Latent Class Analysis of Online Platforms for Partner-Seeking and Sexual Behaviors Among Men Who Have Sex with Men from Central Kentucky.

Little is known whether engagement in sexual behaviors associated with potential HIV risks differs by subgroups of men who have sex with men (MSM), who are distinct regarding patterns of use of online tools for partner-seeking. Using latent class analysis, we revealed four classes of app-using MSM (n = 181, 18-34 y.o., 82.4% identified as White and non-Hispanic) residing in Central Kentucky: the Grindr/Tinder class; the Poly App Use class of MSM-oriented apps; the General Social Media class, and the Bumble class. Unadjusted penalized logistic regressions showed associations of the Poly App Use class with increased numbers of receptive anal sex partners and reporting condomless receptive anal sex. Adjusting for other covariates, poly app users versus others were more likely to be older (25-34 vs. 18-24, AOR = 3.81, 95%CI = 1.70-9.03), to report past six-month illicit drug use (AOR = 2.93, 95%CI = 1.25-7.43) and to have ever used pre-exposure prophylaxis (AOR = 2.79, 95%CI = 1.10-7.12). Poly app users had behavior profiles associated with an elevated HIV risk and also reported HIV-related protective behaviors likely indicating increased risk awareness among this class. Our findings warrant differentiation of behavior profiles by patterns of app use and suggest not to generalize sexual behaviors associated with potential HIV risks to all app-using MSM.

RESUMEN: Poco se sabe si la participación en comportamientos sexuales asociados con riesgos potenciales de VIH difiere según distintos subgrupos de hombres que tienen sexo con hombres (HSH) en base a patrones en el uso de herramientas online para la búsqueda de pareja. Mediante el análisis de clases latentes, identificamos cuatro clases de HSH que usan aplicaciones (n = 181, 18­34 años, 82.4% identificados como Blancos y no-Hispanos) y residen en Kentucky Central: la clase Grindr/Tinder, la clase Poly App Use de aplicaciones orientadas a HSH, la clase General Social Media y la clase Bumble. Las regresiones logísticas penalizadas no ajustadas mostraron asociaciones de la clase Poly App Use con un alza en el número de parejas receptivas en relaciones sexuales anales y con reportes de sexo anal receptivo sin condón. Al ajustar por otras covariables, los miembros de la clase Poly App Use, con respecto a las otras clases, tuvieron más probabilidades de ser mayores (25­34 vs. 18­24, ORA = 3,81; IC95%=1,70 − 9,03), de informar el uso de drogas ilícitas en los últimos 6 meses (ORA = 2,93; IC95%=1,25 − 7,43) y haber utilizado alguna vez profilaxis-preexposición (ORA = 2,79; IC95%=1,10 − 7,12). Así mismo, los miembros de esta clase tuvieron perfiles de comportamiento asociado con el riesgo elevado de VIH y también informaron comportamientos de protección relacionados con el VIH que probablemente indican una mayor conciencia del riesgo entre ellos. Nuestros hallazgos justifican la diferenciación de perfiles de comportamiento en base a patrones de uso de aplicaciones y sugieren no generalizar los comportamientos sexuales asociados con riesgos potenciales de VIH a todos los HSH que las usan.

A digital health application for managing pediatric asthma: Use and benefits.

Childhood asthma is a common and serious chronic lung disease. Mobile health (mHealth) technologies may assist clinical providers, caregivers, and children in managing pediatric asthma. This study evaluated the Nemours app, an mHealth application. We examined: a) frequency of data access by providers and feature use by caregivers (parents/legal guardians) of 5-11-year-old children diagnosed with asthma and b) whether utilization was related to benefits. Nine providers (allergists/pulmonologists) and 80 patient-families (caregiver/child dyads) participated. Two-years of retrospective data were obtained for asthma control, in-person urgent healthcare utilization, and app utilization. Six-months of prospective data included asthma control, in-person urgent healthcare utilization, app utilization, surveys, and health literacy screeners. Providers (56%) accessed app data and caregivers (61%) utilized the app. Caregiver use of messaging feature predicted gains in health literacy scores (b = .44, p = .041), suggesting app use may offer some educational benefits. Implementation of strategies that support app engagement and utilization may help to maximize intended benefits.

