Factors Influencing Patients' Intentions to Use Diabetes Management Apps Based on an Extended Unified Theory of Acceptance and Use of Technology Model: Web-Based Survey

Applying the Unified Theory of Acceptance and Use of Technology to Identify Factors Associated With Intention to Use Teledelivered Supportive Care Among Recently Diagnosed Breast Cancer Survivors During COVID-19 in Hong Kong: Cross-Sectional Survey

BACKGROUND

Many supportive cancer care (SCC) services were teledelivered during COVID-19, but what facilitates patients' intentions to use teledelivered SCC is unknown.

OBJECTIVE

The study aimed to use the unified theory of acceptance and use of technology to investigate the factors associated with the intentions of breast cancer survivors (BCS) in Hong Kong to use various types of teledelivered SCC (including psychosocial care, medical consultation, complementary care, peer support groups). Favorable telehealth-related perceptions (higher performance expectancy, lower effort expectancy, more facilitating conditions, positive social influences), less technological anxiety, and greater fear of COVID-19 were hypothesized to be associated with higher intentions to use teledelivered SCC. Moreover, the associations between telehealth-related perceptions and intentions to use teledelivered SCC were hypothesized to be moderated by education level, such that associations between telehealth-related perceptions and intentions to use teledelivered SCC would be stronger among those with a higher education level.

METHODS

A sample of 209 (209/287, 72.8% completion rate) women diagnosed with breast cancer since the start of the COVID-19 outbreak in Hong Kong (ie, January 2020) were recruited from the Hong Kong Breast Cancer Registry to complete a cross-sectional survey between June 2022 and December 2022. Participants' intentions to use various types of teledelivered SCC (dependent variables), telehealth-related perceptions (independent variables), and sociodemographic variables (eg, education, as a moderator variable) were measured using self-reported, validated measures.

RESULTS

Hierarchical regression analysis results showed that greater confidence using telehealth, performance expectancy (believing telehealth helps with daily tasks), social influence (important others encouraging telehealth use), and facilitating conditions (having resources for telehealth use) were associated with higher intentions to use teledelivered SCC (range: β=0.16, P=.03 to β=0.34, P<.001). Moreover, 2-way interactions emerged between education level and 2 of the telehealth perception variables. Education level moderated the associations between (1) performance expectancy and intention to use teledelivered complementary care (β=0.34, P=.04) and (2) facilitating conditions and intention to use teledelivered peer support groups (β=0.36, P=.03). The positive associations between those telehealth perceptions and intentions were only significant among those with a higher education level.

CONCLUSIONS

The findings of this study implied that enhancing BCS' skills at using telehealth, BCS' and their important others' perceived benefits of telehealth, and providing assistance for telehealth use could increase BCS' intentions to use teledelivered SCC. For intentions to use specific types of SCC, addressing relevant factors (performance expectancy, facilitating conditions) might be particularly beneficial for those with a higher education level.

Factors Associated with Intention to Use Telerehabilitation for Children with Special Needs: A Cross-Sectional Study

Background: Children with special health care needs (CSHCN) require long-term and ongoing rehabilitation interventions supporting their development. Telerehabilitation can provide continuous rehabilitation services for CSHCN. However, few studies have explored the intention of CSHCN and their caregivers to use telerehabilitation and its impact on them. Objective: The objective of this study was to identify factors that influence the intention to use telerehabilitation among CSHCN and their caregivers. Methods: This study was a cross-sectional study. Based on the unified theory of acceptance and use of technology, extended with additional predictors (trust and perceived risk [PR]), this study developed a research model and proposed 10 hypotheses. A structured questionnaire was distributed to 176 caregivers. Data were analyzed and research hypotheses were tested using partial least squares structural equation modeling to better understand the factors influencing the use of telerehabilitation. Results: A total of 164 valid questionnaires were collected. CSHCN and their caregivers were overall satisfied with this telerehabilitation medical service. The results of the structural model analysis indicated that social influence (SI), facilitating conditions (FC), and trust had significant effects on behavioral intention (BI) to use telerehabilitation, while the paths between performance expectancy (PE), effort expectancy (EE), and PR and BI were not significant. PE, EE, and SI had a significant effect on trust. Moreover, EE and SI had indirect effects on BI, with trust as the mediator. Conclusions: The results indicated that SI, FC, and trust are significant factors influencing CSHCN and their caregivers' use of telerehabilitation. Trust is also an important mediator for the intention and highly influenced by PE, EE, and SI.

Simplified integration of optimal self-management behaviors is associated with improved HbA1c in patients with type 1 diabetes

PURPOSE

Living with type 1 diabetes requires burdensome and complex daily diabetes self-management behaviors. This study aimed to determine the association between integrated behavior performance and HbA1c, while identifying the behavior with the most significant impact on HbA1c.

METHODS

A simple and feasible questionnaire was used to collect diabetes self-management behavior in patients with type 1 diabetes (n = 904). We assessed six dimensions of behavior performance: continuous glucose monitor (CGM) usage, frequent glucose testing, insulin pump usage, carbohydrate counting application, adjustment of insulin doses, and usage of apps for diabetes management. We evaluated the association between these behaviors and HbA1c.

RESULTS

In total, 21.3% of patients performed none of the allotted behavior, while 28.5% of patients had a total behavior score of 3 or more. 63.6% of patients with a behavior score ≥ 3 achieved HbA1c goal, contrasting with only 30.4% of patients with a behavior score of 0-1. There was a mean 0.54% ± 0.05% decrease in HbA1c for each 1-unit increase in total behavior score after adjustment for age, family education and diabetes duration. Each behavior was independently correlated with a lower HbA1c level, with CGM having the most significant effect on HbA1c levels.

CONCLUSIONS

Six optimal self-management behaviors, especially CGM usage, were associated with improved glycemic control, emphasizing the feasibility of implementing a simplified version of DSMES in the routine clinical care.

REGISTRATION NUMBER

ClinicalTrials.gov Identifier: NCT03610984.

Exploring Patients' Intentions for Usage of Video Telemedicine Follow-Up Services: Cross-Sectional Study

Background: Data suggest that regarding completion rates and lower readmission rates, video telemedicine follow-up is as efficient as in-person consultations. However, evidence of patients' intention to adopt such service is lacking. The objective of this study was to determine the essential factors influencing Chinese patients' intention to adopt video telemedicine follow-up. Methods: The researchers extended the technology acceptance model (TAM) by incorporating trust, subjective norms (SNs), perceived risk (PR), and perceived disease threat (PDT). A survey was conducted with 793 Chinese patients, and the collected data were analyzed using the partial least-squares approach. Results: The study revealed that trust emerged as the strongest factor influencing patients' behavioral intention (BI) to use video telemedicine follow-up, followed by SNs, perceived ease of use (PEOU), and perceived usefulness (PU). PR and PDT had no significant influence on patients' intention to adopt video telemedicine follow-up. PEOU mediated the relationship between trust, SNs, and BI, and PU mediated the relationship between trust and BI. The study also found that gender, age, and usage experience moderated certain relationships in the model. Conclusions: Our findings support the use of the extended TAM in understanding individual's motivations for using video telemedicine follow-up in China. In addition, this study contributes to the existing literature on telemedicine promotion by identifying significant mediation mechanisms. These findings have practical implications for planning, creating, and implementing improved video telemedicine follow-up services.

Acceptance of a Web-Based Intervention in Individuals Who Committed Sexual Offenses Against Children: Cross-Sectional Study

BACKGROUND

Individuals who have committed sexual offenses against children often have difficulties finding treatment, despite its potential effectiveness. Although the development of web-based interventions could enhance therapeutic supply, up to now the acceptance thereof among this target group is unknown.

OBJECTIVE

For the first time, this study assesses the acceptance of a web-based intervention among individuals who committed sexual offenses against children and analyzes variables that predict acceptance. Following the Unified Theory of Acceptance and Use of Technology (UTAUT), it is assumed that acceptance of web-based interventions in individuals who have committed sexual offenses against children follows the same mechanisms as for individuals in general psychiatry.

METHODS

This cross-sectional study is based on the data from an ongoing clinical trial (@myTabu) evaluating the effectiveness of a web-based intervention in individuals who committed sexual offenses against children (N=113). Acceptance level was measured using a questionnaire based on the UTAUT and modified for the target group. Furthermore, predictors of acceptance from the UTAUT (performance expectancy, effort expectancy, and social influence [SI]), attitudes toward web-based interventions, and internet anxiety were assessed at baseline.

RESULTS

Most participants (61.1%, 69/113), reported high acceptance, while 36.3% (41/113) of them indicated moderate acceptance, and 2.7% (3/113) of them expressed low acceptance. In a linear regression model, the predictors explained 41.2% of the variance (F11,101=9.055; P=.01). Attitudes toward web-based interventions (B=0.398, 95% CI 0.16-0.64; P=.001) and SI (B=0.183, 95% CI 0.03-0.38; P=.04) significantly predicted acceptance. Post hoc explorative analysis showed that the participants' belief that people close to them would recommend the use of a web-based intervention is a predictor of acceptance. In contrast, the belief that their community supervisor would recommend the use thereof was not predictive in this respect.

CONCLUSIONS

For the participants of this study, we identified high acceptance of web-based interventions for the majority of participants. SI and the participants' attitudes toward web-based interventions were important in predicting acceptance.

TRIAL REGISTRATION

German Clinical Trial Registration (DRKS, Deutsches Register Klinischer Studien) DRKS 00021256; https://drks.de/search/de/trial/DRKS00021256.

Driving the implementation of hospital examination reservation system through hospital management

BACKGROUND

Hospital Examination Reservation System (HERS) was designed for reducing appointment examination waiting time and enhancing patients' medical satisfaction in China, but implementing HERS would encounter many difficulties. This study would investigate the factors that influence patients' utilization of HERS through UTAUT2, and provide valuable insights for hospital managements to drive the effective implementation of HERS. It is helpful for improving patients' medical satisfaction.

METHODS

We conducted a survey through the Sojump platform, targeting patients were who have already used HERS. We collected questionnaire information related to factors behavior intention, performance expectancy, and effort expectancy. Subsequently, we employed a structural equation model to analyze the factors influencing patients' utilization of HERS.

