BackgroundSelf-help interventions without professional contact to curb adult problem drinking in the community are increasingly being delivered via the Internet.ObjectiveThe objective of this meta-analysis was to assess the overall effectiveness of these eHealth interventions.MethodsIn all, 9 randomized controlled trials (RCTs), all from high-income countries, with 9 comparison conditions and a total of 1553 participants, were identified, and their combined effectiveness in reducing alcohol consumption was evaluated by means of a meta-analysis.ResultsAn overall medium effect size (g = 0.44, 95% CI 0.17-0.71, random effect model) was found for the 9 studies, all of which compared no-contact interventions to control conditions. The medium effect was maintained (g = 0.39; 95% CI 0.23-0.57, random effect model) after exclusion of two outliers. Type of control group, treatment location, type of analysis, and sample size did not have differential impacts on treatment outcome. A significant difference (P = .04) emerged between single-session personalized normative feedback interventions (g = 0.27, 95% CI 0.11-0.43) and more extended e- self-help (g = 0.61, 95% CI 0.33-0.90).ConclusionE-self-help interventions without professional contact are effective in curbing adult problem drinking in high-income countries. In view of the easy scalability and low dissemination costs of such interventions, we recommend exploration of whether these could broaden the scope of effective public health interventions in low- and middle-income countries as well.

BackgroundFace-to-face brief interventions for problem drinking are effective, but they have found limited implementation in routine care and the community. Internet-based interventions could overcome this treatment gap. We investigated effectiveness and moderators of treatment outcomes in internet-based interventions for adult problem drinking (iAIs).Methods and findingsSystematic searches were performed in medical and psychological databases to 31 December 2016. A one-stage individual patient data meta-analysis (IPDMA) was conducted with a linear mixed model complete-case approach, using baseline and first follow-up data. The primary outcome measure was mean weekly alcohol consumption in standard units (SUs, 10 grams of ethanol). Secondary outcome was treatment response (TR), defined as less than 14/21 SUs for women/men weekly. Putative participant, intervention, and study moderators were included. Robustness was verified in three sensitivity analyses: a two-stage IPDMA, a one-stage IPDMA using multiple imputation, and a missing-not-at-random (MNAR) analysis. We obtained baseline data for 14,198 adult participants (19 randomised controlled trials [RCTs], mean age 40.7 [SD = 13.2], 47.6% women). Their baseline mean weekly alcohol consumption was 38.1 SUs (SD = 26.9). Most were regular problem drinkers (80.1%, SUs 44.7, SD = 26.4) and 19.9% (SUs 11.9, SD = 4.1) were binge-only drinkers. About one third were heavy drinkers, meaning that women/men consumed, respectively, more than 35/50 SUs of alcohol at baseline (34.2%, SUs 65.9, SD = 27.1). Post-intervention data were available for 8,095 participants. Compared with controls, iAI participants showed a greater mean weekly decrease at follow-up of 5.02 SUs (95% CI −7.57 to −2.48, p < 0.001) and a higher rate of TR (odds ratio [OR] 2.20, 95% CI 1.63–2.95, p < 0.001, number needed to treat [NNT] = 4.15, 95% CI 3.06–6.62). Persons above age 55 showed higher TR than their younger counterparts (OR = 1.66, 95% CI 1.21–2.27, p = 0.002). Drinking profiles were not significantly associated with treatment outcomes. Human-supported interventions were superior to fully automated ones on both outcome measures (comparative reduction: −6.78 SUs, 95% CI −12.11 to −1.45, p = 0.013; TR: OR = 2.23, 95% CI 1.22–4.08, p = 0.009). Participants treated in iAIs based on personalised normative feedback (PNF) alone were significantly less likely to sustain low-risk drinking at follow-up than those in iAIs based on integrated therapeutic principles (OR = 0.52, 95% CI 0.29–0.93, p = 0.029). The use of waitlist control in RCTs was associated with significantly better treatment outcomes than the use of other types of control (comparative reduction: −9.27 SUs, 95% CI −13.97 to −4.57, p < 0.001; TR: OR = 3.74, 95% CI 2.13–6.53, p < 0.001). The overall quality of the RCTs was high; a major limitation included high study dropout (43%). Sensitivity analyses confirmed the robustness of our primary analyses.ConclusionTo our knowledge, this is the first IPDMA on internet-based interventions that has show...

Overweight is becoming more common in children, but we know nearly nothing about the eating behavior of overweight children. Learning theory predicts that overeating follows from learned associations between the smell and taste of palatable food on the one hand and intake on the other hand. It was tested whether overweight children overeat after confrontation to these cues. They indeed failed to regulate food intake after both the exposure to the intense smell of tasty food (without eating it) and after eating a small preload of appetizing food, whereas normal-weight children decreased their intake after both cues. Overweight children are thus more vulnerable to triggers of overeating. Their overeating was not related to psychological factors like mood, body esteem, and a restrained eating style, but it was related to cue-elicited salivation flow. Apart from supporting the cue reactivity model of overeating, the data point to an interesting satiety phenomenon in normal eaters after prolonged and intense smelling palatable food without eating it.

