Specific, but not General, Technology Acceptance Predicts Mobile Weight Loss Program Outcomes

Background: Smartphone apps are capable of facilitating weight loss. However, many individuals fail to engage with these programs and thus experience limited weight loss success. Failure to engage in digital programs could be driven by negative attitudes toward technology generally and/or limited acceptability of the technology utilized by a specific program. In the present study, we tested the hypothesis that two measures of technology attitudes (program-specific and general) would predict weight loss among participants in a mobile behavioral weight loss program (mBWL). Methods: Adults (N = 119; BMI > 25) completed a 10-week-long mBWL consisting of dietary psychoeducation, tracking, and goals plus just-in-time delivery of messages to prevent dietary lapses. Assessments were a 10-item general technology attitudes questionnaire (TAQ) at baseline, and the Technology Acceptance Model Scales (TAMS) to assess satisfaction, perceived usefulness, and usability of the study app at post-treatment. Results: Linear regression analyses indicated that, when controlling for baseline BMI, percent weight loss was associated with TAMS scores (ß = .30, p = .006), but not the TAQ (ß = -.24, p = .81). In fact, those with low TAMS score had only a 38% chance of reaching the 3% weight loss benchmark (X2 = 9.27, p = .002), whereas those with low TAQ and high TAQ were equally likely (~50%) to reach the benchmark (X2 = 0.31, p = .86). Conclusions: Higher acceptability of the study technology, but not a positive attitude about technology in general, resulted in greater success with an app-based self-directed weight loss attempt. A potential implication of these findings is that individuals with a more negative attitude toward technology can still benefit from mBWL if the study technology is well designed and acceptable. Although it was not possible to verify that weight losses were attributable to study-specific technology attitudes, this can be addressed in future longitudinal studies by assessing acceptance at multiple time points.