Smartphone application use patterns for mental health disorders: A systematic literature review and meta-analysis.

BACKGROUND: Mobile mental health applications play a significant role in mental health care to fill gaps in care for mental disorders. Despite the growth in mobile phone apps for mental health conditions, patients' mental health smartphone application use, perceived usefulness, and future interest in using apps for mental disorders have not been systematically examined. METHODS: The authors designed and conducted this systematic review and meta-analysis according to the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) statement. Articles reporting mobile/smartphone applications used for mental disorders describing ownership, application use, perceived helpfulness, future interest to use, use patterns, and attitudes were included. PubMed/MEDLINE, EMBASE, PsychINFO, Scopus, and Google Scholar were searched. Published articles from 2014 up to October 2022 were included. The methodological quality was assessed using the Joanna Briggs Institute critical appraisal tool. The heterogeneity test, publication bias, funnel plots and Egger's test were applied. The outcome was calculated by metaprop command using a random-effects model. RESULTS: Ten studies met the eligibility criteria. The pooled prevalence of smartphone ownership, application use for current mental health disorders, perceived usefulness, and future interest in using the app for their mental health problem was 88.63%, 23.29%, 72.80%, and 78.97%, respectively. Heterogeneity and publication bias were detected. CONCLUSIONS: The results of this study indicate that despite a considerable number of smartphone users, perceived usefulness, and future interest in using smartphone mental health applications among patients with mental disorders, only about one-fifth use an application for mental health disorders. The results show that there is a large potential to increase the use of apps for patients to support self-care in the growing era of digital mental health. Further research with consumers and mental health professionals is recommended to address barriers and improve mhealth app utilization. REGISTRATION: Prospero international prospective register of systematic reviews with ID: CRD42022359416.

The Effects of Adopting Mobile Health and Fitness Apps on Hospital Visits: Quasi-Experimental Study.

BACKGROUND: Overcrowding in public hospitals, a common issue in many countries, leads to a range of negative outcomes, such as insufficient access to medical services and patient dissatisfaction. Prior literature regarding solutions to reducing hospital overcrowding primarily focuses on organizational-level operational efficiency. However, few studies have investigated the strategies from the individual patient perspective. Specifically, we considered using mobile health and fitness apps to promote users' health behaviors and produce health benefits, thereby reducing hospital visits. OBJECTIVE: This study estimated the causal effect of health and fitness app adoption on hospital visits by exploiting the staggered timing of adoption. We also investigated how the effect varied with users' socioeconomic status and digital literacy. This study provides causal evidence for the effects of health apps, extends the digital health literature, and sheds light on mobile health policies. METHODS: This study used a data set containing health and fitness app use and hospital-related geolocation data of 267,651 Chinese mobile phone users from January to December 2019. We used the difference-in-differences and difference-in-difference-in-differences designs to estimate the causal effect. We performed a sensitivity analysis to establish the robustness of the findings. We also conducted heterogeneity analyses based on the interactions of postadoption indicators with users' consumption levels, city tiers, and digital literacy. RESULTS: The preferred model (difference-in-difference-in-differences) showed a significant decrease in hospital visits after the adoption of health and fitness apps. App adoption led to a 5.8% (P<.001), 13.1% (P<.001), and 18.4% reduction (P<.001) in hospital visits 1, 2, and 3 months after adoption, respectively. In addition, the moderation analysis shows that the effect is greater for users with high consumption levels, in high-tier cities, or with high digital literacy. CONCLUSIONS: This study estimated the causal effect of health and fitness app adoption on hospital visits. The results and sensitivity analysis showed that app adoption can reduce users' hospital visits. The effect varies with users' consumption levels, city tiers, and digital literacy. These findings provide useful insights for multiple stakeholders in the Chinese health care context.

Directing smartphone use through the self-nudge app one sec.

Research suggests various associations of smartphone use with a range of physical, psychological, and performance dimensions. Here, we test one sec, a self-nudging app that is installed by the user in order to reduce the mindless use of selected target apps on the smartphone. When users attempt to open a target app of their choice, one sec interferes with a pop-up, which combines a deliberation message, friction by a short waiting time, and the option to dismiss opening the target app. In a field-experiment, we collected behavioral user data from 280 participants over 6 wk, and conducted two surveys before and after the intervention span. one sec reduced the usage of target apps in two ways. First, on average 36% of the times participants attempted opening a target app, they closed that app again after one sec interfered. Second, over the course of 6 wk, users attempted to open target apps 37% less than in the first week. In sum, one sec decreased users' actual opening of target apps by 57% after six consecutive weeks. Afterward, participants also reported spending less time with their apps and indicated increased satisfaction with their consumption. To disentangle one sec's effects, we tested its three psychological features in a preregistered online experiment (N = 500) that measured the consumption of real and viral social media video clips. We found that providing the additional option to dismiss the consumption attempt had the strongest effect. While the friction by time delay also reduced consumption instances, the deliberation message was not effective.

Testing the Outcomes of a Smoking Cessation Smartphone App for Nondaily Smokers: Protocol for a Proof-of-concept Randomized Controlled Trial.

BACKGROUND: Nondaily smoking is a widespread, increasingly prevalent pattern of smoking, particularly in ethnic minority and vulnerable populations. To date, no effective treatment approach for this type of smokers has been identified. OBJECTIVE: This study aims to use a randomized controlled trial to evaluate proof-of-concept markers of the Smiling instead of Smoking (SiS) app, a smoking cessation smartphone app designed specifically for nondaily smokers. This app was developed iteratively and is now in its third version. Previous studies have demonstrated acceptability and feasibility when participants were onboarded in person (study 1) and remotely (study 2) and showed within-person changes in line with hypothesized mechanisms of change. This is the first randomized test of this app. METHODS: In total, 225 adult nondaily smokers will be asked to undertake a quit attempt while using smoking cessation support materials for a period of 7 weeks. Participants will be randomized to use the SiS smartphone app, the National Cancer Institute smartphone app QuitGuide, or the National Cancer Institute smoking cessation brochure "Clearing the Air." Participants will take part in a 15-minute scripted onboarding phone call during which study staff will introduce participants to their support materials. Survey links will be sent 2, 6, 12, and 24 weeks after the participants' initially chosen quit date. The primary outcome is self-efficacy to remain abstinent from smoking at treatment end, measured using the Smoking Self-Efficacy Questionnaire. Secondary outcomes cover several domains relevant to treatment development and implementation: treatment acceptability (eg, satisfaction with smoking cessation support, measured using the Client Satisfaction Questionnaire, and app usability, measured using the System Usability Scale); treatment feasibility (eg, measured using the number of days participants used the SiS or QuitGuide app during the prescribed treatment period); and, in an exploratory way, treatment efficacy assessed using self-reported 30-day point prevalence abstinence. RESULTS: Recruitment began in January 2021 and ended June 2022. The final 24-week follow-up was completed in January 2023. This trial is funded by the American Cancer Society. CONCLUSIONS: This study is designed to test whether the prescribed use of the SiS app results in greater self-efficacy to abstain from smoking in nondaily smokers than commonly recommended alternative treatments and whether the SiS app treatment is acceptable and feasible. Positive results will mean that the SiS app warrants testing in a large-scale randomized controlled trial to test its effectiveness in supporting smoking cessation in nondaily smokers. The design of this study also provides insights into issues pertinent to smoking cessation smartphone app treatment development and implementation by measuring, in a randomized design, markers of treatment satisfaction, engagement with the technology and content of the treatment, and adherence to the treatment plan. TRIAL REGISTRATION: ClinicalTrials.gov NCT04672239; https://clinicaltrials.gov/ct2/show/NCT04672239. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/40867.

Understanding the Antecedents and Effects of mHealth App Use in Pandemics: A Sequential Mixed-Method Investigation.

Pandemics such as COVID-19 pose serious threats to public health and disrupt the established systems for obtaining healthcare services. Mobile health (mHealth) apps serve the general public as a potential method for coping with these exogenous challenges. However, prior research has rarely discussed the antecedents and effects of mHealth apps and their use as a coping method during pandemics. Based on the technology acceptance model, empowerment theory, and event theory, we developed a research model to examine the antecedents (technology characteristics and event strength) and effects (psychological empowerment) of mHealth apps and their use. We tested this research model through a sequential mixed-method investigation. First, a quantitative study based on 402 Chinese mHealth users who used the apps during the COVID-19 pandemic was conducted to validate the theoretical model. A follow-up qualitative study of 191 online articles and reviews on mHealth during the COVID-19 pandemic was conducted to cross-validate the results and explain the unsupported findings of the quantitative study. The results show that (1) the mHealth app characteristics (perceived usefulness and perceived ease of use) positively affect mHealth app use; (2) mHealth app use positively affects the psychological empowerment of mHealth users; and (3) the characteristics of pandemic events (event criticality and event disruption) have positive moderating effects on the relationship between mHealth app characteristics and mHealth app use. This study explains the role of mHealth apps in the COVID-19 pandemic on the micro-level, which has implications for the ways in which mHealth apps are used in response to public pandemics.

How Frequently and for How Long Do Adults With Type 2 Diabetes Use Management Apps? The REALL Study.

OBJECTIVE: The objective of the study is to identify predictors of utilization of a type 2 diabetes (T2D) management App over time for insulin users (IUs) and noninsulin users (NIUs). RESEARCH DESIGN AND METHODS: We followed over 16 weeks a national sample of unselected T2D adults who independently elected to download and pair a CONTOUR DIABETES App with their CONTOUR NEXT ONE glucose meter. App use and frequency of glucose testing were recorded. Baseline surveys recorded participant demographic, disease status, distress, medication taking, and views of technology to predict utilization. RESULTS: Mean age was 51.6 years (108 IUs; 353 NIUs), 48% were female, time with diabetes was 6.9 years, and self-reported HbA1c was 8.1% (36.3 mmol/mol). Mean duration of App use was 85.4 days and 40% stopped using the App before 16 weeks. Continuous users were older and reported higher distress, better medication taking, and more positive attitudes toward technology (all P < .01). IUs tested more frequently than NIUs, but frequency and intensity of testing decreased markedly for both groups over time. More predictors of App use frequency and testing occurred for NIUs than IUs: older age, higher HbA1c, lower distress, more medication taking (all P < .05). CONCLUSIONS: App use and testing decreased markedly over time. Variations in the predictors of frequency of App use suggest that the utilization of mobile technologies requires a tailored approach that addresses the specific needs of individual users, compared with adopting a one-size-fits-all strategy, and that IUs and NIUs may require very different strategies of customization.

Dating App Use and Sexual Risk: Understanding the Associations between Casual Sex Motivation, Number of Sexual Partners, and STI Diagnoses.

Objective: This study focused on casual sex motivation to explore why some users tend to have more sexual partners and are more likely to take risks in sexual practices, thereby raising their chances of contracting sexually transmitted infections (STIs). Methods: We recruited Chinese heterosexual dating app users (N = 582) online to investigate the serial mediation model. Results: Casual sex motivation for dating app use was not directly related to the diagnoses of STIs. Number of sexual partners and frequency of risky sexual behavior serially mediated the relationship between casual sex motivation and STI diagnoses. Conclusions: Using dating apps for casual sex motivation is not necessarily associated with higher incidences of STIs, provided that users do not engage in risky sexual practices.

The Role of Access Type and Age Group in the Breadth of Use of Patient Portals: Observational Study.

BACKGROUND: Health care delivery and patient satisfaction are improved when patients engage with their medical information through patient portals. Despite their wide availability and multiple functionalities, patient portals and their functionalities are still underused. OBJECTIVE: We seek to understand factors that lead to patient engagement through multiple portal functionalities. We provide recommendations that could lead to higher patients' usage of their portals. METHODS: Using data from the Health Information National Trends Survey 5, Cycle 3 (N=2093), we performed descriptive statistics and used a chi-square test to analyze the association between the demographic variables and the use of mobile health apps for accessing medical records. We further fitted a generalized linear model to examine the association between access type and the use of portal functionalities. We further examined the moderation effects of age groups on the impact of access type on portal usage. RESULTS: Our results show that accessing personal health records using a mobile health app is positively associated with greater patient usage of access capabilities (ß=.52; P<.001), patient-provider interaction capabilities (ß=.24, P=.006), and patient-personal health information interaction capabilities (ß=.23, P=.009). Patients are more likely to interact with their records and their providers when accessing their electronic medical records using a mobile health app. The impacts of mobile health app usage fade with age for tasks consisting of viewing, downloading, and transmitting medical results to a third party (ß=-.43, P=.005), but not for those involving patient-provider interaction (ß=.05, P=.76) or patient-personal health information interaction (ß=-.15, P=.19). CONCLUSIONS: These findings provide insights on how to increase engagement with diverse portal functionalities for different age groups and thus improve health care delivery and patient satisfaction.

Predicting symptom response and engagement in a digital intervention among individuals with schizophrenia and related psychoses.

Introduction: Despite existing work examining the effectiveness of smartphone digital interventions for schizophrenia at the group level, response to digital treatments is highly variable and requires more research to determine which persons are most likely to benefit from a digital intervention. Materials and methods: The current work utilized data from an open trial of patients with psychosis (N = 38), primarily schizophrenia spectrum disorders, who were treated with a psychosocial intervention using a smartphone app over a one-month period. Using an ensemble of machine learning models, pre-intervention data, app use data, and semi-structured interview data were utilized to predict response to change in symptom scores, engagement patterns, and qualitative impressions of the app. Results: Machine learning models were capable of moderately (r = 0.32-0.39, R2 = 0.10-0.16, MAE norm = 0.13-0.29) predicting interaction and experience with the app, as well as changes in psychosis-related psychopathology. Conclusion: The results suggest that individual smartphone digital intervention engagement is heterogeneous, and symptom-specific baseline data may be predictive of increased engagement and positive qualitative impressions of digital intervention in patients with psychosis. Taken together, interrogating individual response to and engagement with digital-based intervention with machine learning provides increased insight to otherwise ignored nuances of treatment response.

The Association between mHealth App Use and Healthcare Satisfaction among Clients at Outpatient Clinics: A Cross-Sectional Study in Inner Mongolia, China.

Mobile health (mHealth) applications (apps) have been developed in hospital settings to allocate and manage medical care services, which is one of the national strategies to improve health care in China. Little is known about the comprehensive effects of hospital-based mHealth app use on client satisfaction. The aim of this study was to determine the relationship between the full range of mHealth app use and satisfaction domains among clients attending outpatient clinics. A cross-sectional survey was conducted from January to February 2021 in twelve tertiary hospitals in Inner Mongolia. After the construction of the mHealth app use, structural equation modeling was used for data analysis. Of 1889 participants, the standardized coefficients ß on environment/convenience, health information, and medical service fees were 0.11 (p < 0.001), 0.06 (p = 0.039), and 0.08 (p = 0.004), respectively. However, app use was not significantly associated with satisfaction of doctor−patient communication (ß = 0.05, p = 0.069), short-term outcomes (ß = 0.05, p = 0.054), and general satisfaction (ß = 0.02, p = 0.429). Clients of the study hospitals were satisfied with the services, but their satisfaction was not much associated with mHealth use. The limitation of the mHealth system should be improved to enhance communication and engagement among clients, doctors, and healthcare givers, as well as to pay more attention to health outcomes and satisfaction of clients.

Using Smartphone App Use and Lagged-Ensemble Machine Learning for the Prediction of Work Fatigue and Boredom.

INTRO: As smartphone usage becomes increasingly prevalent in the workplace, the physical and psychological implications of this behavior warrant consideration. Recent research has investigated associations between workplace smartphone use and fatigue and boredom, yet findings are not conclusive. METHODS: To build off recent efforts, we applied an ensemble machine learning model on a previously published dataset of N = 83 graduate students in the Netherlands to predict work boredom and fatigue from passively collected smartphone app use information. Using time-based feature engineering and lagged variations of the data to train, validate, and test idiographic models, we evaluated the efficacy of a lagged-ensemble predictive paradigm on sparse temporal data. Moreover, we probed the relative importance of both derived app use variables and lags within this predictive framework. RESULTS: The ability to predict fatigue and boredom trajectories from app use information was heterogeneous and highly person-specific. Idiographic modeling reflected moderate to high correlative capacity (r > 0.4) in 47% of participants for fatigue and 24% for boredom, with better overall performance in the fatigue prediction task. App use relating to duration, communication, and patterns of use frequency were among the most important features driving predictions across lags, with longer lags contributing more heavily to final ensemble predictions compared with shorter ones. CONCLUSION: A lag- specific ensemble predictive paradigm is a promising approach to leveraging high-dimensional app use behavioral data for the prediction of work fatigue and boredom. Future research will benefit from evaluating associations on densely collected data across longer time scales.

A Comparison of the Use of Smart Devices, Apps, and Social Media Between Adults With and Without Hearing Impairment: Cross-sectional Web-Based Study.

BACKGROUND: eHealth and social media could be of particular benefit to adults with hearing impairment, but it is unknown whether their use of smart devices, apps, and social media is similar to that of the general population. OBJECTIVE: Our aim is to study whether adults with normal hearing and those with impaired hearing differ in their weekly use of smart devices, apps, and social media; reasons for using social media; and benefits from using social media. METHODS: We used data from a Dutch cohort, the National Longitudinal Study on Hearing. Data were collected from September 2016 to April 2020 using a web-based questionnaire and speech-in-noise test. The results from this test were used to categorize normal hearing and hearing impairment. Outcomes were compared using (multiple) logistic regression models. RESULTS: Adults with impaired hearing (n=384) did not differ from normal hearing adults (n=341) in their use of a smartphone or tablet. They were less likely to make use of social media apps on a smartphone, tablet, or smartwatch (age-adjusted odds ratio [OR] 0.67, 95% CI 0.48-0.92; P=.02). Use of social media on all devices and use of other apps did not differ. Adults with hearing impairment were more likely to agree with using social media to stay in touch with family members (OR 1.54, 95% CI 1.16-2.07; P=.003) and friends (age-adjusted OR 1.35, 95% CI 1.01-1.81; P=.046). Furthermore, they were more likely to agree with using social media to perform their work (age-adjusted OR 1.51, 95% CI 1.04-2.18; P=.03). There were no differences in the experienced benefits from social media. CONCLUSIONS: The potential for eHealth is confirmed because adults with hearing impairment are not less likely to use smart devices than their normal hearing peers. Adults with hearing impairment are less likely to use social media apps on a smart device but not less likely to use social media on all types of internet-connected devices. This warrants further research on the types of social media platforms that adults with hearing impairment use and on the type of device on which they prefer to use social media. Given that participants with hearing impairment are more likely than their normal hearing peers to use social media to perform their work, use of social media may be seen as an opportunity to enhance vocational rehabilitation services for persons with hearing impairment.

A Comparison of User Behaviors for a Fertility-Tracking App: Does Training in an NFP Method Improve Persistence and Use?

This study explores differences in the use of CycleProGo™ (CPG), a fertility-tracking app developed by Couple to Couple League (CCL), between those exposed to it as a part of natural family planning (NFP) instruction versus those who find it on their own. An anonymous data set of 17,543 CPG accounts opened between April 2013 and June 2016 was used for analysis. Nonmember users opened the most accounts (58 percent, n = 10,134), CCL members represented 38 percent (n = 6,758) of new accounts, and 207 CCL teachers (4 percent) were using CPG for personal charting. Significantly more nonmember accounts had zero days of use after the initial opening compared to CCL member accounts (61 percent vs. 23 percent, respectively, χ2 = 2,405.9, p < .001). Conversely, significantly more CCL member accounts were used for ninety days or longer than nonmember accounts (47 percent vs. 13 percent, respectively, χ2 = 2,404.2, p < .001). CCL students-those who began using the app as part of a formal NFP teaching curriculum-were more likely to use the app for > six cycles compared to nonmembers. In accounts with at least one complete cycle, CCL students were the most diligent at daily recording (95 percent of cycle days with observation recorded) followed by CCL members (88 percent) and nonmembers (76 percent). CCL teachers had the lowest frequency of cycle days with a recorded observation (73 percent). Within each cohort, accounts with > six recorded cycles had a lower proportion of cycle days with an observation recorded, likely reflecting increasing knowledge of their personal fertility patterns. Long-term users who had no known formal training in NFP still had the lowest proportion cycle days with a fertility observation. We conclude formal NFP instruction increases the probability of long-term app use, and regardless of training, long-term users will likely record observations on about 70 percent of cycle days. SUMMARY: "CycleProGo™ users with NFP training were more persistent and diligent about daily data input than those without training."