RESULTS

A total of 394 valid questionnaires were collected. Habit was the main direct positive factor influencing the behavioral intention of HERS (β = 0.593; 95%CI: 0.072, 1.944; P = 0.002), followed by patient innovation (β = 0.269; 95%CI: 0.002, 0.443; P < 0.001), effort expectancy (β = 0.239; 95%CI: -0.022, 0.478; P = 0.048). Patient innovation and facilitating conditions also have an indirect effect on behavioral intention. Perceived privacy exposure has a significantly negative effect on behavioral intention (β=-0.138; 95%CI: -0.225, -0.047; P < 0.001). The above variables explained 56.7% of the variation in behavioral intention.

CONCLUSIONS

When HERS is implemented in hospitals, managements should arrange volunteers to guide patients to bring up the habit and solve the using difficulties, and managements could invite patients with high innovation to recommend HERS to others, what's more, it is a valid way to retain the old form of appointment to pass the transition period to the new system. HERS utilization and patients' medical satisfaction will be enhanced through the guidance of hospital management means.

Factors Influencing the Behavioral Intentions and Use Behaviors of Telemedicine in Patients With Diabetes: Web-Based Survey Study

BACKGROUND

Telemedicine has great potential for diabetes management. The COVID-19 pandemic has boosted the development of telemedicine. However, the factors influencing the behavioral intentions to use and use behaviors of telemedicine in patients with diabetes in China are not clear.

OBJECTIVE

We aimed to understand the determinants of behavioral intention to use telemedicine based on an extended Unified Theory of Acceptance and Use of Technology model and to identify demographic factors associated with telemedicine use in patients with diabetes in China.

METHODS

Patients with diabetes who are aged ≥18 years were surveyed from February 1 to February 7, 2023. We distributed the survey link in 3 WeChat groups including a total of 988 patients with diabetes from the outpatient department or patients discharged from Changsha Central Hospital. Structural equation modeling was used to understand the determinants of behavioral intention. A multivariate logistic regression analysis was used to identify the demographic factors associated with telemedicine use.

RESULTS

In total, 514 questionnaires were collected. Of the respondents, 186 (36.2%) were diagnosed with COVID-19. The measurement model showed acceptable reliability, convergent validity, discriminant validity, and data fit indices. The model explained 63.8% of the variance in behavioral intention. Social influence, performance expectancy, and facilitating conditions positively influenced behavioral intention (β=.463, P<.001; β=.153, P=.02; and β=.257, P=.004, respectively). Perceived susceptibility, perceived severity, and effort expectancy had no significant impact on behavioral intention (all P>.05). The overall use of telemedicine was 20.6% (104/514). After adjusting for the behavioral intention score, the multivariate regression analysis showed that age, education, and family income were associated with telemedicine use. Telemedicine use was higher in the 40 to 59 years and 18 to 39 years age groups than in the ≥60 years age group (odds ratio [OR] 4.35, 95% CI 1.84-10.29, P=.001; OR 9.20, 95% CI 3.40-24.88, P<.001, respectively). Telemedicine use was higher in the senior high school and the university and more groups than in junior high school education and less group (OR 2.45, 95% CI 1.05-5.73, P=.04; OR 2.63, 95% CI 1.11-6.23, P=.03, respectively). Patients with a higher family income used telemedicine more often than the patients who had an annual family income ≤¥10,000 (CNY ¥1=US $0.1398; ¥10,000-¥50,000 group: OR 3.90, 95% CI 1.21-12.51, P=.02; ¥50,000-¥100,000 group: OR 3.91, 95% CI 1.19-12.79, P=.02; >¥100,000 group: OR 4.63, 95% CI 1.41-15.27, P=.01).

CONCLUSIONS

Social influence, performance expectancy, and facilitating conditions positively affected the behavioral intention of patients with diabetes to use telemedicine. Young patients, highly educated patients, and patients with high family income use telemedicine more often. Promoting behavioral intention and paying special attention to the needs of older adult patients, patients with low income, and patients with low levels of education are needed to encourage telemedicine use.

Intention to use a mobile phone to receive mental health support and its predicting factors among women attending antenatal care at public health facilities in Ambo town, West Shoa zone, Ethiopia 2022

BACKGROUND

Mental health problems are the most common morbidities of women during the prenatal period. In LMICs mobile phones have been identified as a good vehicle for monitoring individuals with a high risk of mental health conditions. However, evidence is scarce and the purpose of this study was to assess the intention to use a mobile phone to receive mental health support and its predicting factors among women attending antenatal care at public health facilities in Ambo town, Ethiopia 2022.

METHODS AND MATERIALS

An institutional-based cross-sectional study design was conducted from May 20th to June 20th, 2022. A total of 715 prenatal women were included and a systematic random sampling technique was employed. An interviewer-administered structured questionnaire was used. Collected data was exported to SPSS version 25 for the descriptive part, and AMOS 26 structural equation modeling was also used to describe and assess the degree and significance of relationships between variables.

RESULTS

A total of 699 (97.8% response rate) responded to complete all the questionnaires. About 530 (77.3%) 95% CI (74%-80.3%) of women intended to use a mobile phone to receive mental health support. The perceived usefulness has a positive effect on attitude (β = 0.391, p < 0.001) and intention to use (β = 0.253, p < 0.001). The perceived ease of use influences perceived usefulness (β = 0.253, p < 0.001) and attitude β = 0.579, p < 0.001). The intention to use is positively affected by attitude (β = 0.662, p < 0.001).Trust has a positive effect on perceived usefulness (β = 0.580, p < 0.001) and intention to use (β = 0.113, p = 0.005). Subjective norm has a direct positive effect on perceived usefulness (β = 0.248, p < 0.001). Attitude serves as a partial mediator between perceived usefulness and intention to use and a complete mediating role between perceived ease of use and intention to use.

CONCLUSION

The level of intention to use a mobile phone among prenatal women is relatively high and attitude, perceived usefulness, and trust had direct positive effects on intention to use a mobile phone. Therefore, hospitals and healthcare providers should take proactive measures to implement the strategies and policies for providing mobile phone-based mental health support to prenatal women in remote areas.

Mobile-Based Application Interventions to Enhance Cancer Control and Care in Low- and Middle-Income Countries: A Systematic Review

Objective: To identify and appraise mobile-based application (mAPP) interventions that have been used to support cancer control and care in low- and middle-income countries (LMICs). Methods: Four electronic databases were systematically searched for studies that reported primary research findings related to mAPP interventions applied in oncology settings in LMICs. A narrative synthesis was performed using the Mhealth Index and Navigation Database as an analytical framework. Results: Twenty studies reporting 18 cancer control and care mAPPs were included in this review. Among these mAPPs, ten focused on prevention, screening and early detection of cancer, five provided information to optimise supportive and palliative care, two provided support to assist treatment-shared decision-making and one covered information for follow-up and survivorship care. Conclusion: Cancer mAPP interventions are gradually gaining attention in LMICs as they provide unique resources for empowering and strengthening the role of people with cancer in their own care. To enhance cancer control, a focus on prevention and early detection is important; however, more mAPP interventions related to cancer treatment, follow-up and survivorship are also needed to enable more cost-effective cancer care.

Adoption of Wearable Insulin Biosensors for Diabetes Management: A Cross-Sectional Study

BACKGROUND

Wearable insulin biosensors represent a novel approach that combines the benefits of real-time glucose monitoring and automated insulin delivery, potentially revolutionizing how individuals with diabetes manage their condition.

STUDY PURPOSE

To analyze the behavioral intentions of wearable insulin biosensors among diabetes patients, the factors that drive or hinder their usage, and the implications for diabetes management and healthcare outcomes.

METHODS

A cross-sectional survey design was adopted in this study. The validated questionnaire included 10 factors (Performance expectancy, effort expectancy, social influence, facilitating conditions, behavioral intention, trust, perceived privacy risk, and personal innovativeness) affecting the acceptance of wearable insulin sensors. A total of 248 diabetic patients who had used wearable sensors participated in the study.

RESULTS

Performance expectancy was rated the highest (Mean = 3.84 out of 5), followed by effort expectancy (Mean = 3.78 out of 5), and trust (Mean = 3.53 out of 5). Statistically significant differences (p < 0.05) were observed with respect to socio-demographic variables including age and gender on various influencing factors and adoption intentions. PE, EE, and trust were positively associated with adoption intentions.

CONCLUSION

While wearable insulin sensors are positively perceived with respect to diabetes management, issues like privacy and security may affect their adoption.

Identification of psychological constructs for a positive psychology intervention to assist with the adjustment to closed loop technology among adolescents living with type 1 diabetes

Aim

Adolescents have been identified as the group who struggle most with successful adjustment to closed loop technology. This study aims to identify the psychological constructs that should form part of a positive psychology intervention to assist with the adjustment to closed loop technology among adolescents living with type 1 diabetes.

Method

Qualitative document analysis was employed to integrate findings from two documents: a published ongoing intervention study and a recent phenomenological study by the authors. Reflexive thematic analysis was used to identify themes from the documents.

Findings

The following themes were identified as important psychological constructs that aid adjustment: the importance of knowledge and education; the process of positive adjustment to closed loop technology; a positive outlook; and building a relationship with diabetes.

Conclusion

Interventions are needed to assist adolescents in their adjustment to closed loop technology. The psychological constructs identified served as a starting point in designing an effective, evidence-based intervention grounded in data and theory. Knowledge and education, responsibility, identity, positive affect, gratitude, support, and trust are psychological constructs that need to be included in an intervention program.

Acceptability and Usability of a Theory-Driven Intervention via Email to Promote Physical Activity in Women Who Are Overweight or Obese: Substudy Within a Randomized Controlled Trial

BACKGROUND

Insufficient physical activity (PA) and excess weight increase illness risk for women. Face-to-face interventions can increase PA levels; however, they are often inaccessible. With growing interest in digital interventions, a Self-Determination Theory (SDT)-driven intervention was developed and delivered via email to promote PA in women who were insufficiently active and overweight or obese.

