Acceptance of Mobile Health Apps for Disease Management Among People With Multiple Sclerosis: Web-Based Survey Study

Negotiating with digital self-monitoring: A qualitative study on how patients with multiple sclerosis use and experience digital self-monitoring within a scientific study

Research shows that patients can have values and use practices that are different from those envisioned by technology developers. Using sociomaterialism as an analytical lens, we show how patients negotiated with digital self-monitoring in the context of a scientific study. Our paper draws on interviews with 26 patients with the chronic neurological disease multiple sclerosis (MS) who were invited to use an activity tracker and a self-monitoring app for a period of 12 months as part of their everyday life. Our study aims to fill a gap: relatively little is known about how digital self-monitoring becomes materialized in the everyday lives of patients with chronic diseases. We show that patients engaged in digital self-monitoring because they are eager to participate in research to contribute knowledge that will benefit the larger community of patients rather than to improve their personal self-management. Although respondents adhered to digital self-monitoring during the study, it is not self-evident that they would do so for private self-monitoring purposes. It became clear that respondents did not necessarily perceive digital self-monitoring as useful for their self-management practices due to their established knowledge and routines. Moreover, respondents referred to the inconvenience of having to perform self-monitoring tasks and the emotional burden of being reminded of the MS because of the digital self-monitoring. We conclude by indicating what could be considered when designing scientific studies, including the suitability of conventional study designs for evaluating technologies used daily by patients and the challenge of integrating patients' experiential knowledge into scientific practices.

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.

Mobile health interventions in multiple sclerosis: A systematic review

BACKGROUND

Persons with multiple sclerosis (pwMS) might be particularly well suited to benefit from digital health applications because they are, on average, younger and less severely disabled than patients with many other chronic diseases. Many digital health applications for pwMS have been developed.

OBJECTIVES

Analysis of the evidence of digital health applications to improve health outcomes from a patient perspective.

METHODS

A systematic review was performed on all randomized controlled trials (RCTs) that have studied mobile health interventions for pwMS, that is, which can be applied with a smartphone, tablet, or laptop to improve patient-reported outcomes.

RESULTS

Of the 1127 articles identified in the literature search, 13 RCTs fit the inclusion criteria. Two trials studied messaging systems, two depression interventions, one addressed MS fatigue, five cognition, and three mobility issues, of which two focused on spasticity management. One trial aimed to enhance physical activity. Most were pilot studies that cannot yield definitive conclusions regarding efficacy. One depression intervention and one fatigue intervention showed significant results across several outcomes.

CONCLUSION

Several mobile self-guided digital health applications for pwMS have been tested in RCTs, and two interventions targeting depression and fatigue have demonstrated significant effects. Challenges remain regarding implementation into routine care.

Portuguese Validation of the Unified Theory of Acceptance and Use of Technology Scale (UTAUT) to a COVID-19 Mobile Application: A Pilot Study

The use of technology has proven to be a powerful tool in the fight against COVID-19 and its variants of concern (Gamma, Beta, Alpha, Delta, and Omicron). The urgency of responding to this worldwide pandemic has accelerated the development of monitoring systems and contact tracing applications. Without technology's contribution, the adverse effects on humanity economically, socially, and psychologically would be even more devastating. This study aimed to translate, adapt, and validate the Unified Theory of Acceptance and Use of Technology (UTAUT) model in a Portuguese university population, to evaluate adherence to a mobile application for tracking COVID-19. An observational cross-sectional study was developed using a sample with 1081 participants (71% female, 59.2% with ages between 16 and 24, and 78.2% of the respondent's university students). The Portuguese version model showed a good reliability (Cronbach's α = 0.82) and an acceptable overall adjustment to the sample under study (χ²/df = 3.732, CFI = 0.955, TLI = 0.944, RMSEA = 0.05, SRMR = 0.06); however, this model could be improved, as we proved. Since this is a pilot study, more studies are needed. The results indicated that the P-UTAUT can be improved for evaluating adherence to a COVID-19 mobile application.

The role of uncertainty intolerance in adjusting to long-term physical health conditions: A systematic review

Long-term physical health conditions (LTPHCs) are associated with poorer psychological well-being, quality of life, and longevity. Additionally, individuals with LTPHCs report uncertainty in terms of condition aetiology, course, treatment, and ability to engage in life. An individual's dispositional ability to tolerate uncertainty-or difficulty to endure the unknown-is termed intolerance of uncertainty (IU), and may play a pivotal role in their adjustment to a LTPHC. Consequently, the current review sought to investigate the relationship between IU and health-related outcomes, including physical symptoms, psychological ramifications, self-management, and treatment adherence in individuals with LTPHCs. A systematic search was conducted for papers published from inception until 27 May 2022 using the databases PsycINFO, PubMed (MEDLINE), CINAHL Plus, PsycARTICLES, and Web of Science. Thirty-one studies (N = 6,201) met the inclusion criteria. Results indicated that higher levels of IU were associated with worse psychological well-being outcomes and poorer quality of life, though impacts on self-management were less clear. With the exception of one study (which looked at IU in children), no differences in IU were observed between patients and healthy controls. Although findings highlight the importance of investigating IU related to LTPHCs, the heterogeneity and limitations of the existing literature preclude definite conclusions. Future longitudinal and experimental research is required to investigate how IU interacts with additional psychological constructs and disease variables to predict individuals' adjustment to living with a LTPHC.

Usability of a mHealth Solution using Speech Recognition for Point-of-care Diagnostic Management

The administrative burden for physicians in the hospital can affect the quality of patient care. The Service Center Medical Informatics (SMI) of the University Hospital Würzburg developed and implemented the smartphone-based mobile application (MA) ukw.mobile1 that uses speech recognition for the point-of-care ordering of radiological examinations. The aim of this study was to examine the usability of the MA workflow for the point-of-care ordering of radiological examinations. All physicians at the Department of Trauma and Plastic Surgery at the University Hospital Würzburg, Germany, were asked to participate in a survey including the short version of the User Experience Questionnaire (UEQ-S) and the Unified Theory of Acceptance and Use of Technology (UTAUT). For the analysis of the different domains of user experience (overall attractiveness, pragmatic quality and hedonic quality), we used a two-sided dependent sample t-test. For the determinants of the acceptance model, we employed regression analysis. Twenty-one of 30 physicians (mean age 34 ± 8 years, 62% male) completed the questionnaire. Compared to the conventional desktop application (DA) workflow, the new MA workflow showed superior overall attractiveness (mean difference 2.15 ± 1.33), pragmatic quality (mean difference 1.90 ± 1.16), and hedonic quality (mean difference 2.41 ± 1.62; all p < .001). The user acceptance measured by the UTAUT (mean 4.49 ± 0.41; min. 1, max. 5) was also high. Performance expectancy (beta = 0.57, p = .02) and effort expectancy (beta = 0.36, p = .04) were identified as predictors of acceptance, the full predictive model explained 65.4% of its variance. Point-of-care mHealth solutions using innovative technology such as speech-recognition seem to address the users' needs and to offer higher usability in comparison to conventional technology. Implementation of user-centered mHealth innovations might therefore help to facilitate physicians' daily work.

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.

Digital health for chronic disease management: An exploratory method to investigating technology adoption potential

INTRODUCTION

The availability of consumer-facing health technologies for chronic disease management is skyrocketing, yet most are limited by low adoption rates. Improving adoption requires a better understanding of a target population's previous exposure to technology. We propose a low-resource approach of capturing and clustering technology exposure, as a mean to better understand patients and target health technologies.

