The Doctor Will "Friend" You Now: A Qualitative Study on Adolescents' Preferences for Weight Management App Features

Adolescent cancer prevention in rural, pediatric primary care settings in the United States: A scoping review

Adolescence is a critical period for establishing habits and engaging in health behaviors to prevent future cancers. Rural areas tend to have higher rates of cancer-related morbidity and mortality as well as higher rates of cancer-risk factors among adolescents. Rural primary care clinicians are well-positioned to address these risk factors. Our goal was to identify existing literature on adolescent cancer prevention in rural primary care and to classify key barriers and facilitators to implementing interventions in such settings. We searched the following databases: Ovid MEDLINE®; Ovid APA PsycInfo; Cochrane Library; CINAHL; and Scopus. Studies were included if they reported on provider and/or clinic-level interventions in rural primary care clinics addressing one of these four behaviors (obesity, tobacco, sun exposure, HPV vaccination) among adolescent populations. We identified 3,403 unique studies and 24 met inclusion criteria for this review. 16 addressed obesity, 6 addressed HPV vaccination, 1 addressed skin cancer, and 1 addressed multiple behaviors including obesity and tobacco use. 10 studies were either non-randomized experimental designs (n = 8) or randomized controlled trials (n = 2). The remaining were observational or descriptive research. We found a dearth of studies addressing implementation of adolescent cancer prevention interventions in rural primary care settings. Priorities to address this should include further research and increased funding to support EBI adaptation and implementation in rural clinics to reduce urban-rural cancer inequities.

Dietary Behavior Assessments in Children-A Mixed-Method Research Exploring the Perspective of Pediatric Dieticians on Innovative Technologies

Background

Assessing dietary intake and eating behavior in children is challenging, owing to children's undeveloped food knowledge and perception of portion sizes. Additionally, caregivers cannot always provide complete surrogate information. Consequently, validated dietary behavior assessment methods for children are limited, but technological innovations offer opportunities for the development of new tools. One of the first steps in the developmental process of a newly developed pediatric dietary assessment tool includes an alignment of the needs and preferences of pediatric dieticians (PDs) as potential users.

Objectives

To explore opinions of Dutch PDs about traditional dietary behavior assessment methods for children and potential technological innovations to replace or support traditional methods.

Methods

Ten PDs participated in semistructured interviews (total of 7.5 h) based on 2 theoretical frameworks, and data saturation was reached after the seventh interview. Interview transcripts were inductively coded in an iterative process, and overarching themes and domains were identified. Interview data were then used as input for an extensive online survey completed by 31 PDs who were not involved in the initial interview rounds.

Results

PDs discussed their perspective on dietary behavior assessments in 4 domains: traditional methods, technological methods, future methods, and external influences on these methods. Generally, PDs felt that traditional methods supported them in reaching their desired goals. However, the time needed to obtain a comprehensive overview of dietary intake behavior and the reliability of conventional methods were mentioned as limitations. For future technologies, PDs mention the ease of use and engaging in children as opportunities.

Conclusions

PDs have a positive attitude toward the use of technology for dietary behavior assessments. Further development of assessment technologies should be tailored to the needs of children in different care situations and age categories to increase its usability among children, their caregivers, and dietician. Curr Dev Nutr 2023;xx:xx.

An addiction-based digital weight loss intervention: A multi-centre randomized controlled trial

OBJECTIVE

This randomized clinical trial tested the effectiveness of an addiction-based digital weight-loss intervention, focusing on withdrawal/abstinence from self-identified problem foods, snacking and excessive amounts at meals, and discomfort displacement, with and without coaching, compared to an in-person, multi-disciplinary, care model among adolescents with obesity. We hypothesized that the digital intervention with coaching would yield greater weight loss and lower delivery burden than the standard clinical arm, and greater participant engagement than the digital arm without coaching.

