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The Effect of Active Plus, a Computer-Tailored Physical Activity Intervention, on the Physical Activity of Older Adults with Chronic Illness(es)-A Cluster Randomized Controlled Trial.

ABSTRACT: eHealth interventions aimed at improving physical activity (PA) can reach large populations with few resources and demands on the population as opposed to centre-based interventions. Active Plus is a proven effective computer-tailored PA intervention for the older adult population focusing on PA in daily life. This manuscript describes the effects of the Active Plus intervention (N = 260) on PA of older adults with chronic illnesses (OACI), compared to a waiting list control group (N = 325). It was part of a larger randomized controlled trial (RCT) on the effects of the Active Plus intervention on cognitive functioning. OACI (?65 years) with at least one chronic illness were allocated to one of the conditions. Intervention group participants received PA advice. Baseline and follow-up measurements were assessed after 6 and 12 months. Intervention effects on objectively measured light PA (LPA) and moderate-to-vigorous PA (MVPA) min/week were analysed with multilevel linear mixed-effects models adjusted for the clustered design. Intervention effects on self-reported MVPA min/week on common types of PA were analysed with two-part generalized linear mixed-effects models adjusted for the clustered design. The dropout rate was 19.1% after 6 months and 25.1% after 12 months. Analyses showed no effects on objectively measured PA. Active Plus increased the likelihood to perform self-reported cycling and gardening at six months and participants who cycled increased their MVPA min/week of cycling. Twelve months after baseline the intervention increased the likelihood to perform self-reported walking and participants who cycled at 12 months increased their MVPA min/week of cycling. Subgroup analyses showed that more vulnerable participants (higher degree of impairment, age or body mass index) benefitted more from the intervention on especially the lower intensity PA outcomes. In conclusion, Active Plus only increased PA behaviour to a limited extent in OACI 6 and 12 months after baseline measurements. The Active Plus intervention may yet be not effective enough by itself in OACI. A blended approach, where this eHealth intervention and face-to-face contact are combined, is advised to improve the effects of Active Plus on PA in this target group.

SUBMITTER: Volders E

PROVIDER: S-EPMC7177821 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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The Effect of Active Plus, a Computer-Tailored Physical Activity Intervention, on the Physical Activity of Older Adults with Chronic Illness(es)-A Cluster Randomized Controlled Trial.

Volders Esmee E Bolman Catherine A W CAW de Groot Renate H M RHM Verboon Peter P Lechner Lilian L

International journal of environmental research and public health 20200410 7

eHealth interventions aimed at improving physical activity (PA) can reach large populations with few resources and demands on the population as opposed to centre-based interventions. Active Plus is a proven effective computer-tailored PA intervention for the older adult population focusing on PA in daily life. This manuscript describes the effects of the Active Plus intervention (<i>N</i> = 260) on PA of older adults with chronic illnesses (OACI), compared to a waiting list control group (<i>N</ ...[more]

PMID: 32290072

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Project description:BackgroundComputer-tailored physical activity (PA) interventions delivered through the Internet represent a promising and appealing method to promote PA at a population level. However, personalized advice is mostly provided based on subjectively measured PA, which is not very accurate and might result in the delivery of advice that is not credible or effective. Therefore, an innovative computer-tailored PA advice was developed, based on objectively pedometer-measured PA.ObjectiveThe study aim was to evaluate the effectiveness of a computer-tailored, pedometer-based PA intervention in working adults.MethodsParticipants (≥18 years) were recruited between May and December 2012 from eight Flemish workplaces. These workplaces were allocated randomly to an intervention or control group. Intervention group participants (n=137) received (1) a booklet with information on how to increase their steps, (2) a non-blinded pedometer, and (3) an Internet link to request computer-tailored step advice. Control group participants (n=137) did not receive any of the intervention components. Self-reported and pedometer-based PA were assessed at baseline (T0), and 1 month (T1) and 3 months (T2) months post baseline. Repeated measures analyses of covariance were used to examine intervention effects for both the total sample and the at-risk sample (ie, adults not reaching 10,000 steps a day at baseline).ResultsThe recruitment process resulted in 274 respondents (response rate of 15.1%) who agreed to participate, of whom 190 (69.3%) belonged to the at-risk sample. Between T0 and T1 (1-month post baseline), significant intervention effects were found for participants' daily step counts in both the total sample (P=.004) and the at-risk sample (P=.001). In the at-risk sample, the intervention effects showed a daily step count increase of 1056 steps in the intervention group, compared to a decrease of 258 steps in the control group. Comparison of participants' self-reported PA revealed a significant intervention effect for time spent walking in the at-risk sample (P=.02). Intervention effects were still significant 3 months post baseline for participants' daily step counts in both the total sample (P=.03) and the at-risk sample (P=.02); however, self-reported PA differences were no longer significant.ConclusionsA computer-tailored, pedometer-based PA intervention was effective in increasing both pedometer-based and self-reported PA levels, mainly in the at-risk participants. However, more effort should be devoted to recruit and retain participants in order to improve the public health impact of the intervention.Trial registrationClinicalTrials.gov: NCT02080585; https://clinicaltrials.gov/ct2/show/NCT02080585 (Archived by WebCite at http://www.webcitation.org/6VvQnRQSy).