OBJECTIVE

This substudy explores users' perspectives about the acceptability and usability of the intervention, which was coupled with a wearable activity monitor and PA recommendations.

METHODS

A 3-arm, parallel group, randomized controlled trial (unblinded) was conducted in Ontario, Canada. Recruitment occurred from September 2018 to March 2019 via advertising through social media, web-based boards, and posters in publicly accessible areas. In total, 47 women with a BMI of ≥25 kg/m2 who were not meeting the Canadian PA guidelines were randomly assigned to 1 of 3 arms (arm 1: n=15, 32%; arm 2: n=16, 34%; arm 3: n=16, 34%). This substudy focused on the 15 participants allocated to the main intervention arm. Participants received an automated intervention consisting of (1) 6 weekly emails, (2) a Polar Electro Inc A300 activity monitor (with access to the Polar Flow website and companion smartphone app), and (3) a copy of the Canadian PA guidelines for adults. Emails were developed using SDT and designed to enhance autonomous motivation by fostering the psychological needs of competence, autonomy, and relatedness. Well-established motivational and behavior change techniques were embedded in the emails to promote needs satisfaction. After the intervention (ie, 7 weeks after randomization), participants were invited to complete a web-based acceptability and usability survey containing open-ended and closed-ended questions; responses were analyzed using descriptive and content analyses, respectively.

RESULTS

The analyses included data from 93% (14/15) of the women (age: mean 33.4, SD 7.5; range 24-44 years; BMI: mean 31.3, SD 5.8 kg/m2; range 25-40.5 kg/m2) who received the main intervention and completed the postintervention survey. Open-ended responses indicated that participants were generally satisfied with the intervention and appreciated that emails prompted self-reflection, kept them on track and accountable, provided informational support, and were nonpressuring. Furthermore, they suggested that the monitor was "enjoyable" and "helpful"; quantitative data corroborated this, as 71% (10/14) said that the monitor was "very valuable/absolutely valuable," 71% (10/14) would "very probably/definitely" still use one, and 86% (12/14) wore it for ≥5 days per week for ≥8 hours per day and checked it "occasionally/frequently/very frequently." Potential threats to acceptability included "long" and "text-heavy" emails; lack of personal contact; and cumbersome, unaesthetic monitors.

CONCLUSIONS

Results suggest that this SDT-driven, email-delivered intervention may be an acceptable low-contact approach to promote PA in women who are overweight or obese and insufficiently active; however, improvements are warranted and studies ascertaining its effectiveness are needed.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03601663; http://clinicaltrials.gov/ct2/show/NCT03601663.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1177/20552076221093134.

A Mobile Health Information Behavior Model: Theoretical Development and Mixed-Method Testing in the Context of Mobile Apps on Child Poisoning Prevention

While several studies have explored the use of mobile health applications, few have observed determinants of mobile health information behavior. To develop a model explaining parents' mobile information behavior on child poisoning prevention, we first explored relevant theories to suggest a theoretical model. In that, we combine existing models on risk and health information seeking, such as the Planned Risk Information Seeking Model, with models on the acceptance of mobile technologies, such as the Unified Theory of Acceptance and Use of Technologies. Thereafter, we employed a sequential mixed-method design with an initial qualitative study (four online focus groups with n = 25 parents in total) and a standardized online survey of n = 1,013 parents to evaluate our research model. Results confirm that both, determinants of information seeking and determinants of technology acceptance, contribute to the explanation of mobile information behavior. App use intention was mainly related to the performance expectancy of app use, the subjective information norm, and social influence on app use. To increase the usage of prevention apps and contribute to the reduction of child injuries, communication on poisoning apps should address subdimensions of the performance expectancy, such as their utility and peoples' trust in app providers. Moreover, physicians are important multipliers for these messages.

A Diabetes Education App for People Living With Type 2 Diabetes: Co-Design Study

BACKGROUND

Type 2 diabetes (T2D) is a growing global health concern, including in Singapore. Diabetes education programs have been shown to be effective in improving health outcomes and diabetes self-management skills. Mobile health apps have emerged as useful tools for diabetes education; however, their use and acceptance by the target population remain inconsistent. Therefore, end-user participation in the design and development of a mobile health app is crucial for designing an acceptable app that can improve outcomes for populations with a chronic disease.

OBJECTIVE

The objective of this study was to apply an end-user participatory approach to co-design a diabetes education app prototype for people living with T2D by exploring their perceptions, acceptance, and usability of an app prototype, as well as their diabetes experience and perspectives on digital diabetes education.

METHODS

A total of 8 people with T2D, who were recruited from diabetes management Facebook groups, participated in 4 web-based surveys via Qualtrics and 2 structured interviews via Zoom (Zoom Video Communications, Inc) between August 20, 2021, and January 28, 2022. Descriptive statistics and thematic analyses of the discussion and iterative feedback on the app prototype were used to assess the participants' perceptions of living with T2D, attitudes toward digital diabetes education, and acceptance of the prototype.

RESULTS

Analyses of the surveys and interview data revealed 3 themes: challenges of living with T2D; validation, acceptability, and usability of the diabetes education app prototype; and perspectives on digital diabetes education. In the first theme, participants highlighted the importance of solitary accountability, translating knowledge into practice, and developing pragmatic self-consciousness. The second theme indicated that the diabetes education app prototype was acceptable, with information and appearance being key; revealed ambivalent and polarized opinions toward the chatbot; and confirmed potential impact of the app on diabetes self-management skills and practice. The third theme comprised the necessity of using a variety of information-seeking strategies and recommendations for desired content and app qualities, including accessibility, adaptability, autonomy, evidence-based design and content, gamification, guidance, integration, personalization, and up-to-date content. The findings were used to reiterate the app design.

CONCLUSIONS

Despite a small sample size, the study demonstrated the feasibility of engaging and empowering people living with T2D to consider digital therapeutics for diabetes self-management skills and practice. Participants gave rather positive feedback on the design and content of the app prototype, with some recommendations for improvements. The findings suggest that incorporating end-user feedback into app design can lead to the creation of feasible and acceptable tools for diabetes education, potentially improving outcomes for populations with a chronic disease. Further research is needed to test the impact of the refined diabetes education app prototype on diabetes self-management skills and practice and quality of life.

Understanding the mobile healthcare applications continuance: The regulatory focus perspective

BACKGROUND

Although mobile healthcare (mHealth) applications have proliferated and offer new opportunities for personal health management, many users exhibit discontinuance behavior. Various factors in mHealth applications can strongly impact users' continuance behavior, but it is not yet fully understood how they interact with each other to yield maximized effects. This study highlights the importance of identifying the antecedents and moderators of continuance intention to broaden the demographic reach of mHealth applications and thus contribute to maintaining a sustainable healthcare system.

OBJECTIVE

This research explores three dimensions of perceived values (hedonic, utilitarian, and social) in mHealth platforms that lead to user satisfaction and, ultimately, continuance intention. It further investigates the moderating effects of personal traits defined by regulatory focus on the relationship between perceived value and user satisfaction.

METHODS

Data was collected from 259 respondents with experience using the Samsung Health application. The research tests the proposed model and hypotheses by implementing PLS-SEM and multi-group analyses.

RESULTS

Each dimension of perceived values positively influences user satisfaction, with hedonic and utilitarian values exhibiting stronger relationships. Regarding moderating effects, promotion (versus prevention) focus has a stronger enhancing effect on the positive relationship between utilitarian value and user satisfaction. In contrast, prevention (versus promotion) focus more strongly enhances the positive relationship between hedonic value and user satisfaction. Regulatory focus does not yield a significant moderating effect on the relationship between social value and user satisfaction. User satisfaction exerts a strong positive influence on continuance intention in mHealth environments.

CONCLUSIONS

The moderating effect of individuals' regulatory focus has been identified. Combined effects of antecedents and moderators on user satisfaction influence their continuance intention in mHealth ecologies. Considering individual users' characteristics may guide mHealth application developers to design personalized platforms and establish enforced marketing strategies.

Exploring factors that influence the behavioural intention of medical students to use 3D gastroscopic model to learn how to operate gastroscope using UTAUT Model

BACKGROUND

The application of virtual reality (VR) in gastroscopic operation teaching can be safe and effective, but the advantages can be realized only when students accept and use it. This study aims to identify the factors influencing Chinese clinical medical postgraduates on their intention to use the 3D gastroscopic model constructed based on VR technology using Unified Theory of Acceptance and Use of Technology (UTAUT) model. Students' demographic factors are also taken into consideration.

METHODS

All methods were carried out in accordance with relevant guidelines. Data were collected from clinical medical postgraduates students in China using stratified sampling. A total of 292 questionnaires including valid responses were used in this study. Data were processed using Amos 24.0 and SPSS 26.0 software and the statistical analysis technique was based on structural equation modeling (SEM).

RESULTS

The results showed that different from the mediator of home location and year of clinical learning, mediator of gender, university kind and graduate degree did not affect the behavioral intention. In addition, performance expectancy, facilitating condition, and social influence directly and indirectly have effect on behavioral intention. Also, the significance between social influence and performance expectancy, social influence and effort expectancy were verified.

CONCLUSIONS

This study manifested that the proposed framework based on the UTAUT had explanatory power to identify the factors influencing the students' behavioral intention to use the 3D gastroscopic model constructed based on VR technology. Whereas, an important variable of effort expectancy in the frame of the SEM were not certified, thereby indicating that particular attention should be paid to this variable by universities and teachers before applying 3D gastroscopic model constructed based on VR technology in teaching. Added preparatory work is required such as explaining the basic knowledge of the operating steps of VR model and make students adequately understand its accessibility, which can probably improve the intentions of them to use it. The positive effects of social influence on performance expectancy and effort expectancy we proposed was also verified in this study, which provided a direction for future research.

