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      Causal mechanisms of a healthy lifestyle intervention for patients with musculoskeletal pain who are overweight or obese

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          Abstract

          Purpose:

          To assess the causal mechanisms of a healthy lifestyle intervention for patients with chronic low back pain and knee osteoarthritis, who are overweight or obese.

          Methods:

          We conducted causal mediation analyses of aggregated data from two randomized controlled trials (RCTs); which included 160 patients with chronic low back pain, and 120 patients with knee osteoarthritis. The intervention consisted of brief advice and referral to a six-month telephone-based healthy lifestyle coaching service. We used causal mediation to estimate the indirect, direct and path-specific effects of hypothesized mediators including: self-reported weight, diet, physical activity, and pain beliefs. Outcomes were pain intensity, disability, and quality of life (QoL).

          Results:

          The intervention did not reduce weight, improve diet or physical activity or change pain beliefs, and these mediators were not associated with the outcomes. Sensitivity analyses showed that our estimates were robust to the possible effects of unknown and unmeasured confounding.

          Conclusions:

          Our findings show that the intervention did not cause a meaningful change in the hypothesized mediators, and these mediators were not associated with patient-reported outcomes.

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          Most cited references45

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          Measures of adult pain: Visual Analog Scale for Pain (VAS Pain), Numeric Rating Scale for Pain (NRS Pain), McGill Pain Questionnaire (MPQ), Short-Form McGill Pain Questionnaire (SF-MPQ), Chronic Pain Grade Scale (CPGS), Short Form-36 Bodily Pain Scale (SF-36 BPS), and Measure of Intermittent and Constant Osteoarthritis Pain (ICOAP).

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            mediation:RPackage for Causal Mediation Analysis

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              A general approach to causal mediation analysis.

              Traditionally in the social sciences, causal mediation analysis has been formulated, understood, and implemented within the framework of linear structural equation models. We argue and demonstrate that this is problematic for 3 reasons: the lack of a general definition of causal mediation effects independent of a particular statistical model, the inability to specify the key identification assumption, and the difficulty of extending the framework to nonlinear models. In this article, we propose an alternative approach that overcomes these limitations. Our approach is general because it offers the definition, identification, estimation, and sensitivity analysis of causal mediation effects without reference to any specific statistical model. Further, our approach explicitly links these 4 elements closely together within a single framework. As a result, the proposed framework can accommodate linear and nonlinear relationships, parametric and nonparametric models, continuous and discrete mediators, and various types of outcome variables. The general definition and identification result also allow us to develop sensitivity analysis in the context of commonly used models, which enables applied researchers to formally assess the robustness of their empirical conclusions to violations of the key assumption. We illustrate our approach by applying it to the Job Search Intervention Study. We also offer easy-to-use software that implements all our proposed methods. PsycINFO Database Record (c) 2010 APA, all rights reserved.
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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Clinical Rehabilitation
                Clin Rehabil
                SAGE Publications
                0269-2155
                1477-0873
                June 2019
                February 27 2019
                June 2019
                : 33
                : 6
                : 1088-1097
                Affiliations
                [1 ]School of Medicine and Public Health, Hunter Medical Research Institute, The University of Newcastle, Newcastle, NSW, Australia
                [2 ]Hunter New England Population Health, Wallsend, NSW, Australia
                [3 ]Centre for Pain, Health and Lifestyle, Newcastle, NSW, Australia
                [4 ]Neuroscience Research Australia (NeuRA), Sydney, NSW, Australia
                [5 ]Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
                [6 ]School of Public Health, The University of Sydney, Camperdown, NSW, Australia
                [7 ]Outpatient Services, John Hunter Hospital, Hunter New England Local Health District, Newcastle, NSW, Australia
                [8 ]School of Medical Sciences, Faculty of Medicine, University of NSW, Sydney, NSW, Australia
                Article
                10.1177/0269215519831419
                30808203
                0b24c982-afc1-425f-97b5-dac55450dc30
                © 2019

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

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