Project description:IntroductionPhysical activity is an integral part of healthy ageing, yet the majority of older adults 65+ years are not sufficiently active. Web-based physical activity interventions hold much promise to reach older adults. Preliminary evidence suggests that web-based interventions with tailored advice and Fitbits may be well suited for older adults.Methods and analysisThis study aims to test the effectiveness of 'Active for Life', a 12-week computer-tailored web-based physical activity intervention using Fitbits for older adults. We will recruit 300 participants who will be randomly assigned to one of three trial arms: (1) web-based physical activity intervention with tailored advice only, (2) web-based physical activity intervention with tailored advice and Fitbit or (3) a wait-list control. The primary outcome, objective moderate to vigorous physical activity (MVPA) and secondary outcomes of objective sedentary behaviour, objective sleep, quality of life, social support, physical function and satisfaction with life will be assessed at baseline and week 12. The secondary outcomes of self-reported physical activity, sitting time and sleep will be assessed at baseline, week 6, 12 and 24. Website usability and participant satisfaction will be assessed at week 12 and website usage and intervention fidelity will be assessed from week 1 to 24. Intention-to-treat linear mixed model analyses will be used to test for group (tailoring only, tailoring +Fitbit, control) differences on changes in the main outcome, MVPA and secondary outcomes. Generalised linear models will be used to compare intervention groups (tailoring only, tailoring +Fitbit) on website usability, participant satisfaction, website usage and intervention fidelity.Ethics and disseminationThe study has received ethics approval from the Central Queensland University Human Research Ethics Committee (H16/12-321). Study outcomes will be disseminated through peer-reviewed publications and academic conferences and used to inform improvements and dissemination of a tailored, web-based physical activity intervention for adults 65+ years.Trial registration numberAustralian and New Zealand Clinical Trials Registry Number: ACTRN12618000646246.

Project description:BACKGROUND:Web-based interventions that provide personalized physical activity advice have demonstrated good effectiveness but rely on self-reported measures of physical activity, which are prone to overreporting, potentially reducing the accuracy and effectiveness of the advice provided. OBJECTIVE:This study aimed to examine whether the effectiveness of a Web-based computer-tailored intervention could be improved by integrating Fitbit activity trackers. METHODS:Participants received the 3-month TaylorActive intervention, which included 8 modules of theory-based, personally tailored physical activity advice and action planning. Participants were randomized to receive the same intervention either with or without Fitbit tracker integration. All intervention materials were delivered on the Web, and there was no face-to-face contact at any time point. Changes in physical activity (Active Australia Survey), sitting time (Workforce Sitting Questionnaire), and body mass index (BMI) were assessed 1 and 3 months post baseline. Advice acceptability, website usability, and module completion were also assessed. RESULTS:A total of 243 Australian adults participated. Linear mixed model analyses showed a significant increase in total weekly physical activity (adjusted mean increase=163.2; 95% CI 52.0-274.5; P=.004) and moderate-to-vigorous physical activity (adjusted mean increase=78.6; 95% CI 24.4-131.9; P=.004) in the Fitbit group compared with the non-Fitbit group at the 3-month follow-up. The sitting time and BMI decreased more in the Fitbit group, but no significant group × time interaction effects were found. The physical activity advice acceptability and the website usability were consistently rated higher by participants in the Fitbit group. Non-Fitbit group participants completed 2.9 (SD 2.5) modules, and Fitbit group participants completed 4.4 (SD 3.1) modules. CONCLUSIONS:Integrating physical activity trackers into a Web-based computer-tailored intervention significantly increased intervention effectiveness. TRIAL REGISTRATION:Australian New Zealand Clinical Trials Registry ACTRN12616001555448; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=371793 (Archived by WebCite at http://www.webcitation.org/73ioTxQX2).

