Patients’ emotional bonding with MHealth apps: An attachment perspective on patients’ use of MHealth applications

Health Maintenance Organization-mHealth Versus Face-to-Face Interaction for Health Care in Israel: Cross-Sectional Web-Based Survey Study

BACKGROUND

Health maintenance organization-mobile health (HMO-mHealth) services have a direct impact on patients' daily lives, and HMOs regularly expand their range of mHealth services. HMO-mHealth apps are saving HMOs time and money, as services are becoming more accessible to patients. However, the willingness to use mHealth apps depends on user perception. Although mHealth apps can change the relationship dynamic between HMOs and patients, patients prefer to use them to facilitate face-to-face interactions rather than replace them.

OBJECTIVE

This study aims to examine the extent to which Israeli adults prefer adopting health care services using HMO-mHealth as a replacement for face-to-face interaction.

METHODS

Israeli adults aged ≥18 years completed an electronic questionnaire. Data were collected from December 2020 to February 2021. All services in the main HMO-mHealth apps of the 4 Israeli HMOs were mapped. The 29 health care services used in this study were identical in all 4 HMO-mHealth apps in Israel. The association between sociodemographic characteristics and health condition with preference for HMO-mHealth or face-to-face interaction was analyzed separately for each health service by using a logistic model.

RESULTS

A total of 6321 respondents completed the questionnaire (female: 4296/6321, 68%; male: 2025/6321, 32%). Approximately 80.9% (5115/6321) to 88.2% (5578/6321) of the respondents preferred using HMO-mHealth apps for administrative matters. However, 55.3% (3498/6321), 52.2% (3301/6321), and 46.9% (2969/6321) preferred face-to-face meetings for the initial medical diagnosis, medical treatment, and medical diagnosis results, respectively. Seven main variables were found to be associated with HMO-mHealth adoption, including gender, age, education, marital status, religious affiliation, and subjective health condition. Female respondents were more likely than male respondents to prefer HMO-mHealth apps for administrative matters and face-to-face interaction for personal medical diagnosis and treatment (odds ratio [OR] 0.74, 95% CI 0.67-0.83; P<.001 and OR 0.82, 95% CI 0.74-0.92; P<.001, respectively). Married individuals preferred using HMO-mHealth apps over face-to-face meetings for a new medical diagnosis (OR 1.31, 95% CI 1.15-1.49; P<.001) or treatment (OR 1.34, 95% CI 1.18-1.52; P<.001). Improved health perception was associated with higher preference for HMO-mHealth apps across all health care services in this study (OR 1.11, 95% CI 1.02-1.22; P<.02 to OR 1.38, 95% CI 1.25-1.53; P<.001). No significant association was found between the presence of a chronic disease and the preferred mode of interaction for most services.

CONCLUSIONS

HMO-mHealth is proving to be a robust and efficient tool for health care service delivery. However, there are barriers that affect vulnerable populations when adopting HMO-mHealth. Therefore, it is important to tailor HMO-mHealth apps for older adults, the chronically ill, and minorities in society, as these groups have a greater need for these services. Future studies should focus on identifying the barriers that affect the utilization of HMO-mHealth in these groups.

Critical success factors for creating sustainable digital health applications: A systematic review of the German case

Objective

The Covid-19 pandemic has accelerated the adoption of digital technologies to address social needs, leading to increased investments in digital healthcare applications. Germany implemented a special law called the "Digitales Versorgungsgesetz" (DVG-Digital Supply Act) in 2019, which enables the reimbursement of digital health applications, including digital therapeutics (DTx), through a fast-track process. The Federal Institute for Drugs and Medical Devices (BfArM), the German federal authority responsible for overseeing digital health applications, has implemented legislative adjustments since the law's introduction, which have increased requirements for these applications and potentially led to the removal of some from the directory as well as a slowdown in the addition of new ones. To counteract this trend, this work aimed to identify key success factors for digital health applications (DiGAs).

Methods

This research identifies critical success factors through a structured literature review for developing sustainable digital health applications within the European healthcare systems, specifically DiGAs. The study aims to support the ongoing digital transformation in healthcare.

Results

The identified success factors that significantly impact the sustainability of DiGAs include patient-centered design, application effectiveness, user-friendliness, and adherence to data protection and information security regulations using standardized approaches. These factors are crucial in preventing the failure of DiGA manufacturers in European countries.

Conclusion

By considering and implementing these critical success factors, DiGA manufacturers can enhance their chances of long-term success and contribute to the digital transformation of the healthcare system in Europe.

