Mobile and tablet apps, ubiquitous and pervasive computing, wearable computing and domotics for health.

Objective: Health coaching (HC) may promote healthy behaviors in incoming college students. Participants: 187 undergraduate students (76% female; age 18.6 ± 1.6) were recruited to participate in a peer HC program. Methods: Participants received four HC sessions in eight-weeks to work toward self-selected goals of physical activity (PA), diet, or stress management. PA was assessed using the International Physical Activity Questionnaire Short-Form, diet with the Eating Habits Confidence Survey, and stress with the Perceived Stress Scale. Results: Repeated measures ANOVAs investigated lifestyle behavior changes in 130 participants. Significant effects of time were reported, with a 39.6% gain in PA, 9.9% increase in dietary habit, and 16.3% decline in stress levels with moderate to large effect sizes (η_p²: 0.07-0.17; p< 0.01). Conclusion: The peer HC model promoted healthy lifestyles in college students. Additional research is needed to understand the effects of HC specifically for each goal, and student reactions to peer-led HC.

Objective: This study investigated differences in stress, anxiety, and social support between collegiate student-athletes and nonathletes during the COVID-19 pandemic. Participants: College students enrolled at a NCAA Division III private liberal arts college in the Midwest. Methods: Participants (n = 58) completed a series of surveys each month for 4 months that included the Generalized Anxiety Disorder Questionnaire, Perceived Stress Scale Questionnaire, and Multidimensional Scale of Perceived Social Support Questionnaire. Results: There were significant main effects of time for stress and social support across the 4 months (p < 0.05), but not for anxiety. There was a significant difference in anxiety levels between athletes and nonathletes (p < 0.01), but not for social support or stress (p > 0.05). Conclusions: Nonathletes maintained support networks, or found alternate outlets of support, in addition to coping with anxiety and stress levels when compared to athletes.

A practicum course was designed to offer undergraduate students the opportunity to learn motivational interviewing (MI), a skill commonly used in health coaching (HC). The 16-week course included online video lectures, in-class activities, experiential training, and supervised practicum experiences. This study evaluated the process, impact, and outcomes of the course (n = 46; 74% female; age 21.9 ± 3.7). Surveys were administered pre- and post-training to assess participant satisfaction of the course and the impact of training on communication using 7-point Likert scales. Recorded MI conversations were obtained after initial training (Week 8) and again following the supervised practicum (Week 16) to assess the fidelity outcomes (n = 23). Recordings were independently coded using the Motivational Interviewing Treatment Integrity (MITI) Coding Manual 4.2.1, with inter-rater agreement calculated between two trained coders. Paired samples t-tests and post-hoc analyses examined differences in pre-post fidelity levels, followed by Cohen’s d effect sizes. Survey results demonstrated that students felt comfortable (5.0 ± 0.7) and confident (4.8 ± 0.6) using MI. Inter-rater reliability among coders was high (ICC = 0.92 [95% CI: 0.90–0.93]). MITI results showed that 97.5% of coaches met proficiency for technical and 90.0% for relational at week 8. At week 16, all trainees met proficiency levels for both technical and global ratings, with t-tests reporting improvements in fidelity scores. Behavior counts were much lower, with the majority of participants not meeting proficiency at either timepoint. Extended real-world practice enhanced MI fidelity levels, and trained students reported high likelihood of continued skill use 1 year after training completion.

BACKGROUND While widely used and endorsed, there is limited evidence supporting the benefits of activity trackers for increasing physical activity; these devices may be more effective when combined with additional strategies that promote sustained behavior change like motivational interviewing (MI) and habit development. OBJECTIVE This study aims to determine the utility of wearable activity trackers alone or in combination with these behavior change strategies for promoting improvements in active and sedentary behaviors. METHODS A sample of 91 adults (48/91 female, 53%) was randomized to receive a Fitbit Charge alone or in combination with MI and habit education for 12 weeks. Active and sedentary behaviors were assessed pre and post using research-grade activity monitors (ActiGraph and activPAL), and the development of habits surrounding the use of the trackers was assessed postintervention with the Self-Reported Habit Index. During the intervention, Fitbit wear time and activity levels were monitored with the activity trackers. Linear regression analyses were used to determine the influence of the trial on outcomes of physical activity and sedentary time. The influence of habits was examined using correlation coefficients relating habits of tracker use (wearing the tracker and checking data on the tracker and associated app) to Fitbit wear time and activity levels during the intervention and at follow-up. RESULTS Regression analyses revealed no significant differences by group in any of the primary outcomes (all P>.05). However, personal characteristics, including lower baseline activity levels (beta=–.49, P=.01) and lack of previous experience with pedometers (beta=–.23, P=.03) were predictive of greater improvements in moderate and vigorous physical activity. Furthermore, for individuals with higher activity levels at the baseline, MI and habit education were more effective for maintaining these activity levels when compared with receiving a Fitbit alone (eg, small increase of ~48 steps/day, d=0.01, vs large decrease of ~1830 steps/day, d=0.95). Finally, habit development was significantly related to steps/day during (r=.30, P=.004) and following the intervention (r=.27, P=.03). CONCLUSIONS This study suggests that activity trackers may have beneficial effects on physical activity in healthy adults, but benefits vary based on individual factors. Furthermore, this study highlights the importance of habit development surrounding the wear and use of activity trackers and the associated software to promote increases in physical activity. CLINICALTRIAL ClinicalTrials.gov NCT03837366; https://clinicaltrials.gov/ct2/show/NCT03837366

Background: Firefighters experience sudden on-duty tasks that challenge the cardiovascular system, and with increased prevalence of poor fitness, lead to risk of adverse cardiac events. This study investigated why firefighters may be inactive when occupational performance relies on fitness. Methods: Perceptions of exercise behaviors in career and volunteer firefighters were compared using the Health Belief Model Scale for Exercise (HBSE-E). A MANCOVA investigated differences in model constructs between groups. Results: The survey was completed by 138 participants. There were significantly higher perceived severity (p = 0.009) and self-efficacy levels (p < 0.001) in career firefighters, while volunteer firefighters had significantly higher objective (p < 0.001) and subjective barriers (p = 0.020). Conclusions: Utilizing the HBMS-E may help departments know what barriers they need to focus on when developing a wellness initiative.