Dataset Information

The Effectiveness of a Web-Based Computer-Tailored Intervention on Workplace Sitting: A Randomized Controlled Trial.

ABSTRACT: Effective interventions to influence workplace sitting are needed, as office-based workers demonstrate high levels of continued sitting, and sitting too much is associated with adverse health effects. Therefore, we developed a theory-driven, Web-based, interactive, computer-tailored intervention aimed at reducing and interrupting sitting at work.The objective of our study was to investigate the effects of this intervention on objectively measured sitting time, standing time, and breaks from sitting, as well as self-reported context-specific sitting among Flemish employees in a field-based approach.Employees (n=213) participated in a 3-group randomized controlled trial that assessed outcomes at baseline, 1-month follow-up, and 3-month follow-up through self-reports. A subsample (n=122) were willing to wear an activity monitor (activPAL) from Monday to Friday. The tailored group received an automated Web-based, computer-tailored intervention including personalized feedback and tips on how to reduce or interrupt workplace sitting. The generic group received an automated Web-based generic advice with tips. The control group was a wait-list control condition, initially receiving no intervention. Intervention effects were tested with repeated-measures multivariate analysis of variance.The tailored intervention was successful in decreasing self-reported total workday sitting (time × group: P<.001), sitting at work (time × group: P<.001), and leisure time sitting (time × group: P=.03), and in increasing objectively measured breaks at work (time × group: P=.07); this was not the case in the other conditions. The changes in self-reported total nonworkday sitting, sitting during transport, television viewing, and personal computer use, objectively measured total sitting time, and sitting and standing time at work did not differ between conditions.Our results point out the significance of computer tailoring for sedentary behavior and its potential use in public health promotion, as the effects of the tailored condition were superior to the generic and control conditions.Clinicaltrials.gov NCT02672215; http://clinicaltrials.gov/ct2/show/NCT02672215 (Archived by WebCite at http://www.webcitation.org/6glPFBLWv).

SUBMITTER: De Cocker K

PROVIDER: S-EPMC4908304 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The Effectiveness of a Web-Based Computer-Tailored Intervention on Workplace Sitting: A Randomized Controlled Trial.

De Cocker Katrien K De Bourdeaudhuij Ilse I Cardon Greet G Vandelanotte Corneel C

Journal of medical Internet research 20160531 5

<h4>Background</h4>Effective interventions to influence workplace sitting are needed, as office-based workers demonstrate high levels of continued sitting, and sitting too much is associated with adverse health effects. Therefore, we developed a theory-driven, Web-based, interactive, computer-tailored intervention aimed at reducing and interrupting sitting at work.<h4>Objective</h4>The objective of our study was to investigate the effects of this intervention on objectively measured sitting time ...[more]

PMID: 27245789

Similar Datasets

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: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:Web-based computer-tailored interventions for multiple health behaviors can improve the strength of behavior habits in people who want to reduce their cardiovascular risk. Nonetheless, few randomized controlled trials have tested this assumption to date.The study aim was to test an 8-week Web-based computer-tailored intervention designed to improve habit strength for physical activity and fruit and vegetable consumption among people who want to reduce their cardiovascular risk. In a randomized controlled design, self-reported changes in perceived habit strength, self-efficacy, and planning across different domains of physical activity as well as fruit and vegetable consumption were evaluated.This study was a randomized controlled trial involving an intervention group (n=403) and a waiting control group (n=387). Web-based data collection was performed in Germany and the Netherlands during 2013-2015. The intervention content was based on the Health Action Process Approach and involved personalized feedback on lifestyle behaviors, which indicated whether participants complied with behavioral guidelines for physical activity and fruit and vegetable consumption. There were three Web-based assessments: baseline (T0, N=790), a posttest 8 weeks after the baseline (T1, n=206), and a follow-up 3 months after the baseline (T2, n=121). Data analysis was conducted by analyzing variances and structural equation analysis.Significant group by time interactions revealed superior treatment effects for the intervention group, with substantially higher increases in self-reported habit strength for physical activity (F1,199=7.71, P=.006, Cohen's d=0.37) and fruit and vegetable consumption (F1,199=7.71, P=.006, Cohen's d=0.30) at posttest T1 for the intervention group. Mediation analyses yielded behavior-specific sequential mediator effects for T1 planning and T1 self-efficacy between the intervention and habit strength at follow-up T2 (fruit and vegetable consumption: beta=0.12, 95% CI 0.09-0.16, P<.001; physical activity: beta=0.04, 95% CI 0.02-0.06, P<.001).Our findings indicate the general effectiveness and practicality of Web-based computer-tailored interventions in terms of increasing self-reported habit strength for physical activity and fruit and vegetable consumption. Self-efficacy and planning may play major roles in the mechanisms that facilitate the habit strength of these behaviors; therefore, they should be actively promoted in Web-based interventions. Although the results need to take into account the high dropout rates and medium effect sizes, a large number of people were reached and changes in habit strength were achieved after 3 months.Clinicaltrials.gov NCT01909349; https://clinicaltrials.gov/ct2/show/NCT01909349 (Archived by WebCite at http://www.webcitation.org/6g5F0qoft) and Nederlands Trial Register NTR3706 http://www.trialregister.nl/ trialreg/admin/rctview.asp?TC=3706 (Archived by WebCite at http://www.webcitation.org/6g5F5HMLX).

