6533b7d1fe1ef96bd125c3a7

RESEARCH PRODUCT

When symptoms become side effects: Development of the side effect attribution scale (SEAS)

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Objectives\ud \ud Symptom misattribution is a central process in the nocebo effect but it is not accurately assessed in current side effect measures. We have developed a new measure, the Side Effect Attribution Scale (SEAS), which examines the degree to which people believe their symptoms are treatment side effects.\ud \ud \ud \ud Methods\ud \ud The SEAS was tested in three New Zealand studies: a vaccination sample (n = 225), patients with gout or rheumatoid arthritis (n = 102), and patients switching to a generic medicine (n = 69). The internal reliability of the scale was examined using Cronbach's alpha. To assess validity, the Side Effect Attribution Total Score and Side Effect Attribution Binary Score were related to a number of psychological measures associated with side effect reporting.\ud \ud \ud \ud Results\ud \ud The scale showed good internal reliability across the three studies, with Cronbach alphas ranging from 0.840 to 0.943. Analysis of the effect sizes showed that the Attribution Total Score was generally more strongly associated with nocebo responding than Attribution Binary Score. Participants had greater Side Effect Attribution Total Scores if they had higher expectations for vaccination side effects (r = 0.18, p = .028), more worry about future vaccine effects (r = 0.16, p = .046), a higher perceived sensitivity to medicines (r = 0.50, p < .001), greater anxiety (r = 0.25, p = .016), greater intentional non-adherence (r = 0.30, p = .003), greater medicine information seeking (r = 0.26, p = .010), lower trust in pharmaceutical agencies (r = −0.29, p = .026), and lower medicine efficacy beliefs (r = −0.46, p < .001).\ud \ud \ud \ud Conclusions\ud \ud The SEAS provides a more nuanced assessment of symptom attribution beliefs. It appears to be more sensitive measure than just a side effect total, as it is associated with a greater number of relevant psychological variables. Future research should examine the scale in other populations and settings.