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 Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn.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: The Internet has become a major means of acquiring health information due to the increasing demand for health information and the development of the Internet. However, Internet health information is of mixed quality and may therefore significantly affects health-related behaviour and decisions. The trust of patients in their physicians may potentially change because of health information obtained from the Internet, thereby affecting their compliance to medical diagnoses and treatment. Hence, it is significant to discuss the relationship between Internet health information and patient compliance from the perspective of trust. Objective: This study aimed to discuss the relationship between Internet health information and patient compliance from the dimensions of quality and source through theoretical principle (i.e. cognition- and affect-based trust) and empirical study. Methods: An online survey involving 375 participants from 28 cities in China was conducted to assess the research model, which included two independent variables (i.e. Internet health information quality and source of Internet health information), two mediator variables (i.e. cognition- and affect-based trust) and one dependent variable (i.e. patient compliance). All variables were measured using multiple-item scales from previously validated instruments. The scales’ reliability and validity were analysed, demographic analysis was performed and hypotheses were tested using structural equation modelling (SEM). Results: The questionnaire response was 89.6%, and the reliability and validity was acceptable (Cronbach’s α = .950 > .700, KMO = .907 > .700, P < .001). This study indicated that the quality and source of Internet health information impacted cognition- and affect-based trust, consequently, patient compliance. In addition, Internet health information source also directly affected patient compliance, and the Internet health information quality was more important than the source of information. Furthermore, cognition- and affect-based trust had significant positive impacts on patient compliance, and cognition-based trust had a significant impact on affect-based trust. Unexpectedly, a nonsignificant relationship between source of Internet health information and affect-based trust was found. Conclusions: The Internet health information quality plays a more important role than the source of information in impacting patient trust, consequently, patient compliance. Therefore, patient compliance should be improved by strengthening the management of Internet health information quality and urging physicians to focus on health websites, and acquire health information from these websites to understand the information accessed by patients and enrich their knowledge structure to show their specialization and reliability in their interaction with patients. Cognition- and affect-based trust directly impact patient compliance. Therefore, physicians can communicate with patients through health websites to allow patients to acquire health information from physicians online and establish cognition-based trust in advance. Furthermore, physicians should focus on providing care and respect for patients and foster a safe atmosphere in which patients can express themselves sufficiently.

The proposed q-rung orthopair fuzzy set (q-ROFS) and picture fuzzy set (PIFS) are two powerful tools for depicting fuzziness and uncertainty. This paper proposes a new tool, called q-rung picture linguistic set (q-RPLS) to deal with vagueness and impreciseness in multi-attribute group decision-making (MAGDM). The proposed q-RPLS takes full advantages of q-ROFS and PIFS and reflects decision-makers’ quantitative and qualitative assessments. To effectively aggregate q-rung picture linguistic information, we extend the classic Heronian mean (HM) to q-RPLSs and propose a family of q-rung picture linguistic Heronian mean operators, such as the q-rung picture linguistic Heronian mean (q-RPLHM) operator, the q-rung picture linguistic weighted Heronian mean (q-RPLWHM) operator, the q-rung picture linguistic geometric Heronian mean (q-RPLGHM) operator, and the q-rung picture linguistic weighted geometric Heronian mean (q-RPLWGHM) operator. The prominent advantage of the proposed operators is that the interrelationship between q-rung picture linguistic numbers (q-RPLNs) can be considered. Further, we put forward a novel approach to MAGDM based on the proposed operators. We also provide a numerical example to demonstrate the validity and superiorities of the proposed method.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet

(1) Background: As people pay more attention to health, mobile health applications (mHealth apps) are becoming popular. These apps offer health services that run on mobile devices to help improve users’ health behaviors. However, few studies explore what motivates users to continue to use these apps. This study proposes antecedents influencing users’ electronic satisfaction (e-satisfaction) and their continued behaviors of using mHealth apps. Based on the extended Unified Theory of Acceptance and Use of Technology (UTAUT2), this study constructs a research model including perceived reliability and online review to predict the continued usage behavior on mHealth apps in China; (2) Methods: We conduct an online survey to collect data from participants who have used mHealth apps. This study receives 327 valid responses and tests the research model using the partial least squares structural equation model approach; (3) Results: Our results find that antecedents positively affect continued usage intention through the mediation role of e-satisfaction with mHealth apps. Interestingly, this study reveals that habit positively affects the continued usage behavior and moderates the effect of e-satisfaction and continued intention of using mHealth apps; (4) Conclusions: This study presents theoretical implications on the extended UTAUT2 and provides practical implications understanding of managing mHealth apps in China.

In respect to the multi-attribute group decision making (MAGDM) problems in which the evaluated value of each attribute is in the form of q-rung orthopair fuzzy numbers (q-ROFNs), a new approach of MAGDM is developed. Firstly, a new aggregation operator, called the partitioned Maclaurin symmetric mean (PMSM) operator, is proposed to deal with the situations where the attributes are partitioned into different parts and there are interrelationships among multiple attributes in same part whereas the attributes in different parts are not related. Some desirable properties of PMSM are investigated. Then, in order to aggregate the q-rung orthopair fuzzy information, the PMSM is extended to q-rung orthopair fuzzy sets (q-ROFSs) and two q-rung orthopair fuzzy partitioned Maclaurin symmetric mean (q-ROFPMSM) operators are developed. To eliminate the negative influence of unreasonable evaluation values of attributes on aggregated result, we further propose two q-rung orthopair fuzzy power partitioned Maclaurin symmetric mean (q-ROFPPMSM) operators, which combine the PMSM with the power average (PA) operator within q-ROFSs. Finally, a numerical instance is provided to illustrate the proposed approach and a comparative analysis is conducted to demonstrate the advantage of the proposed approach.