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      Exploring Attitudes, Subjective Norms and Perceived Behavioural Control in a Genetic-Based and a Population-Based Weight Management Intervention: A One-Year Randomized Controlled Trial

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          Abstract

          Background: Several studies demonstrate that the provision of personalized lifestyle advice, based on genetics, can help motivate individuals to engage in greater nutrition and physical activity changes compared to the provision of population-based advice. The theoretical mechanism behind this phenomenon is poorly understood. The objective of this study was to determine the impact of providing genetically tailored and population-based lifestyle advice on key constructs of the Theory of Planned Behaviour (TPB). Materials and Methods: A pragmatic, cluster randomized controlled trial ( n = 140) took place at the East Elgin Family Health Team, in Aylmer, Ontario, Canada. Participants were primarily Caucasian females enrolled in a weight management program (BMI ≥ 25.0 kg/m 2). Weight management program groups were randomized (1:1) to receive a population-based lifestyle intervention for weight management (Group Lifestyle Balance™ (GLB)) or a lifestyle genomics (LGx)-based lifestyle intervention for weight management (GLB+LGx). Attitudes, subjective norms and perceived behavioural control were measured at baseline, immediately after receiving a report of population-based or genetic-based recommendations and after 3-, 6- and 12-month follow-ups. Linear mixed models were conducted, controlling for measures of actual behavioural control. All analyses were intention-to-treat by originally assigned groups. Results: Significant changes ( p < 0.05) in attitudes, subjective norms, and perceived behavioural control tended to be short-term in the GLB group and long-term for the GLB+LGx group. Short-term and long-term between-group differences in measures of subjective norms were discovered, favouring the GLB+LGx group. Conclusions: The TPB can help provide a theoretical explanation for studies demonstrating enhanced behaviour change with genetic-based lifestyle interventions. Clinical Trial Registration: NCT03015012.

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          Most cited references35

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          The theory of planned behavior

          Icek Ajzen (1991)
          Organizational Behavior and Human Decision Processes, 50(2), 179-211
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            Intention-to-treat concept: A review

            Randomized controlled trials often suffer from two major complications, i.e., noncompliance and missing outcomes. One potential solution to this problem is a statistical concept called intention-to-treat (ITT) analysis. ITT analysis includes every subject who is randomized according to randomized treatment assignment. It ignores noncompliance, protocol deviations, withdrawal, and anything that happens after randomization. ITT analysis maintains prognostic balance generated from the original random treatment allocation. In ITT analysis, estimate of treatment effect is generally conservative. A better application of the ITT approach is possible if complete outcome data are available for all randomized subjects. Per-protocol population is defined as a subset of the ITT population who completed the study without any major protocol violations.
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              Prospective prediction of health-related behaviours with the Theory of Planned Behaviour: a meta-analysis

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                Author and article information

                Journal
                Nutrients
                Nutrients
                nutrients
                Nutrients
                MDPI
                2072-6643
                08 December 2020
                December 2020
                : 12
                : 12
                : 3768
                Affiliations
                [1 ]Health and Rehabilitation Sciences, The University of Western Ontario, London, ON N6A 3K7, Canada
                [2 ]The East Elgin Family Health Team, Aylmer, ON N5H 1K9, Canada
                [3 ]Human Environments Analysis Laboratory, The University of Western Ontario, London, ON N6A 3K7, Canada; jgillila@ 123456uwo.ca
                [4 ]Centre Nutrition, Santé et Société (NUTRISS) and Institute of Nutrition and Functional Foods (INAF), Laval University, Quebec, QC G1V 0A6, Canada; Marie-Claude.Vohl@ 123456fsaa.ulaval.ca
                [5 ]Department of Geography, Western University, London, ON N6A 3K7, Canada
                [6 ]School of Health Studies, Western University, London, ON N6A 3K7, Canada
                [7 ]Department of Paediatrics, Western University, London, ON N6A 3K7, Canada
                [8 ]Department of Epidemiology and Biostatistics, Western University, London, ON N6A 3K7, Canada
                [9 ]Children’s Health Research Institute, London, ON N6A 3K7, Canada
                [10 ]Lawson Health Research Institute, London, ON N6A 3K7, Canada; jmadill7@ 123456uwo.ca
                [11 ]School of Food and Nutritional Sciences, Brescia University College, The University of Western Ontario, London, ON N6A 3K7, Canada
                Author notes
                [* ]Correspondence: jhorne5@ 123456uwo.ca
                Author information
                https://orcid.org/0000-0002-9176-9645
                https://orcid.org/0000-0002-2909-2178
                https://orcid.org/0000-0002-7017-5848
                Article
                nutrients-12-03768
                10.3390/nu12123768
                7764748
                33302460
                6e5e1f27-2878-4497-aded-fbded0d28da7
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 02 November 2020
                : 04 December 2020
                Categories
                Article

                Nutrition & Dietetics
                theory of planned behaviour,theory of planned behavior,randomized controlled trial,behaviour change,behavioural determinants,nutrigenomics,nutrigenetics,lifestyle genomics,personalized nutrition

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