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

Background: Promotion of physical activity, healthy eating, adequate sleep, and reduced sedentary behavior in adolescents is a major priority globally given the current increase in population health challenges of noncommunicable diseases and risk factors such as obesity. Adolescents are highly engaged with mobile technology, but the challenge is to engage them with mobile health (mHealth) technology. Recent innovations in mobile technology provide opportunities to promote a healthy lifestyle in adolescents. An increasingly utilized approach to facilitate increased engagement with mHealth technology is to involve potential users in the creation of the technology. Objective: This study aimed to describe the process of and findings from co-designing and prototyping components of the PEGASO Fit for Future (F4F) mHealth intervention for adolescents from different cultural backgrounds. Methods: A total of 74 adolescents aged 13 to 16 years from Spain, Italy, and the United Kingdom participated in the co-design of the PEGASO F4F technology. In 3 iterative cycles over 12 months, participants were involved in the co-design, refinement, and feasibility testing of a system consisting of diverse mobile apps with a variety of functions and facilities to encourage healthy weight–promoting behaviors. In the first iteration, participants attended a single workshop session and were presented with mock-ups or early-version prototypes of different apps for user requirements assessment and review. During the second iteration, prototypes of all apps were tested by participants for 1 week at home or school. In the third iteration, further developed prototypes were tested for 2 weeks. Participants’ user experience feedback and development ideas were collected through focus groups and completion of questionnaires. Results: For the PEGASO F4F technology to be motivating and engaging, participants suggested that it should (1) allow personalization of the interface, (2) have age-appropriate and easy-to-understand language (of icons, labels, instructions, and notifications), (3) provide easily accessible tutorials on how to use the app or navigate through a game, (4) present a clear purpose and end goal, (5) have an appealing and self-explanatory reward system, (6) offer variation in gamified activities within apps and the serious game, and (7) allow to seek peer support and connect with peers for competitive activities within the technology. Conclusions: Incorporating adolescents’ preferences, the PEGASO F4F technology combines the functions of a self-monitoring, entertainment, advisory, and social support tool. This was the first study demonstrating that it is possible to develop a complex mobile phone-based technological system applying the principles of co-design to mHealth technology with adolescents across 3 countries. The findings from this study informed the development of an mHealth system for healthy weight promotion to be tested in a controlled multinational pilot trial.

Background: Despite the relevance of mobile technologies and social media (MTSM) for adolescents, their association with depressive disorders in this population remains unclear. While there are previous reviews that have identified the use of MTSM as a risk factor for developing depression, other reviews have indicated their possible preventive effect. Objective: The aim of this review was to synthesize the current evidence on the association between MTSM use and the development or prevention of depressive disorders in adolescents. Methods: An umbrella review was conducted using information published up to June 2019 from PubMed/MEDLINE, PsycINFO, Web of Science, and The Cochrane Library. Systematic reviews focusing on the adolescent population (up to 20 years old) and depression and its potential relationship with MTSM use were included. Screening of titles, abstracts, and full texts was performed. After selecting the reviews and given the heterogeneity of the outcome variables and exposures, a narrative synthesis of the results was carried out. Results: The search retrieved 338 documents, from which 7 systematic reviews (3 meta-analyses) were selected for data extraction. There were 11-70 studies and 5582-46,015 participants included in the 7 reviews. All reviews included quantitative research, and 2 reviews also included qualitative studies. A statistically significant association between social media and developing depressive symptoms was reported in 2 reviews, while 5 reviews reported mixed results. Conclusions: Excessive social comparison and personal involvement when using MTSM could be associated with the development of depressive symptomatology. Nevertheless, MTSM might promote social support and even become a point of assistance for people with depression. Due to the mixed results, prospective research could be valuable for providing stronger evidence.

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

Background: The use of apps to tackle overweight and obesity by tracking physical and dietary patterns and providing recommendations and motivation strategies to achieve personalized goals has increased over recent years. However, evidence of the efficacy, effectiveness, and safety of these apps is severely lacking. Objective: The aim of this study was to identify efficacy, safety, and effectiveness criteria used to assess weight control, overweight, and obesity management in mobile health (mHealth) interventions through a systematic review. Methods: PubMed, PsycINFO, Scopus, UK Trial Database, ClinicalTrials.gov, and the Cochrane Library were surveyed up to May 2018. All types of clinical studies were considered. A total of 2 independent reviewers assessed quality using Scottish Intercollegiate Guidelines Network (SIGN) criteria. Ratings were used to provide an overall score for each study (low, moderate, or high). Data were synthesized in evidence tables. Results: From 233 potentially relevant publications, only 28 studies were included. Of these, 13 (46%) were randomized control trials, 11 were single-arm studies (39%), 3 were nonrandomized controlled trials (11%), and 1 study was a cluster randomized trial (4%). The studies were classified as low (15), high (7), and moderate (6) quality according to SIGN criteria. All studies focused on efficacy, with only 1 trial mentioning safety and another 1 effectiveness. In 11 studies, the apps were used as stand-alone interventions, the others were multicomponent studies that included other tools for support such as sensors or websites. The main management tool included in the apps was feedback messaging (24), followed by goal-setting mechanisms (20) and self-monitoring (19). The majority of studies took weight or body mass index loss as the main outcome (22) followed by changes in physical activity (14) and diet (12). Regarding outputs, usability, adherence, and engagement (17) were the most reported, followed by satisfaction (7) and acceptability (4). Conclusions: There is a remarkable heterogeneity among these studies and the majority have methodological limitations that leave considerable room for improvement. Further research is required to identify all relevant criteria for assessing the efficacy of mHealth interventions in the management of overweight and obesity. Trial Registration: PROSPERO CRD42017056761; https://tinyurl.com/y2zhxtjx

Background: The use of apps for weight management has increased over recent years; however, there is a lack of evidence regarding the efficacy and safety of these apps. The EVALAPPS project will develop and validate an assessment instrument to specifically assess the safety and efficacy of weight management apps. Objective: The aim of this study was to reach a consensus among stakeholders on a comprehensive set of criteria to guide development of the EVALAPPS assessment instrument. A modified Delphi process was used in order to verify the robustness of the criteria that had been identified through a literature review and to prioritize a set of the identified criteria. Methods: Stakeholders (n=31) were invited to participate in a 2-round Delphi process with 114 initial criteria that had been identified from the literature. In round 1, participants rated criteria according to relevance on a scale from 0 (“I suggest this criterion is excluded”) to 5 (“This criterion is extremely relevant”). A criterion was accepted if the median rating was 4 or higher and if the relative intraquartile range was equal to 0.67 or lower. In round 2, participants were asked about criteria that had been discarded in round 1. A prioritization strategy was used to identify crucial criteria according to (1) the importance attributed by participants (criteria with a mean rating of 4.00 or higher), (2) the level of consensus (criteria with a score of 4 or 5 by at least 80% of the participants). Results: The response rate was 83.9% (26/31) in round 1 and 90.3% (28/31) in round 2. A total of 107 out of 114 criteria (93.9%) were accepted by consensus—105 criteria in round 1 and 2 criteria in round 2. After prioritization, 53 criteria were deemed crucial. These related mainly to the dimensions of security and privacy (13/53, 24.5%) and usability (9/53, 17.0%), followed by activity data (5/53, 9.4%), clinical effectiveness (5/53, 9.4%), and reliability (5/53, 9.4%). Conclusions: Results confirmed the robustness of the criteria that were identified, with those relating to security and privacy being deemed most relevant by stakeholders. Additionally, a specific set of criteria based on health indicators (activity data, physical state data, and personal data) was also prioritized.