METHODS

Adolescents were randomized to app intervention, with or without coaching, or in-person multidisciplinary obesity intervention for 6 months. The primary outcome was change in %BMIp95 at weeks 12 and 24. A mixed-effects linear regression model was used to assess the association between change in %BMIp95 and intervention arm. We were also interested in assessing delivery burden, participant engagement and evaluating the relationships between weight change and demographic characteristics, mood, executive function and eating behaviours.

RESULTS

All adolescents (n = 161; BMI ≥95th%, age 16 ± 2.5 year; 47% Hispanic, 65% female, 59% publicly insured) lost weight over 24-weeks (-1.29%, [-1.82, -0.76], p < 0.0001), with no significant weight loss difference between groups (p = 0.3). Girls lost more weight than boys, whereas binge eating behaviour at baseline was associated with increase in %BMIp95 when controlling for other covariates. There was no association between ethnicity, mood, timing of intervention in relation to the pandemic, or executive function and change in %BMIp95 .

CONCLUSIONS

Contrary with our hypothesis, our results showed no difference in the change in BMI status between treatment arms. Since efficacy of this digital intervention was not inferior to in-person, multi-disciplinary care, this could offer a reasonable weight management option for clinicians, based on youth and family specific characteristics, such as accessibility, resources, and communication styles.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT035008353.

Use of Machine Learning to Mine User-Generated Content From Mobile Health Apps for Weight Loss to Assess Factors Correlated With User Satisfaction

IMPORTANCE

The effectiveness of mobile health (mHealth) apps for reducing obesity is not ideal in daily life. Therefore, it would be useful to explore factors associated with user satisfaction with weight loss apps. Currently, research on these factors from the perspective of user-generated content is lacking.

OBJECTIVE

To mine the themes and topics frequently discussed in user-generated content in mHealth apps for weight loss, explore correlations of the topics with user satisfaction and dissatisfaction, and assess whether these correlations were asymmetric.

DESIGN, SETTING, AND PARTICIPANTS

In this population-based cross-sectional study, unsupervised machine learning was used to identify themes and topics in online discussions generated between January 1, 2019, and May 20, 2021, by Chinese users of mHealth apps for weight loss.

MAIN OUTCOMES AND MEASURES

Based on the 2-factor theory, a tobit regression model was used to explore the correlation of various app discussion topics with user satisfaction and dissatisfaction. Differences of the coefficients in models of positive rating deviation (PD) and negative rating deviation (ND), defined as the difference between the users' rating of the app and the app's comprehensive rating in the app stores, were analyzed by the Wald test.

RESULTS

In total, 191 619 reviews and ratings from unique usernames were collected for 2139 weight loss apps; 86 423 reviews (45.1%) from 339 apps (15.8%) were included in the study. Most users (65 249 [75.5%]) were satisfied with the mHealth app. Eighteen topics were identified and summarized into 9 themes. Nine topics had significant positive correlations with the PD of user satisfaction, and 6 had significant negative correlations. The factor with the strongest positive correlation with the PD was celebrity effect (β = 0.307; 95% CI, 0.290-0.323), and the factor with the weakest correlation was economic cost (β = -0.426; 95% CI, -0.447 to -0.406). Nine topics had significant positive correlations with the ND of user satisfaction, whereas 7 topics had significant negative correlations. The factor with the strongest positive correlation with the ND was fitness effect (β = 1.369; 95% CI, 1.283-1.455), and the factor with the strongest negative correlation was economic cost (β = -2.813; 95% CI, -2.875 to -2.751). There were significant differences in the PD and ND of user satisfaction. Nine motivation factors (ie, value-added attributes) and 7 hygiene factors (ie, user-expected attributes) for mHealth apps were identified.

CONCLUSIONS AND RELEVANCE

In this cross-sectional study, 16 factors had asymmetric correlations with user satisfaction and dissatisfaction with weight loss apps; 7 were related to basic expected attributes of the apps and 9 to value-added attributes. By distinguishing between expected and value-added factors, the use of weight loss apps may be improved.