METHODS

Using Multiple Sclerosis (MS) as a case study, we applied exploratory multivariate factorial analyses to survey data from the Swiss MS Registry. We calculated individual-level factor scorings, aiming to investigate possible technology adoption clusters with similar digital behavior patterns. The resulting clusters were transformed using radar and then compared across sociodemographic and health status characteristics.

RESULTS

Our analysis included data from 990 respondents, resulting in three clusters, which we defined as the (1) average users, (2) health-interested users, and (3) low frequency users. The average user uses consumer-facing technology regularly, mainly for daily, regular activities and less so for health-related purposes. The health-interested user also uses technology regularly, for daily activities as well as health-related purposes. The low-frequency user uses technology infrequently.

CONCLUSIONS

Only about 10% of our sample has been regularly using (adopting) consumer-facing technology for MS and health-related purposes. That might indicate that many of the current consumer-facing technologies for MS are only attractive to a small proportion of patients. The relatively low-resource exploratory analyses proposed here may allow for a better characterization of prospective user populations and ultimately, future patient-facing technologies that will be targeted to a broader audience.

A Mobile Phone Text Messaging Intervention to Manage Fatigue for People With Multiple Sclerosis, Spinal Cord Injury, and Stroke: Development and Usability Testing

BACKGROUND

Fatigue significantly affects daily functioning in persons with disabilities. Fatigue management can be challenging, and the information provided during routine physician visits to manage fatigue can be overwhelming. One way to address fatigue is to increase knowledge, skills, and confidence for self-management (ie, patient activation). Self-management programs have shown promising effects in targeting fatigue in persons with disabilities. However, satisfaction with self-management programs is low for persons with disabilities, and tailoring interventions to personalized needs has been recommended. SMS text messaging is increasingly being used to implement health behavior change interventions in a person's natural environment. Little has been done to link mobile health approaches with patient activation and self-management to address fatigue in persons with disabilities.

OBJECTIVE

This study aimed to develop and test a mobile phone-based fatigue self-management SMS text messaging intervention targeting patient activation in 3 groups of persons with disabilities: persons with multiple sclerosis, persons who had a stroke, and persons with a spinal cord injury.

METHODS

We used evidence-based resources and input from a consumer advisory board (CAB; composed of 2 participants from each of the 3 disability groups) and a neurologist to develop the intervention. The study was conducted using a 4-step process: development of the initial SMS text messaging library and categorization of the content into 9 content areas, review and modification of the SMS text messages by the neurologist and CAB, integration of the content library into a digital platform, and utility testing by CAB members.

RESULTS

A total of 6 CAB participants rated SMS text messages covering 9 domain areas of fatigue self-management with good clarity (mean ratings=3.5-5.0 out of 5) and relevance (mean ratings=3.2-5.0 out of 5). Overall, SMS text messaging content was reported by CAB participants as helpful, clear, and well suited for a mobile health intervention. The CAB reached consensus on the time of day that SMS text messages should be sent (morning) and their frequency (once per day). This feedback led the research team to narrow down the program to deliver 48 SMS text messages, 1 per day, Monday through Thursday only, a total of 4 SMS text messages per week, over a 12-week period. The final set of SMS text messages was programmed into a digital platform with a predefined delivery schedule. The usability of the intervention was high, with 55 (83%) out of 66 responses endorsing the highest rating.

CONCLUSIONS

This study demonstrates a step-by-step process for developing a fatigue self-management SMS text messaging intervention for persons with disabilities. For this population, whose access to health services is often limited, this intervention provides an alternative delivery model to increase access to fatigue information and deliver content that aligns with the person's needs.

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.

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.

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.

The AI Will See You Now: Feasibility and Acceptability of a Conversational AI Medical Interviewing System

Background

Primary care physicians (PCPs) are often limited in their ability to collect detailed medical histories from patients, which can lead to errors or delays in diagnosis. Recent advances in artificial intelligence (AI) show promise in augmenting current human-driven methods of collecting personal and family histories; however, such tools are largely unproven.

Objective

The main aim of this pilot study was to evaluate the feasibility and acceptability of a conversational AI medical interviewing system among patients.

Methods

The study was conducted among adult patients empaneled at a family medicine clinic within a large academic medical center in Northern California. Participants were asked to test an AI medical interviewing system, which uses a conversational avatar and chatbot to capture medical histories and identify patients with risk factors. After completing an interview with the AI system, participants completed a web-based survey inquiring about the performance of the system, the ease of using the system, and attitudes toward the system. Responses on a 7-point Likert scale were collected and evaluated using descriptive statistics.

Results

A total of 20 patients with a mean age of 50 years completed an interview with the AI system, including 12 females (60%) and 8 males (40%); 11 were White (55%), 8 were Asian (40%), and 1 was Black (5%), and 19 had at least a bachelor’s degree (95%). Most participants agreed that using the system to collect histories could help their PCPs have a better understanding of their health (16/20, 80%) and help them stay healthy through identification of their health risks (14/20, 70%). Those who reported that the system was clear and understandable, and that they were able to learn it quickly, tended to be younger; those who reported that the tool could motivate them to share more comprehensive histories with their PCPs tended to be older.

Conclusions

In this feasibility and acceptability pilot of a conversational AI medical interviewing system, the majority of patients believed that it could help clinicians better understand their health and identify health risks; however, patients were split on the effort required to use the system, and whether AI should be used for medical interviewing. Our findings suggest areas for further research, such as understanding the user interface factors that influence ease of use and adoption, and the reasons behind patients’ attitudes toward AI-assisted history-taking.

Suitability of the Unified Theory of Acceptance and Use of Technology 2 Model for Predicting mHealth Acceptance Using Diabetes as an Example: Qualitative Methods Triangulation Study

Background

In recent years, the use of mobile health (mHealth) apps to manage chronic diseases has increased significantly. Although mHealth apps have many benefits, their acceptance is still low in certain areas and groups. Most mHealth acceptance studies are based on technology acceptance models. In particular, the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model was developed to predict technology acceptance in a consumer context. However, to date, only a few studies have used the UTAUT2 model to predict mHealth acceptance and confirm its suitability for the health sector. Thus, it is unclear whether the UTAUT2 model is suitable for predicting mHealth acceptance and whether essential variables for a health-related context are missing.

Objective

This study aims to validate the suitability of UTAUT2 for predicting mHealth acceptance.

Methods

In this study, diabetes was used as an example as mHealth apps are a significant element of diabetes self-management. In addition, diabetes is one of the most common chronic diseases affecting young and older people worldwide. An explorative literature review and guided interviews with 11 mHealth or technology acceptance experts and 8 mHealth users in Austria and Germany were triangulated to identify all relevant constructs for predicting mHealth acceptance. The interview participants were recruited by purposive sampling until theoretical saturation was reached. Data were analyzed using structured content analysis based on inductive and deductive approaches.

Results

This study was able to confirm the relevance of all exogenous UTAUT2 constructs. However, it revealed two additional constructs that may also need to be considered to better predict mHealth acceptance: trust and perceived disease threat.

Conclusions

This study showed that the UTAUT2 model is suitable for predicting mHealth acceptance. However, the model should be extended to include 2 additional constructs for use in the mHealth context.

Cognitive fatigability assessment test (cFAST): Development of a new instrument to assess cognitive fatigability and pilot study on its association to perceived fatigue in multiple sclerosis

Background

Fatigue is a common symptom of many diseases, including multiple sclerosis. It manifests as a cognitive or physical condition. Fatigue is poorly understood, and effective therapies are missing. Furthermore, there is a lack of methods to measure fatigue objectively. Fatigability, the measurable decline in performance during a task, has been suggested as a complementary method to quantify fatigue.