Project description:BACKGROUND:Alcohol consumption, including binge drinking (BD) and heavy episodic drinking (HED), is one of the leading risk factors among Spanish adolescents leading to significant social, health, and economic consequences. Reduction of BD and HED in adolescents can be achieved using Web-based, computer-tailored (CT) interventions, providing highly personalized feedback that is adapted to a person's individual characteristics and needs. Randomized controlled trials assessing the effects of tailored BD reduction programs among Spanish adolescents are scarce. OBJECTIVE:The aim of this study was to test the effectiveness of the Web-based, CT intervention Alerta Alcohol, aimed at the prevention of BD in Spanish adolescents. As a secondary outcome, effects on HED, weekly consumption, and any consumption were also assessed. The adherence and process evaluation were assessed. METHODS:A cluster randomized controlled trial conducted among 15 Spanish schools was developed. Each school was randomized into either an experimental condition (EC) (N=742) or a control condition (CC) (N=505). Finally, 351 participants for the EC and 261 for the CC were included in the analysis (N=612). Baseline assessment took place in January and February 2017. Demographic variables and alcohol use were assessed at baseline. Follow-up assessment of alcohol use took place 4 months later in May and June 2017. Participants were compared according to their randomization group (EC versus CC). After the baseline assessment, participants in the EC started the intervention, which consisted of short stories about BD, in which CT feedback was based on the I-Change Model for behavior change. Participants in the CC group only received the baseline questionnaire. Effects of the intervention were assessed using a three-level mixed logistic regression analysis for BD, HED, and any consumption, and a three-level mixed linear regression analysis for weekly consumption. RESULTS:In total, 1247 adolescents participated in the baseline assessment and 612 participated in the follow-up assessment; the attrition rate was 50.92%. The intervention was effective in reducing HED among adolescents; the odds of HED in the CC was nine times that in the experimental condition (P=.04). No effects were found for BD, weekly consumption, and any consumption. Process evaluations revealed that the adolescents were satisfied with the program (68.8%), would use the program again (52.9%), and would recommend it to someone else (62.8%). Females and non-binge drinkers showed better responses in the process evaluation. CONCLUSIONS:Our intervention was effective regarding HED but not regarding BD, weekly consumption, and any consumption. It may be that limiting alcohol consumption to prevent HED was easier in the Spanish context than it was to carry out further steps, such as reducing other patterns of alcohol consumption. Hence, additional actions are needed to accomplish these latter goals, including community approaches and policy actions aimed at denormalizing alcohol consumption among Spanish adolescents. TRIAL REGISTRATION:ClinicalTrials.gov NCT03288896; https://clinicaltrials.gov/ct2/show/NCT03288896. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID):RR2-10.1186/s12889-018-5346-4.