Changed Digital Technology Perceptions and Influencing Factors among Older Adults during the COVID-19 Pandemic

This correlational study aimed to identify factors that contribute to changes in perceptions of digital technology among older adults during the COVID-19 pandemic. This study utilized raw data from "The 2021 Report on the Digital Divide," a nationwide survey conducted in South Korea. Data were collected from 1171 older adults (aged ≥ 65 years) from September to December 2021. Multiple regression analyses were performed to examine the factors influencing changes in the perception of digital technology. Over one-third of the participants reported positive changes in their perceptions of digital technology during the pandemic. Key factors included self-efficacy for digital devices (β = 0.35, p < 0.001), digital networking (β = 0.11, p < 0.001), accessibility to digital devices (β = 0.10, p = 0.002), and perceived health (β = 0.08, p = 0.003). The expansion of digital technology owing to the pandemic has served as a catalyst for changes in older adults' perceptions. Healthcare providers and caregivers should consider digital technology perceptions and influencing factors when providing digital healthcare services. The results can be utilized to identify vulnerable older adults with negative perceptions of digital technology, thus minimizing disparities in access to digital healthcare services.

Improving Predictability and Effectiveness in Preventive Digital Health Interventions: Scoping Review

BACKGROUND

Lifestyle-related diseases caused by inadequate diet and physical activity cause premature death, loss of healthy life years, and increased health care costs. Randomized controlled trial (RCT) studies indicate that preventive digital health interventions (P-DHIs) can be effective in preventing these health problems, but the results of these studies are mixed. Adoption studies have identified multiple factors related to individuals and the context in which they live that complicate the transfer of positive results from RCT studies to practical use. Implementation studies have revealed barriers to the large-scale implementation of mobile health (mHealth) solutions in general. Consequently, there is no clear path to delivering predictable outcomes from P-DHIs and achieving effectiveness when scaling up interventions to reduce health problems in society.

OBJECTIVE

This research aimed to expand our understanding of how to increase the outcome predictability of P-DHIs by focusing on physical activity and diet behaviors and amplify our understanding of how to improve effectiveness in large-scale implementations.

METHODS

The research objective was pursued through a multidisciplinary scoping review. This scoping review used the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) as a guide. A comprehensive search of Web of Science and PubMed limited to English-language journal articles published before January 2022 was conducted. Google Scholar was used for hand searches. Information systems theory was used to identify key constructs influencing outcomes of IT in general. Public health and mHealth literature were used to identify factors influencing the adoption of, outcomes from, and implementation of P-DHIs. Finally, the P-DHI investment model was developed based on information systems constructs and factors from the public health and mHealth literature.

RESULTS

In total, 203 articles met the eligibility criteria. The included studies used a variety of methodologies, including literature reviews, interviews, surveys, and RCT studies. The P-DHI investment model suggests which constructs and related factors should be emphasized to increase the predictability of P-DHI outcomes and improve the effectiveness of large-scale implementations.

CONCLUSIONS

The research suggests that outcome predictability could be improved by including descriptions of the constructs and factors in the P-DHI investment model when reporting from empirical studies. Doing so would increase our understanding of when and why P-DHIs succeed or fail. The effectiveness of large-scale implementations may be improved by using the P-DHI investment model to evaluate potential difficulties and possibilities in implementing P-DHIs to create better environments for their use before investing in them and when designing and implementing them. The cost-effectiveness of large-scale implementations is unknown; implementations are far more complicated than just downloading and using apps, and there is uncertainty accompanying implementations given the lack of coordinated control over the constructs and factors that influence the outcome.

Factors Predicting Older People's Acceptance of a Personalized Health Care Service App and the Effect of Chronic Disease: Cross-Sectional Questionnaire Study

BACKGROUND

Mobile health (mHealth) services enable real-time measurement of information on individuals' biosignals and environmental risk factors; accordingly, research on health management using mHealth is being actively conducted.

OBJECTIVE

The study aims to identify the predictors of older people's intention to use mHealth in South Korea and verify whether chronic disease moderates the effect of the identified predictors on behavioral intentions.

METHODS

A cross-sectional questionnaire study was conducted among 500 participants aged 60 to 75 years. The research hypotheses were tested using structural equation modeling, and indirect effects were verified through bootstrapping. Bootstrapping was performed 10,000 times, and the significance of the indirect effects was confirmed through the bias-corrected percentile method.

RESULTS

Of 477 participants, 278 (58.3%) had at least 1 chronic disease. Performance expectancy (β=.453; P=.003) and social influence (β=.693; P<.001) were significant predictors of behavioral intention. Bootstrapping results showed that facilitating conditions (β=.325; P=.006; 95% CI 0.115-0.759) were found to have a significant indirect effect on behavioral intention. Multigroup structural equation modeling testing the presence or absence of chronic disease revealed a significant difference in the path of device trust to performance expectancy (critical ratio=-2.165). Bootstrapping also confirmed that device trust (β=.122; P=.039; 95% CI 0.007-0.346) had a significant indirect effect on behavioral intention in people with chronic disease.

CONCLUSIONS

This study, which explored the predictors of the intention to use mHealth through a web-based survey of older people, suggests similar results to those of other studies that applied the unified theory of acceptance and use of technology model to the acceptance of mHealth. Performance expectancy, social influence, and facilitating conditions were revealed as predictors of accepting mHealth. In addition, trust in a wearable device for measuring biosignals was investigated as an additional predictor in people with chronic disease. This suggests that different strategies are needed, depending on the characteristics of users.

Factors influencing user acceptance of weight management apps among Chinese obese individuals during the COVID-19 pandemic

Background

During the COVID-19 epidemic, the number of obesities increased rapidly in China. Weight management apps have potential value in controlling obesity.

Objective

Explore the mechanisms behind the adoption of weight management applications by overweight and obese individuals, including psychological factors and demographic variables.

Methods

The theoretical model was extended from the technology acceptance model (TAM), and the structural equation model was used for hypothesis testing. From January 2020 to December 2021, we conducted a cross-sectional survey in six megacities in mainland China during the COVID-19 pandemic by an online questionnaire.

Results

1364 participants completed the questionnaire, and the proposed theoretical model explained 55.7% of the variance in behavioral intention. Perceived usefulness was predicted by perceived ease of use (β = 0. 290), attitude was jointly predicted by perceived usefulness (β = 0.118) and perceived ease of use (β = 0.159). Behavioral intention was predicted by perceived usefulness (β = 0. 256), perceived ease of use (β = 0. 463), attitude (β = 0. 293), and perceived risk (β = -0.136). Health awareness (β=0.016) did not significantly affect behavioral intention. Four demographic variables gender, age, education, and residence exerted significant moderating effects in theoretical model.

Conclusions

During the COVID-19 epidemic, the health awareness and behavior patterns of obese people have changed significantly. Psychological factors and demographic characteristics dynamically interact to generate user behavioral intentions of weight management applications. Weight management application developers and marketers should focus on perceived usefulness, safety, ease of use, and health awareness.

A fuzzy-set qualitative comparative analysis exploration of multiple paths to users' continuous use behavior of diabetes self-management apps

BACKGROUND

Despite the obvious potential benefits of diabetes self-management apps, users' continuous use of diabetes self-management apps is still not widespread. Influential factors coexisted in information ecologies are likely to have a synthetic effect on users' continuous use behavior. However, it is less clear how factors in information ecologies combine to influence users' continuous use behavior.

OBJECTIVE

The objectives of this study are to explore combinations of factors (perceived severity, information quality, service quality, system quality, and social influence) in information ecologies that lead to users' continuous use behavior of diabetes self-management apps and which combination is the most important.

METHODS

Purpose sampling was used to recruit diabetes self-management app users from July 1, 2021 to January 31, 2022. Fuzzy-set qualitative comparative analysis (fsQCA) was then employed by conducting necessity and sufficiency analysis.

RESULTS

In total 280 diabetes self-management app users participated. The necessity analysis indicated that no single factor was necessary to cause users' continuous use behavior, and the sufficiency analysis identified five different combinations of factors that lead to users' continuous use behavior. Of these five, the combination of high information quality, high service quality, and high social influence was found to be the most important path.

CONCLUSIONS

Users' continuous use behavior of diabetes self-management apps results from the synergistic effects of factors in information ecologies. The five paths that directly contribute to users' continuous use, as well as the four user types preliminarily identified in this study may provide a reference for healthcare providers and app developers.

Determinants Influencing the Adoption of Internet Health Care Technology Among Chinese Health Care Professionals: Extension of the Value-Based Adoption Model With Burnout Theory

BACKGROUND

The global COVID-19 pandemic has been widely regarded as a catalyst for adopting internet health care technology (IHT) in China. IHT consists of new health care technologies that are shaping health services and medical consultations. Health care professionals play a substantial role in the adoption of any IHT, but the consequences of doing so can often be challenging, particularly when employee burnout is prevalent. Few studies have explored whether employee burnout influences the adoption intention of IHT in health care professionals.

OBJECTIVE

This study aims to explain the determinants influencing the adoption of IHT from the perspective of health care professionals. To do so, the study extends the value-based adoption model (VAM) with consideration for employee burnout as a determining factor.

METHODS

A cross-sectional web-based survey using a sample of 12,031 health care professionals selected through multistage cluster sampling from 3 provinces in mainland China was conducted. The hypotheses of our research model were developed based on the VAM and employee burnout theory. Structural equation modeling was then used to test the research hypotheses.

RESULTS

The results indicate that perceived usefulness, perceived enjoyment, and perceived complexity positively correlate with perceived value (β=.131, P=.01; β=.638, P<.001; β=.198, P<.001, respectively). Perceived value had a positive direct effect on adoption intention (β=.725, P<.001), perceived risk negatively correlated with perceived value (β=-.083, P<.001), and perceived value negatively correlated with employee burnout (β=-.308, P<.001). In addition, employee burnout was negatively related to adoption intention (β=-.170, P<.001) and mediated the relationship between perceived value and adoption intention (β=.052, P<.001).

CONCLUSIONS

Perceived value, perceived enjoyment, and employee burnout were the most important determinants of IHT adoption intention by health care professionals. In addition, while employee burnout was negatively related to adoption intention, perceived value inhibited employee burnout. Therefore, this study finds that it is necessary to develop strategies to improve the perceived value and reduce employee burnout, which will benefit the promotion of the adoption intention of IHT in health care professionals. This study supports the use of the VAM and employee burnout in explaining health care professionals' adoption intention regarding IHT.