Efficacy of Intellect's self-guided anxiety and worry mobile health programme: A randomized controlled trial with an active control and a 2-week follow-up

Digital self-guided mobile health [mHealth] applications are cost-effective, accessible, and well-suited to improve mental health at scale. This randomized controlled trial [RCT] evaluated the efficacy of a recently developed mHealth programme based on cognitive-behavioral therapy [CBT] principles in improving worry and anxiety. We also examined psychological mindedness [PM] as a mediator by which app engagement is thought to improve outcomes. The Intervention group completed a 2-week "Anxiety and Worry" programme with daily CBT-informed activities, while the active waitlist-control completed a matched 2-week mHealth programme on procrastination. Participants filled out the Generalized Anxiety Disorder [GAD-7], Patient Health Questionnaire [PHQ-9], and Psychological Mindedness Scale [PMS] at baseline, post-intervention, and 2-week follow-up. App engagement was measured at post-intervention only. Contrary to prediction, the Intervention group did not perform better than the Active Control group; both groups showed significant improvements on anxiety and depressive symptoms from baseline to follow-up. From post-intervention to follow-up, only the Intervention group showed further improvements for anxiety symptoms. Higher engagement with the mHealth app predicted lower anxiety and depressive symptoms at follow-up, and this relationship was fully mediated by psychological mindedness. This study provides evidence that [a] engaging in a CBT mHealth programme can reduce anxiety and worry, and [b] Psychological mindedness is a potential pathway by which engaging with a mHealth app improves anxiety and depressive symptoms. While overall effect sizes were small, at the population level, these can make significant contributions to public mental health.

Increasing acceptance of medical AI: The role of medical staff participation in AI development

BACKGROUND

Medical artificial intelligence (AI) in varying degrees has exerted significant influence on many medical fields, especially in the midst of the COVID-19 pandemic. However, little is known regarding how to address the reluctance of medical staff to use AI technology. While recent research has highlighted the importance of medical staff participation in the development of AI, the current understanding of influence of medical staff participation on acceptance of AI is limited.

OBJECTIVES

To provide insights into the mechanism that how medical staff participation impacts on the medical staff's acceptance of AI and to examine the moderating effect of speciesism.

METHODS

This study was conducted from 6th August to 3rd September. Data was collected from doctors and nurses and a total of 288 valid questionnaires were obtained. Smart PLS 3.2.8 was used as partial least square (PLS) software to validate the research model.

RESULTS

The study determined that medical staff participation had a significant impact on acceptance of medical AI-IDT (β = 0.35, p ≤ 0.001) and acceptance of medical AI-ADT (β = 0.44, p ≤ 0.001). The results also show that AI self-efficacy and AI anxiety have significant mediating effects and speciesism has significant moderating effects among the theoretical model.

CONCLUSIONS

This study provides insights into ways to explore influence factors of acceptance of AI based on user participation perspective. The results indicate that medical staff participation enhances acceptance of medical AI through the cognitive path (i.e., AI self-efficacy) and the affective path (i.e., AI anxiety). These results have practical implications for how organizations assist the staff to accommodate themselves to AI technology in the future.

Exploring the factors that affect user experience in mobile-health applications: A text-mining and machine-learning approach

Recent years have witnessed an increased demand for mobile health (mHealth) platforms owing to the COVID-19 pandemic and preference for doorstep delivery. However, factors impacting user experiences and satisfaction levels across these platforms, using customer reviews, are still largely unexplored in academic research. The empirical framework we proposed in this paper addressed this research gap by analysing unmonitored user comments for some popular mHealth platforms. Using topic-modelling techniques, we identified the impacting factors (predictors) and categorised them into two major dimensions based on strategic adoption and motivational association. Findings from our study suggest that time and money, convenience, responsiveness, and availability emerge as significant predictors for delivering a positive user experience on m-health platforms. Next, we identified substantial moderating effects of review polarity on the predictors related to brand association and hedonic motivation, such as online booking and video consultation. Further, we also identified the top predictors for successful user experience across these platforms. Recommendations from our study will benefit business managers by offering an improved service design leading to higher user satisfaction across these m-health platforms.

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.

Digital Health Technologies for Long-term Self-management of Osteoporosis: Systematic Review and Meta-analysis

Background

Osteoporosis is the fourth most common chronic disease worldwide. The adoption of preventative measures and effective self-management interventions can help improve bone health. Mobile health (mHealth) technologies can play a key role in the care and self-management of patients with osteoporosis.

Objective

This study presents a systematic review and meta-analysis of the currently available mHealth apps targeting osteoporosis self-management, aiming to determine the current status, gaps, and challenges that future research could address, as well as propose appropriate recommendations.