Objective

To develop a new and objective measurement of cognitive fatigability and investigate its association with perceived fatigue.

Methods

We introduced the cognitive fatigability assessment test (cFAST), a novel smartphone-based test to quantify cognitive fatigability. Forty-two people with multiple sclerosis (23 fatigued and 19 non-fatigued, defined by the Fatigue Scale for Motor and Cognitive Functions) took part in our validation study. Patients completed cFAST twice. We used t-tests, Monte Carlo sampling, and area under the receiver operating characteristic curves to evaluate our approach using two sets of proposed metrics.

Results

When classifying fatigue, our fatigability metric Δresponse time has a mean area under the receiver operating characteristic curve of 0.74 (95% CI 0.64–0.84), making it the best performing metric for this task. Furthermore, Δresponse time shows a statistically significant difference between the fatigued and non-fatigued groups (t = 2.27, P = .03). Particularly, cognitively-fatigued patients decline in performance, while non-fatigued patients do not.

Conclusions

We introduce cFAST, a new instrument to quantify cognitive fatigability. Our pilot study provides evidence that cognitive fatigability assessment test produces a quantifiable drop in cognitive performance in a short period. Furthermore, our results indicate that cFAST may have the potential to serve as a surrogate for subjective cognitive fatigue. cFAST is significantly shorter than the existing fatigability assessments and does not require specialized equipment. Thus, it could enable frequent and remote monitoring, which could substantially aid clinicians in better understanding and treating fatigue.

Creating a Digital Toolkit to Reduce Fatigue and Promote Quality of Life in Multiple Sclerosis: Participatory Design and Usability Study

Background

Fatigue is one of the most common and debilitating symptoms of multiple sclerosis (MS), experienced by more than 80% of people with MS. FACETS (Fatigue: Applying Cognitive Behavioral and Energy Effectiveness Techniques to Lifestyle) is an evidence-based, face-to-face, 6-session group fatigue management program for people with MS. Homework tasks are an integral part of FACETS and are currently undertaken in a paper-based form. Feedback from a consultation undertaken with FACETS attendees and health care professionals with experience in delivering the FACETS program suggested that being able to complete the homework tasks digitally would be desirable, potentially enhancing engagement and adherence and enabling on-the-go access to fit into busy lifestyles. Relative to other long-term conditions, there are few apps specifically for MS and, of those available, many have been developed with little or no input from people with MS.

Objective

The purpose of this mixed methods study was to create a digital toolkit comprising the homework tasks (eg, activity diary, goal planner, thought diary) of the FACETS program for people with MS, considering end users’ unique requirements throughout the design, build, prototyping, and testing stages.

Methods

Phase 1 involved the elicitation of detailed user requirements for the toolkit via 2 focus groups with previous attendees of FACETS (n=3 and n=6) and wireframing. Phase 2 involved supervised usability testing with people with MS (n=11) with iterative prototyping. The usability sessions involved going through test scenarios using the FACETS toolkit on an Android test phone with video capture and concurrent think-aloud followed by completion of the System Usability Scale (SUS) and a semistructured interview collecting feedback about design, content, and functionality.

Results

The mean SUS score for the digital toolkit was 74.3 (SD 16.8, 95% CI 63.2-85.6; range 37.5-95), which equates to an adjective rating of good and a B grade (70th-79th percentile range) on the Sauro-Lewis curved grading scale. A number of usability and design issues (such as simplifying overall screen flow to better meet users’ needs) and suggestions for improvements (such as using location-based services and displaying personalized information and progress via a central dashboard) were addressed and implemented during the usability testing cycle.

Conclusions

This work highlights the importance of the participation of people with MS across the entire development cycle, working to a human-centered design methodology to enable a considered and MS-centered solution to be developed. Continued horizon scanning for emergent technological enhancements will enable us to identify opportunities for further improvements to the FACETS toolkit prior to launch. The toolkit supports self-monitoring and management of fatigue and has potential applicability to other long-term conditions where fatigue is a significant issue.

Acceptance towards digital health interventions - Model validation and further development of the Unified Theory of Acceptance and Use of Technology

Internet- and mobile-based interventions (IMI) offer an effective way to complement health care. Acceptance of IMI, a key facilitator of their implementation in routine care, is often low. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT), this study validates and adapts the UTAUT to digital health care. Following a systematic literature search, 10 UTAUT-grounded original studies (N = 1588) assessing patients' and health professionals' acceptance of IMI for different somatic and mental health conditions were included. All included studies assessed Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions and acceptance as well as age, gender, internet experience, and internet anxiety via self-report questionnaires. For the model validation primary data was obtained and analyzed using structural equation modeling. The best fitting model (RMSEA = 0.035, SRMR = 0.029) replicated the basic structure of UTAUT's core predictors of acceptance. Performance Expectancy was the strongest predictor (γ = 0.68, p < .001). Internet anxiety was identified as an additional determinant of acceptance (γ = -0.07, p < .05) and moderated the effects of Social Influence (γ = 0.07, p < .05) and Effort Expectancy (γ = -0.05, p < .05). Age, gender and experience had no moderating effects. Acceptance is a fundamental prerequisite for harnessing the full potential of IMI. The adapted UTAUT provides a powerful model identifying important factors - primarily Performance Expectancy - to increase the acceptance across patient populations and health professionals.

The Use of mHealth in Orthopedic Surgery: A Scoping Review

(1) Background: It is well known that the success of surgical procedures is related to optimal postoperative management and follow-up. In this regard, mHealth technologies could potentially improve perioperative care. Based on these considerations, the objective of this scoping review is to evaluate the current status and use of mHealth interventions designed to provide perioperative care in orthopedic surgery. (2) Methods: This scoping review was conducted in accordance with the PRISMA statement (Extension for Scoping Review) and follows the framework of Arskey and O'Malley. (3) Results: The use of mHealth in the surgical setting is mainly oriented towards the development of applications for monitoring post-operative pain and optimizing communication between the various health professionals involved in patient care. (4) Conclusions: The mHealth systems can have a positive impact both on patient participation in the therapeutic process and on the communication between health professionals, increasing the quality of care.

Factors Influencing the Intention of MSM to Use the PrEP Intelligent Reminder System

PURPOSE

Low adherence to medication is an important reason why pre-exposure prophylaxis (PrEP) is not effective at reducing the rate of new human immunodeficiency virus (HIV) infections among men who have sex with men (MSM). The intelligent reminder system (IRS) has been designed to improve user compliance, but the intention of MSM to use the IRS remains unclear. This study establishes a theoretical model to analyze the factors influencing their intention to use the IRS.

PATIENTS AND METHODS

Non-probability sampling was used to recruit MSM volunteers in Chongqing and Sichuan, China, and the data were collected from MSM who had used the IRS. A model based on the unified theory of acceptance and use of technology (UTAUT) was established for the data through a structural equation model, and the perceived privacy risk was considered to explore the subjects' behavior intention.

RESULTS

A total of 111 volunteers who had used the IRS filled out a questionnaire. Social influence had the greatest impact on behavior intention (β = 0.360, P < 0.001), followed by performance expectancy (β = 0.331, P < 0.001), and perceived privacy risk had a negative impact on behavior intention (β = -0.151, P = 0.040). In addition, social influence had an indirect effect on behavior intention (β = 0.182, P = 0.003) and performance expectancy played a mediating role in this indirect effect.

