Computer-tailored Physical Activity Research Articles

Promoting the implementation of a computer-tailored physical activity intervention: development and feasibility testing of an implementation intervention

BackgroundAlthough there are many proven effective physical activity (PA) interventions for older adults, implementation in a real world setting is often limited. This study describes the systematic development of a multifaceted implementation intervention targeting the implementation of an evidence-based computer-tailored PA intervention and evaluates its use and feasibility.MethodsThe implementation intervention was developed following the Intervention Mapping (IM) protocol, supplemented with insights from implementation science literature. The implementation intervention targets the municipal healthcare policy advisors, as an important implementation stakeholder in Dutch healthcare system. The feasibility of the implementation intervention was studied among these stakeholders using a pretest–posttest design within 8 municipal healthcare settings. Quantitative questionnaires were used to assess task performance (i.e. achievement of performance objectives), and utilization of implementation strategies (as part of the intervention). Furthermore, changes in implementation determinants were studied by gathering quantitative data before, during and after applying the implementation intervention within a one-year period. Additionally, semi-structured interviews with stakeholders assessed their considerations regarding the feasibility of the implementation intervention.ResultsA multi-faceted implementation intervention was developed in which implementation strategies (e.g. funding, educational materials, meetings, building a coalition) were selected to target the most relevant identified implementation determinants. Most implementation strategies were used as intended. Execution of performance objectives for adoption and implementation was relatively high (75–100%). Maintenance objectives were executed to a lesser degree (13–63%). No positive changes in implementation determinants were found. None of the stakeholders decided to continue implementation of the PA intervention further, mainly due to the unforeseen amount of labour and the disappointing reach of end-users.ConclusionThe current study highlights the importance of a thorough feasibility study in addition to the use of IM. Although feasibility results may have demonstrated that stakeholders broadly accepted the implementation intervention, implementation determinants did not change favorably, and stakeholders had no plans to continue the PA intervention. Yet, choices made during the development of the implementation intervention (i.e. the operationalization of Implementation Mapping) might not have been optimal. The current study describes important lessons learned when developing an implementation intervention, and provides recommendations for developers of future implementation interventions.

Does intervention engagement mediate physical activity change in a web-based computer-tailored physical activity intervention?-Secondary outcomes from a randomised controlled trial.

The relationship between intervention engagement and behaviour change may vary depending on the specific engagement metric being examined. To counter this composite engagement measures may provide a deeper understanding of the relationship between engagement and behaviour change, though few studies have applied such multidimensional engagement metrics. The aim of this secondary analysis of RCT data was to examine how a composite engagement score mediates the effect of a web-based computer-tailored physical activity intervention. 501 inactive Australian adults were randomised to a no-treatment control or intervention group. Intervention participants received 8 sessions of web-based personalised physical activity advice over a 12-week intervention period and the ability to complete action plans. Change in physical activity was assessed using Actigraph accelerometers at baseline, 3-months and 9-months. Engagement with the intervention (i.e., a composite score including frequency, intensity, duration and type) was continuously assessed during the intervention period using website tracking software and database metrics. Generalised structural equation models were used to examine how a composite engagement score mediated intervention effects at 3 months and 9 months. At 3 months, mediation analysis revealed that the intervention group had significantly higher engagement scores than the control group [a-path exp(b) = 6.462, 95% CI = 5.121-7.804, p < 0.001]. Further, increased engagement with the intervention platform was associated with an increased time spent in moderate-to-vigorous physical activity [ab-coefficient exp(b) = 1.008, 95% CI = 1.004-1.014, P < 0.001]; however, the magnitude of this effect was small. There were no significant mediation effects at the 9-month time point. The findings suggest that a composite intervention engagement score has a small positive influence on physical activity changes and that other factors (e.g., behaviour change techniques) are likely to be more important drivers of behaviour change.

The moderating effect of social support on the effectiveness of a web-based, computer-tailored physical activity intervention for older adults.

