scholarly journals 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

2020 ◽  
Vol 17 (1) ◽  
Author(s):  
Helene Schroé ◽  
Delfien Van Dyck ◽  
Annick De Paepe ◽  
Louise Poppe ◽  
Wen Wei Loh ◽  
...  
Keyword(s):  
Physical Activity ◽  
Sedentary Behaviour ◽  
Behaviour Change ◽  
Action Planning ◽  
Health Intervention ◽  
Health Interventions ◽  
Behaviour Change Techniques ◽  
Self Monitoring ◽  
Coping Planning ◽  
The Impact

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 (x2 = 8849, p = 0.003) whereas the combination of action planning and self-monitoring was most effective to decrease SB (x2 = 3.918, p = 0.048). To increase PA, action planning was always more effective in combination with coping planning (x2 = 5.590, p = 0.014; x2 = 17.722, p < 0.001; x2 = 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 (x2 = 4.389, p = 0.031) and self-monitoring alone (x2 = 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.

scholarly journals 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

2020 ◽  
Author(s):  
Helene Schroé ◽  
Delfien Van Dyck ◽  
Annick De Paepe ◽  
Louise Poppe ◽  
Wen Wei Loh ◽  
...  
Keyword(s):  
Physical Activity ◽  
Sedentary Behaviour ◽  
Behaviour Change ◽  
Action Planning ◽  
Health Intervention ◽  
Health Interventions ◽  
Behaviour Change Techniques ◽  
Self Monitoring ◽  
Coping Planning ◽  
The Impact

Abstract BackgroundE- 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 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).MethodsIn a 2(action planning: present vs absent) x2(coping planning: present vs absent) x2(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.ResultsFirst, 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 (x2 = 8,849,p = 0.003) whereas the combination of action planning and self-monitoring was most effective to decrease SB (x2 = 3.918,p = 0.048). To increase PA, action planning was always more effective in combination with coping planning (x2 = 5.590,p = 0.014;x2 = 17.722,p < 0.001;x2 = 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 (x2 = 4.389,p = 0.031) and self-monitoring alone (x2 = 8.858,p = 003), respectively.ConclusionsThis 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 registrationThis study was preregistered as a clinical trial (ID number: NCT03274271). Release date: 20 October 2017, http://clinicaltrials.gov/ct2/show/NCT03274271

scholarly journals 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

2020 ◽  
Author(s):  
Helene Schroé ◽  
Delfien Van Dyck ◽  
Annick De Paepe ◽  
Louise Poppe ◽  
Wen Wei Loh ◽  
...  
Keyword(s):  
Physical Activity ◽  
Sedentary Behaviour ◽  
Behaviour Change ◽  
Action Planning ◽  
Health Intervention ◽  
Health Interventions ◽  
Behaviour Change Techniques ◽  
Self Monitoring ◽  
Coping Planning ◽  
The Impact

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) x2 (coping planning: present vs absent) x2 (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 (x2=8,849,p=0.003) whereas the combination of action planning and self-monitoring was most effective to decrease SB (x2=3.918,p=0.048). To increase PA, action planning was always more effective in combination with coping planning (x2=5.590,p=0.014;x2=17.722,p<0.001;x2=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 (x2=4.389,p=0.031) and self-monitoring alone (x2=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, http://clinicaltrials.gov/ct2/show/NCT03274271

scholarly journals Mobile health interventions to promote physical activity and reduce sedentary behaviour in the workplace: A systematic review

2019 ◽  
Vol 5 ◽  
pp. 205520761983988 ◽  
Author(s):  
Sarah Ann Buckingham ◽  
Andrew James Williams ◽  
Karyn Morrissey ◽  
Lisa Price ◽  
John Harrison
Keyword(s):  
Physical Activity ◽  
Systematic Review ◽  
Sedentary Behaviour ◽  
Mobile Health ◽  
Technology Use ◽  
Methodological Quality ◽  
Experimental Studies ◽  
Cochrane Library ◽  
Behaviour Change Techniques ◽  
The Impact