CONCLUSION

Developments in the IRS are required to improve its usefulness and adequately explain its role when recommending it to MSM. It is also important to improve the system's ability to protect user privacy. Clinical evidence for the effectiveness of the IRS is conducive to its widespread use.

Toward a Conversational Agent to Support the Self-Management of Adults and Young Adults With Sickle Cell Disease: Usability and Usefulness Study

Sickle cell disease (SCD) is the most common genetic blood disorder in the world and affects millions of people. With aging, patients encounter an increasing number of comorbidities that can be acute, chronic, and potentially lethal (e.g., pain, multiple organ damages, lung disease). Comprehensive and preventive care for adults with SCD faces disparities (e.g., shortage of well-trained providers). Consequently, many patients do not receive adequate treatment, as outlined by evidence-based guidelines, and suffer from mistrust, stigmatization or neglect. Thus, adult patients often avoid necessary care, seek treatment only as a last resort, and rely on self-management to maintain control over the course of the disease. Hopefully, self-management positively impacts health outcomes. However, few patients possess the required skills (e.g., disease-specific knowledge, self-efficacy), and many lack motivation for effective self-care. Health coaching has emerged as a new approach to enhance patients' self-management and support health behavior changes. Recent studies have demonstrated that conversational agents (chatbots) could effectively support chronic patients' self-management needs, improve self-efficacy, encourage behavior changes, and reduce disease-severity. To date, the use of chatbots to support SCD self-management remains largely under-researched. Consequently, we developed a high-fidelity prototype of a fully automated health coaching chatbot, following patient-important requirements and preferences collected during our previous work. We recruited a small convenience sample of adults with SCD to examine the usability and perceived usefulness of the system. Participants completed a post-test survey using the System Usability Scale and the Usefulness Scale for Patient Information Material questionnaire. Thirty-three patients participated. The majority (64%) was affected by the most clinically severe SCD genotypes (Hb SS, HbSβ0). Most participants (94%) rated the chatbots as easy and fun to use, while 88% perceived it as useful support for patient empowerment. In the qualitative phase, 72% of participants expressed their enthusiasm using the chatbot, and 82% emphasized its ability to improve their knowledge about self-management. Findings suggest that chatbots could be used to promote the acquisition of recommended health behaviors and self-care practices related to the prevention of the main symptoms of SCD. Further work is needed to refine the system, and to assess clinical validity.

Wearable technologies to measure clinical outcomes in multiple sclerosis: A scoping review

Wearable technology refers to any sensor worn on the person, making continuous and remote monitoring available to many people with chronic disease, including multiple sclerosis (MS). Daily monitoring seems an ideal solution either as an outcome measure or as an adjunct to support rater-based monitoring in both clinical and research settings. There has been an increase in solutions that are available, yet there is little consensus on the most appropriate solution to use in either MS research or clinical practice. We completed a scoping review (using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines) to summarise the wearable solutions available in MS, to identify those approaches that could potentially be utilised in clinical trials, by evaluating the following: scalability, cost, patient adaptability and accuracy. We identified 35 unique products that measure gait, cognition, upper limb function, activity, mood and fatigue, with most of these solutions being phone applications.

Technology Acceptance Among Patients With Hemophilia in Hong Kong and Their Expectations of a Mobile Health App to Promote Self-management: Survey Study

Background

The lifelong management of hemophilia is demanding and complex. In July 2019, we published a review in the Journal of Medical Internet Research, summarizing telehealth interventions that facilitate monitoring of bleeding events and promoting the appropriate use of clotting factors among patients with hemophilia. This work has led to the development of a community program that aims to harness technology to promote self-management among patients with hemophilia in Hong Kong.

Objective

Before the inception of this program, we conducted a cross-sectional survey to evaluate the patients’ level of technology acceptance and identify their expectations of the use of mobile technology for self-management of hemophilia.

Methods

In total, 56 participants (75% adult patients and 25% parents of pediatric patients; 87.5% with moderate to severe disease) were recruited from a local nongovernmental organization that serves patients with hemophilia. They rated their perceived confidence and acceptance in using the new mobile technology (score 1 to 5 for each item, with a higher score indicating better acceptance) using a structured questionnaire (adapted from the Technology Acceptance Model). They also identified the top features that they perceived to be the most important components of a mobile app for the self-management of hemophilia. The Mann–Whitney U test was used to compare technology acceptance scores across subgroups of different clinical and socioeconomic characteristics.

Results

In general, the participants considered themselves skilled in using mobile apps (mean 4.3, 95% CI 4.1-4.5). They were willing to learn to use the new mobile app to organize their bleeding records (mean 4.0, 95% CI 3.7-4.3) and to manage their health (mean 4.2, 95% CI 4.1-4.5). Participants who lived in public housing (a surrogate marker for lower socioeconomic status in Hong Kong) reported lower technology acceptance than those who lived in private housing (P=.04). The most important features identified by the participants concerned documenting of infusion logs (n=49, 87.5%), bleeding events (n=48, 85.7%), and the secure delivery of the bleeding information to health care professionals (n=40, 71.4%).

Conclusions

It is encouraging to infer that patients with hemophilia in Hong Kong are receptive to the use of mobile health technology. The findings of this survey are applicable in designing the key features of a patient-centered, multimodal program harnessing mobile technology to promote self-management among patients with hemophilia. Future studies should evaluate participants’ acceptability and perceived usability of the mobile app via user metrics and assess clinical and humanistic outcomes of this program.

Determining Acceptance of e-Mental Health Interventions in Digital Psychodiabetology Using a Quantitative Web-Based Survey: Cross-sectional Study

Background

Diabetes is a very common chronic disease that exerts massive physiological and psychological burdens on patients. The digitalization of mental health care has generated effective e-mental health approaches, which offer an indubitable practical value for patient treatment. However, before implementing and optimizing e-mental health tools, their acceptance and underlying barriers and resources should be first determined for developing and establishing effective patient-oriented interventions.

Objective

This study aims to assess the acceptance of e-mental health interventions among patients with diabetes and explore its underlying barriers and resources.

Methods

A cross-sectional study was conducted in Germany from April 9, 2020, to June 15, 2020, through a web-based survey for which patients were recruited via web-based diabetes channels. The eligibility requirements were adult age (18 years or older), a good command of the German language, internet access, and a diagnosis of diabetes. Acceptance was measured using a modified questionnaire, which was based on the well-established Unified Theory of Acceptance and Use of Technology (UTAUT) and assessed health-related internet use, acceptance of e-mental health interventions, and its barriers and resources. Mental health was measured using validated and established instruments, namely the Generalized Anxiety Disorder Scale-7, Patient Health Questionnaire-2, and Distress Thermometer. In addition, sociodemographic and medical data regarding diabetes were collected.

Results

Of the 340 participants who started the survey, 261 (76.8%) completed it and the final sample comprised 258 participants with complete data sets. The acceptance of e-mental health interventions in patients with diabetes was overall moderate (mean 3.02, SD 1.14). Gender and having a mental disorder had a significant influence on acceptance (P<.001). In an extended UTAUT regression model (UTAUT predictors plus sociodemographics and mental health variables), distress (β=.11; P=.03) as well as the UTAUT predictors performance expectancy (β=.50; P<.001), effort expectancy (β=.15; P=.001), and social influence (β=.28; P<.001) significantly predicted acceptance. The comparison between an extended UTAUT regression model (13 predictors) and the UTAUT-only regression model (performance expectancy, effort expectancy, social influence) revealed no significant difference in explained variance (F_10,244=1.567; P=.12).

