Dataset Information

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

ABSTRACT:

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.

SUBMITTER: Buckingham SA

PROVIDER: S-EPMC6437332 | biostudies-literature | 2019 Jan-Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Buckingham Sarah Ann SA Williams Andrew James AJ Morrissey Karyn K Price Lisa L Harrison John J

Digital health 20190101

<h4>Objective</h4>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.<h4>Methods</h4>Systematic searches were conducted in seven electronic databases (MEDLINE, SPORTDiscus, Scopus, EMBASE, PsycINFO, Web of Science and the Cochrane library). Studies were include ...[more]

PMID: 30944728

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Project description:BackgroundHigh levels of sedentary behaviour (SB) are associated with negative health consequences. Technology enhanced solutions such as mobile applications, activity monitors, prompting software, texts, emails and websites are being harnessed to reduce SB. The aim of this paper is to evaluate the effectiveness of such technology enhanced interventions aimed at reducing SB in healthy adults and to examine the behaviour change techniques (BCTs) used.MethodsFive electronic databases were searched to identify randomised-controlled trials (RCTs), published up to June 2016. Interventions using computer, mobile or wearable technologies to facilitate a reduction in SB, using a measure of sedentary time as an outcome, were eligible for inclusion. Risk of bias was assessed using the Cochrane Collaboration's tool and interventions were coded using the BCT Taxonomy (v1).ResultsMeta-analysis of 15/17 RCTs suggested that computer, mobile and wearable technology tools resulted in a mean reduction of -41.28 min per day (min/day) of sitting time (95% CI -60.99, -21.58, I2 = 77%, n = 1402), in favour of the intervention group at end point follow-up. The pooled effects showed mean reductions at short (≤ 3 months), medium (>3 to 6 months), and long-term follow-up (>6 months) of -42.42 min/day, -37.23 min/day and -1.65 min/day, respectively. Overall, 16/17 studies were deemed as having a high or unclear risk of bias, and 1/17 was judged to be at a low risk of bias. A total of 46 BCTs (14 unique) were coded for the computer, mobile and wearable components of the interventions. The most frequently coded were "prompts and cues", "self-monitoring of behaviour", "social support (unspecified)" and "goal setting (behaviour)".ConclusionInterventions using computer, mobile and wearable technologies can be effective in reducing SB. Effectiveness appeared most prominent in the short-term and lessened over time. A range of BCTs have been implemented in these interventions. Future studies need to improve reporting of BCTs within interventions and address the methodological flaws identified within the review through the use of more rigorously controlled study designs with longer-term follow-ups, objective measures of SB and the incorporation of strategies to reduce attrition.Trial registrationThe review protocol was registered with PROSPERO: CRD42016038187.

Project description:BackgroundSedentary behaviour is any waking behaviour characterised by an energy expenditure of ≤1.5 metabolic equivalent of task while in a sitting or reclining posture. Prolonged bouts of sedentary behaviour have been associated with negative health outcomes in all age groups. We examined qualitative research investigating perceptions and experiences of sedentary behaviour and of participation in non-workplace interventions designed to reduce sedentary behaviour in adult populations.MethodA systematic search of seven databases (MEDLINE, AMED, Cochrane, PsychINFO, SPORTDiscus, CINAHL and Web of Science) was conducted in September 2017. Studies were assessed for methodological quality and a thematic synthesis was conducted. Prospero database ID: CRD42017083436.ResultsThirty individual studies capturing the experiences of 918 individuals were included. Eleven studies examined experiences and/or perceptions of sedentary behaviour in older adults (typically ≥60 years); ten studies focused on sedentary behaviour in people experiencing a clinical condition, four explored influences on sedentary behaviour in adults living in socio-economically disadvantaged communities, two examined university students' experiences of sedentary behaviour, two on those of working-age adults, and one focused on cultural influences on sedentary behaviour. Three analytical themes were identified: 1) the impact of different life stages on sedentary behaviour 2) lifestyle factors influencing sedentary behaviour and 3) barriers and facilitators to changing sedentary behaviour.ConclusionsSedentary behaviour is multifaceted and influenced by a complex interaction between individual, environmental and socio-cultural factors. Micro and macro pressures are experienced at different life stages and in the context of illness; these shape individuals' beliefs and behaviour related to sedentariness. Knowledge of sedentary behaviour and the associated health consequences appears limited in adult populations, therefore there is a need for provision of accessible information about ways in which sedentary behaviour reduction can be integrated in people's daily lives. Interventions targeting a reduction in sedentary behaviour need to consider the multiple influences on sedentariness when designing and implementing interventions.

