Multicomponent (bio)markers for obesity risk prediction: a scoping review protocol.

INTRODUCTION: Despite international efforts, the number of individuals struggling with obesity is still increasing. An important aspect of obesity prevention relates to identifying individuals at risk at early stage, allowing for timely risk stratification and initiation of countermeasures. However, obesity is complex and multifactorial by nature, and one isolated (bio)marker is unlikely to enable an optimal risk stratification and prognosis for the individual; rather, a combined set is required. Such a multicomponent interpretation would integrate biomarkers from various domains, such as classical markers (eg, anthropometrics, blood lipids), multiomics (eg, genetics, proteomics, metabolomics), lifestyle and behavioural attributes (eg, diet, physical activity, sleep patterns), psychological traits (mental health status such as depression) and additional host factors (eg, gut microbiota diversity), also by means of advanced interpretation tools such as machine learning. In this paper, we will present a protocol that will be employed for a scoping review that attempts to summarise and map the state-of-the-art in the area of multicomponent (bio)markers related to obesity, focusing on the usability and effectiveness of such biomarkers. METHODS AND ANALYSIS: PubMed, Scopus, CINAHL and Embase databases will be searched using predefined key terms to identify peer-reviewed articles published in English until January 2024. Once downloaded into EndNote for deduplication, CADIMA will be employed to review and select abstracts and full-text articles in a two-step procedure, by two independent reviewers. Data extraction will then be carried out by several independent reviewers. Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews and Peer Review of Electronic Search Strategies guidelines will be followed. Combinations employing at least two biomarkers from different domains will be mapped and discussed. ETHICS AND DISSEMINATION: Ethical approval is not required; data will rely on published articles. Findings will be published open access in an international peer-reviewed journal. This review will allow guiding future directions for research and public health strategies on obesity prevention, paving the way towards multicomponent interventions.

Features and Components Preferred by Adolescents in Smartphone Apps for the Promotion of Physical Activity: Focus Group Study.

BACKGROUND: There is solid evidence that lack of physical activity (PA) is a risk factor for chronic diseases. Sufficient levels of PA in childhood and adolescence are particularly important, as they can set the standards for PA levels in adulthood. The latest reports show that only a small percentage of adolescents reach the recommended levels of PA in European Union countries at the age of 15 years. In view of the scale of the problem, it is crucial to develop interventions that promote and support PA in adolescents. Considering their low implementation costs and ubiquitous presence, smartphone apps could be advantageous as a part of PA interventions. OBJECTIVE: This study aimed at investigating the attitudes and preferences of adolescents aged 16-18 years toward various PA app features and components that could (1) make the app more attractive for them and consequently (2) increase their interest and engagement with the app. METHODS: Two separate focus group discussions were conducted in 2 groups of adolescents (n=4 each) aged 16-18 years. Focus groups were carried out online via video conference. The discussions were conducted using a semistructured interview. Participants (n=8; 4 males and 4 females) had a mean age of 17.25 years (SD 0.82 years). Transcripts were analyzed following the approach by Krueger and Casey, that is, categorizing participants' answers and comments according to the questions and themes from the focus group schedule. RESULTS: Features, such as "goal setting and planning," "coaching and training programs," "activity tracking," "feedback," and "location tracking" were appraised as attractive, motivating, and interesting. An "automatic activity recognition" feature was perceived as useful only under the condition that its precision was high. The "reminders" component was also deemed as useful only if a range of conditions was fulfilled (timeliness, opportunity for customization, etc). The features "mood and sleep tracking," "sharing workout results via social networks," "digital avatar and coach," and "rewards" were generally perceived negatively and considered as useless and not motivating. In general, participants preferred features with an easy-to-navigate interface and a clear, simplistic, and straightforward layout with a modern design. Customization and personalization qualities were highly appreciated throughout an app, together with data precision. CONCLUSIONS: This study contributes to the understanding of the features and components preferred by adolescents in apps promoting PA. Such apps should provide users with precise data, and have a simplistic modern design and a straightforward easy-to-use interface. Apps should be personalized and customizable. Desired features to be included in an app are goal setting and planning, feedback, coaching and training programs, and activity tracking. The features should involve high levels of data precision and timely delivery while taking into consideration the real-life context.