Objective This systematic review aimed to assess the effectiveness, feasibility and acceptability of mobile health (mHealth) technology (including wearable activity monitors and smartphone applications) for promoting physical activity (PA) and reducing sedentary behaviour (SB) in workplace settings. Methods Systematic searches were conducted in seven electronic databases (MEDLINE, SPORTDiscus, Scopus, EMBASE, PsycINFO, Web of Science and the Cochrane library). Studies were included if mHealth was a major intervention component, PA/SB was a primary outcome, and participants were recruited and/or the intervention was delivered in the workplace. Study quality was assessed using the Effective Public Health Practice Project (EPHPP) tool. Interventions were coded for behaviour change techniques (BCTs) using the Coventry, Aberdeen and London – Refined (CALO-RE) taxonomy. Results Twenty-five experimental and quasi-experimental studies were included. Studies were highly heterogeneous and only one was rated as ‘strong’ methodological quality. Common BCTs included self-monitoring, feedback, goal-setting and social comparison. A total of 14/25 (56%) studies reported a significant increase in PA, and 4/10 (40%) reported a significant reduction in sedentary time; 11/16 (69%) studies reported a significant impact on secondary outcomes including reductions in weight, systolic blood pressure and total cholesterol. While overall acceptability was high, a large decline in technology use and engagement was observed over time. Conclusions While methodological quality was generally weak, there is reasonable evidence for mHealth in a workplace context as a feasible, acceptable and effective tool to promote PA. The impact in the longer term and on SB is less clear. Higher quality, mixed methods studies are needed to explore the reasons for decline in engagement with time and the longer-term potential of mHealth in workplace interventions. Protocol registration: The review protocol was registered with PROSPERO: CRD42017058856

scholarly journals PARIS: protocol for a prospective single arm, theory-based, group-based feasibility intervention study to increase Physical Activity and reduce sedentary behaviouR after barIatric Surgery

BMJ Open ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. e051638
Author(s):  
Jennifer James ◽  
Wendy Hardeman ◽  
Helen Eborall ◽  
Mark Goodall ◽  
John Wilding
Keyword(s):  
Physical Activity ◽  
Bariatric Surgery ◽  
Sedentary Behaviour ◽  
Behaviour Change ◽  
Feasibility Study ◽  
Theoretical Domains Framework ◽  
Comparative Approach ◽  
Service Research ◽  
Behaviour Change Techniques ◽  
Behaviour Change Intervention

IntroductionIncreased physical activity and reduced sedentary behaviour can encourage favourable outcomes after bariatric surgery. However, there is a lack of evidence as to how to support patients with behaviour change. The aim of this study is to assess the feasibility of a physiotherapist led, online group-based behaviour change intervention to increase physical activity and reduce sedentary behaviour following bariatric surgery.Methods and analysisSingle arm feasibility study of a theory and evidence-based group behaviour change intervention based on the Behaviour Change Wheel and Theoretical Domains Framework using behaviour change techniques from the Behaviour Change Technique Taxonomy v1. The intervention has eight objectives and specifies behaviour change techniques that will be used to address each of these. Groups of up to eight participants who have had surgery within the previous 5 years will meet weekly over 6 weeks for up to 1½ hours. Groups will be held online led by a physiotherapist and supported by an intervention handbook. Feasibility study outcomes include: rate of recruitment, retention, intervention fidelity, participant engagement and acceptability. Secondary outcomes include: physical activity, sedentary behaviour, body composition, self-reported health status and will be analysed descriptively. Change in these outcomes will be used to calculate the sample size for a future evaluation study. Qualitative interviews will explore participants’ views of the intervention including its acceptability. Data will be analysed according to the constant comparative approach of grounded theory.Ethics and disseminationThis study has National Health Service Research Ethics Committee approval; Haydock 20/NW/0472. All participants will provide informed consent and can withdraw at any point. Findings will be disseminated through peer-reviewed journals, conference and clinical service presentations.Trial registration numberISRCTN31524689.

scholarly journals Optimising Web-Based Computer-Tailored Physical Activity Interventions for Prostate Cancer Survivors: A Randomised Controlled Trial Examining the Impact of Website Architecture on User Engagement

2020 ◽  
Vol 17 (21) ◽  
pp. 7920
Author(s):  
Amy Finlay ◽  
Holly Evans ◽  
Andrew Vincent ◽  
Gary Wittert ◽  
Corneel Vandelanotte ◽  
...  
Keyword(s):  
Physical Activity ◽  
Prostate Cancer ◽  
Cancer Survivors ◽  
Behaviour Change ◽  
Free Choice ◽  
Self Monitoring ◽  
Web Based ◽  
Prostate Cancer Survivors ◽  
Secondary Outcomes ◽  
The Impact