Project description:BackgroundTraditional psychological theories are inadequate to fully leverage the potential of smartphones and improve the effectiveness of physical activity (PA) and sedentary behavior (SB) change interventions. Future interventions need to consider dynamic models taken from other disciplines, such as engineering (eg, control systems). The extent to which such dynamic models have been incorporated in the development of interventions for PA and SB remains unclear.ObjectiveThis review aims to quantify the number of studies that have used dynamic models to develop smartphone-based interventions to promote PA and reduce SB, describe their features, and evaluate their effectiveness where possible.MethodsDatabases including PubMed, PsycINFO, IEEE Xplore, Cochrane, and Scopus were searched from inception to May 15, 2019, using terms related to mobile health, dynamic models, SB, and PA. The included studies involved the following: PA or SB interventions involving human adults; either developed or evaluated integrated psychological theory with dynamic theories; used smartphones for the intervention delivery; the interventions were adaptive or just-in-time adaptive; included randomized controlled trials (RCTs), pilot RCTs, quasi-experimental, and pre-post study designs; and were published from 2000 onward. Outcomes included general characteristics, dynamic models, theory or construct integration, and measured SB and PA behaviors. Data were synthesized narratively. There was limited scope for meta-analysis because of the variability in the study results.ResultsA total of 1087 publications were screened, with 11 publications describing 8 studies included in the review. All studies targeted PA; 4 also included SB. Social cognitive theory was the major psychological theory upon which the studies were based. Behavioral intervention technology, control systems, computational agent model, exploit-explore strategy, behavioral analytic algorithm, and dynamic decision network were the dynamic models used in the included studies. The effectiveness of quasi-experimental studies involved reduced SB (1 study; P=.08), increased light PA (1 study; P=.002), walking steps (2 studies; P=.06 and P<.001), walking time (1 study; P=.02), moderate-to-vigorous PA (2 studies; P=.08 and P=.81), and nonwalking exercise time (1 study; P=.31). RCT studies showed increased walking steps (1 study; P=.003) and walking time (1 study; P=.06). To measure activity, 5 studies used built-in smartphone sensors (ie, accelerometers), 3 of which used the phone's GPS, and 3 studies used wearable activity trackers.ConclusionsTo our knowledge, this is the first systematic review to report on smartphone-based studies to reduce SB and promote PA with a focus on integrated dynamic models. These findings highlight the scarcity of dynamic model-based smartphone studies to reduce SB or promote PA. The limited number of studies that incorporate these models shows promising findings. Future research is required to assess the effectiveness of dynamic models in promoting PA and reducing SB.Trial registrationInternational Prospective Register of Systematic Reviews (PROSPERO) CRD42020139350; https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=139350.

Project description: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 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.MethodsIn 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.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 = 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.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.

Project description:PurposeThe aim of this mixed-studies systematic review was to ascertain the effectiveness of school-based interventions in increasing physical activity (PA) and/or reducing sedentary time (ST) in children aged 5-11 years, as well as to explore their effectiveness in relation to categories of the theory of expanded, extended, and enhanced opportunity (TEO).MethodsAdhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, 5 databases were searched using predefined search terms. Following title and abstract screening of 1115 records, the removal of duplicates (n = 584) and articles that did not meet the inclusion criteria agreed to a priori (n = 419) resulted in 112 records that were full-text screened. Two independent reviewers subsequently used the mixed-methods appraisal tool to assess the methodological quality of 57 full-text studies that met the inclusion criteria after full-text screening. The interventions were summarised using the TIDierR checklist and TEO. The strength of evidence was determined using a 5-level rating system utilising a published decision tree.ResultsOverall evidence ratings for interventions implemented within school settings were: no evidence of effects on moderate-to-vigorous physical activity (MVPA) and inconclusive evidence of effects on sedentary time. In relation to the TEO, expansion of PA appeared to be the most promising intervention type for MVPA, with moderate evidence of effect, whereas extension and enhancement of PA opportunity demonstrated no evidence of effect. A critical issue of possible compensatory behavior was identified by analysis of intervention effect in relation to PA measurement duration; when studies measured changes in PA during the actual intervention, there was moderate evidence of effect, whereas those that measured changes in PA during the school day presented inconclusive evidence of effect, and those that measured changes in PA over a whole day yielded no evidence of effect. Two meta-analyses of those studies using a whole-day accelerometer measure for MVPA or ST showed a significant but moderate effect for MVPA (effect size = 0.51; 95% confidence interval (CI): 0.02-0.99) and a large but nonsignificant effect for ST (effect size = 1.15; 95%CI: -1.03 to 3.33); both meta-analyses demonstrated low precision, considerable inconsistency, and high heterogeneity.ConclusionThe findings have important implications for future intervention research in terms of intervention design, implementation, and evaluation.

Dataset Information

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

Objective

Methods

Results

Conclusions

Publications

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

Similar Datasets

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