A Theory-Informed, Personalized mHealth Intervention for Adolescents (Mobile App for Physical Activity): Development and Pilot Study.

BACKGROUND: Evidence suggests that physical activity (PA) during childhood and adolescence is crucial as it usually results in adequate PA levels in adulthood. Given the ubiquitous use of smartphones by adolescents, these devices may offer feasible means to reach young populations and deliver interventions aiming to increase PA participation and decrease sedentary time. To date, very few studies have reported smartphone-based interventions promoting PA for adolescents. In addition, most available fitness apps do not include the latest evidence-based content. OBJECTIVE: This paper described the systematic development of a behavior change, theory-informed Mobile App for Physical Activity intervention with personalized prompts for adolescents aged 16 to 18 years. The within-subject trial results provided the first evidence of the general effectiveness of the intervention based on the outcomes step count, sedentary time, and moderate to vigorous PA (MVPA) minutes. The effectiveness of the intervention component personalized PA prompt was also assessed. METHODS: A 4-week within-subject trial with 18 healthy adolescents aged 16 to 18 years was conducted (mean age 16.33, SD 0.57 years). After the baseline week, the participants used the Mobile App for Physical Activity intervention (Fitbit fitness tracker+app), which included a daily personalized PA prompt delivered via a pop-up notification. A paired 1-tailed t test was performed to assess the effectiveness of the intervention. Change-point analysis was performed to assess the effectiveness of a personalized PA prompt 30 and 60 minutes after prompt delivery. RESULTS: The results showed that the intervention significantly reduced sedentary time in adolescents during the first week of the trial (t17=-1.79; P=.04; bootstrapped P=.02). This trend, although remaining positive, diminished over time. Our findings indicate that the intervention had no effect on metabolic equivalent of task-based MVPA minutes, although the descriptive increase may give reason for further investigation. Although the results suggested no overall change in heart rate-based MVPA minutes, the results from the change-point analyses suggest that the personalized PA prompts significantly increased heart rate per minute during the second week of the study (t16=1.84; P=.04; bootstrapped P=.04). There were no significant increases in participants' overall step count; however, the personalized PA prompts resulted in a marginally significant increase in step counts per minute in the second week of the study (t17=1.35; P=.09; bootstrapped P=.05). CONCLUSIONS: The results of the trial provide preliminary evidence of the benefit of the Mobile App for Physical Activity intervention for modest yet significant reductions in participants' sedentary time and the beneficial role of personalized PA prompts. These results also provide further evidence of the benefits and relative efficacy of personalized activity suggestions for inclusion in smartphone-based PA interventions. This study provides an example of how to guide the development of smartphone-based mobile health PA interventions for adolescents.

Smartphone-Based Interventions for Physical Activity Promotion: Scoping Review of the Evidence Over the Last 10 Years.

BACKGROUND: Several reviews of mobile health (mHealth) physical activity (PA) interventions suggest their beneficial effects on behavior change in adolescents and adults. Owing to the ubiquitous presence of smartphones, their use in mHealth PA interventions seems obvious; nevertheless, there are gaps in the literature on the evaluation reporting processes and best practices of such interventions. OBJECTIVE: The primary objective of this review is to analyze the development and evaluation trajectory of smartphone-based mHealth PA interventions and to review systematic theory- and evidence-based practices and methods that are implemented along this trajectory. The secondary objective is to identify the range of evidence (both quantitative and qualitative) available on smartphone-based mHealth PA interventions to provide a comprehensive tabular and narrative review of the available literature in terms of its nature, features, and volume. METHODS: We conducted a scoping review of qualitative and quantitative studies examining smartphone-based PA interventions published between 2008 and 2018. In line with scoping review guidelines, studies were not rejected based on their research design or quality. This review, therefore, includes experimental and descriptive studies, as well as reviews addressing smartphone-based mHealth interventions aimed at promoting PA in all age groups (with a subanalysis conducted for adolescents). Two groups of studies were additionally included: reviews or content analyses of PA trackers and meta-analyses exploring behavior change techniques and their efficacy. RESULTS: Included articles (N=148) were categorized into 10 groups: commercial smartphone app content analyses, smartphone-based intervention review studies, activity tracker content analyses, activity tracker review studies, meta-analyses of PA intervention studies, smartphone-based intervention studies, qualitative formative studies, app development descriptive studies, qualitative follow-up studies, and other related articles. Only 24 articles targeted children or adolescents (age range: 5-19 years). There is no agreed evaluation framework or taxonomy to code or report smartphone-based PA interventions. Researchers did not state the coding method, used various evaluation frameworks, or used different versions of behavior change technique taxonomies. In addition, there is no consensus on the best behavior change theory or model that should be used in smartphone-based interventions for PA promotion. Commonly reported systematic practices and methods have been successfully identified. They include PA recommendations, trial designs (randomized controlled trials, experimental trials, and rapid design trials), mixed methods data collection (surveys, questionnaires, interviews, and focus group discussions), scales to assess app quality, and industry-recognized reporting guidelines. CONCLUSIONS: Smartphone-based mHealth interventions aimed at promoting PA showed promising results for behavior change. Although there is a plethora of published studies on the adult target group, the number of studies and consequently the evidence base for adolescents is limited. Overall, the efficacy of smartphone-based mHealth PA interventions can be considerably improved through a more systematic approach of developing, reporting, and coding of the interventions.