Project description:BackgroundWeb-based interventions can play an important role in promoting physical activity (PA) behavior among older adults. Although the effectiveness of these interventions is promising, they are often characterized by low reach and high attrition, which considerably hampers their potential impact on public health.ObjectiveThe aim of this study was to identify the participant characteristics associated with the preference for a Web-based or a printed delivery mode and to determine whether an association exists between delivery modes or participant characteristics and attrition in an intervention. This knowledge may enhance implementation, sustainability of participation, and effectiveness of future interventions for older adults.MethodsA real-life pretest-posttest intervention study was performed (N=409) among community-living single adults who were older than 65 years, with physical impairments caused by chronic diseases. Measurements were taken at baseline and 3 months after the start of the intervention. Hierarchical logistic regression was used to assess demographic and behavioral characteristics (age, gender, body mass index, educational attainment, degree of loneliness, and PA level), as well as psychosocial characteristics (social support for PA, modeling, self-efficacy, attitude, and intention) related to delivery mode preference at baseline and attrition after 3 months.ResultsThe printed delivery mode achieved higher participation (58.9%, 241/409) than the Web-based delivery mode (41.1%, 168/409). Participation in the Web-based delivery mode was associated with younger age (B=-0.10; SE 0.02; Exp (B)=0.91; P<.001) and higher levels of social support for PA (B=0.38; SE 0.14; Exp (B)=1.46; P=.01); attrition was associated with participation in the Web-based delivery mode (B=1.28; SE 0.28; Exp (B)=3.58; P<.001) and low educational attainment (B=-0.53; SE 0.28; Exp (B)=0.59; P=.049).ConclusionsA total of 41% of the participants chose the Web-based delivery mode, thus demonstrating a potential interest of single older adults with physical impairments in Web-based delivered interventions. However, attrition was demonstrated to be higher in the Web-based delivery mode, and lower educational attainment was found to be a predictor for attrition. Characteristics predicting a preference for the printed delivery mode included being older and receiving less social support. Although Web-based delivery modes are generally less expensive and easier to distribute, it may be advisable to offer a printed delivery mode alongside a Web-based delivery mode to prevent exclusion of a large part of the target population.Trial registrationNetherlands Trial Register NTR2297; https://www.trialregister.nl/trial/2173.International registered report identifier (irrid)RR2-DOI: 10.2196/resprot.8093.

Project description:Background In a hospital setting and among older patients, inactivity and bedrest are associated with a wide range of negative outcomes such as functional decline, increased risk of falls, longer hospitalization and institutionalization. Our aim was to assess the distribution, determinants and predictors of physical activity (PA) levels using wrist-worn accelerometers in older patients hospitalized with acute medical illness. Methods Observational study conducted from February to November 2018 at an acute internal medicine unit in the University hospital of Lausanne, Switzerland. We enrolled 177 patients aged ?65?years, able to walk prior to admission. PA during acute hospital stay was continuously recorded via a 3D wrist accelerometer. Clinical data was collected from medical records or by interview. Autonomy level prior to inclusion was assessed using Barthel Index score. PA levels were defined as <?30?mg for inactivity, 30–99?mg for light and???100 for moderate PA. Physically active patients were defined as 1) being in the highest quartile of time spent in light and moderate PA or 2) spending ?20?min/day in moderate PA. Results Median [interquartile range - IQR] age was 83 [74–87] years and 60% of participants were male. The median [IQR] time spent inactive and in light PA was 613 [518–663] and 63 [30–97] minutes/day, respectively. PA peaked between 8 and 10?am, at 12?am and at 6?pm. Less than 10% of patients were considered physically active according to definition 2. For both definitions, active patients had a lower prevalence of walking aids and a lower dependency level according to Barthel Index score. For definition 1, use of medical equipment was associated with a 70% reduction in the likelihood of being active: odds ratio (OR) 0.30 [0.10–0.92] p =?0.034; for definition 2, use of walking aids was associated with a 75% reduction in the likelihood of being active: OR?=?0.24 [0.06–0.89], p =?0.032. Conclusion Older hospitalized patients are physically active only 10% of daily time and concentrate their PA around eating periods. Whether a Barthel Index below 95 prior to admission may be used to identify patients at risk of inactivity during hospital stay remains to be proven.

Dataset Information

The Effect of Active Plus, a Computer-Tailored Physical Activity Intervention, on the Physical Activity of Older Adults with Chronic Illness(es)-A Cluster Randomized Controlled Trial.

Publications

The Effect of Active Plus, a Computer-Tailored Physical Activity Intervention, on the Physical Activity of Older Adults with Chronic Illness(es)-A Cluster Randomized Controlled Trial.

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