Toward Diabetes Device Development That Is Mindful to the Needs of Young People Living With Type 1 Diabetes: A Data- and Theory-Driven Qualitative Study

BACKGROUND

An important strategy to understand young people's needs regarding technologies for type 1 diabetes mellitus (T1DM) management is to examine their day-to-day experiences with these technologies.

OBJECTIVE

This study aimed to examine young people's and their caregivers' experiences with diabetes technologies in an exploratory way and relate the findings to the existing technology acceptance and technology design theories. On the basis of this procedure, we aimed to develop device characteristics that meet young people's needs.

METHODS

Overall, 16 in-person and web-based face-to-face interviews were conducted with 7 female and 9 male young people with T1DM (aged between 12 and 17 years) and their parents between December 2019 and July 2020. The participants were recruited through a pediatric diabetes clinic based at Canberra Hospital. Data-driven thematic analysis was performed before theory-driven analysis to incorporate empirical data results into the unified theory of acceptance and use of technology (UTAUT) and value-sensitive design (VSD). We used the COREQ (Consolidated Criteria for Reporting Qualitative Research) checklist for reporting our research procedure and findings. In this paper, we summarize the key device characteristics that meet young people's needs.

RESULTS

Summarized interview themes from the data-driven analysis included aspects of self-management, device use, technological characteristics, and feelings associated with device types. In the subsequent theory-driven analysis, the interview themes aligned with all UTAUT and VSD factors except for one (privacy). Privacy concerns or related aspects were not reported throughout the interviews, and none of the participants made any mention of data privacy. Discussions around ideal device characteristics focused on reliability, flexibility, and automated closed loop systems that enable young people with T1DM to lead an independent life and alleviate parental anxiety. However, in line with a previous systematic review by Brew-Sam et al, the analysis showed that reality deviated from these expectations, with inaccuracy problems reported in continuous glucose monitoring devices and technical failures occurring in both continuous glucose monitoring devices and insulin pumps.

CONCLUSIONS

Our research highlights the benefits of the transdisciplinary use of exploratory and theory-informed methods for designing improved technologies. Technologies for diabetes self-management require continual advancement to meet the needs and expectations of young people with T1DM and their caregivers. The UTAUT and VSD approaches were found useful as a combined foundation for structuring the findings of our study.

A qualitative exploration of the experiences of peer leaders in an intervention to improve diabetes medication adherence in African Americans

BACKGROUND

African Americans chronically managing their diabetes benefit from receiving support from peers with shared experiences. Peer support is known to improve the well-being of individuals receiving support, however, there is limited literature on the experiences of those providing the support. The Peers Supporting Health Literacy, Self-efficacy, Self-Advocacy, and Adherence (Peers LEAD) program pairs Peer Ambassadors who are adherent to their diabetes medication, with Peer Buddies who need support with their medication adherence. Peer Ambassadors engage with Peer Buddies as they receive diabetes information, develop the skills and motivation to address identified psychosocial/sociocultural issues to enhance their diabetes medication adherence. This study qualitatively explores the experiences of African Americans who provided peer support in the Peers LEAD medication adherence intervention.

METHODS

Two focus groups were conducted with twelve Peer Ambassadors to explore their experiences of providing peer support in the Peers LEAD medication adherence intervention. Qualitative content analysis was conducted using an inductive open coding approach.

RESULTS

Emergent themes provided insight into Peer Ambassador' rationale for providing peer support and the benefits and challenges they experienced in their roles. Themes regarding their rationale included: their desire to receive support for their diabetes self-management as well as to contribute to their communities in reducing the stigma associated with diabetes. The perceived benefits they gained centered on creating interpersonal connections, experiencing personal growth as they adapted to their roles, and experiencing opportunities to contribute to an intervention regardless of professional training. Peer Ambassadors reflected on the challenges which included difficulties on coming to terms with their role as Peer Ambassadors, seeing African Americans experience complications associated with diabetes, and navigating supporting Peer Buddies who are also burdened with the challenges their family members are experiencing with managing their diabetes.

CONCLUSIONS

This study provides unique insight to what motivates individuals to provide peer support and what they gain from these experiences despite the challenges. Understanding the experiences of peers participating in such interventions may help inform the structure and content of programs that use peer support to focus on the benefits of and the motivation for participating in the program.

Public perceptions on the application of artificial intelligence in healthcare: a qualitative meta-synthesis

OBJECTIVES

Medical artificial intelligence (AI) has been used widely applied in clinical field due to its convenience and innovation. However, several policy and regulatory issues such as credibility, sharing of responsibility and ethics have raised concerns in the use of AI. It is therefore necessary to understand the general public's views on medical AI. Here, a meta-synthesis was conducted to analyse and summarise the public's understanding of the application of AI in the healthcare field, to provide recommendations for future use and management of AI in medical practice.

DESIGN

This was a meta-synthesis of qualitative studies.

METHOD

A search was performed on the following databases to identify studies published in English and Chinese: MEDLINE, CINAHL, Web of science, Cochrane library, Embase, PsycINFO, CNKI, Wanfang and VIP. The search was conducted from database inception to 25 December 2021. The meta-aggregation approach of JBI was used to summarise findings from qualitative studies, focusing on the public's perception of the application of AI in healthcare.

RESULTS

Of the 5128 studies screened, 12 met the inclusion criteria, hence were incorporated into analysis. Three synthesised findings were used as the basis of our conclusions, including advantages of medical AI from the public's perspective, ethical and legal concerns about medical AI from the public's perspective, and public suggestions on the application of AI in medical field.

CONCLUSION

Results showed that the public acknowledges the unique advantages and convenience of medical AI. Meanwhile, several concerns about the application of medical AI were observed, most of which involve ethical and legal issues. The standard application and reasonable supervision of medical AI is key to ensuring its effective utilisation. Based on the public's perspective, this analysis provides insights and suggestions for health managers on how to implement and apply medical AI smoothly, while ensuring safety in healthcare practice.

PROSPERO REGISTRATION NUMBER

CRD42022315033.

Factors affecting wearable ECG device adoption by general practitioners for atrial fibrillation screening: cross-sectional study

Introduction

Atrial fibrillation (AF) is a challenging cardiovascular disease worldwide. Wearable electrocardiograph devices (WEDs) have great potential to improve the detection rate of AF in primary care. However, the factors that influence general practitioners' (GPs) perception and acceptance of WEDs are not well understood. To identify factors that influence the intention of GPs to utilize WEDs in a clinical setting to screen patients for AF.

Method

The research hypotheses and questionnaire items were designed and developed based on the unified theory of acceptance and technology (UTAUT) framework. We used stratified sampling and obtained the data through an online survey. Structural equation modeling was used to analyze the collected data.Results: A total of 1,004 valid questionnaires from GPs across Sichuan province in China were collected. Three factors increased GPs' intention to utilize WEDs to screen patients for AF, including performance expectancy (β = 0.121, p = 0.004), social influence (β = 0.356, p < 0.001), and price perception (β = 0.587, p < 0.001). Perception risk (β = -0.059, p < 0.001) decreased usage intention, while effort expectancy (β = -0.079, p = 0.155) and facilitating conditions (β = -0.014, p = 0.868) did not affect usage intention. Gender (β = -0.022, p = 0.179), age (β = 0.006, p = 0.699), education level (β = -0.22, p = 0.184) and training (β = 0.007, p = 0.69) were not significantly correlated with usage intention, and these four factors had no moderating effect on the path coefficients.

Discussion

GPs' intention to utilize WEDs is affected by performance expectancy, price perception, perception risk and social influence. Researcher should improve the usability and perception of WEDs for screening and carry out studies to provide high-quality evidence for the security and efficacy of wearable devices.

How information processing and risk/benefit perception affect COVID-19 vaccination intention of users in online health communities

Objective

To investigate the relationship among information processing, risk/benefit perception and the COVID-19 vaccination intention of OHCs users with the heuristic-systematic model (HSM).

Methods

This study conducted a cross-sectional questionnaire via an online survey among Chinese adults. A structural equation model (SEM) was used to examine the research hypotheses.

Results

Systematic information processing positively influenced benefit perception, and heuristic information processing positively influenced risk perception. Benefit perception had a significant positive effect on users' vaccination intention. Risk perception had a negative impact on vaccination intention. Findings revealed that differences in information processing methods affect users' perceptions of risk and benefit, which decide their vaccination intention.

Conclusion

Online health communities can provide more systematic cues and users should process information systematically to increase their perceived benefits, consequently increase their willingness to receive COVID-19 vaccine.

Patterns of acceptance and use of digital health services among the persistent frequent attenders of outpatient care: A qualitatively driven multimethod analysis

Objective

Utilising digital health services in the treatment of patients who frequently attend outpatient care could be beneficial for patients' health and the sustainability of health systems but carries the risk of digital exclusion. This study aimed to explore the patterns of acceptance and use of digital health services among frequent attenders (FAs), which may help in the assessment of patients' digital suitability.

Methods

Persistent FAs (N = 30) were recruited by random sampling from one Finnish municipality. The semistructured interviews were conducted in February-May 2021. We analysed the data with qualitative content analysis using the Unified Theory of Acceptance and Use of Technology (UTAUT) model. Additionally, we quantified the data for two-step cluster analyses to create separate cluster models that grouped FAs based on acceptance and use of (a) digital services for self-management of health and (b) telemedicine services.

Results

Based on digital self-management, FAs were defined as Self-Managers, Supported Self-Managers, and Non-Self-Managers. Based on telemedicine use, they were grouped into Telemedicine Users, Doubtful Telemedicine Users, and Telemedicine Refusers. The clusters described different opportunities, awareness, and interest in using digital health services. Referral from professionals seemed to promote digital service use. For some, digital services were not accessible.

Conclusions

Our findings emphasise the importance of assessing the suitability of FAs to digital health services, as their readiness to use may vary. Professionals should recommend digital services that support individual health to suitable patients. More accessible digital services could promote digital suitability despite functional limitations.