This study aimed to assess the moderating effect of social support on the effectiveness of a web-based, computer-tailored physical activity intervention for older adults. In the Active for Life trial, 243 inactive adults aged 65+ years were randomised into: (1) tailoring + Fitbit (n = 78), (2) tailoring-only (n = 96) or (3) control (n = 69). For the current study, participants were categorised as having higher (n = 146) or lower (n = 97) social support based on the Duke Social Support Index (DSSI_10). Moderate-to-vigorous physical activity (MVPA) was measured through accelerometers at baseline and post-intervention. A linear mixed model analysis demonstrated that among participants with lower social support, the tailoring + Fitbit participants, but not the tailoring only participants increased their MVPA more than the control. Among participants with higher social support, no differences in MVPA changes were observed between groups. Web-based computer-tailored interventions with Fitbit integration may be more effective in older adults with lower levels of social support.

O.1.2-4 Evaluation of a multifaceted implementation plan for a computer-tailored physical activity intervention: a mixed methods study

Abstract Background Although there are many proven effective physical activity (PA) interventions for older adults, implementation in a real world setting is often lacking, limiting their actual impact on public health. This study describes the systematic development of a multifaceted implementation plan and evaluates its use during implementation of the evidence-based computer-tailored Active Plus PA intervention. Important lessons learned during this process will be presented. Methods The implementation plan was developed following the steps of Implementation Mapping, linking multilevel determinants of implementation to implementation theory and strategies. Municipalities (n = 33) were invited to implement the intervention among their inhabitants aged 65 years and older. Quantitative and qualitative data were gathered within municipalities to assess the implementation process, i.e. achievement of the performance objectives (i.e. sub-behaviours of implementers) and utilization of implementation strategies. We also assessed implementation determinants (i.e. perceptions of the intervention characteristics, the inner setting of the organization and the outer setting) before, during and after utilization of the implementation plan. Results A total of 8 municipalities (i.e. 24% adoption) implemented Active Plus, and 624 people aged over 65 participated in the intervention (8% adoption). Implementation strategies were used adequately. Execution of the performance objectives for adoption and implementation was relatively high (75-100%). Maintenance objectives were executed to a lesser degree (13-63%). No positive changes in implementation determinants were observed and none of the municipalities decided to further continue intervention implementation. Conclusion Implementation Mapping was found to be a useful protocol to develop and evaluate the implementation plan. Yet, implementers’ determinants did not change favorably, and municipalities did not continue intervention implementation, although implementation strategies were used as intended. We might have not addressed the most relevant determinants with the selected implementation strategies. Whereas the current implementation plan mainly targeted implementation determinants related to the individual and the perceived intervention characteristics, a stronger focus on strategies targeting implementation determinants related to the inner setting, the outer setting and the implementation process itself is recommendable. In addition, it is advisable to use a more iterative approach, evaluating goals and determinants regularly, and consequently adapting the required implementation strategies.

O.3.2-6 A computer-tailored physical activity intervention for prostate and colorectal cancer patients and survivors: long-term efficacy and behavior change maintenance of OncoActive

Abstract Purpose To improve the long-term physical and psychological health of prostate and colorectal cancer survivors, physical activity (PA) interventions aimed at maintaining PA are necessary. OncoActive is a print- and web-based intervention that was was able to increase PA of prostate and colorectal cancer patients and survirors shortly after the intervention ended. This study evaluated the long-term efficacy (12-month follow-up) comparing OncoActive and a control group. Furthermore, we explored whether the increased PA was maintained after an 8 month non-intervention follow-up period. Methods Prostate or colorectal cancer patients were randomly assigned to OncoActive (N = 249) or a usual care control group (N = 229). OncoActive participants received 3 times PA advice and a pedometer. PA outcomes (i.e., ActiGraph and self-report MVPA min/week and days with ≥ 30 min PA) and health-related outcomes (i.e., fatigue, depression, physical functioning) that were significantly changed by the intervention at 6-month follow-up, were included. Differences between groups and changes over time were assessed with multilevel linear regressions. Results At 12 months, OncoActive participants did not perform better than control group participants at ActiGraph MVPA min/week, self-report MVPA min/week or ActiGraph days with PA. Only self-report days with PA were significantly higher in OncoActive compared to the control group. Fatigue was the only health-related outcome that was significantly lower in OncoActive compared to the control group at 12-month follow-up. When exploratively looking within the OncoActive group, the previously found PA increase shortly after the intervention (6 months follow-up) was maintained at 12 months and PA improved significantly from baseline to 12 months. The control group showed small but non-significant improvements from 6 to 12 resulting in a decline of differences between groups. Conclusion At long-term follow-up (i.e., 12-months), most significant differences between OncoActive and the control group at short-term follow-up (i.e., 6 months) were no longer significant. Natural improvements in the control group may have contributed to this. Fatigue was significantly lower in OncoActive compared to control group participants at 12 months. Computer-tailored PA advice may give participants an early start to recovery and potentially contributes to improving long-term health. Funding KWF Kankerbestrijding (Dutch cancer society) NOU2012-5585

Long-term efficacy of a computer-tailored physical activity intervention for prostate and colorectal cancer patients and survivors: A randomized controlled trial

BackgroundPhysical activity (PA) can improve the physical and psychological health of prostate and colorectal cancer survivors, but PA behavior change maintenance is necessary for long-term health benefits. OncoActive is a print- and web-based intervention in which prostate and colorectal cancer patients and survivors receive automatically generated, personalized feedback aimed at integrating PA into daily life to increase and maintain PA. We evaluated the long-term outcomes of OncoActive by examining the 12-month follow-up differences between OncoActive and a control group, and we explored whether PA was maintained during a 6-month non-intervention follow-up period. MethodsProstate or colorectal cancer patients were randomly assigned to an OncoActive (n = 249) or a usual care waitlist control group (n = 229). OncoActive participants received PA advice and a pedometer. PA outcomes (i.e., ActiGraph and self-report moderate-to-vigorous intensity PA (MVPA) min/week and days with ≥30 min PA) and health-related outcomes (i.e., fatigue, depression, physical functioning) were assessed at baseline, 6 months, and 12 months. Differences between groups and changes over time were assessed with multilevel linear regressions for the primary outcome (ActiGraph MVPA min/week) and all additional outcomes. ResultsAt 12 months, OncoActive participants did not perform better than control group participants at ActiGraph MVPA min/week, self-report MVPA min/week, or ActiGraph days with PA. Only self-report days with PA were significantly higher in OncoActive compared to the control group. For health-related outcomes only long-term fatigue was significantly lower in OncoActive. When exploratively examining PA within OncoActive, the previously found PA effects at the end of the intervention (6 months follow-up) were maintained at 12 months. Furthermore, all PA outcomes improved significantly from baseline to 12 months. The control group showed small but non-significant improvements from 6 months to 12 months (and from baseline to 12 months), resulting in a decline of differences between groups. ConclusionThe majority of previously reported significant between-group differences at 6 months follow-up were no longer present at long-term follow-up, possibly because of natural improvement in the control group. At long-term follow-up, fatigue was significantly lower in OncoActive compared to control group participants. Computer-tailored PA advice may give participants an early start toward recovery and potentially contributes to improving long-term health.

The impact of action plans on habit and intention strength for physical activity in a web-based intervention: is it the thought that counts?