Background: Web-based computer-tailored interventions can assist prostate cancer survivors to become more physically active by providing personally relevant behaviour change support. This study aimed to explore how changing the website architecture (free choice vs. tunnelled) impacted engagement within a physical activity computer-tailored intervention targeting prostate cancer survivors. Methods: On a 2:2:1 ratio, 71 Australian prostate cancer survivors with local or locally advanced disease (mean age: 66.6 years ± 9.66) were randomised into either a free-choice (N = 27), tunnelled (N = 27) or minimal intervention control arm (N =17). The primary outcome was differences in usage of the physical activity self-monitoring and feedback modules between the two intervention arms. Differences in usage of other website components between the two intervention groups were explored as secondary outcomes. Further, secondary outcomes involving comparisons between all study groups (including the control) included usability, personal relevance, and behaviour change. Results: The average number of physical activity self-monitoring and feedback modules accessed was higher in the tunnelled arm (M 2.6 SD 1.3) compared to the free-choice arm (M 1.5 SD 1.4), p = 0.01. However, free-choice participants were significantly more likely to have engaged with the social support (p = 0.008) and habit formation (p = 0.003) ‘once-off’ modules compared to the standard tunnelled arm. There were no other between-group differences found for any other study outcomes. Conclusion: This study indicated that website architecture influences behavioural engagement. Further research is needed to examine the impact of differential usage on mechanisms of action and behaviour change.

scholarly journals Using Intervention Mapping to Develop and Facilitate Implementation of a Multifaceted Behavioural Intervention Targeting Physical Activity and Sedentary Behaviour in Stroke Survivors: Physical Activity Routines After Stroke (PARAS)

2021 ◽  
Author(s):  
Sarah Moore ◽  
Darren Flynn ◽  
Christopher Price ◽  
Leah Avery
Keyword(s):  
Physical Activity ◽  
Systematic Review ◽  
Sedentary Behaviour ◽  
Behaviour Change ◽  
Stroke Rehabilitation ◽  
Intervention Mapping ◽  
Behavioural Intervention ◽  
Behaviour Change Techniques ◽  
Stroke Survivors ◽  
Face To Face

Abstract BackgroundThe benefits of increased physical activity for stroke survivors include improved walking ability, balance and mood. However, less than 30% achieve recommended levels of physical activity, and high levels of sedentary behaviour are reported. We engaged stroke survivors, informal carers and healthcare professionals (HCPs) in a co-design process to develop an evidence-informed behavioural intervention targeting physical activity and sedentary behaviour for use by stroke rehabilitation teams. MethodsIntervention Mapping was used as a framework for intervention development. Step 1 involved a systematic review, focus group discussions and a review of existing care pathways. Step 2 involved identification of social cognitive determinants of behavioural change and behavioural outcomes of the intervention. Step 3 involved linking the determinants of behavioural outcomes with specific behaviour change techniques to target the behaviours of interest. Step 4 involved the development of the intervention informed by steps 1 to 3. Subsequently, an implementation plan was developed (Step 5) followed by an evaluation plan (Step 6). ResultsSystematic review findings informed selection of nine ‘promising’ behaviour change techniques (e.g. goal setting-behaviour; problem-solving). Focus groups with stroke survivors (n=18) and HCPs (n=24) identified the need for an intervention that could be delivered at different time points within the rehabilitation pathway, tailored to individual needs and circumstances with training for HCPs delivering the intervention. Intervention delivery was considered feasible within local community stroke services. The target behaviours for the intervention were physical activity and sedentary behaviour of stroke survivors. Assessment of acceptability and usability with 11 HCPs and 21 stroke survivors/relatives identified issues around self-monitoring tools; the need for a repository of local services for physical activity; and the need for face-to-face feedback provision to HCPs following delivery of the intervention for optimisation purposes. Face-to-face training for HCPs was delivered to support faithful delivery of the intervention within community settings. A feasibility study protocol was designed to evaluate the intervention.ConclusionsA systematic development process using intervention mapping resulted in a multi-faceted evidence- and theory-informed intervention (Physical Activity Routines After Stroke - PARAS) for delivery by community stroke rehabilitation teams. Trial registration: Trial identifier: ISRCTN35516780, date of registration: 24/10/2018, URL http://www.isrctn.com/ISRCTN35516780

scholarly journals Determinants of Behaviour Change in a Multi-Component Telemonitoring Intervention for Community-Dwelling Older Adults