Exploration of the health needs of patients with poorly controlled type 2 diabetes using a user-centred co-production approach in the area of mHealth: an exploratory sequential mixed-method protocol

INTRODUCTION

Research on the needs and preferences of patients with poorly controlled type 2 diabetes mellitus (T2DM) with mobile health (mHealth) service is limited. With the principles of co-production, this study aims to address this research gap by exploring the health needs of Chinese patients with poorly controlled T2DM.

METHODS AND ANALYSIS

This study uses a three-phase, exploratory sequential mixed-method design. Phase 1 aims to assess the health needs of patients with poorly controlled T2DM by conducting semi-structured interviews with patients, doctors and nurses. Participants will be recruited by purposive sampling with maximum variation. Content analysis will be employed. Phase 2 will form item generation and develop the mHealth need scale. The scale will be subject to pilot testing and psychometric evaluation, including content validity, construct validity, discriminant validity, internal validity and test-retest reliability. Phase 3 will explore the priority of health needs perceived by patients with poorly controlled T2DM through a cross-sectional study. The measurement tools include an mHealth needs scale, the Summary of Diabetes Self-care Activities Questionnaire, the Diabetes Empowerment Scale-Short Form, the Diabetes Health Literacy Scale and the eHealth Literacy Scale. Multiple regression techniques with a hierarchical block design will be used for the model building to identify the factors contributing to the heterogeneity of the perceived mHealth needs. The findings of phase 1 and phase 3 will be integrated using data correlation, comparison and consolidation.

ETHICS AND DISSEMINATION

The Ethics Committee of the School of Nursing, Sun Yat-sen University, has approved this study (No. 2021ZSLYEC). The results of this study will be disseminated through conference presentations and peer-reviewed publications.

Factors Affecting mHealth Technology Adoption in Developing Countries: The Case of Egypt

Mobile health apps are seeing rapid growth in the potential to improve access to healthcare services for disadvantaged communities, while enhancing the efficiency of the healthcare delivery value chain. Still, the adoption of mHealth apps is relatively low, especially in developing countries. In Egypt, an initiative for national-level healthcare coverage was launched in 2021, accompanied by a rise in mHealth start-ups. However, many of these projects did not progress beyond the pilot stage, with very little known about the antecedents of mHealth adoption for the Egyptian user. Semi-structured interviews were conducted with 22 Egyptians, aiming to uncover factors affecting the use of mHealth apps for Egyptian citizens. Some of these factors were introduced by previous studies, such as Perceived Service Quality, Perceived Risk, Perceived Ease of Use, and Trust. Others were not well established in the mHealth research strand, such as Perceived Reputation and Perceived Familiarity, while Governance, Personalized Experience, Explain-ability, Interaction, Language, and Cultural Issues, are novel factors introduced by the current research. The effect of these suggested independent variables on the willingness to adopt mHealth apps was validated using a survey administered to 150 Egyptians, confirming the significant positive effect of most of these factors on mHealth adoption in Egypt. This research contributes to methodology by introducing novel constructs in the mHealth research context, which might be specific to the target developing country. Practical implications were suggested for designers and healthcare service providers might increase the adoption of their apps in developing countries, such as Egypt.

Determining factors affecting the perceived usability of air pollution detection mobile application "AirVisual" in Thailand: A structural equation model forest classifier approach

Air pollution has been evident worldwide. It presented numerous pieces of evidence that affect health-related adverse effects causing diseases and even death and the development of technology has helped monitor the exposure of people to air pollution. This research analyzed factors affecting the perceived usability of air pollution detection on the 'AirVisual' mobile application based on the integrated model of Protection Motivation Theory (PMT) and Unified Theory of Acceptance and Use of Technology (UTAUT2). A total of 416 participants voluntarily answered a self-administered survey consisting of adapted constructs covering factors such as Performance expectancy (PE), Effort expectancy (EE), Social influence (SI), Facilitating conditions (FC), Habit (HB), Perceived risk (PR), Perceived trust (PT), Intention to use (IU), and Perceived usability (PU). Structural Equation Modeling and Random Forest Classifier were utilized to determine factors affecting perceived usability of the 'AirVisual' mobile application. The results showed that PE, EE, SI, and FC were key factors leading to very high PU among users. Moreover, IU was seen to be the most significant factor affecting PU, followed by PT, PR, and HB. This study is one of the first studies that considered the evaluation of usability among health-related mobile applications covering air pollution. The results and the framework utilized in this model may be applied to evaluate other factors and applications related to health among people. Lastly, this study can also be extended to evaluate other mobile applications worldwide.

Social Acceptance of Mobile Health among Young Adults in Japan: An Extension of the UTAUT Model

The unprecedented development of information and communication technologies has opened up immense possibilities in the field of health care. Mobile health (mHealth) is gaining increasing attention as an important technology for solving health-related problems. Although a high rate of smartphone usage among young people in Japan has been identified, smartphone usage for health management is not high. As Japanese youth are important potential users of mHealth, it is necessary to explore theories that influence the behavioral intention of Japanese youth to adopt mHealth. This study conducted a questionnaire survey in a Japanese university and collected 233 valuable responses. This study was adapted and extended from the unified theory of acceptance and use of technology (UTAUT) model to measure eight constructs: health consciousness, social influence, facilitation conditions, perceived risk, trust, performance expectancy, effort expectancy, and behavioral intention. Structural equation modeling was used for hypothesis testing. We found that trust, performance expectancy, and effort expectancy directly influenced the behavioral intention to use mHealth. Health consciousness and social influence indirectly influence behavioral intention through trust and performance expectancy. Facilitation conditions indirectly influenced behavioral intention through effort expectancy. This study makes a vital theoretical contribution to policymakers and product developers for the further diffusion of mHealth among young people in Japan.

Extension of the Unified Theory of Acceptance and Use of Technology 2 model for predicting mHealth acceptance using diabetes as an example: a cross-sectional validation study

OBJECTIVES

Mobile health applications are instrumental in the self-management of chronic diseases like diabetes. Technology acceptance models such as Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) have proven essential for predicting the acceptance of information technology. However, earlier research has found that the constructs "perceived disease threat" and "trust" should be added to UTAUT2 in the mHealth acceptance context. This study aims to evaluate the extended UTAUT2 model for predicting mHealth acceptance, represented by behavioral intention, using mobile diabetes applications as an example.

METHODS

We extended UTAUT2 with the additional constructs "perceived disease threat" and "trust". We conducted a web-based survey in German-speaking countries focusing on patients with diabetes and their relatives who have been using mobile diabetes applications for at least 3 months. We analysed 413 completed questionnaires by structural equation modelling.

RESULTS

We could confirm that the newly added constructs "perceived disease threat" and "trust" indeed predict behavioural intention to use mobile diabetes applications. We could also confirm the UTAUT2 constructs "performance expectancy" and "habit" to predict behavioural intention to use mobile diabetes applications. The results show that the extended UTAUT2 model could explain 35.0% of the variance in behavioural intention.

DISCUSSION

Even if UTAUT2 is well established in the information technologies sector to predict technology acceptance, our results reveal that the original UTAUT2 should be extended by "perceived disease threat" and "trust" to better predict mHealth acceptance.

CONCLUSION

Despite the newly added constructs, UTAUT2 can only partially predict mHealth acceptance. Future research should investigate additional mHealth acceptance factors, including how patients perceive trust in mHealth applications.

Research on the influencing factors of users’ information processing in online health communities based on heuristic-systematic model

With the rapid development of the Internet and the normalization of COVID-19 epidemic prevention and control, Online health communities (OHCs) have gradually become one of the important ways for people to obtain health information, and users have to go through a series of information processing when facing the massive amount of data. Understanding the factors influencing user information processing is necessary to promote users’ health literacy, health knowledge popularization and health behavior shaping. Based on the Heuristic-Systematic Model (HSM), Information Ecology Theory, Privacy Trade-Off and Self-Efficacy Theory, we constructed a model of factors influencing user information processing in online health communities. We found that information quality and emotional support had indirect effects on heuristic and systematic information processing, and these effects were mediated by privacy concerns and self-efficacy. In our research model, systematic information processing was most positively influenced directly by self-efficacy. Privacy concerns had a direct negative correlation with both dual information processing pathways. Therefore, OHCs managers should develop relevant regulations to ensure the information quality in OHCs and improve privacy protection services to promote user information processing by improving users’ self-efficacy and reducing their privacy concerns. Providing a user-friendly and interactive environment for users is also recommended to create more emotional support, thus facilitating more systematic information processing.

Neurological Outpatients Prefer EEG Home-Monitoring over Inpatient Monitoring-An Analysis Based on the UTAUT Model

Home monitoring examinations offer diagnostic and economic advantages compared to inpatient monitoring. In addition, these technical solutions support the preservation of health care in rural areas in the absence of local care providers. The acceptance of patients is crucial for the implementation of home monitoring concepts. The present research assesses the preference for a health service that is to be introduced, namely an EEG home-monitoring of neurological outpatients-using a mobile, dry-electrode EEG (electroencephalography) system-in comparison to the traditional long-time EEG examination in a hospital. Results of a representative study for Germany (n = 421) reveal a preference for home monitoring. Importantly, this preference is partially driven by a video explaining the home monitoring system. We subsequently analyzed factors that influence the behavioral intention (BI) to use the new EEG system, drawing on an extended Unified Theory of Acceptance and Use of Technology (UTAUT) model. The strongest positive predictor of BI is the belief that EEG home-monitoring will improve health quality, while computer anxiety and effort expectancy represent the strongest barriers. Furthermore, we find the UTAUT model's behavioral intention construct to predict the patients' decision for or against home monitoring more strongly than any other patient's characteristic such as gender, health condition, or age, underlying the model's usefulness.

