Computer-tailored Intervention Research Articles

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.

Increasing physical activity using an just-in-time adaptive digital assistant supported by machine learning: A novel approach for hyper-personalised mHealth interventions

ObjectivePhysical inactivity is a leading modifiable cause of death and disease worldwide. Population-based interventions to increase physical activity are needed. Existing automated expert systems (e.g., computer-tailored interventions) have significant limitations that result in low long-term effectiveness. Therefore, innovative approaches are needed. This special communication aims to describe and discuss a novel mHealth intervention approach that proactively offers participants with hyper-personalised intervention content adjusted in real-time. MethodsUsing machine learning approaches, we propose a novel physical activity intervention approach that can learn and adapt in real-time to achieve high levels of personalisation and user engagement, underpinned by a likeable digital assistant. It will consist of three major components: (1) conversations: to increase user’s knowledge on a wide range of activity-related topics underpinned by Natural Language Processing; (2) nudge engine: to provide users with hyper-personalised cues to action underpinned by reinforcement learning (i.e., contextual bandit) and integrating real-time data from activity tracking, GPS, GIS, weather, and user provided data; (3) Q&A: to facilitate users asking any physical activity related questions underpinned by generative AI (e.g., ChatGPT, Bard) for content generation. ResultsThe detailed concept of the proposed physical activity intervention platform demonstrates the practical application of a just-in-time adaptive intervention applying various machine learning techniques to deliver a hyper-personalised physical activity intervention in an engaging way. Compared to traditional interventions, the novel platform is expected to show potential for increased user engagement and long-term effectiveness due to: (1) using new variables to personalise content (e.g., GPS, weather), (2) providing behavioural support at the right time in real-time, (3) implementing an engaging digital assistant and (4) improving the relevance of content through applying machine learning algorithms. ConclusionThe use of machine learning is on the rise in every aspect of today’s society, however few attempts have been undertaken to harness its potential to achieve health behaviour change. By sharing our intervention concept, we contribute to the ongoing dialogue on creating effective methods for promoting health and well-being in the informatics research community. Future research should focus on refining these techniques and evaluating their effectiveness in controlled and real-world circumstances.

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

Cost-effectiveness and cost-utility analyses of a web-based computer-tailored intervention for prevention of binge drinking among Spanish adolescents.

Binge drinking (BD) among adolescents is a public health concern worldwide. This study assessed the cost-effectiveness and cost-utility of a web-based computer-tailored intervention to prevent BD in adolescence. The sample was drawn from a study evaluating the Alerta Alcohol program. The population consisted of adolescents 15 to 19 years of age. Data were recorded at baseline (January to February 2016) and after 4 months (May to June 2017) and were used to estimate costs and health outcomes, as measured by the number of BD occasions and quality-adjusted life years (QALYs). Incremental cost-effectiveness and cost-utility ratios were calculated from National Health Service (NHS) and societal perspectives and for a time horizon of 4 months. A multivariate deterministic sensitivity analysis of best/worst scenarios by subgroups was used to account for uncertainty. The cost of reducing BD occasions by one per month was €16.63 from the NHS perspective, which from the societal perspective resulted in savings of €7986.37. From the societal perspective, the intervention resulted in an incremental cost of €71.05 per QALY gained from the NHS perspective and this was dominant, resulting in savings of €34,126.64 per QALY gained in comparison with the control group. Subgroup analyses showed that the intervention was dominant for girls from both the perspectives and for individuals 17 years or older from the NHS perspective. Computer-tailored feedback is a cost-effective way to reduce BD and increase QALYs among adolescents. However, long-term follow-up is needed to evaluate more fully changes in both BD and health-related quality of life.

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.

An economic evaluation of an online computer-tailored smoking cessation intervention that includes message frame-tailoring: A randomized controlled trial

Evidence of economic evaluations of behaviour change interventions is scarce, but needed to guide policy makers' decision-making. This study economically evaluated 4 versions of an innovative online computer-tailored smoking cessation intervention. The economic evaluation from a societal perspective was embedded in a randomized controlled trial among 532 smokers using a 2 (message frame-tailoring, i.e. how messages are presented: autonomy-supportive vs controlling) x 2 (content-tailoring, i.e. what content is presented: tailored vs. generic) design. Both kinds of tailoring, content-tailoring and message frame-tailoring, were based on a set of questions asked at baseline. Self-reported costs, prolonged smoking abstinence (cost-effectiveness) and quality of life (cost-utility) were assessed during a 6-month-follow-up. For cost-effectiveness analysis, costs per abstinent smoker were calculated. For cost-utility analysis, costs per QALY (i.e. quality-adjusted life year) gained were calculated. A willingness-to-pay (WTP) threshold of €20.000 was used. Bootstrapping and sensitivity analysis were conducted. Cost-effectiveness analysis showed that up to a WTP of €2.000, the combination of message frame- and content-tailoring dominated all study groups. From a WTP of €2.005, the content-tailored group dominated all study groups. Cost-utility analysis revealed that the combination of message frame-tailoring and content-tailoring had the highest probability of being the most efficient study group at all levels of the WTP. The combination of message frame-tailoring and content-tailoring in online smoking cessation programmes seemed to have high potential for cost-effectiveness (smoking abstinence) and cost-utility (quality of life), thus providing good value for money. Yet, when the WTP for each abstinent smoker is high (i.e., €2.005 or higher), the addition of message frame-tailoring might not be worth the effort and content-tailoring only is preferred.

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.

Adding Mobile Elements to Online Physical Activity Interventions Targeted at Adults Aged 50 Years and Older: Protocol for a Systematic Design.

BackgroundPhysical activity (PA) can increase mental and physical health in adults aged 50 years and older. However, it has been shown that PA guidelines are often not met within this population. Therefore, our research group developed 2 computer-tailored intervention programs in the last decade to stimulate PA: Active Plus and I Move. Although these programs were proven effective, positive effects diminished over time and attrition rates were relatively high. To respond to this, we will integrate 3 interactive mobile elements into the existing programs: activity tracker, ecological momentary intervention program, and virtual coach app.ObjectiveThe goal of the research is to define systematic and evidence-based steps for extending our online computer-based PA intervention programs with 3 interactive mobile elements.MethodsComponents often included in other (eHealth) design models were identified as key components and served as a base for the definition of systematic steps: exploration of context, involvement of the target population, prototype and intervention testing, and implementation. Based on these key components, 10 systematic steps were defined. The initial step is a literature search, with the results serving as a base for development of the low-fidelity prototypes in step 2. The pilot phase comprises the 3rd to 6th steps and includes semistructured interviews, pilot tests, and adaptations of the prototypes with intensive involvement of the target population of adults aged 50 years and older, where particular attention will be paid to lower educated persons. The 7th step is an effect evaluation in the form of a randomized controlled trial. During the 8th step, the most effective intervention programs will be selected and reinforced. These reinforced intervention programs will be used during the design of an implementation plan in the 9th step and the subsequent field study in the 10th step.ResultsThe project will be executed from December 2019 to December 2023. During this period, the systematic approach presented will be practically executed according to the methodological procedures described.ConclusionsBased on the 4 identified key components, we were able to design an evidence-based systematic design approach for separately adding 3 mobile elements to our existing online PA intervention programs. The 10 steps are presented as a useful approach to guide future eHealth design studies.International Registered Report Identifier (IRRID)DERR1-10.2196/31677

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

The effects of a web-based computer-tailored diet and physical activity intervention based on self-determination theory and motivational interviewing: A randomized controlled trial

