Motivational technologies to promote weight loss--from internet to gadgets

The change in eating behaviors in a Web-based weight loss program: a longitudinal analysis of study completers

Background

Eating behaviors are essential components in weight loss programs, but limited research has explored eating behaviors in Web-based weight loss programs.

Objectives

The aim was to evaluate an interactive Web-based weight loss program on eating behaviors using the 18-item Three-Factor Eating Questionnaire Revised (TFEQ-R18) which measures uncontrolled eating, emotional eating, and cognitive restrained eating. Our Web-based weight loss program is comprised of information about healthy lifestyle choices, weekly chats with experts, social networking features, databases for recipe searches, and features allowing members to self-report and track their weight, physical activity, and dietary intake on the website.

Methods

On registering for the weight loss program, 23,333 members agreed to take part in the research study. The participants were then asked to complete the TFEQ-R18 questionnaire at baseline and after 3 and 6 months of participation. All data collection was conducted online, with no face-to-face contact. To study changes in TFEQ-R18 eating behaviors we restricted our study to those members who completed all 3 TFEQ-R18 questionnaires. These participants were defined as “completers” and the remaining as “noncompleters.” The relationships between sex, change in eating behaviors, and total weight loss were studied using repeated measures ANOVA and Pearson correlation coefficient.

Results

In total, 22,800 individuals participated (females: 19,065/22,800, 83.62%; mean age 39.6, SD 11.4 years; BMI 29.0 kg/m²; males: 3735/22,800, 16.38%; mean age 43.2, SD 11.7 years; BMI 30.8 kg/m²). Noncompleters (n=22,180) were younger and reported a lower score of uncontrolled eating and a higher score of cognitive restrained eating. Over time, completers (n=620) decreased their uncontrolled eating score (from 56.3 to 32.0; P<.001) and increased their cognitive restrained eating (from 50.6 to 62.9; P<.001). Males decreased their emotional eating (from 57.2 to 35.9; P<.001), but no significant change was found among females. The baseline cognitive restrained eating score was significantly and positively associated with weight loss for completers in both men (P=.02) and women (P=.002).

Conclusions

To our knowledge, this is the largest TFEQ sample that has been documented. This Web-based weight loss intervention suggests that eating behaviors (cognitive restrained eating, uncontrolled eating, and emotional eating) measured by TFEQ-R18 were significantly changed during 6 months of participation. Our findings indicate differences in eating behaviors with respect to sex, but should be interpreted with caution because attrition was high.

Integrating user perspectives into the development of a web-based weight management intervention

The objective of this study was to adapt the design of our weight management intervention to the needs, expectations and capabilities of potential users. In study 1, we interviewed 25 people about their experiences of weight management. The findings of these interviews were combined with findings from existing theory and research in a process of 'intervention planning' that informed the design of the intervention. Study 2 comprised in-depth think-aloud studies with a further 16 people interested in using a web-based intervention to manage their weight, in order to elicit reactions to the intervention techniques and materials. In study 1, overly intrusive and restrictive aspects of eating self-regulation were commonly cited reasons for failure to maintain weight management long-term. We therefore designed an intervention with a more flexible approach to autonomous self-regulation. This approach was broadly welcomed in study 2, but there were indications that some participants might have difficulty effectively implementing self-regulation techniques independently. A flexible and autonomous approach to changing eating habits is attractive to potential intervention users but may be difficult for some users to implement successfully.

Managing obesity--from childhood and onwards

It is unclear whether the obesity epidemic has come to a halt. Perhaps the incidence is declining, at least in pre-school children. However, the obesity rate is higher than ever before. Prevention is a priority, especially in children, but has not been very successful to date. Treatment has basically offered the same tools for decades. The recent development of obesity pharmacotherapy has regressed with--in most countries--only one drug of modest effect available. Bariatric surgery has therefore been considered one of the few solutions in the adult setting and is gaining increasing attention as a treatment option, even in pediatric extreme obesity. In some countries, government action for prevention has been taken, but too often resources have not been set aside. This review addresses new and old strategies to manage obesity--from childhood and onwards.

The effect of computers for weight loss: a systematic review and meta-analysis of randomized trials

BACKGROUND

The use of computers to deliver education and support strategies has been shown to be effective in a variety of conditions. We conducted a systematic review and meta-analysis to evaluate the impact of computer-based technology on interventions for reducing weight.

METHODS

We searched MEDLINE, CENTRAL, CINAHL, PsycINFO, Google Scholar and ClinicalTrials.gov (all updated through June 2010) for randomized controlled trials evaluating the effect of computer-based technology on education or support interventions aimed at reducing weight in overweight or obese adults. We calculated weighted mean differences (WMD) and 95% confidence intervals (CI) using random effects models.

RESULTS

Eleven trials with 13 comparisons met inclusion criteria. Based on six comparisons, subjects who received a computer-based intervention as an addition to the standard intervention given to both groups lost significantly more weight (WMD -1.48 kg, 95% CI -2.52, -0.43). Conversely, based on six comparisons, subjects for whom computer-based technology was substituted to deliver an identical or highly comparable intervention to that of the control group lost significantly less weight (WMD 1.47 kg, 95% CI 0.13, 2.81). Significantly different weight loss seen in "addition" comparisons with less than six months of follow-up (WMD -1.95 kg, 95% CI -3.50, -0.40, two comparisons) was not seen in comparisons with longer follow-up (-1.08 kg, 95% CI -2.50, 0.34, four comparisons). Analyses based on quality and publication date did not substantially differ.

CONCLUSIONS

While the addition of computer-based technology to weight loss interventions led to statistically greater weight loss, the magnitude (<1.5 kg) was small and unsustained.