) with substantial heterogeneity (I² = 71 %). Subgroup analyses based on the taxonomy found that interventions using “enablement” were efficacious (ES, 0.35 [−0.63, −0.08]; P = 0.01), whereas those lacking this component were not (ES, 0.18 [−0.46, 0.10]; P = 0.20). However, the subgroup effect was nonsignificant (P = 0.39), and heterogeneity was not reduced. Factoring in the variable of individualized versus non-individualized influenced neither efficacy nor heterogeneity.
Conclusions
The current meta-analysis follows a trend in using theory to understand the mechanisms of complex interventions. We suggest that future efforts focus on interventions that target patient self-efficacy. Authors are encouraged to report comprehensive details of interventions and methods to inform synthesis, replication, and refinement.