Objective Action planning is a common approach used in physical activity interventions. The aim of this study was to assess the association of frequency, consistency and content of action planning with physical activity behaviour, intention strength and habit strength. Methods and Measures Within a 3-month web-based, computer-tailored physical activity intervention, participants (N = 115; 68.7% female, M age =43.9; range = 22–73 years) could create 6 rounds of action plans for 4 activities each (24 total). Results Consistency of action planning during the intervention was associated with change in physical activity at 9-months, and intention and habit strength at 3-months and 9-months. Frequency of action planning was negatively associated with intention at 3-months and 9-months. The effect of action planning consistency on physical activity behaviour was no longer significant when accounting for change in intention and habit strength. Conclusion Consistency of how, where, when and with whom people plan their physical activity may translate into stronger physical activity habits. Interventions should avoid encouraging making many distinct action plans, but rather encourage stable contexts through consistent action planning.

Engagement, acceptability, usability and satisfaction with Active for Life, a computer-tailored web-based physical activity intervention using Fitbits in older adults

BackgroundPreliminary evidence suggests that web-based physical activity interventions with tailored advice and Fitbit integration are effective and may be well suited to older adults. Therefore, this study aimed to examine the engagement, acceptability, usability, and satisfaction with ‘Active for Life,’ a web-based physical activity intervention providing computer-tailored physical activity advice to older adults.MethodsInactive older adults (n = 243) were randomly assigned into 3 groups: 1) tailoring + Fitbit, 2) tailoring only, or 3) a wait-list control. The tailoring + Fitbit group and the tailoring-only group received 6 modules of computer-tailored physical activity advice over 12 weeks. The advice was informed by objective Fitbit data in the tailoring + Fitbit group and self-reported physical activity in the tailoring-only group. This study examined the engagement, acceptability, usability, and satisfaction of Active for Life in intervention participants (tailoring + Fitbit n = 78, tailoring only n = 96). Wait-list participants were not included. Engagement (Module completion, time on site) were objectively recorded through the intervention website. Acceptability (7-point Likert scale), usability (System Usability Scale), and satisfaction (open-ended questions) were assessed using an online survey at post intervention. ANOVA and Chi square analyses were conducted to compare outcomes between intervention groups and content analysis was used to analyse program satisfaction.ResultsAt post-intervention (week 12), study attrition was 28% (22/78) in the Fitbit + tailoring group and 39% (37/96) in the tailoring-only group. Engagement and acceptability were good in both groups, however there were no group differences (module completions: tailoring + Fitbit: 4.72 ± 2.04, Tailoring-only: 4.23 ± 2.25 out of 6 modules, p = .14, time on site: tailoring + Fitbit: 103.46 ± 70.63, Tailoring-only: 96.90 ± 76.37 min in total, p = .56, and acceptability of the advice: tailoring + Fitbit: 5.62 ± 0.89, Tailoring-only: 5.75 ± 0.75 out of 7, p = .41). Intervention usability was modest but significantly higher in the tailoring + Fitbit group (tailoring + Fitbit: 64.55 ± 13.59, Tailoring-only: 57.04 ± 2.58 out of 100, p = .003). Participants reported that Active for Life helped motivate them, held them accountable, improved their awareness of how active they were and helped them to become more active. Conversely, many participants felt as though they would prefer personal contact, more detailed tailoring and more survey response options.ConclusionsThis study supports web-based physical activity interventions with computer-tailored advice and Fitbit integration as engaging and acceptable in older adults.Trial registrationAustralian and New Zealand Clinical Trials Registry: ACTRN12618000646246. Registered April 23 2018, https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=374901

Does matching a personally tailored physical activity intervention to participants' learning style improve intervention effectiveness and engagement?

This study aims to compare the effectiveness, engagement, usability, and acceptability of a web-based, computer-tailored physical activity intervention (provided as video or text) between participants who were matched or mismatched to their self-reported learning style (visual and auditory delivery through video or text-based information). Generalised linear mixed models were conducted to compare time (baseline, 3 months) by group (matched, mismatched) on ActiGraph-GT3X+measured moderate-to-vigorous physical activity (MVPA) and steps. Generalised linear models were used to compare group (matched and mismatched) on session completion, time-on-site, usability, and acceptability. MVPA and steps improved from baseline to 3-months, however this did not differ between participants whose learning styles were matched or mismatched to the intervention they received. Session completion, time-on-site, usability, and acceptability did not differ between matched and mismatched participants. Therefore, aligning intervention delivery format to learning style is unlikely to influence intervention effectiveness or engagement.