Conclusions

This study supports the viability of the UTAUT model and its predictors in assessing the acceptance of e-mental health interventions among patients with diabetes. Three UTAUT predictors reached a notable amount of explained variance of 75% in the acceptance, indicating that it is a very useful and efficient method for measuring e-mental health intervention acceptance in patients with diabetes. Owing to the close link between acceptance and use, acceptance-facilitating interventions focusing on these three UTAUT predictors should be fostered to bring forward the highly needed establishment of effective e-mental health interventions in psychodiabetology.

Challenges of Implementing an mHealth Application for Personalized Physical Activity Counselling in Primary Health Care: A Qualitative Study

Introduction

A mobile health (mHealth) technology has the potential to facilitate personalized physical activity (PA) counselling. We aimed to explore the feasibility and challenges of implementing a newly developed mHealth application (PAC app) for personalized PA counselling.

Material and Methods

A qualitative design employed a descriptive phenomenology approach. Data were collected through focus group discussions (FGDs) with primary health care (PHC) providers and were analyzed using a deductive thematic approach.

Results

A total of 16 participants participated in four FGDs. Four major themes were found: application for personalized PA counselling, barriers to the use of the application by providers, patient involvement, and impact on PHC services.

Discussion

The results showed that the new mHealth application can potentially facilitate PA counselling. However, its use in PHC settings requires an understanding of the context of service delivery; the challenges faced by providers and patients and effects on services must be considered.

Conclusion

Future research should focus on the long-term use of PAC app and its impact on behavioral and health outcomes.

Mobile health (mHealth) usage, barriers, and technological considerations in persons with multiple sclerosis: a literature review

OBJECTIVES

Persons with multiple sclerosis (MS) can face a number of potential healthcare-related barriers, for which mobile health (mHealth) technology can be potentially beneficial. This review aimed to understand the frequency, current uses, and potential barriers with mHealth usage among persons with MS.

METHODS

A query string was used to identify articles on PubMed, MEDLINE, CINAHL, and IEEE Xplore that were published in English between January 2010 and December 2019. Abstracts were reviewed and selected based on a priori inclusion and exclusion criteria. Fifty-nine peer-reviewed research studies related to the study questions are summarized.

RESULTS

The majority of persons with MS were reported as using smartphones, although rates of mHealth utilization varied widely. mHealth usage was grouped into 3 broad categories: (1) disability and symptom measurement; (2) interventions and symptom management; and (3) tracking and promoting adherence. While there have been an increasing number of mHealth options, certain limitations associated with MS (eg, poor dexterity, memory problems) may affect usage, although including persons with MS in the design process can address some of these issues.

DISCUSSION

Given the increased attention to mHealth in this population and the current need for telehealth and at home devices, it is important that persons with MS and healthcare providers are involved in the development of new mHealth tools to ensure that the end product meets their needs. Considerations for addressing the potential mHealth use barriers in persons with MS are discussed.

A Smartphone-based Application for Self-Management in Multiple Sclerosis

Background

Multiple sclerosis (MS) is a chronic inflammation of the central nervous system and self-management is necessary for MS patients. The purpose of the present study was to develop a smartphone-based application for self-management in multiple sclerosis.

Methods

This research was conducted in two phases. In the first phase, users' requirements were investigated by using a questionnaire. The participants were 120 MS patients and six neurologists. In the second phase, a prototype of the application was designed and its usability was evaluated by using QUIS questionnaire.

Results

Most of the proposed educational content, data elements, and the application functions, such as medication time reminder, assessing the severity of fatigue, and calculating the score of the Fatigue Severity Scale were found necessary to be included in the application. Finally, the usability of the application was evaluated by the users and the average of mean values was 7.6 out of 9 which indicated a “good” level of user satisfaction.

Conclusions

The application designed in this study was able to collect patient data and facilitated consulting physicians at the point of need. It is expected that the patients' quality of life and health status can be improved by using this application. However, more research is required to investigate the efficiency and effectiveness of this application in terms of reducing the number of visits to the medical centers, improving self-management skills of MS patients and their quality of life.

Digital Technology in Clinical Trials for Multiple Sclerosis: Systematic Review

Clinical trials in multiple sclerosis (MS) have been including digital technology tools to overcome limitations in treatment delivery and disease monitoring. In March 2020, we conducted a systematic search on pubmed.gov and clinicaltrials.gov databases (with no restrictions) to identify all relevant published and unpublished clinical trials, in English language, including MS patients, in which digital technology was applied. We used “multiple sclerosis” and “clinical trial” as the main search words, and “app”, “digital”, “electronic”, “internet” and “mobile” as additional search words, separately. Digital technology is part of clinical trial interventions to deliver psychotherapy and motor rehabilitation, with exergames, e-training, and robot-assisted exercises. Digital technology has been used to standardise previously existing outcome measures, with automatic acquisitions, reduced inconsistencies, and improved detection of symptoms (e.g., electronic recording of motor performance). Other clinical trials have been using digital technology for monitoring symptoms that would be otherwise difficult to detect (e.g., fatigue, balance), for measuring treatment adherence and side effects, and for self-assessment purposes. Collection of outcome measures is progressively shifting from paper-based on site, to internet-based on site, and, in the future, to internet-based at home, with the detection of clinical and treatment features that would have remained otherwise invisible. Similarly, remote interventions provide new possibilities of motor and cognitive rehabilitation.

Designing the Optimal Digital Health Intervention for Patients' Use Before and After Elective Orthopedic Surgery: Qualitative Study

Background

Health behavior changes made by patients during the perioperative period can impact the outcomes and success of elective surgeries. However, there remains a limited understanding of how best to support patients during this time, particularly through the use of digital health interventions. Recognizing and understanding the potential unmet needs of elective orthopedic surgery patients is central to motivating healthier behavior change, improving recovery, and optimizing overall surgical success in the short and long term.

Objective

The aim of this study is to explore patient perspectives on technology features that would help support them to change their lifestyle behaviors during the pre- and postoperative periods, and that could potentially maintain long-term healthy lifestyles following recovery.

Methods

Semistructured interviews with pre- and postoperative elective orthopedic patients were conducted between May and June 2020 using telephone and video call–based software. Patient perspectives on the use of digital technologies to complement current surgical care and support with lifestyle behavior changes were discussed. Interviews were audio recorded and transcribed verbatim. Reflexive thematic analysis enabled the development of themes from the data, with QSR NVivo software (version 12) facilitating data management. Ethical approval was obtained from the National Health Service Health Research Authority.

Results

A total of 18 participants were interviewed. Four themes were developed from the data regarding the design and functionality of digital technologies to best support the perioperative journey. These center around an intervention’s ability to incorporate interactive, user-centered features; direct a descriptive and structured recovery; enable customizable, patient-controlled settings; and deliver both general and specific surgical advice in a timely manner. Interventions that are initiated preoperatively and continued postoperatively were perceived as beneficial. Interventions designed with personalized milestones were found to better guide patients through a structured recovery. Individualized tailoring of preparatory and recovery information was desired by patients with previously high levels of physical activity before surgery. The use of personalized progression-based exercises further encouraged physical recovery; game-like rewards and incentives were regarded as motivational for making and sustaining health behavior change. In-built video calling and messaging features offered connectivity with peers and clinicians for supported care delivery.

