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

BackgroundComputer-tailored eHealth interventions to improve health behavior have been demonstrated to be effective and cost-effective if they are used as recommended. However, different subgroups may use the Internet differently, which might also affect intervention use and effectiveness. To date, there is little research available depicting whether adherence to intervention recommendations differs according to personal characteristics.ObjectiveThe aim was to assess which personal characteristics are associated with using an eHealth intervention as recommended.MethodsA randomized controlled trial was conducted among a sample of the adult Dutch population (N=1638) testing an intervention aimed at improving 5 healthy lifestyle behaviors: increasing fruit and vegetable consumption, increasing physical activity, reducing alcohol intake, and promoting smoking cessation. Participants were asked to participate in those specific online modules for which they did not meet the national guideline(s) for the respective behavior(s). Participants who started with fewer than the recommended number of modules of the intervention were defined as users who did not follow the intervention recommendation.ResultsThe fewer modules recommended to participants, the better participants adhered to the intervention modules. Following the intervention recommendation increased when participants were older (χ2 1=39.8, P<.001), female (χ2 1=15.8, P<.001), unemployed (χ2 1=7.9, P=.003), ill (χ2 1=4.5, P=.02), or in a relationship (χ2 1=7.8, P=.003). No significant relevant differences were found between groups with different levels of education, incomes, or quality of life.ConclusionOur findings indicate that eHealth interventions were used differently by subgroups. The more frequent as-recommended intervention use by unemployed, older, and ill participants may be an indication that these eHealth interventions are attractive to people with a greater need for health care information. Further research is necessary to make intervention use more attractive for people with unhealthy lifestyle patterns.

BackgroundWeb-based tailored interventions provide users with information that is adapted to their individual characteristics and needs. Randomized controlled trials assessing the effects of tailored alcohol self-help programs among adults are scarce. Furthermore, it is a challenge to develop programs that can hold respondents’ attention in online interventions.ObjectiveTo assess whether a 3-session, Web-based tailored intervention is effective in reducing alcohol intake in high-risk adult drinkers and to compare 2 computer-tailoring feedback strategies (alternating vs summative) on behavioral change, dropout, and appreciation of the program.MethodsA single-blind randomized controlled trial was conducted with an experimental group and a control group (N=448) in Germany in 2010-2011. Follow-up took place after 6 months. Drinking behavior, health status, motivational determinants, and demographics were assessed among participants recruited via an online access panel. The experimental group was divided into 2 subgroups. In the alternating condition (n=132), the tailored feedback was split into a series of messages discussing individual topics offered while the respondent was filling out the program. Participants in the summative condition (n=181) received all advice at once after having answered all questions. The actual texts were identical for both conditions. The control group (n=135) only filled in 3 questionnaires. To identify intervention effects, logistic and linear regression analyses were conducted among complete cases (n=197) and after using multiple imputation.ResultsAmong the complete cases (response rate: 197/448, 44.0%) who did not comply with the German national guideline for low-risk drinking at baseline, 21.1% of respondents in the experimental group complied after 6 months compared with 5.8% in the control group (effect size=0.42; OR 2.65, 95% CI 1.14-6.16, P=.02). The experimental group decreased by 3.9 drinks per week compared to 0.4 drinks per week in the control group, but this did not reach statistical significance (effect size=0.26; beta=−0.12, 95% CI −7.96 to 0.03, P=.05). Intention-to-treat analyses also indicated no statistically significant effect. Separate analyses of the 2 experimental subgroups showed no differences in intervention effects. The dropout rate during the first visit to the intervention website was significantly lower in the alternating condition than in the summative condition (OR 0.23, 95% CI 0.08-0.60, P=.003). Program appreciation was comparable for the 2 experimental groups.ConclusionsComplete case analyses revealed that Web-based tailored feedback can be an effective way to reduce alcohol intake among adults. However, this effect was not confirmed when applying multiple imputations. There was no indication that one of the tailoring strategies was more effective in lowering alcohol intake. Nevertheless, the lower attrition rates we found during the first visit suggest that the version of the intervention with alternating questions and advice may be preferred.Trial Reg...

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Background: In order to improve the transition from an intention to a change in health behaviour, action planning is a frequently used behavioural change method. The quality of action plans in terms of instrumentality and specificity is important in terms of supporting a successful change in health behaviour. Until now, little has been known about the predictors of action plan generation and the predictors of high quality action plans and, therefore, the current study investigates these predictors.