Methods

A systematic review of all English articles was conducted, in addition to a survey of all apps available in iOS and Android app stores as of May 2021. A comprehensive literature search (2010 to May 2021) of PubMed, Scopus, EBSCO, Web of Science, and IEEE Xplore was conducted. Articles were included if they described apps dedicated to or useful for osteoporosis (targeting self-management, nutrition, physical activity, and risk assessment) delivered on smartphone devices for adults aged ≥18 years. Of the 32 articles, a random effects meta-analysis was performed on 13 (41%) studies of randomized controlled trials, whereas the 19 (59%) remaining studies were only included in the narrative synthesis as they did not provide enough data.

Results

In total, 3906 unique articles were identified. Of these 3906 articles, 32 (0.81%) articles met the inclusion criteria and were reviewed in depth. The 32 studies comprised 14,235 participants, of whom, on average, 69.5% (n=9893) were female, with a mean age of 49.8 (SD 17.8) years. The app search identified 23 relevant apps for osteoporosis self-management. The meta-analysis revealed that mHealth-supported interventions resulted in a significant reduction in pain (Hedges g −1.09, 95% CI −1.68 to −0.45) and disability (Hedges g −0.77, 95% CI −1.59 to 0.05). The posttreatment effect of the digital intervention was significant for physical function (Hedges g 2.54, 95% CI −4.08 to 4.08) but nonsignificant for well-being (Hedges g 0.17, 95% CI −1.84 to 2.17), physical activity (Hedges g 0.09, 95% CI −0.59 to 0.50), anxiety (Hedges g −0.29, 95% CI −6.11 to 5.53), fatigue (Hedges g −0.34, 95% CI −5.84 to 5.16), calcium (Hedges g −0.05, 95% CI −0.59 to 0.50), vitamin D intake (Hedges g 0.10, 95% CI −4.05 to 4.26), and trabecular score (Hedges g 0.06, 95% CI −1.00 to 1.12).

Conclusions

Osteoporosis apps have the potential to support and improve the management of the disease and its symptoms; they also appear to be valuable tools for patients and health professionals. However, most of the apps that are currently available lack clinically validated evidence of their efficacy and focus on a limited number of symptoms. A more holistic and personalized approach within a cocreation design ecosystem is needed.

Trial Registration

PROSPERO 2021 CRD42021269399; https://tinyurl.com/2sw454a9

Intrinsic antecedents to mHealth adoption intention - A SEM-ANN approach

Healthcare is not left behind in the technological era, where almost every industry uses technological advances to serve customers' needs and wants. Increasingly, patients and doctors are using modern technological infrastructure to deliver care services. This study focuses on the intrinsic factors that lead to provider adoption of mHealth. The study uses PLS-SEM and neural networks to build on UTAUT theory. Study collects data from 316 care providers practicing in government and private health canters, hospitals and clinic found that intrinsic factors like self-efficacy, personal innovativeness, and performance expectancy positively related to mHealth adoption by physicians, whereas technology anxiety negatively related to adoption behaviour. Effort expectancy is not significant, indicating that m-Health adoption is driven by usefulness and result rather than convenience. If the expertise is not easily available, the physician's best interest for the patient may often drive them to adopt m-Health.

The Effects of Service Characteristics on Intention to Use Mobile Health Services: The Moderating Role of Innovativeness and Privacy Concern

Objectives: In this study, we explored how service characteristics (service relevance and service accuracy) interact to influence individuals' use intention of mHealth services. We also investigated the moderating roles of innovativeness and privacy concerns. Methods: To meet these objectives, we developed 6 hypotheses that were subsequently empirically validated using a survey to test the effects of service characteristics and personal traits on intention to use mHealth. Results: We confirm that service relevance and service accuracy positively and directly influence individuals' intention to use mHealth services. In addition, innovativeness positively affects the relationship between service relevance and use intention. Privacy concern negatively influences the relationship between service relevance and use intention, but positively influences the relationship between service accuracy and use intention. Conclusions: The present study provides new insights into the influencing factors of individuals' usage behavior toward mHealth services. Such insight could provide further understanding of how individuals adopt new information services or technologies, which contribute to both information system and healthcare research areas in a promising way.

Digital Therapeutic Alliance With Fully Automated Mental Health Smartphone Apps: A Narrative Review