BackgroundDepression is a worldwide problem warranting global solutions to tackle it. Enhancing well-being has benefits in its own right and could be a good strategy for preventing depression. Providing well-being interventions via the Internet may have synergetic effects.ObjectivePsyfit (“mental fitness online”) is a fully automated self-help intervention to improve well-being based on positive psychology. This study examines the clinical effects of this intervention.MethodsWe conducted a 2-armed randomized controlled trial that compared the effects of access to Psyfit for 2 months (n=143) to a waiting-list control condition (n=141). Mild to moderately depressed adults in the general population seeking self-help were recruited. Primary outcome was well-being measured by Mental Health Continuum-Short Form (MHC-SF) and WHO Well-being Index (WHO-5); secondary outcomes were depressive symptoms, anxiety, vitality, and general health measured by Center for Epidemiological Studies Depression Scale (CES-D), Hospital Anxiety and Depression Scale Anxiety subscale (HADS-A), and Medical Outcomes Study-Short Form (MOS-SF) vitality and general health subscales, respectively. Online measurements were taken at baseline, 2 months, and 6 months after baseline.ResultsThe dropout rate was 37.8% in the Psyfit group and 22.7% in the control group. At 2-month follow-up, Psyfit tended to be more effective in enhancing well-being (nonsignificantly for MHC-SF: Cohen’s d=0.27, P=.06; significantly for WHO-5: Cohen’s d=0.31, P=.01), compared to the waiting-list control group. For the secondary outcomes, small but significant effects were found for general health (Cohen’s d=0.14, P=.01), vitality (d=0.22, P=.02), anxiety symptoms (Cohen’s d=0.32, P=.001), and depressive symptoms (Cohen’s d=0.36, P=.02). At 6-month follow-up, there were no significant effects on well-being (MHC-SF: Cohen’s d=0.01, P=.90; WHO-5: Cohen’s d=0.26, P=.11), whereas depressive symptoms (Cohen’s d=0.35, P=.02) and anxiety symptoms (Cohen’s d=0.35, P=.001) were still significantly reduced compared to the control group. There was no clear dose–response relationship between adherence and effectiveness, although some significant differences appeared across most outcomes in favor of those completing at least 1 lesson in the intervention.ConclusionsThis study shows that an online well-being intervention can effectively enhance well-being (at least in the short-term and for 1 well-being measure) and can help to reduce anxiety and depression symptoms. Further research should focus on increasing adherence and motivation, reaching and serving lower-educated people, and widening the target group to include people with different levels of depressive symptoms.Trial RegistrationNetherlands Trial Register (NTR) number: NTR2126; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=2126 (archived by WebCite at http://www.webcitation.org/6IIiVrLcO).

BackgroundPrevention of weight gain has been suggested as an important strategy in the prevention of obesity and people who are overweight are a specifically important group to target. Currently there is a lack of weight gain prevention interventions that can reach large numbers of people. Therefore, we developed an Internet-delivered, computer-tailored weight management intervention for overweight adults. The focus of the intervention was on making small (100 kcal per day), but sustained changes in dietary intake (DI) or physical activity (PA) behaviors in order to maintain current weight or achieve modest weight loss. Self-regulation theory was used as the basis of the intervention.ObjectiveThis study aims to evaluate the efficacy of the computer-tailored intervention in weight-related anthropometric measures (Body Mass Index, skin folds and waist circumference) and energy balance-related behaviors (physical activity; intake of fat, snacks and sweetened drinks) in a randomized controlled trial.MethodsThe tailored intervention (TI) was compared to a generic information website (GI). Participants were 539 overweight adults (mean age 47.8 years, mean Body Mass Index (BMI) 28.04, 30.9% male, 10.7% low educated) who where recruited among the general population and among employees from large companies by means of advertisements and flyers. Anthropometric measurements were measured by trained research assistants at baseline and 6-months post-intervention. DI and PA behaviors were assessed at baseline, 1-month and 6-month post-intervention, using self-reported questionnaires.ResultsRepeated measurement analyses showed that BMI remained stable over time and that there were no statistically significant differences between the study groups (BMI: TI=28.09, GI=27.61, P=.09). Similar results were found for waist circumference and skin fold thickness. Amount of physical activity increased and intake of fat, snacks and sweetened drinks decreased during the course of the study, but there were no differences between the study groups (eg, fat intake: TI=15.4, GI=15.9, P=.74). The first module of the tailored intervention was visited by almost all participants, but only 15% completed all four modules of the tailored intervention, while 46% completed the three modules of the general information intervention. The tailored intervention was considered more personally relevant (TI=3.20, GI=2.83, P=.001), containing more new information (TI=3.11, GI=2.73, P=.003) and having longer texts (TI=3.20, GI=3.07, P=.01), while there were no group differences on other process measures such as attractiveness and comprehensibility of the information (eg, attractive design: TI=3.22, GI=3.16, P=.58).ConclusionsThe online, computer-tailored weight management intervention resulted in changes in the desired direction, such as stabilization of weight and improvements in dietary intake, but the intervention was not more effective in preventing weight gain or modifying dietary and physical activity behaviors than generic information. A possible reason for...