Nutrients ◽  
2018 ◽  
Vol 10 (8) ◽  
pp. 1062 ◽  
Author(s):  
Marije van Doorn-van Atten ◽  
Lisette de Groot ◽  
Jeanne de Vries ◽  
Annemien Haveman-Nies
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Behaviour Change ◽  
Diet Quality ◽  
Community Dwelling ◽  
Control Group ◽  
Behaviour Change Techniques ◽  
Self Monitoring ◽  
Behavioural Determinants

Optimal diet quality and physical activity levels are essential for healthy ageing. This study evaluated the effects of a multi-component telemonitoring intervention on behavioural determinants of diet quality and physical activity in older adults, and assessed the mediating role of these determinants and two behaviour change techniques in the intervention’s effects. A non-randomised controlled design was used including 214 participants (average age 80 years) who were allocated to the intervention or control group based on municipality. The six-month intervention consisted of self-measurements of nutritional outcomes and physical activity, education, and follow-up by a nurse. The control group received regular care. Measurements took place at baseline, after 4.5 months and at the end of the study. The intervention increased self-monitoring and improved knowledge and perceived behavioural control for physical activity. Increased self-monitoring mediated the intervention’s effect on diet quality, fruit intake, and saturated fatty acids intake. Improved knowledge mediated the effect on protein intake. Concluding, this intervention led to improvements in behavioural determinants of diet quality and physical activity. The role of the hypothesised mediators was limited. Insight into these mechanisms of impact provides directions for future development of nutritional eHealth interventions for older adults, in which self-monitoring may be a promising behaviour change technique. More research is necessary into how behaviour change is established in telemonitoring interventions for older adults.

scholarly journals The APPropriateness of physical activity apps during pregnancy: a systematic review of quality, features and behaviour change techniques. (Preprint)

2020 ◽  
Author(s):  
Melanie Hayman
Keyword(s):  
Physical Activity ◽  
Pregnant Women ◽  
Behaviour Change ◽  
Information Quality ◽  
Rating Scale ◽  
Information Source ◽  
Health Benefits ◽  
Behaviour Change Techniques ◽  
Self Monitoring ◽  
The Many

BACKGROUND Physical activity during pregnancy is associated with a variety of health benefits for the mother and her child. Despite the many health benefits of physical activity during pregnancy, few women participate in regular physical activity during pregnancy. ehealth platforms, such as the internet and mobile applications (apps), are now altering how women access information about their pregnancy and have become an important information source for pregnant women. Whilst the use of pregnancy-related apps has significantly increased among pregnant women, very little is known about their theoretical underpinnings, including their utilisation of behaviour change techniques. This is despite research suggesting the inclusion of behaviour change techniques in ehealth interventions can play an important role in improving, supporting and maintain healthy behaviours, including physical activity. OBJECTIVE To review physical activity apps designed for pregnant women with a focus on app content, quality and features, and the presence and efficacy of Behaviour Change Techniques (BCTs). METHODS A systematic search in the Australian AppStore and GooglePlay stores using search terms relating to exercise and pregnancy. App features and quality was assessed using the 19-item Mobile Application Rating Scale (MARS) and a taxonomy of BCTs was used to determine presence of BCTs (26 items). BCTs previously demonstrating efficacy in behaviour change during pregnancy were also identified from a review of the literature. RESULTS Nineteen exercise apps were deemed eligible for this review and accessed via GooglePlay (n=13) or AppStore (n=6). MARS Overall Quality scores showed moderate app quality (m=3.5, SD=0.52). Functionality was the highest scoring MARS domain (m=4.2, SD=0.5), followed by Aesthetics (m=3.7, SD=0.6) and Information Quality (m=3.16, SD=0.42). Engagement (m=3.01, SD=0.9), Subjective App Quality (m=2.54, SD=0.64) and Likelihood for Behavioural Impact (m=2.5, SD=0.6) were the lowest scoring MARS domains. All 19 apps were found to incorporate at least two BCTs (m=4.74, SD=2.51, range=2–10), with provide instructions (95%) and provide information on consequences (89%) being the most common BCTs. Eleven apps included BCTs that previously demonstrated efficacy for behaviour change during pregnancy, the most common of these being provide opportunities for social comparison (n=8) and prompt self-monitoring of behaviour (n=7). CONCLUSIONS Apps to improve exercise in pregnant women were functional and aesthetically pleasing, with overall moderate quality. However, the incorporation of BCTs was low, with the prevalence of BCTs previously demonstrating efficacy in promoting and/or supporting physical activity during pregnancy scarce. Thus, it is unlikely that apps reviewed in this study will effectively promote and/or support the exercise behaviours among pregnant women. CLINICALTRIAL Not required.

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