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      Mediators of Treatment Effect in the Back In Action Trial : Using Latent Growth Modeling to Take Change Over Time Into Account

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          Abstract

          Objectives:

          To test whether change in fear-avoidance beliefs was a mediator of the effect of treatment on disability outcome, and to test an analytical approach, latent growth modeling, not often applied to mediation analysis.

          Methods:

          Secondary analysis was carried out on a randomized controlled trial designed to compare an intervention addressing fear-avoidance beliefs (n=119) with treatment as usual (n=121) for patients with low back pain, which found the intervention to be effective. Latent growth modelling was used to perform a mediation analysis on the trial data to assess the role of change in fear-avoidance beliefs on disability outcome. The product of coefficients with bias-corrected bootstrapped confidence intervals was used to calculate the mediating effect.

          Results:

          A statistically significant mediating effect of fear-avoidance beliefs on the effect of treatment on disability outcome was found (standardized indirect effect −0.35; bias-corrected 95% CI, −0.47 to −0.24). Poor fit of the model to the data suggested that other factors not accounted for in this model are likely to be part of the same mediating pathway.

          Discussion:

          Fear-avoidance beliefs were found to mediate the effect of treatment on disability outcome. Measurement of all potential mediator variables in future studies would help to more strongly identify which factors explain observed treatment effects. Latent growth modelling was found to be a useful technique to apply to studies of treatment mediation, suggesting that future studies could use this approach.

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          Most cited references67

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          The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations.

          In this article, we attempt to distinguish between the properties of moderator and mediator variables at a number of levels. First, we seek to make theorists and researchers aware of the importance of not using the terms moderator and mediator interchangeably by carefully elaborating, both conceptually and strategically, the many ways in which moderators and mediators differ. We then go beyond this largely pedagogical function and delineate the conceptual and strategic implications of making use of such distinctions with regard to a wide range of phenomena, including control and stress, attitudes, and personality traits. We also provide a specific compendium of analytic procedures appropriate for making the most effective use of the moderator and mediator distinction, both separately and in terms of a broader causal system that includes both moderators and mediators.
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            Using Mutivariate Statistics

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              Beyond Baron and Kenny: Statistical Mediation Analysis in the New Millennium

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                Author and article information

                Journal
                Clin J Pain
                Clin J Pain
                AJP
                The Clinical Journal of Pain
                Lippincott Williams & Wilkins
                0749-8047
                1536-5409
                September 2017
                18 August 2017
                : 33
                : 9
                : 811-819
                Affiliations
                [* ]Research Institute for Primary Care & Health Sciences, Keele University, Keele, Staffordshire, UK
                []Group Health Research Institute, Seattle, WA
                Author notes
                Reprints: Gemma Mansell, PhD, Research Institute for Primary Care & Health Sciences, Keele University, Keele, Staffordshire, ST5 5BG, UK (e-mail: g.mansell@ 123456keele.ac.uk ).
                Article
                10.1097/AJP.0000000000000463
                5638429
                27930393
                16cb8181-bd86-4fd1-868b-27a6c6efce85
                Copyright © 2017 The Author(s). Published by Wolters Kluwer Health, Inc.

                This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0/

                History
                : 5 July 2016
                : 26 December 2016
                : 19 November 2016
                Categories
                Original Articles
                Custom metadata
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                mediation analysis,latent growth modeling,low back pain

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