Conclusions

Specific intervention design and functionality features can provide better, structured support for elective orthopedic patients across the entire surgical journey and beyond. This study provides much-needed evidence relating to the optimal design and timing of digital interventions for elective orthopedic surgical patients. Findings from this study suggest a desire for personalized perioperative care, in turn, supporting patients to make health behavior changes to optimize surgical success. These findings should be used to influence future co-design projects to enable the design and implementation of patient-focused, tailored, and targeted digital health technologies within modern health care settings.

The Types and Pattern of Use of Mobile Health Applications Among the General Population: A Cross-Sectional Study from Selangor, Malaysia

PURPOSE

The aims of this study are to explore the types and patterns of use of health mobile apps among pharmacy clients in Selangor, Malaysia, and to explore the users' experiences and views regarding the benefits of and issues with the use of the health apps.

PATIENTS AND METHODS

A cross-sectional survey was conducted with 278 pharmacy clients who were using health apps on their smartphones. A survey was developed, piloted, and rolled out, comprised of socio-demographic characteristics, information regarding the common types and the pattern of health app use, the benefits of health apps, and issues that users faced while using these apps. Statistical analysis was performed using IBM SPSS version 21.

RESULTS

The mean (±SD) age of health app users was 29.8 (±11.74) years old, and over half of them (51.8%) were male, while less than half were female (48.2%). There were 48 different types of mobile health apps used by the participants in this study. The two most common were multi-purpose general health apps (53.6%) and fitness apps (38.1%). In terms of pattern of use, 33.5% of the participants reported using their health apps daily, 36.7% at least once weekly, and 25.2% monthly. The main benefits reported by the users were tracking of health status (47%), motivation (41%), and knowledge about health and fitness (9%). The main issues reported by the participants included inaccuracy of the app (24%), inconvenience (20.7%), and not being user-friendly (18.5%).

CONCLUSION

The study showed that the participants used many different types of mobile health apps for several purposes, including general health, wellness, fitness, and self-management of diseases. These apps helped the participants to track their health-related activities and motivated them to maintain their wellness and fitness. Further areas of improvement were identified to ensure evidence-based and effective utilization of apps to achieve required health outcomes.

Drivers of Mobile Health Acceptance and Use From the Patient Perspective: Survey Study and Quantitative Model Development

Background

Mobile health (mHealth) has potential to play a significant role in realizing a reversal of the current paradigm in health care toward a more patient-centric and more collaborative system to improve the outcomes obtained along with the quality and sustainability of health care systems.

Objective

The aim of this study was to explore and understand individual mHealth acceptance drivers between two groups of users: those with chronic health conditions and those without.

Methods

The extended unified theory of acceptance and usage of technology (UTAUT2) was enhanced with a new health-related framework: behavior intention to recommend and new mediation effects. We applied partial least squares (PLS) causal modeling to test the research model.

Results

We obtained 322 valid responses through an online questionnaire. The drivers of behavior intention with statistical significance were performance expectancy (β=.29, P<.001), habit (β=.39, P<.001), and personal empowerment (β=.18, P=.01). The precursors of use behavior were habit (β= .47, P<.001) and personal empowerment (β=.17, P=.01). Behavior intention to recommend was significantly influenced by behavior intention (β=.58, P<.001) and personal empowerment (β=.26, P<.001). The model explained 66% of the total variance in behavior intention, 54% of the variance in use behavior, and 70% of the variance in behavior intention to recommend.

Conclusions

Our study demonstrates a significant role of personal empowerment, as a second-order construct, in the mHealth acceptance context. The presence of a chronic health condition predicates an impact on acceptance of this technology.

Differential influences of social support on app use for diabetes self-management - a mixed methods approach

Background

Recent studies increasingly examine social support for diabetes self-management delivered via mHealth. In contrast to previous studies examining social support as an outcome of technology use, or technology as a means for delivering social support, this paper argues that social support has an impact on the use of diabetes mHealth apps. Specifically, we postulate differences between the impact of healthcare professional versus non-professional (family/friends) support on mobile app use for diabetes self-management.

Methods

This research employed a triangulation of methods including exploratory semi-structured face-to-face interviews (N = 21, Study 1) and an online survey (N = 65, Study 2) with adult type 1 and type 2 diabetes patients. Thematic analysis (Study 1) was used to explore the relevance of social support (by professionals versus non-professionals) for diabetes app use. Binary logistic regression (Study 2) was applied to compare healthcare decision-making, healthcare-patient communication, and the support by the personal patient network as predictors of diabetes app use, complemented by other predictors from self-management and technology adoption theory.

Results

The interviews (Study 1) demonstrated that (technology-supported) shared decision-making and supportive communication by healthcare professionals depended on their medical specialty. The personal patient network was perceived as either facilitating or hindering the use of mHealth for self-management. Binary logistic regression (Study 2) showed that the physician specialty significantly predicted the use of diabetes apps, with supervision by diabetes specialists increasing the likelihood of app use (as opposed to general practitioners). Additionally, specialist care positively related to a higher chance of shared decision-making and better physician-patient communication. The support by the personal patient network predicted diabetes app use in the opposite direction, with less family/friend support increasing the likelihood of app use.

Conclusion

The results emphasize the relevance of support by healthcare professionals and by the patient network for diabetes app use and disclose differences from the existing literature. In particular, the use of diabetes apps may increase in the absence of social support by family or friends (e.g., compensation for lack of support), and may decrease when such support is high (e.g., no perceived need to use technology).

'It struck at the heart of who I thought I was': A meta-synthesis of the qualitative literature examining the experiences of people with multiple sclerosis

Background

People with multiple sclerosis (MS) have varied experiences and approaches to self‐management. This review aimed to explore the experiences of people with MS, and consider the implications of these experiences for clinical practice and research.

Methods

A meta‐synthesis of the qualitative literature examining experiences of people with MS was conducted using systematic searches of ProQuest, PubMed, CINAHL and PsycINFO. We incorporated feedback from team members with MS as expert patient knowledge‐users to capture the complex subjectivities of persons with lived experience responding to research on lived experience of the same disease.

Results

Of 1680 unique articles, 77 met the inclusion criteria. We identified five experiential themes: (a) the quest for knowledge, expertise and understanding, (b) uncertain trajectories (c) loss of valued roles and activities, and the threat of a changing identity, (d) managing fatigue and its impacts on life and relationships, and (f) adapting to life with MS. These themes were distributed across three domains related to disease (symptoms; diagnosis; progression and relapse) and two contexts (the health‐care sector; and work, social and family life).

Conclusion

The majority of people in the studies included in this review expressed a determination to adapt to MS, indicating a strong motivation for people with MS and clinicians to collaborate in the quest for knowledge. Clinicians caring for people with MS need to consider the experiential and social outcomes of this disease such as fatigue and the preservation of valued social roles, and incorporate this into case management and clinical planning.

Feasibility of a smartphone app to enhance physical activity in progressive MS: a pilot randomized controlled pilot trial over three months

BACKGROUND

People with chronic progressive multiple sclerosis (CPMS) have limited options in medical treatment. Enhancing physical activity (PA) might promote neuroregeneration in multiple sclerosis (MS) and positively influence disability, thus providing an alternative to medical treatment. Previous studies indicate that evidence-based patient information (EBPI) is essential for inducing behavioral change, e.g. enhancing PA.

OBJECTIVE

To investigate feasibility of a smartphone app providing EBPI about the benefit of PA and a simple activity feedback to enhance PA in people with CPMS in a pilot randomized controlled trial over 3 months.