BackgroundAccording to self-determination theory (SDT), autonomous forms of motivation are more likely to result in sustained behavioral changes than controlled forms. Principles of motivational interviewing (MI) can be applied to facilitate more autonomous forms of motivation. This study investigated whether a combined diet and physical activity (PA) web-based computer-tailored intervention based on SDT and MI, called MyLifestyleCoach, was effective in promoting dietary and PA behaviors. MethodsA two-arm randomized controlled trial with 1142 Dutch adults was conducted. The intervention and control group completed questionnaires at baseline, 6, and 12 months from baseline. Only participants in the intervention condition had access to MyLifestyleCoach. The waiting list control condition had access to the intervention after completing the 12-month follow-up questionnaire. A modified food frequency questionnaire was used to measure dietary behaviors (fruit, vegetables, fish, and unhealthy snacks). The Dutch Short Questionnaire to ASsess Health was used to measure the weekly minutes of moderate-to-vigorous PA (MVPA). Usage data, which is operationalized as completed sessions in this study, was objectively assessed by log data. We conducted two-step linear mixed effect models. In the first step, a model consisting of condition, time, potentially confounding variables and a random intercept for participants was tested. In the second step, an interaction term was added to investigate the intervention's (time × condition) and usage (time × opening session and time × completed sessions) effects over time for the dietary and PA outcomes. ResultsThe findings showed no differences between the groups for all four dietary behaviors and the weekly minutes of MVPA at any of the time points. In-depth analyses showed that participants who followed the opening session of the intervention, in which they received personalized feedback on their behaviors, had a stronger increase in fruit consumption at 6 months and 12 months than participants who did not follow the interventions' opening session. Lastly, participants who followed more sessions in the diet module had a stronger increase in fruit and vegetable consumption at 6 months, and a stronger decrease in the consumption frequency of unhealthy snacks at 12 months post-baseline. ConclusionOverall, the intervention was not effective in changing dietary and PA behavior. However, moderation analyses suggest that the intervention is effective in changing dietary behavior for those participants who used the intervention more intensively. Further research should focus on improving intervention use.

Development of a Computer-Tailored Intervention/Decision Aid To Increase Colorectal Cancer Screening in Health Systems.

BackgroundNon-compliance with scheduled colonoscopy is common among patients, especially in underserved populations. High no-show and late cancelation rates result in wasted resources, increased costs, and missed opportunities for colorectal cancer (CRC) screening. Among the barriers to colonoscopy is a lack of knowledge about the benefits, fears, and limited time for patient counseling.MethodologyWe produced a digital video disc and a website program to enhance awareness about CRC screening and address patient barriers in a population with low screening adherence.ResultsPatients can be educated via an interactive computer-tailored intervention with both DVD and web versions. It details the benefits and need for CRC screening, different methods of screening, and addresses patient-related barriers.ConclusionsPatient education is crucial to increase CRC screening among eligible individuals. Because online engagement is affected by attention, interest, and affect, content should be concise but comprehensive.

Use and Appreciation of a Web-Based, Computer-Tailored Diet and Physical Activity Intervention Based on the Self-determination Theory: Evaluation Study of Process and Predictors.

BackgroundeHealth is a promising tool for promoting lifestyle behaviors such as a healthy diet and physical activity (PA). However, making people use interventions is a crucial and challenging problem in eHealth. More insight into use patterns and predicting factors is needed to improve future interventions.ObjectiveThis study aims to examine the use, predictors of use, and appreciation of a web-based, computer-tailored, dietary and PA promotion intervention, MyLifestyleCoach, which is based on the self-determination theory. First, we depict the participants’ flow in the intervention and identify moments when they are likely to discontinue use. Second, we investigate whether demographic, motivational, and program-related characteristics predict the use of several intervention elements. Finally, we report the appreciation scores for the intervention and the participant and program characteristics associated with these scores.MethodsThis study was based on data from web-based self-report questionnaires. Here, objectively assessed intervention use data were analyzed from participants randomized to the intervention condition. Multiple stepwise (logistic) regression analyses were conducted to examine the predictors of intervention use and evaluation scores.ResultsOur findings indicate a low full completion rate for the intervention among those who chose and completed the diet module (49/146, 33.6%), the PA module (2/12, 17%), and both modules (58/273, 21.2%). Several points in the intervention where participants were likely to stop using the intervention were identified. Autonomous and intrinsic motivation toward diet were related to the completion of the initial sessions of the intervention (ie, the opening session in which participants could choose which module to follow and the first session of the diet module). In contrast, controlled motivation was linked to the completion of both modules (initial and follow-up sessions). Appreciation scores were somewhat positive. Appreciation was predicted by several motivational constructs, such as amotivation and basic psychological needs (eg, competence) and program-related features (eg, number of completed sessions).ConclusionsThis study adds meaningful information on the use and appreciation of a web-based, computer-tailored dietary and PA intervention, MyLifestyleCoach. The results indicate that different types of motivations, such as extrinsic and intrinsic motivation, are at play at the points when people are likely to stop using the intervention. The intervention was appreciated fairly well, and several motivational constructs and fulfillment of basic psychological needs were associated with appreciation. Practical implications of these findings have been provided in this study.