Project description:BACKGROUND:Wearable activity trackers are now a common feature of workplace wellness programs; however, their ability to impact sitting time (the behavior in which most of the desk-based workday is spent) is relatively unknown. This study evaluated the LUMOback, an activity tracker that targets sitting time, as part of a cluster-randomized workplace sitting intervention in desk-based office workers. OBJECTIVE:Study objectives were to explore: (1) office workers' self-directed LUMOback use, (2) individual-level characteristics associated with LUMOback use, (3) the impact of LUMOback use on activity and sitting behaviors, and (4) office workers' perceived LUMOback acceptability. METHODS:Exploratory analyses were conducted within the activity tracker intervention group (n=66) of a 2-arm cluster-randomized trial (n=153) with follow-up at 3 and 12 months. The intervention, delivered from within the workplace, consisted of organizational support strategies (eg, manager support, emails) to stand up, sit less, and move more, plus the provision of a LUMOback activity tracker. The LUMOback, worn belted around the waist, provides real-time sitting feedback through a mobile app. LUMOback usage data (n=62), Web-based questionnaires (n=33), activPAL-assessed sitting, prolonged (≥30 min bouts) and nonprolonged (<30 min bouts) sitting, standing and stepping time (7-day, 24 h/day protocol; n=40), and telephone interviews (n=27) were used to evaluate study aims. LUMOback usage data were downloaded and described. Associations between user characteristics and LUMOback usage (in the first 3 months) were analyzed using zero-inflated negative binomial models. Associations between LUMOback usage and 3-month activity outcomes were analyzed using mixed models, correcting for cluster. LUMOback acceptability was explored using 3-month questionnaire data and thematic analysis of telephone interviews (conducted 6 to 10 months post intervention commencement). RESULTS:Tracker uptake was modest (43/61, 70%), and among users, usage over the first 3 months was low (1-48 days, median 8). Usage was greatest among team leaders and those with low self-perceived scores for job control and supervisor relationships. Greater tracker use (≥5 days vs <5 days) was significantly associated only with changes in prolonged unbroken sitting (-50.7 min/16 h; 95% CI -94.0 to -7.3; P=.02) during all waking hours, and changes in nonprolonged sitting (+32.5 min/10 h; 95% CI 5.0 to 59.9; P=.02) during work hours. Participants found the LUMOback easy to use but only somewhat comfortable. Qualitatively, participants valued the real-time app feedback. Nonuptake was attributed to being busy and setup issues. Low usage was attributed to discomfort wearing the LUMOback. CONCLUSIONS:The LUMOback-although able to reduce prolonged sitting time-was only used to a limited extent, and its low usage may provide a partial explanation for the limited behavior changes that occurred. Discomfort limited the feasibility of the LUMOback for ongoing use. Such findings yield insight into how to improve upon implementing activity trackers in workplace settings.

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:There is now a body of evidence on the effectiveness of interventions to reduce workplace sitting time. However, there has been limited reporting of how such interventions may impact behaviour both during and outside of work. Sitting, standing and stepping changes following a workplace intervention were examined across five timeframes (work time on work days; non-work time on work days; work days; non-work days; overall (i.e. work and non-work time on all days)), and the relationships between changes during and outside of work was assessed. METHODS:The cluster-randomised controlled trial, 'Stand Up Victoria', delivered a multi-component workplace-delivered intervention that successfully reduced workplace and overall sitting time (relative to controls). Separately, over the five timeframes, changes in device (activPAL3)-assessed outcomes - sitting; prolonged sitting (?30?min bouts); standing; and, stepping - were compared between intervention (n?=?114) and controls (n?=?84), along with the time-course of sitting changes during work hours, using mixed models. The potential relationships of changes during work with changes outside of work were examined using compositional data analysis. RESULTS:On workdays, intervention participants significantly (p?<?0.05) improved their activity profile relative to controls, with reduced sitting (-?117?min/8-h workday, 95% CI: -?141, -?93) and prolonged sitting (-?77?min/8?h workday, 95% CI: -?101, -?52); increased standing (114?min/8?h workday, 95% CI: 92, 136) and maintenance of stepping (3?min/8?h workday, 95% CI: -?7, 11, p?=?0.576). Effects were nearly identical for time at work; similar but slightly weaker for overall; and, small and non-significant outside of work on workdays and non-work days. Improvements occurred at all times, but not equally, during work hours (p?<?0.001). Correlations between changes during and outside of work on workdays were very weak in both the intervention group (r?=?-?0.07) and controls (r?=?-?0.09). CONCLUSIONS:Sitting time was reduced almost exclusively during work hours (via replacement with standing), with reductions evident during all working hours, to varying degrees. There was no evidence of compensation, with minimal change in activity outside of work, in response to changes in activity at work. Future interventions may benefit from exploring how best to elicit change throughout the whole day, and across work and non-work domains. TRIAL REGISTRATION:This trial was prospectively registered with the Australian New Zealand Clinical Trials register (ACTRN12611000742976) on 15 July 2011.