METHODS

Thirty-eight people with CPMS (mean age 51 years, median Expanded Disability Status Scale 4.0) were 1:1 randomized into either a control group (n = 20) or an intervention group (n = 18). The intervention group received access to a multimedia EBPI app including activity feedback, texts, figures and videos. In the control group, participants received a leaflet with unspecific information about exercising in general. The EPBI itself was designed based on a systematic review. At baseline and after 3 months, all participants underwent clinical performance tests, filled in questionnaires and received an activity monitor (Actigraph®) for 7 days. The primary endpoint was the rate of responders defined as participants with a 20% increase of physical acitivity (time of moderate or vigiorous PA-MVPA) or 20% increase of the number of steps, both assessed with the activity monitor. As secondary endpoints, we compared accelerometry, performance and questionnaires adjusted for baseline measurments between the groups (ANCOVA). Moreover, we used questionnaires to compare knowledge about exercise (activity requiring physical effort, carried out to improve or improve health and fitness) in MS, usability of the app in general and motivation towards a more active lifestyle after 3 months in both groups.

RESULTS

The groups showed significant differences in disease duration and PA according to the Godin-Leisure Time Exercise Questionnaire at baseline. After 3 months, we detected no difference in the rate of responders, which was an overall 22%. However, MVPA significantly increased in both groups (p < 0.001) and the intervention group tended to have a higher motivation towards a more active lifestyle (Cohens D = 0.7, p = 0.09) as measured by the questionnaire. Reponses also showed, that participants appreciated the app but claimed a lack of interactivity as a short-coming.

CONCLUSION

Just providing information in a multimedia smartphone app did not enhance physical activitiy more than a simple leaflet in this small pilot trial in CPMS. However, the group of app users tended to have a higher motivation towards a more active lifestyle. Overall, the concept of a smartphone app to support an active lifestyle in MS is highly appreciated by participants.

Telecommunication and rehabilitation for patients with multiple sclerosis: access and willingness to use. A cross-sectional study

BACKGROUND

Telerehabilitation is a promising approach for patients with multiple sclerosis (MS), but uncertainties regarding patients' access and preferences remain.

AIM

To investigate the access to telecommunication technologies and rehabilitation services of patients with MS, and their willingness to use these technologies for rehabilitation.

DESIGN

Cross-sectional survey.

SETTING

Outpatient neurological facility.

POPULATION

Patients with MS.

METHODS

Patients with MS attending consultations in the Neurology department were asked to fill in a paper questionnaire. This anonymous z was designed to gain information about needs and access to rehabilitation and telecommunication technologies, as well as interests and perspectives of telerehabilitation among these patients. Descriptive statistics, Chi-squared tests and logistic regressions were used to describe the sample and survey answers.

RESULTS

Two hundred patients completed the questionnaire. Mean age was 44.41(±12.52) years. Seventy-one percent were women, and 49% were unemployed. Ninety-one percent of the patients regularly used internet and 73% used apps. Most patients were interested in using telecommunication technologies to receive a program of physical exercises (62%), for information and personalized advice about physical activity and MS (69%), and to communicate with caregivers (75%). Patients with EDSS>4 were less interested than patients with EDSS≤4 in communicating with the caregivers via apps (33% vs. 52%,Δ19%[CI-36%;-2%],P=0.04) but expressed greater interest in receiving information and personal advice about physical activity and MS via the internet (70% vs. 51%,Δ19%[CI+2%;+36%],P=0.03). One third of the patients was not interested in receiving telerehabilitation interventions (32%), notably patients with EDSS>4 and non-workers.

CONCLUSIONS

Patients with MS are mainly interested in using telecommunication technologies for rehabilitation services, and most of these patients have access to the required technology. Being mildly disabled and having a professional activity are associated with a greater interest in telerehabilitation. In contrary, patients with moderate-to-severe disability and non-workers have reportedly less access and ease in using the required technologies.

CLINICAL REHABILITATION IMPACT

Telerehabilitation is feasible and wished by patients with MS, specifically in patients with low EDSS scores and workers. Given the strong need for rehabilitation in more disabled patients, the barriers to its access, the lower access and ease of use of telecommunication technologies, a special effort is needed to facilitate their use in these patients.

The Interactive Web-Based Program MSmonitor for Self-Management and Multidisciplinary Care in Persons With Multiple Sclerosis: Quasi-Experimental Study of Short-Term Effects on Patient Empowerment

BACKGROUND

Empowerment helps persons with a chronic disease to self-manage their condition and increase their autonomy and participation. MSmonitor (Curavista bv) is an interactive Web-based program for self-management and multidisciplinary care in multiple sclerosis (MS). It includes, among others, short questionnaires on fatigue (Modified Fatigue Impact Scale-5 [MFIS-5]) and health-related quality of life (HRQoL, Leeds Multiple Sclerosis Quality of Life [LMSQoL]); long questionnaires on disabilities, perception of disabilities (Multiple Sclerosis Impact Profile), and HRQoL (Multiple Sclerosis Quality of Life-54); a Medication and Adherence Inventory and an Activity Diary. The combination MFIS-5, LMSQoL, and Medication and Adherence Inventory constitutes the Quick Scan.

OBJECTIVE

This study aimed to investigate the short-term effects of MSmonitor on empowerment in patients with MS.

METHODS

We conducted a quasi-experimental study in a general hospital. Of the 180 patients with MS, 125 were eligible, 30 used MSmonitor, and 21 participated in the study (mean age 45.4 years, SD 10.2 years). A total of 24 eligible patients who did not use MSmonitor constituted the control group (mean age 49.3 years, SD 11.4 years). At baseline and at 4 months, we assessed self-efficacy (Multiple Sclerosis Self-Efficacy Scale [MSSES]), participation and autonomy (Impact on Participation and Autonomy [IPA] questionnaire), and self-management (Partners In Health [PIH] questionnaire). Differences between time points and groups were tested with paired t tests and χ² tests.

RESULTS

In the MSmonitor group, follow-up values remained unchanged for MSSES control (P=.19), MSSES function (P=.62), IPA limitations (P=.26), IPA problems (P=.40), PIH recognition and management of symptoms (P=.52), PIH adherence to treatment (P=.80), and PIH coping (P=.73), whereas the PIH knowledge score had improved (mean 27.8, SD 1.7 vs mean 28.7, SD 2.0; P=.02). The overall utilization rate of the program components was 83% and that of the Quick Scan was 95%. In the control group, all outcomes had remained unchanged.

CONCLUSIONS

The results suggest that for first-time users of the MSmonitor program and their health care providers, it may not be justified to expect a short-term improvement in empowerment in terms of self-efficacy, self-management, autonomy, or participation. Furthermore, a lack of effect on empowerment is not because of nonusage of the program components.

Determinant Factors of Public Acceptance of Stress Management Apps: Survey Study

BACKGROUND

Chronic stress is a major public health concern. Mobile health (mHealth) apps can help promote coping skills in daily life and prevent stress-related issues. However, little is known about the determinant factors of public acceptance of stress management in relation to preferences for psychological services.

OBJECTIVE

The aim of this survey study was to (1) assess determinant factors of public acceptance (behavioral use intention) of stress management apps based on an adapted and extended version of the Unified Theory of Acceptance and Use of Technology (UTAUT) model and (2) explore preferences for mHealth apps compared with other mental health services.

