BACKGROUND: Leveraging free smartphone apps can help expand the availability and use of evidence-based smoking cessation interventions. However, there is a need for additional research investigating how the use of different features within such apps impacts their effectiveness.
OBJECTIVE: We used observational data collected from an experiment of a publicly available smoking cessation app to develop supervised machine learning (SML) algorithms intended to distinguish the app features that promote successful smoking cessation. We then assessed the extent to which patterns of app feature use accounted for variance in cessation that could not be explained by other known predictors of cessation (eg, tobacco use behaviors).
METHODS: Data came from an experiment (ClinicalTrials.gov NCT04623736) testing the impacts of incentivizing ecological momentary assessments within the National Cancer Institute\'s quitSTART app. Participants\' (N=133) app activity, including every action they took within the app and its corresponding time stamp, was recorded. Demographic and baseline tobacco use characteristics were measured at the start of the experiment, and short-term smoking cessation (7-day point prevalence abstinence) was measured at 4 weeks after baseline. Logistic regression SML modeling was used to estimate participants\' probability of cessation from 28 variables reflecting participants\' use of different app features, assigned experimental conditions, and phone type (iPhone [Apple Inc] or Android [Google]). The SML model was first fit in a training set (n=100) and then its accuracy was assessed in a held-aside test set (n=33). Within the test set, a likelihood ratio test (n=30) assessed whether adding individuals\' SML-predicted probabilities of cessation to a logistic regression model that included demographic and tobacco use (eg, polyuse) variables explained additional variance in 4-week cessation.
RESULTS: The SML model\'s sensitivity (0.67) and specificity (0.67) in the held-aside test set indicated that individuals\' patterns of using different app features predicted cessation with reasonable accuracy. The likelihood ratio test showed that the logistic regression, which included the SML model-predicted probabilities, was statistically equivalent to the model that only included the demographic and tobacco use variables (P=.16).
CONCLUSIONS: Harnessing user data through SML could help determine the features of smoking cessation apps that are most useful. This methodological approach could be applied in future research focusing on smoking cessation app features to inform the development and improvement of smoking cessation apps.
BACKGROUND: ClinicalTrials.gov NCT04623736; https://clinicaltrials.gov/study/NCT04623736.

UNASSIGNED: Smartphone use has grown in providing healthcare for patients with low back pain (LBP), but the literature lacks an analysis of the use of smartphone apps. This scoping review aimed to identify current areas of smartphone apps use for managing LBP. We also aimed to evaluate the current status of the effectiveness or scientific validity of such use and determine perspectives for their potential development.
UNASSIGNED: We searched PubMed, PEDro and Embase for articles published in English up to May 3 rd, 2021 that investigated smartphone use for LBP healthcare and their purpose. All types of study design were accepted. Studies concerning telemedicine or telerehabilitation but without use of a smartphone were not included. The same search strategy was performed by two researchers independently and a third researcher validated the synthesis of the included studies.
UNASSIGNED: We included 43 articles: randomised controlled trials (RCTs) (n=12), study protocols (n=6), reliability/validity studies (n=6), systematic reviews (n=7), cohort studies (n=4), qualitative studies (n=6), and case series (n=1). The purposes of the smartphone app were for 1) evaluation, 2) telerehabilitation, 3) self-management, and 4) data collection. Self-management was the most-studied use, showing promising results derived from moderate- to good-quality RCTs for patients with chronic LBP and patients after spinal surgery. Promising results exist regarding evaluation and data collection use and contradictory results regarding measurement use.
UNASSIGNED: This scoping review revealed a notable interest in the scientific literatures regarding the use of smartphone apps for LBP patients. The identified purposes point to current scientific status and perspectives for further studies including RCTs and systematic reviews targeting specific usage.

OBJECTIVE: Smartphones have become a powerful instrument in academic life for medical professions worldwide. Global lockdown due to COVID-19 pandemic culminated in the closure of educational institutions and resulted in shifting to online teaching. In our newly implemented competency-based medical education curriculum (CBME) for medical graduates, self-directed learning (SDL) is one of the teachings-learning methods. Smartphones are an essential tool for SDL in medical school. This main objective of the study is to determine the usage of health apps in a tertiary care teaching hospital to encourage the medical students and compulsory rotatory residential internship (CRRI) to continue SDL process.
METHODS: This cross-sectional questionnaire-based study was conducted for the period of 30 days for medical students and CRRI\'s at a tertiary care teaching hospital. The population was selected using convenient sampling method. This anonymous questionnaire was validated by the experts and the questions encompassing knowledge, attitude and perception (KAP Survey) of the students toward smartphone medical apps was utilized for this survey.
RESULTS: Out of 582 participants, only 250 students (43%) have participated in the survey. Our study shows that 95% of students were handling android smartphones, and 84% of them were using various medical applications on them and it leads to SDL.
CONCLUSIONS: The impact of the lockdown has increased SDL. Majority of the students (51.8-69.8%) have agreed that medical apps enhanced their SDL and helped them to study independently.

Technology-delivered cognitive behavioral therapy (CBT) has enabled more people to access effective, affordable mental health care. This study provides an overview of the most common types of technology-delivered CBT, including Internet-delivered, smartphone app, and telehealth CBT, as well as their evidence for the treatment of a range of mental health conditions. We discuss gaps in the existing evidence and future directions in the field for the use of technology CBT interventions.

BACKGROUND: Obesity is a prevalent and serious chronic condition associated with abnormal or excessive fat buildup that poses significant health risks. The rates of overweight and obesity in adults and children continue to rise, with global rates of children with overweight or obesity aged 5-19 years growing from 4% to 18% between 1975 and 2016. Furthermore, in 2017, nearly 4 million people died due to complications arising from being overweight or obese.
OBJECTIVE: This study aims to investigate the potential impact of the mobile app Heia Meg on promoting healthier lifestyle choices regarding nutrition and physical activity.
METHODS: A prospective longitudinal study was conducted in collaboration with the Norwegian Directorate of Health. Participants were recruited through the Heia Meg app and were asked to complete a questionnaire before and after using the app. A total of 199 responses were included in the first (preintervention) questionnaire, while 99 valid responses were obtained in the second (postintervention) questionnaire.
RESULTS: The majority (159/199, 79.9%) of participants were female, and their age ranged from 18 years to 70 years and older. The results show a reduction in BMI after the digital intervention. However, some variables influence the BMI reduction effect: sex, age, education, and smoking. The group that obtained the most benefit from the intervention consisted of those who were male, aged 30-39 years, highly educated, and nonsmokers. Although positive, some of the findings are slightly above the statistical significance threshold and therefore should be interpreted carefully.
CONCLUSIONS: Our study found weak evidence to support the effectiveness of the Heia Meg app in promoting healthier lifestyle choices. However, limitations and confounding factors suggest that further research in different populations with larger sample sizes is needed to confirm or disprove our findings.

BACKGROUND: The number of smartphone apps for brain training is increasing, and the number of people who are working on brain training is also increasing. However, researchers disagree about the effectiveness of brain training.
METHODS: Therefore, in this study, we conducted an intervention test with the participation of 70 healthy middle-aged men and women and measured the effect of smartphone apps on lifestyle improvement using brain healthcare quotient calculated from brain imaging data.
RESULTS: As a result, in the intervention group, significant improvements were seen in fractional anisotropy (FA) of the whole brain, corpus callosum, internal capsule, corona radiata, posterior thalamic radiation, external capsule, and superior longitudinal fasciculus. Additionally, in the intervention group, these FA increments correlated with improvements in cognitive function as measured by the trail-making test and vigor as measured by the Profile of Mood States 2nd Edition.
CONCLUSIONS: The results of this study suggest that improving lifestyle habits through smartphone apps can improve brain health and cognitive and emotional performance of healthy middle-aged adults. This is consistent with previous research that suggests that FA integrity in the limbic-thalamo-cortical pathway influences cognitive function and emotion regulation.

BACKGROUND: Men who have sex with men (MSM) are disproportionately burdened by poor mental health. Despite the increasing burden, evidence-based interventions for MSM are largely nonexistent in Nepal.
OBJECTIVE: This study explored mental health concerns, contributing factors, barriers to mental health care and support, and preferred interventions to improve access to and use of mental health support services among MSM in Nepal.
METHODS: We conducted focus groups with MSM in Kathmandu, Nepal, in January 2023. In total, 28 participants took part in 5 focus group sessions. Participants discussed several topics related to the mental health issues they experienced, factors contributing to these issues, and their suggestions for potential interventions to address existing barriers. The discussions were recorded, transcribed, and analyzed using Dedoose (version 9.0.54; SocioCultural Research Consultants, LLC) software for thematic analysis.
RESULTS: Participants reported substantial mental health problems, including anxiety, depression, suicidal ideation, and behaviors. Contributing factors included family rejection, isolation, bullying, stigma, discrimination, and fear of HIV and other sexually transmitted infections. Barriers to accessing services included cost, lack of lesbian, gay, bisexual, transgender, intersex, queer, and asexual (LGBTIQA+)-friendly providers, and the stigma associated with mental health and sexuality. Participants suggested a smartphone app with features such as a mental health screening tool, digital consultation, helpline number, directory of LGBTIQA+-friendly providers, mental health resources, and a discussion forum for peer support as potential solutions. Participants emphasized the importance of privacy and confidentiality to ensure mobile apps are safe and accessible.
CONCLUSIONS: The findings of this study have potential transferability to other low-resource settings facing similar challenges. Intervention developers can use these findings to design tailored mobile apps to facilitate mental health care delivery and support for MSM and other marginalized groups.

Integrating smartphone applications into screening and identifying autism spectrum disorder (ASD) represents a promising and innovative frontier within healthcare. This forward-looking paper examines the current landscape of ASD screening apps, shedding light on their potential advantages and addressing and navigating significant challenges. One of the most compelling aspects of these apps lies in their potential to democratize access to ASD screening, effectively breaking down geographical barriers. By using the widespread availability of smartphones, these apps make it possible for individuals, caregivers, and healthcare providers to engage in early ASD screening from virtually anywhere. This accessibility is especially crucial in underserved areas or regions with limited access to specialized healthcare services. Moreover, these apps offer a degree of objectivity that traditional screening methods may need help to match. By relying on data-driven algorithms and machine learning, they can provide a more impartial assessment of a child\'s behavior, minimizing the potential for subjective bias. This objectivity, combined with the ability to monitor and assess a child\'s development over time, empowers caregivers with valuable insights into their child\'s progress. However, as with any technological advancement in healthcare, integrating smartphone apps for ASD screening is not without its share of ethical and privacy considerations. Ensuring informed consent is obtained, especially when collecting data from children, is complex and critical. Striking the right balance between collecting necessary data and protecting an individual\'s privacy requires careful thought and transparent communication. Additionally, the \"digital divide\" represents a challenge that needs to be acknowledged and addressed. Not all individuals and families have equal access to smartphones or the technological literacy required to use these apps effectively. This disparity in access must be considered when developing and implementing app-based screening solutions to prevent exacerbating existing healthcare inequalities. Nevertheless, the future of ASD screening apps holds significant promise. Advancements in technology, including integrating advanced sensors, wearables, augmented reality, and machine learning, can further enhance the accuracy and depth of screening. Interdisciplinary collaboration between researchers, developers, clinicians, and educators is crucial to ensure that these apps are effective, culturally sensitive, and user-friendly. Furthermore, integrating these apps into broader healthcare systems, including electronic health records and telehealth platforms, can streamline the screening process and enable a more seamless transition from screening to diagnosis and intervention.

BACKGROUND: Depression is one of the most common mental disorders that leads to anxiety, sleep disturbances, and suicidal thoughts. Due to the high cost of treatment and the reluctance of many patients to seek medical help, major depressive disorder (MDD) is becoming more prevalent. Therefore, alternative methods like smartphone applications can help prevent and improve depression symptoms. The present study aimed to determine the effect of the newly developed Yara smartphone application on anxiety, sleep quality, and suicidal thoughts in patients with MDD.
METHODS: This randomized controlled trial with a pretest-posttest design was conducted on Iranian patients with MDD in 2022. Sixty-four patients were recruited using convenience sampling and randomly assigned to two control and intervention groups. The intervention was conducted using the Yara smartphone application for three months. Data were collected using the Spielberger State-Trait Anxiety Inventory (STAI), Pittsburgh Sleep Quality Index (PSQI), and Beck Scale for Suicidal Ideation (BSSI). Data were first entered into IBM SPSS Statistics for Windows, version 22 (IBM Corp., Armonk, N.Y., USA) and then analyzed using descriptive and analytical statistics.
RESULTS: There was no statistically significant difference in the mean score of anxiety and sleep quality between the intervention and control groups before the intervention (p ≥ .05). However, this difference in the mean score of anxiety and sleep quality was statistically significant in the two groups after the intervention (p < .05). The results showed no statistically significant difference in the mean score of suicidal thoughts between the two groups before and after the intervention (p ≥ .05). The use of the Yara smartphone application had a significant positive effect on anxiety and sleep quality in depressed patients (p < .001). At the same time, it had no significant effect on suicidal thoughts (p ≥ .05).
CONCLUSIONS: Considering the positive effect of using the Yara smartphone application on reducing anxiety and improving sleep quality in depressed patients, this application can help alleviate the problems of depressed patients alongside existing treatment methods. Thus, this application is recommended for this group of patients in psychiatric clinics and departments. The Yara application\'s effectiveness was not approved on suicidal thoughts in this study so that further investigation would be necessary.
BACKGROUND: Iranian Registry of Clinical Trial approval code (IRCT# IRCT20131112015390N7).

BACKGROUND: Digital transformation is shaping the future of orthopedics and trauma surgery. Telemedicine, digital health applications, electronic patient records and artificial intelligence play a central role in this. These technologies have the potential to improve medical care, enable individualized patient treatment plans and reduce the burden on the treatment process. However, there are currently challenges in the areas of infrastructure, regulation, reimbursement and data protection.
UNASSIGNED: Effective transformation requires a deep understanding of both technology and clinical practice. Orthopedic and trauma surgeons need to take a leadership role by actively engaging with new technologies, designing new treatment processes and enhancing their medical skills with digital and AI competencies. The integration of digital skills into medical education and specialist training will be crucial for actively shaping the digital transformation and exploiting its full potential.
UNASSIGNED: HINTERGRUND: Die digitale Transformation prägt die Zukunft der Orthopädie und Unfallchirurgie maßgeblich. Telemedizin, digitale Gesundheitsanwendungen, elektronische Patientenakten und künstliche Intelligenz spielen dabei eine zentrale Rolle. Diese Technologien haben das Potenzial, die medizinische Versorgung zu verbessern, individualisierte Behandlungspläne zu ermöglichen und den Behandlungsprozess zu entlasten. Allerdings bestehen aktuell Herausforderungen in den Bereichen Infrastruktur, Regulatorik, Erstattung und Datenschutz.
UNASSIGNED: Eine effektive Transformation erfordert ein tiefgreifendes Verständnis sowohl der Technologie als auch der klinischen Praxis. Orthopäden und Unfallchirurgen müssen eine Führungsrolle übernehmen, indem sie sich aktiv mit den neuen Technologien auseinandersetzen, neue Behandlungsabläufe gestalten und ihre medizinischen Kompetenzen durch digitale und KI-Kompetenzen erweitern. Die Integration digitaler Kompetenzen in die medizinische Aus- und fachärztliche Weiter‑/Fortbildung wird entscheidend sein für die aktive Gestaltung der digitalen Transformation und die Nutzung ihres vollen Potenzials.