Paving the way for increased e-health record use: elaborating intentions of Gen-Z

This paper presents the determinants of personal e-health records adoption by the Gen-Z population and reveals barriers to use. Gen-Z members are one of the most prominent users of digital health services that have an influence on older generations' technology adoption but have often been overlooked in scholarly research. A survey of 1,000 Gen-Z university students based on modified UTAUT was used to address this research gap. The analysis revealed the vital role of social influence in paving the way for higher adoption among Gen-Z. Moreover, significant influences of performance expectancy, facilitating conditions, and e-health literacy on behavioural intentions were detected. Effort expectancy was found to be insignificant in impacting Gen-Z's intentions to adopt electronic health record systems. Moreover, privacy concerns acted as a barrier to adoption, yet the offsetting effect of users' trust in health systems was shown to be instrumental in overcoming such privacy-related barriers.

Exploring Users' Health Behavior Changes in Online Health Communities: Heuristic-Systematic Perspective Study

(1) Background: With the continuous advancement of internet technology, use of the internet along with medical service provides a new solution to solve the shortage of medical resources and the uneven distribution of available resources. Online health communities (OHCs) that emerged at this historical moment have flourished with various advantages, such as being free from location and time constraints. Understanding users' behavior changes via engagement in OHCs is necessary to support the development of internet medicine and promote public health. (2) Methods: The hypotheses of our research model were developed based on the protective action decision model (PADM) and heuristic-systematic model (HSM). A questionnaire was developed with seven constructs through previous studies and verified using a presurvey. Our survey respondents are online health community users. We used structural equation modelling to test the research hypotheses. (3) Results: The results of the analysis of 290 valid samples showed that the research model fit the data collected well. The perceived benefits (PB) positively affect information needs (IN) (beta = 0.280, p < 0.001, R² = 0.252), thereby promoting users' engagement in OHCs (EOHCs) (beta = 0.353, p < 0.001, R² = 0.387); EOHCs has a significant positive impact on health behavior change (HBC) (beta = 0.314, p < 0.001), and it also significantly positively affects users' health behavior change through systematic processing indirectly (beta = 0.252, p < 0.001, R² = 0.387). (4) Conclusions: Our study offers support for the usefulness of the PADM and HSM in explaining users' health behavior changes. For practitioners, this study introduces influence processes as policy tools that managers can employ for health-promoting with mHealth.

Evaluation of a Novel Step Training Mobile App Intervention in Cardiopulmonary Rehabilitation: A Single-Arm Prospective Cohort Study

Objective: To establish the usability, acceptability, safety, and exercise adherence of a step training mobile app. Design: A single-arm prospective cohort study. Setting: Royal Brisbane and Women's Hospital, Australia. Subjects: Twenty-six cardiopulmonary rehabilitation participants. Intervention: Twelve weeks of step training using the mobile app Clock Yourself. Participants used Clock Yourself at home and during cardiopulmonary rehabilitation sessions, prescribed for a total of 15-20 minutes three times a week. Main Measures: The primary outcomes of interest were usability and acceptability and were measured using the System Usability Scale (SUS) and Attitudes to Falls-Related Interventions Scale (AFRIS) questionnaire, respectively. Safety and adherence were measured by self-report and participant diary, respectively. Secondary outcomes measuring changes in stepping, gait, balance, and physical performance included Manual test of Choice Stepping Reaction Time (CSRT-M), Short Physical Performance Battery (SPPB), Gait speed with and without a cognitive dual task (DT) and Timed Up and Go with and without a cognitive DT (TUG and TUGcog). Results: Twenty-one participants completed the study. Clock Yourself was considered highly useable (SUS [median] = 82.5/100; interquartile range [IQR, 67.5-95], equating to an "A" rating [A-F scale]) and acceptable (AFRIS [median] = 38/42 [IQR, 31-41]). Participants practiced Clock Yourself for a median of 18.29 minutes per week and no adverse events were reported. At 12 weeks, mean change in CSRT-M, SPPB, gait speed, DT gait speed, TUG, and TUGcog were all statistically significant (P < 0.01). Conclusion: Twelve weeks of mobile app-based step training was safe and considered usable and acceptable by participants. On average, participants did not meet the prescribed practice dosage. Statistically significant changes were observed in all physical measures; however, results are confounded by participation in cardiopulmonary rehabilitation and lack of control group.

Adoption of Covid-19 contact tracing app by extending UTAUT theory: Perceived disease threat as moderator

Objectives

Contact tracing applications are technological solutions that can quickly trace and notify users of their potential exposure to the Covid-19 virus and help contain the spread of the disease. However, extant research delineating the various factors predicting the adoption of contact tracing apps is scant. The study's primary objective is to develop and validate a research model based on the unified theory of acceptance and use of technology (UTAUT), health belief model (HBM), perceived privacy risk and perceived security risk to understand the adoption of contact tracing application.

Methods

An online survey was carried out among users of the ‘Aarogya Setu’ contact tracing app in India. The partial least squares structural equation modelling (PLS-SEM) tool was employed to analyze data from 307 respondents.

Results

The results showed that performance expectancy, social influence, and facilitating conditions positively influenced users’ intention to adopt the app. In contrast, perceived privacy and security risks were significant barriers to app adoption. Perceived disease threat as a moderator mitigated the adverse impact of perceived privacy risk on users' intention to adopt contact tracing apps.

Conclusions

The current study gives insights on both drivers and barriers to the adoption of contract tracing applications. Various theoretical and practical implications of significance are provided for academicians and practitioners to effectively promote app adoption to tackle the Covid-19 pandemic.

Role of Social and App-Related Factors in Behavioral Engagement With mHealth for Improved Well-being Among Chronically Ill Patients: Scenario-Based Survey Study

Background

The last decade has seen a considerable increase in the number of mobile health (mHealth) apps in everyday life. These mHealth apps have the potential to significantly improve the well-being of chronically ill patients. However, behavioral engagement with mHealth apps remains low.

Objective

The aim of this study was to describe the behavioral engagement of chronically ill patients with mHealth apps by investigating (1) how it is affected by social factors (ie, physician recommendation) and app-related factors (ie, app integration) and (2) how it affects patient well-being. This study also considers the moderating effect of attachment to traditional health care and the mobile app experience among patients.

Methods

We carried out a scenario-based survey study of chronically ill patients (N=521). A Bayesian structural equation modeling with mediation and moderation analysis was conducted in MPlus.

Results

Both physician recommendations for mHealth app use and app integration have positive effects on the behavioral engagement of chronically ill patients with mHealth apps. Higher behavioral engagement positively affects the hedonic well-being (extent of pleasure) and the eudaemonic well-being (extent of self-efficacy) of chronically ill patients. Mobile app experience, however, positively moderates the relationship between app integration and behavioral engagement, whereas patient attachment to traditional care does not moderate the relationship between physician recommendation and behavioral engagement. Taken together, the proportion of variance explained (R²) equals 21% for behavioral engagement and 52.8% and 62.2% for hedonic and eudaemonic well-being, respectively, thereby providing support for the strong influence of app integration and physician recommendation via the mediation of the patients’ behavioral engagement on both patients’ hedonic and eudaemonic well-being.

Conclusions

Physician recommendation and app integration enable behavioral engagement and promote well-being among chronically ill patients. It is thus important to take social and app-related factors into consideration during and after the development of mHealth apps.

Acceptance of clinical decision support system to prevent venous thromboembolism among nurses: an extension of the UTAUT model

Background

Venous thromboembolism has been a major public health problem and caused a heavy disease burden. Venous thromboembolism clinical decision support system was proved to have a positive influence on the prevention and management of venous thromboembolism. As the direct users, nurses' acceptance of this system is of great importance to support the successful implementation of it. However, there are few relevant studies to investigate nurses' acceptance and the associated factors are still unclear.

Objective

To investigate the determinant factors of nurses' acceptance of venous thromboembolism clinical decision support system with the modified Unified Theory of Acceptance and Use of Technology.

Methods

We designed a questionnaire based on the modified Unified Theory of Acceptance and Use of Technology and then a cross-sectional survey was conducted among nurses in a tertiary hospital in Nanjing, China. Statistically, a Structural Equation Modeling -Partial Least Squares path modeling approach was applied to examine the research model.

Results

A total of 1100 valid questionnaires were recycled. The modified model explained 74.7%, 83.0% and 86% of the variance in user satisfaction, behavioral intention and user behavior, respectively. The results showed that performance expectancy (β = 0.254, p = 0.000), social influence (β = 0.136, p = 0.047), facilitating conditions (β = 0.245, p = 0.000), self-efficacy (β = 0.121, p = 0.048) and user satisfaction (β = 0.193, p = 0.001) all had significant effects on nurses' intention. Although effort expectancy (β = 0.010, p = 0.785) did not have a direct effect on nurses' intention, it could indirectly influence nurses' intention with user satisfaction as the mediator (β = 0.296, p = 0.000). User behavior was significantly predicted by facilitating conditions (β = 0.298, p = 0.000) and user intention (β = 0.654, p = 0.001).

Conclusion

The research enhances our understanding of the determinants of nurses' acceptance of venous thromboembolism clinical decision support system. Among these factors, performance expectancy was considered as the top priority. It highlights the importance of optimizing system performance to fit the users' needs. Generally, the findings in our research provide clinical technology designers and administrators with valuable information to better meet users' requirements and promote the implementation of venous thromboembolism clinical decision support system.

Diabetes Self-management Apps: Systematic Review of Adoption Determinants and Future Research Agenda

BACKGROUND

Most diabetes management involves self-management. Effective self-management of the condition improves diabetes control, reduces the risk of complications, and improves patient outcomes. Mobile apps for diabetes self-management (DSM) can enhance patients' self-management activities. However, they are only effective if clinicians recommend them, and patients use them.

OBJECTIVE

This study aimed to explore the determinants of DSM apps' use by patients and their recommendations by health care professionals (HCPs). It also outlines the future research agenda for using DSM apps in diabetes care.

METHODS

We systematically reviewed the factors affecting the adoption of DSM apps by both patients and HCPs. Searches were performed using PubMed, Scopus, CINAHL, Cochrane Central, ACM, and Xplore digital libraries for articles published from 2008 to 2020. The search terms were diabetes, mobile apps, and self-management. Relevant data were extracted from the included studies and analyzed using a thematic synthesis approach.