Evaluating a web-based computer-tailored physical activity intervention for those living with and beyond lung cancer (ExerciseGuide UK): protocol for a single group feasibility and acceptability study

BackgroundLung cancer is the leading cause of cancer-related death globally. Physical activity and exercise provide unequivocal benefits to those living with and beyond lung cancer. However, few of those living with and beyond cancer meet the national physical activity guidelines. Various barriers exist for this population’s engagement in physical activity and exercise, such as the lack of knowledge and lack of tailored information, little access to exercise specialists, fatigue, and mobility challenges. Digitally delivered programmes have the potential to address several of these barriers, with techniques like “computer-tailoring” available to enable the delivery of tailored content at a time and place that is convenient. However, evaluation of such programmes is needed prior to implementation. This protocol describes a single group study that will examine the feasibility and acceptability of an online tool (ExerciseGuide UK) that provides those living with and beyond lung cancer web-based computer-tailored physical activity prescription and modules underpinned by behaviour change theories.MethodsThirty-five individuals diagnosed with lung cancer, or cancer affecting the lung (e.g. pleural mesothelioma), will be recruited into a single-intervention arm. The platform will provide tailored resources and a personalised physical activity programme using IF-THEN algorithms. Exercise prescription will be tailored on factors such as self-reported specific pain location, exercise history, and current physical fitness. In addition, modules grounded in behaviour change will supplement the physical activity programme and will focus on topics such as exercise benefits, safety, goal setting, and tracking. The primary outcome will be assessed using pre-established criteria on feasibility and mixed-methods approach for acceptability.Secondary outcomes will explore changes in the physical activity, quality of life, anxiety, and depression.DiscussionThis manuscript describes the protocol for a study examining the feasibility and acceptability of a web-based computer-tailored physical activity intervention for those living with and beyond lung cancer. The publication of this protocol aims to increase the transparency of the methods, report pre-determined criteria, and aid replication of the study and associated materials. If feasible and acceptable, this intervention will inform future studies of digital-based interventions.Trail registrationClinicalTrails.gov, NCT05121259. Registered on November 16, 2021.

The Effectiveness of a Computer-Tailored Web-Based Physical Activity Intervention Using Fitbit Activity Trackers in Older Adults (Active for Life): Randomized Controlled Trial.