Project description:BackgroundAdherence to core type 2 diabetes mellitus (T2DM) treatment behaviors is suboptimal, and nonadherence is generally not limited to one treatment behavior. The internet holds promise for programs that aim to improve adherence. We developed a computer-tailored eHealth program for patients with T2DM to improve their treatment adherence, that is, adherence to both a healthy lifestyle and medical behaviors.ObjectiveThe objective of this study is to examine the effectiveness of the eHealth program in a randomized controlled trial.MethodsPatients with T2DM were recruited by their health professionals and randomized into either the intervention group, that is, access to the eHealth program for 6 months, or a waiting-list control group. In total, 478 participants completed the baseline questionnaire, of which 234 gained access to the eHealth program. Of the 478 participants, 323 were male and 155 were female, the mean age was 60 years, and the participants had unfavorable BMI and HbA1c levels on average. Outcome data were collected through web-based assessments on physical activity (PA) levels, caloric intake from unhealthy snacks, and adherence to oral hypoglycemic agents (OHAs) and insulin therapy. Changes to separate behaviors were standardized and summed into a composite change score representing changes in the overall treatment adherence. Further standardization of this composite change score yielded the primary outcome, which can be interpreted as Cohen d (effect size). Standardized change scores observed in separate behaviors acted as secondary outcomes. Mixed linear regression analyses were conducted to examine the effectiveness of the intervention on overall and separate treatment behavior adherence, accommodating relevant covariates and patient nesting.ResultsAfter the 6-month follow-up assessment, 47.4% (111/234) of participants in the intervention group and 72.5% (177/244) of participants in the control group were retained. The overall treatment adherence improved significantly in the intervention group compared with the control group, reflected by a small effect size (d=0.27; 95% CI 0.032 to 0.509; P=.03). When considering changes in separate treatment behaviors, a significant decrease was observed only in caloric intake from unhealthy snacks in comparison with the control group (d=0.36; 95% CI 0.136 to 0.584; P=.002). For adherence to PA (d=-0.14; 95% CI -0.388 to 0.109; P=.27), OHAs (d=0.27; 95% CI -0.027 to 0.457; P=.08), and insulin therapy (d=0.35; 95% CI -0.066 to 0.773; P=.10), no significant changes were observed. These results from the unadjusted analyses were comparable with the results of the adjusted analyses, the per-protocol analyses, and the sensitivity analyses.ConclusionsOur multibehavior program significantly improved the overall treatment adherence compared with the control group. To further enhance the impact of the intervention in the personal, societal, and economic areas, a wide-scale implementation of our eHealth intervention is suggested.Trial registrationNetherlands Trial Register NL664; https://www.trialregister.nl/trial/6664.

Project description:BACKGROUND:Tailoring an online intervention to participant preferences (eg, by giving participants a choice which modules to follow) may increase engagement in the intervention, motivation for behavioral change, and possibly intervention effects. So far, little is known about what characteristics predict these module choices. Filling this knowledge gap is useful for optimizing program engagement. OBJECTIVE:We investigated participant choice for a dietary and/or physical activity (PA) promotion module in our web-based computer-tailored intervention based on self-determination theory (SDT) and motivational interviewing (MI). Furthermore, we investigated which demographic characteristics, current behavior, psychosocial constructs and constructs from SDT and MI, and program-related variables such as advice on which module to follow were associated with these choices. METHODS:Observational data were used from the randomized controlled trial MyLifestyleCoach of participants who were randomized into the intervention condition, completed the baseline questionnaire, and made a module choice in the opening session of the intervention. Here, they received advice on their own dietary and PA behavior. At the session's end, they chose which lifestyle modules they would like to follow (both, diet, PA, or no module). Measurements included demographic information; self-reported diet and PA; and several psychosocial, SDT, and MI constructs. In total, data from 619 Dutch adults (59.6% women; mean age was 51.9 [SD 13.5] years) were analyzed. A stepwise multinomial logistic regression analysis was conducted to investigate which characteristics are related to module choice; the diet module served as reference category as almost everyone was advised to follow this module. RESULTS:Of this sample, 54.8% (339/619) chose to do both the diet and PA module, 25.4% (157/619) chose to follow the diet module, 17.8% (110/619) preferred to follow no module, and 2.1% (13/619) chose to do the PA module only. Furthermore, it was found that older people, those who consumed more fruit, and those who scored lower on importance to change their current diet were more likely to choose no module compared to the diet module. People who had more motivation to change their current PA and those who received strong advice compared with slight advice to follow the diet module were more likely to choose both modules compared with the diet module only. CONCLUSIONS:The results show that more than half of the sample was interested in following both the diet and PA module in this online lifestyle intervention. Several characteristics were found to be related to module choice. A future challenge is to examine how this knowledge can be used to improve future interventions, such as tailoring (messages or content) on specific groups or examining where and how MI could be used to motivate people to make a certain module choice. TRIAL REGISTRATION:Netherlands Trial Register NL7333; https://www.trialregister.nl/trial/7333.

Dataset Information

The Effectiveness of a Web-Based Computer-Tailored Intervention on Workplace Sitting: A Randomized Controlled Trial.

Publications

The Effectiveness of a Web-Based Computer-Tailored Intervention on Workplace Sitting: A Randomized Controlled Trial.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure