Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: Diabetes and related complications signify US727 billion dollars in costs yearly. Type 1 diabetes, Type 2 diabetes, and gestational diabetes are three subtypes of diabetes which share the same behavioral risk factors with prediabetic conditions. The efforts taken in lifestyle modifications can improve the health levels of diabetics and reduce the risks of contracting diabetes. However, lifestyle modifications mainly performed in a face-to-face manner is costly and leads to few people undertaking services for diabetes management. Alternatively, smartphone applications provide mobile platforms for the monitoring of lifestyle factors, as well as for health education; and different types of feedback. Objective: The purpose of this review is to assess the efficacy of smartphone applications for both patients with different subtypes of diabetes as well as prediabetic patients in the short and long terms. Methods: In June 2018, literature retrieval was conducted in five databases (CENTRAL, MEDLINE, EMBASE, CINAHL, PsycINFO). Inclusion criteria were randomized controlled trials involving diabetics or prediabetic patients, aged 18 or above. Lifestyle outcomes investigated were physical activities and healthy diets. All the studies included in this review were assessed by Cochrane Collaboration’s risk of bias tool. Meta-analysis conducted for HbA1c (glycated hemoglobin) investigated the mean effect of post-treatment (or the mean change from the baseline) with standard deviations. Subgroup analysis was conducted if possible. Heterogeneity was tested by I2. Results: A total of 2,669 articles was identified through database searching, and of these, 26 articles, 23 studies were included in this review and 18 studies were eligible for meta-analysis. Among the studies, five of them examined Type 1 diabetes, 11 examined Type 2 diabetes and two of them examined prediabetic patients. Regarding Type 1 diabetes, the overall effect on HbA1c was statistically insignificant (P=0.42) with acceptable heterogeneity (I2=39%) in the short term. Heterogeneity existed between the short-term and long-term subgroups (I2=64%). Regarding Type 2 diabetes, the overall effect on HbA1c was statistically significant (P<0.01) without heterogeneity in the short term. The overall effect on HbA1c was statistically significant (P<0.01) with an acceptable heterogeneity of I2=2%) in the long term. Heterogeneity did not exist between the short-term and long-term subgroups. For prediabetic patients, the overall effect on HbA1c was statistically insignificant (P=0.67) with the heterogeneity of I2=65%. Also, the publication bias of the Type 2 diabetes studies was assessed by the trim and fill method, and showed no effect on the overall effect size of the 11 studies. Conclusions: This review demonstrated the efficacy of smartphone applications for the different subtypes of diabetes and prediabetic conditions. For Type 1 diabetes, the efficacy of smartphone applications seemed insignificant in the short term. Concerning Type 2 diabetes, the efficacy of smartphone applications showed an attenuation with prolonged time usage. As for prediabetic conditions, heterogeneity existed between a small number of studies. More research with prediabetic conditions and long-term follow-up in Type 1 diabetes cases, we propose, should be conducted to assess the efficacy of apps, respectively.

With the swift emergence of electronic medical information, the global popularity of mobile health (mHealth) services continues to increase steadily. This study aims to investigate the efficacy factors that directly or indirectly influence individuals’ acceptance of mHealth services. Based on the technology acceptance model, this research incorporates efficacy factors into the acceptance decision process. A research model was proposed involving the direct and indirect effects of self-efficacy and response-efficacy on acceptance intention, along with their moderating effects. The model and hypotheses were validated using data collected from a field survey of 650 potential service users. The results reveal that: (1) self-efficacy and response-efficacy are both positively associated with perceived ease of use; and (2) self-efficacy and response-efficacy moderate the impact of perceived usefulness toward adoption intention. Self-efficacy and response-efficacy both play an important role in individuals’ acceptance of mHealth services, which not only affect their perceived ease of use of mHealth services, but also positively moderate the effects of perceived usefulness on adoption intention. Our findings serve to provide recommendations that are specifically customized for mHealth service providers and their marketers.

Insufficient research exists on the impact of reputation in online health-care market communities, especially from the multilevel and cross-level perspectives. Based on prior research on individual and organizational reputation, we hypothesize multilevel and cross-level reputation determinants of physicians’ performance in online health-care market communities. Using hierarchical linear modeling, we analyzed the data of 47,182 physicians from 660 hospitals in a Chinese online health-care market community to test our hypotheses. Our results suggest that the number of physicians’ appointments is positively associated with their individual offline and online reputations, as well as the offline and online reputation of the hospital in which the physicians work. We also find that organizational reputation moderates the relationship between an individual’s reputation and a physician’s performance, in such a way that the hospital’s offline reputation increases the importance of physicians’ online reputation in promoting the number of physicians’ appointments. However, the hospital’s online reputation enhances the relationship between physicians’ offline reputation and the number of appointments. Our study contributes to existing theories of reputation and the signaling theory, and also provides physicians with guidelines that support them in effectively improving their performance.

Background: Mobile health (m-health) services are becoming increasingly important and widely accepted. However, empirical studies on potential users' m-health acceptance behavior remain underexplored. Indeed, m-health adoption is not only a technology acceptance behavior, but also a health-related behavior. Materials and Methods: Based on the Protection Motivation Theory, this article explores users' m-health adoption behavior from the perspectives of threat appraisal and coping appraisal, and also examines the moderating role of gender and age through a survey of potential users. The survey was conducted among 500 potential m-health service participants. Results: Our results show that threat appraisal and coping appraisal factors influence adoption intention through attitude. It is also found that gender and age play different moderating roles with threat appraisal and coping appraisal factors. Conclusions: Gender and age play different roles between threat appraisal and coping appraisal factors in the acceptance of m-health. Implications for research and practice are discussed.

Purpose: Mobile health (mHealth) services are considered an important means of relieving the problems of the aging population. The efficiency of mHealth services can be enhanced by engaging more elderly users and guaranteeing their continued use. However, limited attention has been directed toward investigating elderly users' continuance intention regarding mHealth services. The purpose of this paper is to explain elderly users' continuance intention by investigating the contingent role of technology anxiety and health anxiety on affective trust and cognitive trust.Design/methodology/approach: Survey data were collected from 232 elderly users to verify the research model and hypotheses based on structural equation modeling (SEM).Findings: This study revealed that both affective and cognitive trust enhance elderly users' continuance intention regarding their use of mHealth services. Health anxiety strengthens the effect of cognitive trust but weakens the effect of affective trust with regard to continuance intention. Furthermore, technology anxiety strengthens the effect of affective trust but not the effect of cognitive trust with regard to continuance intention.Originality/value: This study is one of the first to examine elderly users' continuance intention regarding mHealth services use from the perspective of affective and cognitive trust, thus enriching the extant literature on the use of mHealth services. Additionally, this study sheds light on the contingent effects of technology anxiety and health anxiety on affective and cognitive trust, which have been neglected by previous research.