RESULTS

A total of 28 studies met the inclusion criteria. We identified a range of determinants related to patients' and HCPs' characteristics, experiences, and preferences. Young female patients were more likely to adopt DSM apps. Patients' perceptions of the benefits of apps, ease of use, and recommendations by patients and other HCPs strongly affect their intention to use DSM apps. HCPs are less likely to recommend these apps if they do not perceive their benefits and may not recommend their use if they are unaware of their existence or credibility. Young and technology-savvy HCPs were more likely to recommend DSM apps.

CONCLUSIONS

Despite the potential of DSM apps to improve patients' self-care activities and diabetes outcomes, HCPs and patients remain hesitant to use them. However, the COVID-19 pandemic may hasten the integration of technology into diabetes care. The use of DSM apps may become a part of the new normal.

Study of the factors influencing the use of MyData platform based on personal health record data sharing system

Background

The application of telemedicine and electronic health (eHealth) technology has grown in importance during the COVID-19 pandemic, and a new approach in personal data management and processing MyData, has emerged. Data portability and informational self-determination are fundamental concepts of MyData. This study analysed the factors that influence acceptance of the MyData platform, which, reflects the right to self-determine personal data.

Methods

The study involved participants having experience using the MyData platform, and the key factors of the unified theory of acceptance and use of technology were used in the research model (performance expectancy, effort expectancy, social influence, facilitation condition and behavioural intention to use). The questionnaire comprided 27 items, and system usage log data were used to confirm that behavioural intention to use affected actual use behaviour through structural equation modeling.

Results

In total, 1153 participants completed the survey. The goodness of fit in the structural equation model indices indicates that the data fit the research model well. Performance expectancy, social influence, and facilitating conditions had direct effects on behavioural intention to use. We used system usage log data to confirm that behavioural intention to use positively affected actual use behaviour. The impact of the main factors in the unified theory of acceptance and use of technology was not moderated by age or gender, except for performance expectancy.

Conclusions

This study is the first to examine the factors influencing the use of the MyData platform based on the personal health record data sharing system in Korea. In addition, the study confirmed the use behaviour of the MyData platform utilising the system’s actual usage log for each function and analysing the effect of the intention of use on actual use. Our study serves as a significant foundation for the acceptance of data portability and sharing concepts. It also lays the foundation for expanding the data economy and ecosystem in the pandemic era.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12911-022-01929-z.

Factors Affecting Customer Intention to Adopt a Mobile Chronic Disease Management Service

The Mobile Chronic Disease Management Service (MCDMS) is an emerging medical service for chronic disease prevention and treatment, but limited attention has been paid to the factors that affect users’ intention to adopt the service. Based on the unified theory of acceptance and use of technology 2 and the protection motivation theory, the authors built an MCDMS adoption model. The authors also verified the differentiating age effect on the service adoption intention from experiential distance perspective of the construal level theory. Empirical results showed that the young group focused more on the impact of effort expectancy, whereas the elderly group focused more on performance expectancy, imitating others, and perceived severity. Furthermore, the young group, however, focused more on the impact of perceived vulnerability, and offline medical habits showed no significant influence on either group’s intention to adopt, which were not consistent with the original hypotheses. The findings can aid MCDMS providers in selecting marketing strategies targeted toward different age groups.

Online health management continuance and the moderating effect of service type and age difference: A meta-analysis

Numerous empirical studies have been carried out to explore factors of online health management continuance. However, results were not unified. We thus conducted a meta-analysis to identify influential factors and potential moderators. A systematic literature search was performed in nine databases (PubMed, Web of Science, the Cochrane Library, Ovid of JBI, CINAHL, Embase, CNKI, VIP, and CBM) published up to December 2020 in the English or Chinese language. Meta-analysis of combined effect size, heterogeneity, moderator analysis, publication bias assessment, and inter-rater reliability was conducted. Totally 41 studies and 12 pairwise relationships were identified. Confirmation, perceived usefulness, satisfaction, information quality, service quality, perceived ease of use, and trust were all critical predictors. Service type and age difference showed their moderating effects respectively. The perceived usefulness was more noteworthy in medical service than health and fitness service. The trust was more noteworthy in young adults. The results confirmed the validity and robustness of the Expectation Confirmation Model, Information Systems Success Model, and trust theory in online health management continuance. Moderators included but are not limited to age difference and service type. The elderly research in the healthcare context and other analytical methods such as qualitative comparative analysis should be applied in the future.

The Effects of Drowsiness Detection Technology and Education on Nurses' Beliefs and Attitudes Towards Drowsy Driving

Background: Drowsy driving is prevalent among night-shift nurses, yet there is a gap in understanding nurses' beliefs and attitudes that may affect their intention to avoid drowsy driving.Objectives: The objectives of the study were twofold: 1) investigate how behavioral constructs such as beliefs and attitudes may affect nurses' intention to avoid drowsy driving; and 2) assess changes in such beliefs and attitudes during a study that evaluated the effectiveness of educational and technological interventions.Methods: Three-hundred night-shift nurses were recruited from a large hospital in Texas to participate in a randomized control trial. Participants were randomly assigned to three groups: 1) control; 2) educational intervention; and 3) combined educational and technological intervention. The study utilized an integrated model drawing from the constructs of the Theory of Planned Behavior and the Health Belief Model to elicit attitudes, beliefs, and intentions to use in-vehicle drowsiness detection technologies. Each group was surveyed pre- intervention and at post-intervention around 3 months later to assess changes in beliefs and attitudes. Structural equation models and path analysis were used to analyze changes in beliefs.Results: Seventy-nine participants completed the pre-intervention questionnaire, and 44 nurses completed the pre- and post-intervention surveys. Intention was predicted primarily by attitude and perceived health threat. Perceived health threat also mediated the relationship between behavioral intention and the influence of subjective norms as well as perceived behavioral control. Participants who received education about drowsy driving had positive changes in beliefs.Conclusions: Nurses' perceived health threat from driving drowsy and their attitude towards our intervention were important motivators to avoid drowsy driving. Interventions aiming at raising awareness of the risks associated with drowsy driving may be effective at motivating nurses to avoid drowsy driving.

Determinants of Acceptance of Weight Management Applications in Overweight and Obese Individuals: Using an Extended Unified Theory of Acceptance and Use of Technology Model

Overweight and obesity carry a tremendous burden in terms of physiological and psychological comorbidities. There is a great variety of weight management applications to support weight reduction, but a systematical analysis of individuals’ needs and requirements to adopt sustaining lifestyle changes is missing so far. This study aimed to assess the acceptance of such applications and its underlying predictors in individuals with overweight/obesity. A cross-sectional study was conducted, including 439 overweight/obese individuals. Health-related internet use and acceptance of weight management applications were examined using a modified questionnaire based on the Unified Theory of Acceptance and Use of Technology (UTAUT). The general acceptance of weight management applications was high, with significant age differences. Compared to older individuals, younger ones showed a higher acceptance. BMI was not significantly associated with acceptance. Besides psychometric data and eHealth-related data, performance expectancy, effort expectancy, and social influence proved to be significant predictors for acceptance. The total variance explanation provided by the extended UTAUT model was 61.2%. The knowledge of the influencing factors on acceptance might be useful in developing, optimizing, and establishing weight management applications. For determining acceptance and its predictors of weight management applications, the UTAUT model is a valid approach.

Clinician Acceptance of Order Sets for Pain Management: A Survey in Two Urban Hospitals

BACKGROUND

 Order sets are a clinical decision support (CDS) tool in computerized provider order entry systems. Order set use has been associated with improved quality of care. Particularly related to opioids and pain management, order sets have been shown to standardize and reduce the prescription of opioids. However, clinician-level barriers often limit the uptake of this CDS modality.

OBJECTIVE

 To identify the barriers to order sets adoption, we surveyed clinicians on their training, knowledge, and perceptions related to order sets for pain management.

METHODS

 We distributed a cross-sectional survey between October 2020 and April 2021 to clinicians eligible to place orders at two campuses of a major academic medical center. Survey questions were adapted from the widely used framework of Unified Theory of Acceptance and Use of Technology. We hypothesize that performance expectancy (PE) and facilitating conditions (FC) are associated with order set use. Survey responses were analyzed using logistic regression.

RESULTS

 The intention to use order sets for pain management was associated with PE to existing order sets, social influence (SI) by leadership and peers, and FC for electronic health record (EHR) training and function integration. Intention to use did not significantly differ by gender or clinician role. Moderate differences were observed in the perception of the effort of, and FC for, order set use across gender and roles of clinicians, particularly emergency medicine and internal medicine departments.

CONCLUSION

 This study attempts to identify barriers to the adoption of order sets for pain management and suggests future directions in designing and implementing CDS systems that can improve order sets adoption by clinicians. Study findings imply the importance of order set effectiveness, peer influence, and EHR integration in determining the acceptability of the order sets.

Emergency e-learning acceptance in second-cycle institutions in Ghana: a conditional mediation analysis

This paper investigates the determinants that will influence students' acceptance of the electronic learning (e-learning) system of education after the COVID-19 emergency. Specifically, the paper assesses the attitudes and intentions of students in second-cycle institutions to accept e-learning after the pandemic, using constructs derived from the health belief model and technology acceptance model. Also, we test if there is any significant difference in the attitudes and intentions of students in public and private institutions. Using data collected from 370 students in upper and lower levels of a second-cycle institutions in Ghana, we found that student attitude is significantly influenced by perceived usefulness and moderately affected by perceived severity, whereas, student's intention is moderately affected by the perceived severity but substantially influenced by the student's attitude towards usage. Also, the results revealed that students' attitudes and intentions to use e-learning are moderately affected by the severity of the ongoing COVID-19 pandemic. Finally, there were no significant differences in the attitudes and intentions of the sampled students in public and private second-cycle institutions in Ghana, regarding their acceptance and usage of e-learning after the COVID-19 emergency. Given the study's findings, the paper concludes that students' attitudes and intention to use e-learning are the main determinants that will influence the students' acceptance of the e-learning system of education in second-cycle institutions in Ghana after the COVID-19 emergency. The paper contributes to knowledge by providing evidence of students' acceptance of the e-learning system of education after the COVID-19 emergency in the context of a developing country like Ghana.