Clarifying the Overlap Between Motivation and Negative Symptom Measures in Schizophrenia Research: A Meta-analysis

Overview

Journal Schizophr Res

Specialty Psychiatry

Date 2018 Dec 23

PMID 30577993

Citations 9

Authors

Lauren Luther

Melanie W Fischer

Ruth L Firmin

Michelle P Salyers

Affiliations

Soon will be listed here.

Abstract

Motivation and negative symptom research has recently been hampered by a series of inconsistent findings, leading to calls for a greater consensus on the type of measures used across studies. To inform this issue, we conducted a meta-analysis that quantified the association between motivation measures (self-report, performance-based) and clinician-rated negative symptom measures as well as a series of moderator analyses to develop a greater understanding of the measurement factors impacting this relationship. Forty-seven eligible studies with people with schizophrenia-spectrum disorders were included. Using a random-effects meta-analytic model, a small but significant overall effect size emerged between motivation and clinician-rated negative symptoms (r = -0.18). Several significant moderators were identified, including the generation of negative symptom measures such that there was a significantly stronger relationship between motivation and second-generation (r = -0.38) than first-generation negative symptom measures (r = -0.17). Further, the type of performance-based measure used moderated the relationship, with effort discounting tasks most strongly related to negative symptoms (r = -0.44). The domain of motivation assessed (intrinsic, extrinsic, amotivation) also moderated the relationship. These findings help to identify sources of inconsistencies observed in prior studies and point to both second-generation and effort discounting tasks as the most promising types of measures, particularly for those interested in validating motivation measures or assessing the effectiveness of motivation treatments. Although additional research is needed, our results suggest that using these measures may help to reduce inconsistencies across studies and move the field forward.

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