Social Influence Factors for Utilization Rate of Medical and Health App / 医学信息学杂志

Addressing the problems that the unitization rate of medical and health App are generally low,based on the empirical approach,the paper demonstrates the positive influence of social factors on the utilization rate of mobile health App,and deeply analyzes the action mechanism and linkage effect of social factors such as social relation network,social support and subjective norms,so as to nationally design the socialized development strategies for mobile health App,thus providing the decision-making basis for the sustainable development and user cultivation of m-Health.

The Use of Mobile Phone and Medical Apps among General Practitioners in Hangzhou City, Eastern China.

BACKGROUND: Mobile phones and mobile phone apps have expanded new forms of health professionals' work. There are many studies on the use of mobile phone apps for different specialists. However, there are no studies on the current use of mobile phone apps among general practitioners (GPs). OBJECTIVE: The objective of the study was to investigate the extent to which GPs own smartphones with apps and use them to aid their clinical activities. METHODS: A questionnaire survey of GPs was undertaken in Hangzhou, Eastern China. Data probing GPs' current use of medical apps in their clinical activities and factors influencing app use were collected and analyzed RESULTS: 125 GPs participated in the survey. 90.4% of GPs owned a mobile phone, with 48.7% owning an iPhone and 47.8% owning an Android phone. Most mobile phone owners had 1-3 medical-related apps, with very few owning more than 4. There was no difference in number of apps between iPhone and Android owners (χ(2)=1.388, P=0.846). 36% of GPs reported using medical-related apps on a daily basis. The majority of doctors reported using apps to aid clinical activities less than 30 minutes per day. CONCLUSIONS: A high level of mobile phone ownership and usage among GPs was found in this study, but few people chose medical-related apps to support their clinical practice.

Mobile Manifestations of Alertness: Connecting Biological Rhythms with Patterns of Smartphone App Use.

Our body clock causes considerable variations in our behavioral, mental, and physical processes, including alertness, throughout the day. While much research has studied technology usage patterns, the potential impact of underlying biological processes on these patterns is under-explored. Using data from 20 participants over 40 days, this paper presents the first study to connect patterns of mobile application usage with these contributing biological factors. Among other results, we find that usage patterns vary for individuals with different body clock types, that usage correlates with rhythms of alertness, that app use features such as duration and switching can distinguish periods of low and high alertness, and that app use reflects sleep interruptions as well as sleep duration. We conclude by discussing how our findings inform the design of biologically-friendly technology that can better support personal rhythms of performance.

Cognitive factors of using health apps: systematic analysis of relationships among health consciousness, health information orientation, eHealth literacy, and health app use efficacy.

BACKGROUND: Interest in smartphone health apps has been increasing recently. However, we have little understanding of the cognitive and motivational factors that influence the extent of health-app use. OBJECTIVE: This study aimed to examine the effects of four cognitive factors-health consciousness, health information orientation, eHealth literacy, and health-app use efficacy-on the extent of health-app use. It also explored the influence of two different use patterns-information and information-behavior use of health apps-with regard to the relationships among the main study variables. METHODS: We collected and analyzed 765 surveys in South Korea. According to the results, there was a negligible gender difference: males (50.6%, 387/765) and females (49.4%, 378/765). All participants were adults whose ages ranged from 19 to 59. In order to test the proposed hypotheses, we used a path analysis as a specific form of structural equation modeling. RESULTS: Through a path analysis, we discovered that individuals' health consciousness had a direct effect on their use of health apps. However, unlike the initial expectations, the effects of health information orientation and eHealth literacy on health-app use were mediated by health-app use efficacy. CONCLUSIONS: The results from the path analysis addressed a significant direct effect of health consciousness as well as strong mediating effects of health-app use efficacy. These findings contribute to widening our comprehension of the new, digital dimensions of health management, particularly those revolving around mobile technology.