BackgroundPhysical activity is an integral part of healthy aging; yet, most adults aged ≥65 years are not sufficiently active. Preliminary evidence suggests that web-based interventions with computer-tailored advice and Fitbit activity trackers may be well suited for older adults.ObjectiveThe aim of this study was to examine the effectiveness of Active for Life, a 12-week web-based physical activity intervention with 6 web-based modules of computer-tailored advice to increase physical activity in older Australians.MethodsParticipants were recruited both through the web and offline and were randomly assigned to 1 of 3 trial arms: tailoring+Fitbit, tailoring only, or a wait-list control. The computer-tailored advice was based on either participants’ Fitbit data (tailoring+Fitbit participants) or self-reported physical activity (tailoring-only participants). The main outcome was change in wrist-worn accelerometer (ActiGraph GT9X)–measured moderate to vigorous physical activity (MVPA) from baseline to after the intervention (week 12). The secondary outcomes were change in self-reported physical activity measured by means of the Active Australia Survey at the midintervention point (6 weeks), after the intervention (week 12), and at follow-up (week 24). Participants had a face-to-face meeting at baseline for a demonstration of the intervention and at baseline and week 12 to return the accelerometers. Generalized linear mixed model analyses were conducted with a γ distribution and log link to compare MVPA and self-reported physical activity changes over time within each trial arm and between each of the trial arms.ResultsA total of 243 participants were randomly assigned to tailoring+Fitbit (n=78, 32.1%), tailoring only (n=96, 39.5%), and wait-list control (n=69, 28.4%). Attrition was 28.8% (70/243) at 6 weeks, 31.7% (77/243) at 12 weeks, and 35.4% (86/243) at 24 weeks. No significant overall time by group interaction was observed for MVPA (P=.05). There were no significant within-group changes for MVPA over time in the tailoring+Fitbit group (+3%, 95% CI –24% to 40%) or the tailoring-only group (–4%, 95% CI –24% to 30%); however, a significant decline was seen in the control group (–35%, 95% CI –52% to –11%). The tailoring+Fitbit group participants increased their MVPA 59% (95% CI 6%-138%) more than those in the control group. A significant time by group interaction was observed for self-reported physical activity (P=.02). All groups increased their self-reported physical activity from baseline to week 6, week 12, and week 24, and this increase was greater in the tailoring+Fitbit group than in the control group at 6 weeks (+61%, 95% CI 11%-133%).ConclusionsA computer-tailored physical activity intervention with Fitbit integration resulted in improved MVPA outcomes in comparison with a control group in older adults.Trial RegistrationAustralian New Zealand Clinical Trials Registry ACTRN12618000646246; https://anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12618000646246

A randomized controlled trial into the cognitive effects of a computer-tailored physical activity intervention in older adults with chronic disease(s)

BackgroundCognitive functioning (CF) is important for wellbeing and an independent life. However, older adults with chronic diseases are at a higher risk of poorer CF levels. Although, research suggests that physical activity (PA) could play an essential role in maintaining good CF, older adults with chronic diseases have low levels of PA. PA interventions to prevent cognitive decline for this specific group exist. Yet, until now these interventions focused on a single specific chronic disease. Active Plus is a proven effective computer-tailored PA stimulating intervention focused on increasing PA in daily life for the older adult population suffering from a broad range of chronic diseases. This study tests the cognitive effects of Active Plus in older adults with chronic diseases.MethodsIn this RCT older adults with at least one chronic disease (≥65 years) were allocated to the intervention group (N = 260, mean age = 74.2) or waiting list control group (N = 325, mean age = 74.5). In total, intervention group participants received three times computer-tailored PA stimulating advice within four months (i.e., at baseline, after two months, and after three to four months). The online and print delivered advice were tailored to the specific needs and wishes of the participant and focused on incorporating PA in daily life. Baseline and follow-up measurements of the CF verbal memory (Verbal Learning Test), shifting (Trailmaking Test), inhibition (Stop-signal Task) and processing speed (Letter Digit Substitution Test) were assessed after six and 12 months. Intervention effects were analyzed with multilevel linear mixed-effects models adjusted for the clustered design and confounding variables.ResultsThe dropout rate was 19.1% after 6 months and 25.1% after 12 months. Although both conditions improved on all verbal memory outcomes after 6 months, and all CF outcomes except inhibition after 12 months, no intervention effects were found, not even in subgroups (p > .05).ConclusionsTo our knowledge this is the first study to test the cognitive effects of a computer-tailored PA stimulating intervention in older adults suffering from a broad range of chronic diseases. The effects of the Active Plus intervention were not strong enough to improve CF or prevent cognitive decline. A blended approach, in which this computer-tailored intervention is combined with a face-to-face PA intervention and / or cognitive training, might be a good suggestion to increase the effects of Active Plus on PA and CF in older adults with chronic diseases.Trial registrationNetherlands Trial Register NL6005; Date of Registration 03-21-2017; https://www.trialregister.nl/trial/6005

Examining moderators of the effectiveness of a web- and video-based computer-tailored physical activity intervention.

Understanding for whom behaviour change interventions work is important, however there is a lack of studies examining potential moderators in such interventions. This study investigated potential moderators on the effectiveness of a computer-tailored intervention to increase physical activity among Australian adults. People who had <150 min of moderate-vigorous physical activity (MVPA) a week, able to speak and read English, aged ≥18 years, lived in Australia, and had internet access were eligible to participate. Participants recruited through social media, emails, and third-party databases, were randomly assigned to either the control (n = 167) or intervention groups (n = 334). Physical activity was measured objectively by ActiGraph GT3X and also by self-report at baseline and three months. Three-way interaction terms were tested to identify moderators (i.e., demographic characteristics, BMI, and perceived neighbourhood walkability). The results showed that the three-way interaction was marginally significant for sex on accelerometer measured MVPA/week (p = 0.061) and steps/day (p = 0.047). The intervention appeared to be more effective for women compared to men. No significant three-way interactions were found for the other potential moderators. Strategies to improve levels of personalisation may be needed so that physical activity interventions can be better tailored to different subgroups, especially sex, and therefore improve intervention effectiveness.

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.

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.

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.

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.

Development and Testing of a Personalized Web-Based Diet and Physical Activity Intervention Based on Motivational Interviewing and the Self-Determination Theory: Protocol for the MyLifestyleCoach Randomized Controlled Trial.

BackgroundUnhealthy dietary patterns and insufficient physical activity (PA) are associated with negative health outcomes, such as cardiovascular diseases, type 2 diabetes, cancer, overweight, and obesity. This makes the promotion of healthy dietary and PA behaviors a public health priority.ObjectiveThis paper describes the development, design, and evaluation protocol of a Web-based computer-tailored (CT) dietary and PA promotion intervention, MyLifestyleCoach. A Web-based format was chosen for its accessibility and large-scale reach and low-cost potential. To achieve effective and persistent behavioral change, this innovative intervention is tailored to individual characteristics and is based on the self-determination theory and motivational interviewing (MI).MethodsThe 6 steps of the intervention mapping protocol were used to systematically develop MyLifestyleCoach based on the existing effective CT PA promotion intervention I Move. The MyLifestyleCoach intervention consists of 2 modules: I Move, which is aimed at promoting PA, and I Eat, which is aimed at promoting healthy eating. Development of the I Eat module was informed by the previously developed I Move. Both modules were integrated to form the comprehensive MyLifestyleCoach program. Furthermore, I Move was slightly adapted, for example, the new Dutch PA guidelines were implemented. A randomized controlled trial consisting of an intervention condition and waiting list control group will be used to evaluate the effectiveness of the intervention on diet and PA.ResultsSelf-reported measures take place at baseline, 6 months, and 12 months after baseline. Enrollment started in October 2018 and will be completed in June 2020. Data analysis is currently under way, and the first results are expected to be submitted for publication in 2020.ConclusionsMyLifestyleCoach is one of the first interventions to translate and apply self-determination theory and techniques from MI in Web-based computer tailoring for an intervention targeting PA and dietary behavior. Intervention mapping served as a blueprint for the development of this intervention. We will evaluate whether this approach is also successful in promoting eating healthier and increasing PA using an randomized controlled trial by comparing the intervention to a waiting list control condition. The results will provide an insight into the short- and long-term efficacy and will result in recommendations for the implementation and promotion of healthy eating and PA among adults in the Netherlands.Trial RegistrationDutch Trial Register NL7333; https://www.trialregister.nl/trial/7333International Registered Report Identifier (IRRID)DERR1-10.2196/14491

Effectiveness of a web-based computer-tailored intervention promoting physical activity for adults from Quebec City: a randomized controlled trial

ABSTRACT Background The primary objective of this study was to determine the effectiveness of a 3-month web-based computer-tailored intervention on moderate-to-vigorous physical activity (MVPA) in adults. Methods A total of 242 Canadian adults aged between 35 and 70 years were randomized to an experimental group receiving the intervention or a waiting list control group. The fully automated web-based computer-tailored physical activity intervention consists of seven 10- to 15-min sessions over an 8-week period. The theoretical underpinning of the intervention is based on the I-Change Model. Results A repeated-measures ANOVA using a linear mixed model showed a significant ‘group-by-time’ interaction favoring the intervention group in self-reported MVPA (p = .02). The MVPA was similar in both groups at baseline (mean ± SD; 176 ± 13 vs. 172 ± 15 min/week, p = .72) and higher in the intervention than in the control group at a 3-month follow-up (259 ± 21 vs. 201 ± 22 min/week, p = .04). This finding was comparable across women and men (group-by-sex, p = .57) and across participants meeting or not physical activity guidelines at baseline (group-by-baseline physical activity, p = .43). Although engagement to the web-based sessions declined over time, participants completing more web sessions achieved higher self-reported MVPA (p < .05). Conclusion These findings suggest that this intervention is effective in enhancing self-reported MVPA in this adult population in the short term; however, this needs to be confirmed in a larger trial with better engagement to the web-based sessions.

The effect of Active Plus, a computer-tailored physical activity intervention, on cognitive functioning of elderly people with chronic illness(es) \u2013 study protocol for a randomized controlled trial

BackgroundPhysical activity not only is beneficial to a person’s health, but can also have a positive influence on cognitive functioning. However, elderly people with chronic illness(es) often do not meet the physical activity guidelines. Physical activity programs for the elderly exist, but these are often expensive and not easily accessible to the elderly with chronic illness(es). In addition, the beneficial effects of these physical activity programs on cognitive functioning have never been specifically tested in this target group. Hence, this randomized controlled trial aims to test whether Active Plus, a proven effective physical activity intervention, is able to improve the cognitive functioning of elderly people with chronic illness(es) or to slow down cognitive decline. In addition, it studies what kind of activity, intensity, duration and frequency of physical activity most strongly influence cognitive functioning.MethodsA randomized controlled trial is performed, comparing the Active Plus intervention group to a waiting list control group. In total 540 older adults (≥65 years) with at least one chronic illness that limits mobility are recruited from 7 municipalities. Comparable neighborhoods within a municipality are randomly allocated to the intervention or control group. Baseline and follow-up measurements after 6 and 12 months assess cognitive functioning and physical activity behavior, measured both objectively with an accelerometer and subjectively with a self-report questionnaire. Multilevel analyses are conducted to assess effects on cognitive functioning, including analyses on moderation effects for physical activity type, frequency, duration and intensity.DiscussionTo our knowledge this is the first study to investigate effectiveness of a physical activity program on cognitive functioning in elderly people suffering from a broad range of chronic illnesses. If proven effective Active Plus would be a very cost effective intervention not only to increase physical activity, but also to improve cognitive functioning or slow down cognitive decline. Up till now clear evidence is lacking on the kind of physical activity, intensity, duration and frequency needed to achieve cognitive benefits. By measuring both with accelerometers and self-report questionnaires we hope to gain insight in these processes.Trial registrationNederlands Trial Register NL6005; Date of Registration 21-03-2017.

A Web-Based and Print-Delivered Computer-Tailored Physical Activity Intervention for Older Adults: Pretest-Posttest Intervention Study Comparing Delivery Mode Preference and Attrition.

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/2173International Registered Report Identifier (IRRID)RR2-DOI: 10.2196/resprot.8093

The Effectiveness of a Web-Based Computer-Tailored Physical Activity Intervention Using Fitbit Activity Trackers: Randomized Trial.

BackgroundWeb-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.ObjectiveThis study aimed to examine whether the effectiveness of a Web-based computer-tailored intervention could be improved by integrating Fitbit activity trackers.MethodsParticipants 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.ResultsA 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.ConclusionsIntegrating physical activity trackers into a Web-based computer-tailored intervention significantly increased intervention effectiveness.Trial RegistrationAustralian 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)