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      Which behaviour change techniques are effective to promote physical activity and reduce sedentary behaviour in adults: a factorial randomized trial of an e- and m-health intervention

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          Abstract

          Background

          E- and m-health interventions are promising to change health behaviour. Many of these interventions use a large variety of behaviour change techniques (BCTs), but it’s not known which BCTs or which combination of BCTs contribute to their efficacy. Therefore, this experimental study investigated the efficacy of three BCTs (i.e. action planning, coping planning and self-monitoring) and their combinations on physical activity (PA) and sedentary behaviour (SB) against a background set of other BCTs.

          Methods

          In a 2 (action planning: present vs absent) × 2 (coping planning: present vs absent) × 2 (self-monitoring: present vs absent) factorial trial, 473 adults from the general population used the self-regulation based e- and m-health intervention ‘MyPlan2.0’ for five weeks. All combinations of BCTs were considered, resulting in eight groups. Participants selected their preferred target behaviour, either PA ( n = 335, age = 35.8, 28.1% men) or SB ( n = 138, age = 37.8, 37.7% men), and were then randomly allocated to the experimental groups. Levels of PA (MVPA in minutes/week) or SB (total sedentary time in hours/day) were assessed at baseline and post-intervention using self-reported questionnaires. Linear mixed-effect models were fitted to assess the impact of the different combinations of the BCTs on PA and SB.

          Results

          First, overall efficacy of each BCT was examined. The delivery of self-monitoring increased PA (t = 2.735,  p = 0.007) and reduced SB (t = − 2.573,  p = 0.012) compared with no delivery of self-monitoring. Also, the delivery of coping planning increased PA (t = 2.302,  p = 0.022) compared with no delivery of coping planning. Second, we investigated to what extent adding BCTs increased efficacy. Using the combination of the three BCTs was most effective to increase PA (x 2 = 8849,  p = 0.003) whereas the combination of action planning and self-monitoring was most effective to decrease SB (x 2 = 3.918,  p = 0.048). To increase PA, action planning was always more effective in combination with coping planning (x 2 = 5.590,  p = 0.014; x 2 = 17.722,  p < 0.001; x 2 = 4.552,  p = 0.033) compared with using action planning without coping planning. Of note, the use of action planning alone reduced PA compared with using coping planning alone (x 2 = 4.389,  p = 0.031) and self-monitoring alone (x 2 = 8.858,  p = 003), respectively.

          Conclusions

          This study provides indications that different (combinations of) BCTs may be effective to promote PA and reduce SB. More experimental research to investigate the effectiveness of BCTs is needed, which can contribute to improved design and more effective e- and m-health interventions in the future.

          Trial registration

          This study was preregistered as a clinical trial (ID number: NCT03274271). Release date: 20 October 2017.

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          Most cited references80

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          Fitting Linear Mixed-Effects Models Usinglme4

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            G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences

            G*Power (Erdfelder, Faul, & Buchner, 1996) was designed as a general stand-alone power analysis program for statistical tests commonly used in social and behavioral research. G*Power 3 is a major extension of, and improvement over, the previous versions. It runs on widely used computer platforms (i.e., Windows XP, Windows Vista, and Mac OS X 10.4) and covers many different statistical tests of the t, F, and chi2 test families. In addition, it includes power analyses for z tests and some exact tests. G*Power 3 provides improved effect size calculators and graphic options, supports both distribution-based and design-based input modes, and offers all types of power analyses in which users might be interested. Like its predecessors, G*Power 3 is free.
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              Better reporting of interventions: template for intervention description and replication (TIDieR) checklist and guide

              Without a complete published description of interventions, clinicians and patients cannot reliably implement interventions that are shown to be useful, and other researchers cannot replicate or build on research findings. The quality of description of interventions in publications, however, is remarkably poor. To improve the completeness of reporting, and ultimately the replicability, of interventions, an international group of experts and stakeholders developed the Template for Intervention Description and Replication (TIDieR) checklist and guide. The process involved a literature review for relevant checklists and research, a Delphi survey of an international panel of experts to guide item selection, and a face to face panel meeting. The resultant 12 item TIDieR checklist (brief name, why, what (materials), what (procedure), who provided, how, where, when and how much, tailoring, modifications, how well (planned), how well (actual)) is an extension of the CONSORT 2010 statement (item 5) and the SPIRIT 2013 statement (item 11). While the emphasis of the checklist is on trials, the guidance is intended to apply across all evaluative study designs. This paper presents the TIDieR checklist and guide, with an explanation and elaboration for each item, and examples of good reporting. The TIDieR checklist and guide should improve the reporting of interventions and make it easier for authors to structure accounts of their interventions, reviewers and editors to assess the descriptions, and readers to use the information.
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                Author and article information

                Contributors
                helene.schroe@ugent.be
                Journal
                Int J Behav Nutr Phys Act
                Int J Behav Nutr Phys Act
                The International Journal of Behavioral Nutrition and Physical Activity
                BioMed Central (London )
                1479-5868
                7 October 2020
                7 October 2020
                2020
                : 17
                : 127
                Affiliations
                [1 ]GRID grid.5342.0, ISNI 0000 0001 2069 7798, Ghent Health Psychology Lab, Department of Experimental-Clinical and Health Psychology, Faculty of Psychology and Educational Sciences, , Ghent University, ; Henri Dunantlaan 2, Ghent, 9000 Belgium
                [2 ]GRID grid.5342.0, ISNI 0000 0001 2069 7798, Research Group Physical Activity and Health, Department of Movement and Sports Sciences, Faculty of Medicine and Health, , Ghent University, ; Watersportlaan 2, 9000 Ghent, Belgium
                [3 ]GRID grid.5342.0, ISNI 0000 0001 2069 7798, Department of Public Health and Primary Care, Faculty of Medicine and Health Sciences, , Ghent University, ; Ghent, Belgium
                [4 ]GRID grid.5342.0, ISNI 0000 0001 2069 7798, Department of Data Analysis, Faculty of Psychology and Educational Sciences, , Ghent University, ; Ghent, Belgium
                Author information
                http://orcid.org/0000-0001-8473-552X
                Article
                1001
                10.1186/s12966-020-01001-x
                7539442
                33028335
                0b13fc04-75a5-42fe-a59e-44adafbf839b
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 22 April 2020
                : 22 July 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100007229, Bijzonder Onderzoeksfonds;
                Award ID: BOF.DOC.2018.0028.01
                Award ID: 01J05819
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100003130, Fonds Wetenschappelijk Onderzoek;
                Award ID: 3G068519
                Award ID: G019317N
                Award ID: G043319N
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2020

                Nutrition & Dietetics
                e-health,m-health,self-regulation,behaviour change techniques,physical activity,sedentary behaviour,factorial trial

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