Utilisation des nouvelles technologies dans les interventions

Background: Multicomponent digital interventions have the potential to reduce occupational sedentary behaviour (SB), but less is known about the feasibility of these interventions among hybrid office workers.Purpose: The aim of this pilot study was to examine the usage, acceptability, usability, perceived usefulness, and satisfaction of home-office workers with the Click2Move Application (C2M App).Methods: A single-group test was undertaken for one working week. Home-office workers at least once per week (n=21) received the C2M App, consisting of an activity-tracker and a smartphone application, including strategies at environmental and individual level. Outcomes were assessed after the study using four 5-point Likert scales including more than one item and three open questions. Descriptive analysis, utilizing median and median absolute deviation (MAD-M), and content analysis were conducted.Results: Participants used the C2M App in average 4 days for 8 hours each day. The app was considered as acceptable (median: 4; MAD-M: 0.33 – 0.86), and easy to use (median: 4; MAD-M: 0.71). Additionally, the activity tracker improved the application information. Participants perceived the contents of the programme as quite a bit useful (median: 4; MAD-M: 0.71 – 0.86), in exception of cooperative challenges (median: 3; MAD-M: 0.76). Participants were satisfied with the programme (median: 4; MAD-M: 0.95), with the awareness about their own activity patterns being the most liked item, while the connection problems between activity tracker and the application was the most annoying thing, needing a refine.Conclusions: The C2M App was acceptable, useful, and satisfactory for home-office workers. Therefore, after applying improvements, future research should evaluate the effectiveness of these interventions.Practical implications: These results contribute to the understanding of digital solutions for reducing SB among home-office workers, leading a way for future occupational interventions.Funding: The Click2Move project is supported by the European Commission under the Erasmus+ programme (ERASMUS-SPORT-2021-SCP-101050490).

Background Digital interventions are generally safe and can enhance physical activity. However, it is less known which components and delivery modes are promoting the largest improvement.Purpose To estimate the effect of different components and modes of delivery of digital interventions targeting physical activity in people with chronic conditions by performing a component network meta-analysis.Methods We searched four databases for randomised control trials (RCTs) using digital interventions to promote physical activity for people with one or more of 13 predefined chronic conditions. The primary outcome was overall physical activity at the end of treatment follow-up. We employed a component network meta-analysis with a random effects model and conducted subgroup, sensitivity, and meta-regression analyses exploring the effect of different components and modes of delivery of digital interventions. Certainty of the evidence was assessed using the CINeMA framework. Protocol (https://osf.io/ftvya/).Results We included 114 RCT’s (15,586 participants). Compared to usual care, self-management proved more efficacious (SMD 0.27 [95%CI 0.17–0.37; moderate certainty]), as did exercise combined with self-management (SMD 0.39 [95%CI 0.19–0.58; low certainty]). Interventions primarily delivered through combined digital modes such as an app plus phone calls or a web platform and a device (SMD 0·36 [95% CI 0·27–0·45; moderate certainty]) were more efficacious than usual care (i.e., providing information about the importance of physically activity).Conclusions The optimal digital interventions to promote physical activity may include self-management and exercise components delivered via combined digital delivery modes.Practical implications When recommending digital tools to improve physical activity clinicians should guide patients in selecting digital tools that incorporate both self-management strategies and exercise components which can be delivered with at least two digital tools.Funding European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (MOBILIZE, grant agreement No 801790) and Region Zealand (Exercise First).

Background: In countries with low rates of active travel, low-cost, wide-reaching interventions aimed at promoting active travel are a public health priority.Purpose: To explore the acceptability and feasibility of an existing smartphone app (TRavelVU) to promote active travel in the Australian context.Methods: 41 adults (mean age of 44 years, 59% female) downloaded and interacted with TRavelVU for four weeks. Once downloaded, the app uses GPS to collect location and speed data. Algorithms identify the most likely mode of transport. Users view and can edit their journeys when recorded incorrectly. Participants completed a survey about their level of engagement, the apps ease of use and accuracy and suggested behaviour change add-ons.Results: In terms of ease, 49% stated that TravelVu was very easy to use, 44% stated it was somewhat easy to use and 7% stated it was not at all easy to use. In terms of accuracy, 32% felt it was it was accurate, 59% that it somewhat accurate and 10% that it was not at all accurate. The reason for the poor accuracy appeared to reflect the view that the app was unable to correctly identify car journeys when traffic was congested and multi-modal journeys. 83% of participants stated TRavelVU was useful for tracking and monitoring travel behaviour while only 34% reported they would use it over the longer term. Over two thirds of participants agreed that they would like to be able to set travel goals (66%), track their progress in relation to these goals (71%), and receive positive feedback (63%).Conclusion: TravelVu was generally well received by participants with most reporting it to be accurate and easy to use. Additional functions such as setting goals and tracking progress may be useful to encourage a shift to active travel.