METHODS

Using convenience sampling, participants completed a multiscale 54-item Web-based survey. Based on significant correlations with acceptance, hierarchical stepwise regression analysis was performed within three blocks: (1) background and stress-related control variables, (2) beliefs and attitudes toward using mHealth, and (3) the core UTAUT determinants. The preference for mHealth apps in comparison with nine other mental health services (operationalized as readiness to use) was analyzed using paired t tests.

RESULTS

Of 141 participants, nearly half (69/141, 48.9%) indicated prior mHealth use. Acceptance of stress coping apps was moderate (mean 3.10, SD 1.03, range 1-5). Hierarchical stepwise regression including four of 11 variables (R²=.62; P=.01, f²=1.63) identified positive attitudes toward using mHealth for stress coping (beta=0.69, P<.001, 46% R² increase above block 1, f²=0.85), skepticism/perceived risks (beta=-0.14, P=.01, f²=0.16), and stress symptoms (beta=0.12, P=.03, f²=0.14) as significant predictors of acceptance. UTAUT determinants added no predictive contribution beyond attitudes (all P>.05, R² increase of 1%), whereas post hoc analysis showed significant R² increases of attitudes and skepticism/perceived risks beyond UTAUT determinants (all P<.001, R² increase of 13%). The readiness to use apps was equivalent to or significantly higher than most service types, but lower than information websites.

CONCLUSIONS

Attitudes may be at least as predictive for the acceptance of stress management apps as for more elaborated outcome beliefs. Efforts aimed at improving the public adoption of mHealth could put more emphasis on the pleasant aspects of app use, address misconceptions, offer stress screening tools on health websites, and increase options to try high-quality apps.

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

BACKGROUND

Diabetes poses heavy social and economic burdens worldwide. Diabetes management apps show great potential for diabetes self-management. However, the adoption of diabetes management apps by diabetes patients is poor. The factors influencing patients' intention to use these apps are unclear. Understanding the patients' behavioral intention is necessary to support the development and promotion of diabetes app use.

OBJECTIVE

This study aimed to identify the determinants of patients' intention to use diabetes management apps based on an integrated theoretical model.

METHODS

The hypotheses of our research model were developed based on an extended Unified Theory of Acceptance and Use of Technology (UTAUT). From April 20 to May 20, 2019, adult patients with diabetes across China, who were familiar with diabetes management apps, were surveyed using the Web-based survey tool Sojump. Structural equation modeling was used to analyze the data.

RESULTS

A total of 746 participants who met the inclusion criteria completed the survey. The fitness indices suggested that the collected data fit well with the research model. The model explained 62.6% of the variance in performance expectancy and 57.1% of the variance in behavioral intention. Performance expectancy and social influence had the strongest total effects on behavioral intention (β=0.482; P=.001). Performance expectancy (β=0.482; P=.001), social influence (β=0.223; P=.003), facilitating conditions (β=0.17; P=.006), perceived disease threat (β=0.073; P=.005), and perceived privacy risk (β=-0.073; P=.012) had direct effects on behavioral intention. Additionally, social influence, effort expectancy, and facilitating conditions had indirect effects on behavioral intention that were mediated by performance expectancy. Social influence had the highest indirect effects among the three constructs (β=0.259; P=.001).

CONCLUSIONS

Performance expectancy and social influence are the most important determinants of the intention to use diabetes management apps. Health care technology companies should improve the usefulness of apps and carry out research to provide clinical evidence for the apps' effectiveness, which will benefit the promotion of these apps. Facilitating conditions and perceived privacy risk also have an impact on behavioral intention. Therefore, it is necessary to improve facilitating conditions and provide solid privacy protection. Our study supports the use of UTAUT in explaining patients' intention to use diabetes management apps. Context-related determinants should also be taken into consideration.

Digitizing a Face-to-Face Group Fatigue Management Program: Exploring the Views of People With Multiple Sclerosis and Health Care Professionals Via Consultation Groups and Interviews

BACKGROUND

Fatigue is one of the most common and debilitating symptoms of multiple sclerosis (MS) and is the main reason why people with MS stop working early. The MS Society in the United Kingdom funded a randomized controlled trial of FACETS-a face-to-face group-based fatigue management program for people with multiple sclerosis (pwMS)-developed by members of the research team. Given the favorable trial results and to help with implementation, the MS Society supported the design and printing of the FACETS manual and materials and the national delivery of FACETS training courses (designed by the research team) for health care professionals (HCPs). By 2015 more than 1500 pwMS had received the FACETS program, but it is not available in all areas and a face-to-face format may not be suitable for, or appeal to, everyone. For these reasons, the MS Society funded a consultation to explore an alternative Web-based model of service delivery.

OBJECTIVE

The aim of this study was to gather views about a Web-based model of service delivery from HCPs who had delivered FACETS and from pwMS who had attended FACETS.

METHODS

Telephone consultations were undertaken with FACETS-trained HCPs who had experience of delivering FACETS (n=8). Three face-to-face consultation groups were held with pwMS who had attended the FACETS program: London (n=4), Liverpool (n=4), and Bristol (n=7). The interviews and consultation groups were digitally recorded and transcribed. A thematic analysis was undertaken to identify key themes. Toward the end of the study, a roundtable meeting was held to discuss outcomes from the consultation with representatives from the MS Society, HCPs, and pwMS.

RESULTS

Key challenges and opportunities of designing and delivering an integrated Web-based version of FACETS and maintaining user engagement were identified across 7 themes (delivery, online delivery, design, group, engagement, interactivity, and HCP relationships). Particularly of interest were themes related to replicating the group dynamics and the lack of high-quality solutions that would support the FACETS' weekly homework tasks and symptom monitoring and management.

CONCLUSIONS

A minimum viable Web-based version of FACETS was suggested as the best starting point for a phased implementation, enabling a solution that could then be added to over time. It was also proposed that a separate study should look to create a free stand-alone digital toolkit focusing on the homework elements of FACETS. This study has commenced with a first version of the toolkit in development involving pwMS throughout the design and build stages to ensure a user-centered solution.

What Kind Of A Mobile Health App Do Patients Truly Want? A Pilot Study Among Ambulatory Surgery Patients

BACKGROUND

An increasing number of surgeries are performed as ambulatory surgeries, and mobile health applications (m-health apps) have therefore been designed to help provide patients with more convenient health-care services and improve the working efficiency of health-care professionals (HCPs). To find an effective approach to design such m-health apps, a study to evaluate ambulatory surgery patients' preferences is necessary.

METHODS

A structured questionnaire was distributed to 360 patients undergoing ambulatory surgery to understand their demographic characteristics, preferences regarding the features and functions of m-health apps and willingness to engage with m-health apps.

RESULTS

In total, 84.16% of ambulatory surgery patients stated that they would be willing to engage with an m-health app during the perioperative period. In addition, their top 10 necessary features and functions of m-health apps were related mainly to ambulatory surgery and communication with HCPs. Furthermore, younger age (χ ²=10.42, p<0.01), employment (χ ²=9.04, p<0.01), higher education (χ ²=13.67, p<0.01), longer daily use of phones (χ ²=11.84, p<0.01) and more frequent usage of m-health apps (χ ²=23.23, p<0.01) were associated with patients' willingness to engage with m-health apps, but only more frequent usage of m-health apps (OR=2.97, 95% CI=1.54-5.71, p<0.01) was found to be a predictor.

CONCLUSION

This study presents an initial evaluation of ambulatory surgery patients' preferences regarding m-health apps. Gaining these insights will be useful to help us design an evidence-based, highly functional m-health app that best meets the needs of patients undergoing ambulatory surgery.