Influence of Animation- Versus Text-Based Delivery of a Web-Based Computer-Tailored Smoking Cessation Intervention on User Perceptions

Computer-tailored (CT) digital health interventions have shown to be effective in obtaining behaviour change. Yet, user perceptions of these interventions are often unsatisfactory. Traditional CT interventions rely mostly on text-based feedback messages. A way of presenting feedback messages in a more engaging manner may be the use of narrated animations instead of text. The goal of this study was to assess the effect of manipulating the mode of delivery (animation vs. text) in a smoking cessation intervention on user perceptions among smokers and non-smokers. Smokers and non-smokers (N = 181) were randomized into either the animation or text condition. Participants in the animation condition assessed the intervention as more effective (ηp2 = .035), more trustworthy (ηp2 = .048), more enjoyable (ηp2 = .022), more aesthetic (ηp2 = .233), and more engaging (ηp2 = .043) compared to participants in the text condition. Participants that received animations compared to text messages also reported to actively trust the intervention more (ηp2 = .039) and graded the intervention better (ηp2 = .056). These findings suggest that animation-based interventions are superior to text-based interventions with respect to user perceptions.

Usability, Acceptability, and Safety Analysis of a Computer-Tailored Web-Based Exercise Intervention (ExerciseGuide) for Individuals With Metastatic Prostate Cancer: Multi-Methods Laboratory-Based Study.

BackgroundDigital health interventions such as tailored websites are emerging as valuable tools to provide individualized exercise and behavioral change information for individuals diagnosed with cancer.ObjectiveThe aim of this study is to investigate and iteratively refine the acceptability and usability of a web-based exercise intervention (ExerciseGuide) for men with metastatic prostate cancer and determine how well individuals can replicate the video-based exercise prescription.MethodsA laboratory-based multi-methods design was used, incorporating questionnaires, think-aloud tests, interviews, and movement screening among 11 men aged 63 to 82 years with metastatic prostate cancer. Overall, 9 participants were undergoing androgen deprivation therapy, and 2 were completing chemotherapy. Data were collected in two waves, with changes made for quality improvement after participant 5.ResultsThe intervention’s usability score was deemed moderate overall but improved after modifications (from 60, SD 2.9 to 69.6, SD 2.2 out of 100). Overall, the participants found the intervention acceptable, with scores improving from wave 1 (24.2, SD 1.1 out of 30) to wave 2 (26.3, SD 2.1 out of 30). The personalized multimodal exercise prescription and computer-tailored education were seen as valuable. After wave 1, website navigation videos were added, medical terminology was simplified, and a telehealth component was included after expert real-time telehealth support was requested. Wave 2 changes included the added variety for aerobic exercise modes, reduced computer-tailoring question loads, and improved consistency of style and grammar. Finally, the participants could replicate the resistance exercise videos to a satisfactory level as judged by the movement screen; however, additional technique cueing within the videos is recommended to address safety concerns.ConclusionsThe acceptability and usability of ExerciseGuide were deemed satisfactory. Various problems were identified and resolved. Notably, the participants requested the inclusion of personalized expert support through telehealth. The resistance training algorithms were shown to provide appropriate content safely, and the users could replicate the exercise technique unaided to a satisfactory level. This study has optimized the ExerciseGuide intervention for further investigation in this population.Trial RegistrationAustralian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12618001978257; https://anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12618001978257

Long-Term Effects on Loneliness of a Computer-Tailored Intervention for Older Adults With Chronic Diseases: A Randomized Controlled Trial.

Objectives: This study explores the effects of the Active Plus intervention aiming to decrease loneliness among older adults (>65 years) with chronic diseases. Methods: A randomized controlled trial (RCT) was performed (N = 585; age: M = 74.5 years, SD = 6.4), assessing loneliness at baseline, 6 months and 12 months. Outcome measures in the multilevel linear regression analyses were total, social and emotional loneliness. Results: At 12 months, significant decreases in total (B = −.37, p = .01) and social loneliness (B = −.24, p = .02) were found. Age was a significant moderator for total and social loneliness; however, the intervention was effective only for participants aged 80 years and older. Discussion: The Active Plus intervention showed a significant decrease in total and social loneliness and was especially beneficial for the vulnerable age group of 80 years and older. A more comprehensive tool for measuring social activity and mobility impairments, and using a longer time frame to detect loneliness changes, may form interesting future research.

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