Background The benefits of regular physical activity (PA) are established. Underrepresented groups such as older adults, ethnic minorities and people with learning disabilities are less physically active than the rest of the population and the technologies to encourage exercise usually do not reach them. Purpose To investigate the acceptability and feasibility of FitBees technology (digital monitoring + social connection platform) on PA among participants from underrepresented groups from HFT and Community Housing Group, charities supporting learning-disabled people and providing social housing; and Dhek Bhal (Respite services for Carers of South Asian elders). Methods Six British and four South Asian adults (M=3, F =7), aged 66.7±20.6 years participated in the 8-week programme. FitBees Hestia sensor (https://tendertec.org/products/) was set in their homes for activity monitoring and necessary training was provided to establish social connections between users. Participants received an instructor’s one-hour/week exercise session and were advised to continue these exercises every day. Standardised outcome measures (Berg Balance score, 6-minute walk test -6MWT) and sensor readings were taken at baseline and the end of 8 weeks. Participants’ experience of using FitBees was evaluated through semi-structured interviews. Result An increase of 5.6 metres between the pre-and post-evaluation of the 6MWT (from 244.5±135.3 to 250.1±142.2) suggests improvement over the 8 weeks. Berg’s balance score revealed a decrease of 0.4 points from 46 ± 9.3 to 45.6 ± 9.4, implying a maintained balance capability. Hestia data: work in progress, first readings suggest the 8-week programme was beneficial, helping to improve self-awareness and motivation to exercise. Conclusion FitBees is perceived as acceptable and beneficial in motivating and promoting PA for underrepresented adults, thus promoting health & well-being. Practical Implication Findings underscore the importance of tailored interventions, such as FitBees, in addressing disparities in PA participation among underrepresented groups. Funding Funded by Innovate UK: Healthy Ageing Challenge (2022-24)

Background: Diverse and disadvantaged populations, including those experiencing high deprivation (IMD 1-4), disability, long term health conditions (LTC) and from an ethnically culturally diverse backgrounds (ECD), can have a higher prevalence of inactivity, decreased life satisfaction, typically resulting in a greater risk of ill health. Purpose: Explore the behaviour change in diverse populations of children and adults as a result of gamification intervention, Beat the Street (BTS). Methods: 18054 adults and children (57% adults, 20% ECD, 4% disability, 17 % LTC, 65% female, 48 % from IMD1-4) from the 2022 and 2023 BTS games were included with the proportional decrease in inactivity according to group analysed via McNemar Test. BTS is a gamified behaviour change intervention (Intelligent Health UK) incentivising active travel, engagement with nature and community and a mass shared positive experience. Items from the Active Lives Survey captured physical activity, active travel, wellbeing, and life satisfaction. Results: The greatest proportional change of inactive to active for both children and adults was found in diverse populations compared to the overall population (6%; X2 (1)7740.9, p<0.01 and 8%; X2 (1)10310, p<0.01, respectively). 6% decrease in children’s inactivity, with the greatest decrease observed in those with a disability (8%; X2 (3)156.3, p<0.01). 8% decrease in adults classed as inactive, with the largest decreases in those with a disability and a LTC (15%; X2(3)390.7, p<0.01). Conclusions: These outcomes further support the use of gamification as effective in promoting engagement in PA, regardless of background or ability. Practical implications: Inclusive engagement in physical activity to crucial to support those most in need, especially in the current climate of rising inequality and inequity. Funding: Individual BTs interventions were funded by local public sector agencies, with additional funding for England based games by Sport England.

Background: There is international consensus that the benefits of increasing physical activity (PA) outweigh the risks for individuals living with the most common and serious long term health conditions, including diabetes, cardiovascular disease, cancer, obesity, and depression. Exercise Intelligence (EXI) is a medically validated, evidence-based digital platform that provides automated, individualized, progressive PA programs, based on users’ unique combination of health conditions, PA history and current fitness levels. EXI incorporates behavioural science to support insufficiently active users to overcome barriers to achieving recommended PA levels. Purpose: Assess differences in the effectiveness of EXI for increasing PA in real world settings according to: baseline activity levels, use of a wearable activity tracker vs. no wearable, and independent vs. care pathway user. Methods: Retrospective analysis of routinely collected PA data from EXI users. Repeated measures analysis of variance was employed to assess and compare change over time in user sub-groups. Results: When users were split by week 1 activity level, after 16 weeks, weekly activity minutes increased by 1922% (190 mins) in the first quartile (lowest activity), by 369% (143 mins) in the second quartile, and by 97% (96 mins) in the third quartile (N=334). A similar pattern was seen in weekly steps increases. Adherence to the PA prescription (N=1,172) and weekly steps (N=2,439) were significantly higher in users with wearable devices compared to users without, at 16 weeks. Users who joined EXI via a healthcare professional or program had consistently higher adherence compared to those who joined independently. Conclusions: EXI appears to be highly effective for individuals with very low PA levels, enabling the achievement of recommended PA levels in 16 weeks. Practical implications: Digital personalised PA programs should be integrated into care pathways, combined with wearable activity trackers and targeted towards populations with the lowest PA levels. Funding: None