Female thermal sensitivity to hot and cold during rest and exercise.

Regional differences in thermal sensation to a hot or cold stimulus are often limited to male participants, in a rested state and cover minimal locations. Therefore, magnitude sensation to both a hot and cold stimulus were investigated during rest and exercise in 8 females (age: 20.4 ± 1.4 years, mass: 61.7 ± 4.0 kg, height: 166.9 ± 5.4 cm, VO2max: 36.8 ± 4.5 ml·kg(-1)·min(-1)). Using a repeated measures cross over design, participants rested in a stable environment (22.3 ± 0.9°C, 37.7 ± 5.5% RH) whilst a thermal probe (25 cm(2)), set at either 40°C or 20°C, was applied in a balanced order to 29 locations across the body. Participants reported their thermal sensation after 10s of application. Following this, participants cycled at 50% VO2max for 20 min and then 30% VO2max whilst the sensitivity test was repeated. Females experienced significantly stronger magnitude sensations to the cold than the hot stimulus (5.5 ± 1.7 and 4.3 ± 1.3, p<0.05, respectively). A significant effect of location was found during the cold stimulation (p<0.05). Thermal sensation was greatest at the head then the torso and declined towards the extremities. No significant effect of location was found in response to the hot stimulation and the pattern across the body was more homogenous. In comparison to rest, exercise caused a significant overall reduction in thermal sensation (5.2 ± 1.5 and 4.6 ± 1.7, respectively, p<0.05). Body maps were produced for both stimuli during rest and exercise, which highlight sensitive areas across the body.

Thermal sensitivity to warmth during rest and exercise: a sex comparison.

PURPOSE: The study aimed to compare thermal sensation in response to a fixed warm stimulus across 31 body locations in resting and active males and females. METHODS: Twelve males (20.6 ± 1.0 years, 78.1 ± 15.6 kg, 180 ± 8.9 cm, 34.4 ± 5.2 ml kg(-1) min(-1)) and 12 females (20.6 ± 1.4 years, 62.9 ± 5.5 kg, 167 ± 5.7 cm, 36.5 ± 6.6 ml kg(-1) min(-1)) rested in a thermoneutral (22.2 ± 2.2 °C, 35.1 ± 5.8 % RH) room whilst a thermal probe (25 cm(2)), set at 40 °C was applied in a balanced order to 31 locations across the body. Participants reported their thermal sensation 10 s after initial application. Following this, participants began cycling at 50 % [Formula: see text] for 20 min, which was then lowered to 30 % [Formula: see text] and the sensitivity test repeated. RESULTS: Females had significantly warmer magnitude sensations than males at all locations (4.7 ± 1.8 vs 3.6 ± 2.2, p < 0.05, respectively). Regional differences in thermal sensation were evident but were more prominent for females. Thermal sensation was greatest at the head then the torso and declined towards the extremities. In comparison to rest, exercise caused a significant reduction in thermal sensation for males (∆thermal sensation; 0.86 ± 0.3, p < 0.05), but only at select locations in females (0.31 ± 0.56, p > 0.05). CONCLUSION: The data provide evidence that the thermal sensation response to warmth varies between genders and between body regions and reduces during exercise. These findings have important implications for clothing design and thermophysiological modelling.