Behavior Change Techniques Implemented in Electronic Lifestyle Activity Monitors: A Systematic Content Analysis

Background: Electronic activity monitors (such as those manufactured by Fitbit, Jawbone, and Nike) improve on standard pedometers by providing automated feedback and interactive behavior change tools via mobile device or personal computer. These monitors are commercially popular and show promise for use in public health interventions. However, little is known about the content of their feedback applications and how individual monitors may differ from one another. Objective: The purpose of this study was to describe the behavior change techniques implemented in commercially available electronic activity monitors. Methods: Electronic activity monitors (N=13) were systematically identified and tested by 3 trained coders for at least 1 week each. All monitors measured lifestyle physical activity and provided feedback via an app (computer or mobile). Coding was based on a hierarchical list of 93 behavior change techniques. Further coding of potentially effective techniques and adherence to theory-based recommendations were based on findings from meta-analyses and meta-regressions in the research literature. Results: All monitors provided tools for self-monitoring, feedback, and environmental change by definition. The next most prevalent techniques (13 out of 13 monitors) were goal-setting and emphasizing discrepancy between current and goal behavior. Review of behavioral goals, social support, social comparison, prompts/cues, rewards, and a focus on past success were found in more than half of the systems. The monitors included a range of 5-10 of 14 total techniques identified from the research literature as potentially effective. Most of the monitors included goal-setting, self-monitoring, and feedback content that closely matched recommendations from social cognitive theory. Conclusions: Electronic activity monitors contain a wide range of behavior change techniques typically used in clinical behavioral interventions. Thus, the monitors may represent a medium by which these interventions could be translated for widespread use. This technology has broad applications for use in clinical, public health, and rehabilitation settings

Impact of medium and long chain triglycerides consumption on appetite and food intake in overweight men

BACKGROUND: Medium chain triglycerides (MCT) enhance thermogenesis and may reduce food intake relative to long chain triglycerides (LCT). The goal of this study was to establish the effects of MCT on appetite and food intake and determine whether differences were due to differences in hormone concentrations. METHODS: Two randomized, crossover studies were conducted in which overweight men consumed 20 g of MCT or corn oil (LCT) at breakfast. Blood samples were obtained over 3 h. In Study 1 (n=10), an ad lib lunch was served after 3 h. In Study 2 (n=7), a pre-load containing 10 g of test oil was given at 3 h and lunch was served 1 h later. Linear mixed model analyses were performed to determine the effects of MCT and LCT oil on change in hormones and metabolites from fasting, adjusting for body weight. Correlations were computed between differences in hormones just before the test meals and differences in intakes after the two oils for Study 1 only. RESULTS: Food intake at the lunch test meal after the MCT pre-load (Study 2) was (mean ± SEM) 532 ± 389 kcal vs. 804 ± 486 kcal after LCT (P < 0.05). MCT consumption resulted in a lower rise in triglycerides (P = 0.014) and glucose (P = 0.066) and a higher rise in peptide YY (P = 0.017) and leptin (P = 0.036) compared to LCT (combined data). Correlations between differences in hormone levels (GLP-1, PYY) and differences in food intake were in the opposite direction to expectations. CONCLUSIONS: MCT consumption reduced food intake acutely but this does not seem to be mediated by changes in GLP-1, PYY, and insulin