Fully automated mental health smartphone apps show strong promise in increasing access to psychological support. Therefore, it is crucial to understand how to make these apps effective. The therapeutic alliance (TA), or the relationship between healthcare professionals and clients, is considered fundamental to successful treatment outcomes in face-to-face therapy. Thus, understanding the TA in the context of fully automated apps would bring us insights into building effective smartphone apps which engage users. However, the concept of a digital therapeutic alliance (DTA) in the context of fully automated mental health smartphone apps is nascent and under-researched, and only a handful of studies have been published in this area. In particular, no published review paper examined the DTA in the context of fully automated apps. The objective of this review was to integrate the extant literature to identify research gaps and future directions in the investigation of DTA in relation to fully automated mental health smartphone apps. Our findings suggest that the DTA in relation to fully automated smartphone apps needs to be conceptualized differently to traditional face-to-face TA. First, the role of bond in the context of fully automated apps is unclear. Second, human components of face-to-face TA, such as empathy, are hard to achieve in the digital context. Third, some users may perceive apps as more non-judgmental and flexible, which may further influence DTA formation. Subdisciplines of computer science, such as affective computing and positive computing, and some human-computer interaction (HCI) theories, such as those of persuasive technology and human-app attachment, can potentially help to foster a sense of empathy, build tasks and goals and develop bond or an attachment between users and apps, which may further contribute to DTA formation in fully automated smartphone apps. Whilst the review produced a relatively limited quantity of literature, this reflects the novelty of the topic and the need for further research.

Research on the Impact of mHealth Apps on the Primary Healthcare Professionals in Patient Care

The goal of this study was to develop and use a questionnaire in order to analyse the effects of eHealth apps on patient care using Jordanian population. A two-stage cross-sectional research was conducted. A questionnaire was developed in the beginning to evaluate its consistency and legitimacy using Cronbach's alpha coefficient, a multitrait connection atmosphere; the multivariate technique is component examination. In the study's another phase, correlation and regression are used to determine the influence of eHealth apps on patient care. The five major axes of the final surveys were healthcare efficiency, teaching, notices, consultation, and follow-up. Individuals from diverse demographic aspects, such as gender, age, job experience, and education level, have no differing perspectives on cell phone use in their amenities, according to a staff's viewpoint evaluation. In general, mobile health applications had a good influence on health services and healthcare, which would be an important setting for the operative use of mobile headphones in public policy; such a background would affect in workers' intents to practice and adopt mHealth.

Interactive System for Similarity-Based Inspection and Assessment of the Well-Being of mHealth Users

Recent digitization technologies empower mHealth users to conveniently record their Ecological Momentary Assessments (EMA) through web applications, smartphones, and wearable devices. These recordings can help clinicians understand how the users’ condition changes, but appropriate learning and visualization mechanisms are required for this purpose. We propose a web-based visual analytics tool, which processes clinical data as well as EMAs that were recorded through a mHealth application. The goals we pursue are (1) to predict the condition of the user in the near and the far future, while also identifying the clinical data that mostly contribute to EMA predictions, (2) to identify users with outlier EMA, and (3) to show to what extent the EMAs of a user are in line with or diverge from those users similar to him/her. We report our findings based on a pilot study on patient empowerment, involving tinnitus patients who recorded EMAs with the mHealth app TinnitusTips. To validate our method, we also derived synthetic data from the same pilot study. Based on this setting, results for different use cases are reported.

The impact of perceived crisis severity on intention to use voluntary proximity tracing applications

During a crisis such as COVID-19, governments ask citizens to adopt various precautionary behaviours, such as using a voluntary proximity tracing application (PTA) for smartphones. However, the willingness of individual citizens to use such an app is crucial. Crisis decision theory can be used to better understand how individuals assess the severity of the crisis and how they decide whether or not to adopt the precautionary behaviour. We propose a research model to examine the direct influence of perceived crisis severity on intention to use the technology, as well as the indirect impact via PTAs' benefits for citizens. Exploratory and confirmatory factor analyses confirm the two dimensions of the benefits, namely personal and societal benefits. We used PLS-MGA to evaluate our research model. The results confirm the influence of the perceived severity of COVID-19 on the intention to use the PTA, as well as the mediating effects of personal and societal benefits on this relationship. Our findings contribute to the technology adoption literature and showcase the use of crisis decision theory in the field of information systems.

Toward a Better Understanding of the Intention to Use mHealth Apps: Exploratory Study

BACKGROUND

An increasing number of mobile health (mHealth) apps are becoming available for download and use on mobile devices. Even with the increase in availability and use of mHealth apps, there has still not been a lot of research into understanding the intention to use this kind of apps.

OBJECTIVE

The purpose of this study was to investigate a technology acceptance model (TAM) that has been specially designed for primary health care applications.

METHODS

The proposed model is an extension of the TAM, and was empirically tested using data obtained from a survey of mHealth app users (n=310). The research analyzed 2 additional external factors: promotion of health and health benefits. Data were analyzed with a PLS-SEM software and confirmed that gender moderates the adoption of mHealth apps in Spain. The explanatory capacity (R2 for behavioral intention to use) of the proposed model was 76.4%. Likewise, the relationships of the external constructs of the extended TAM were found to be significant.

RESULTS

The results show the importance of healthy habits developed by using mHealth apps. In addition, communication campaigns for these apps should be aimed at transferring the usefulness of eHealth as an agent for transforming attitudes; additionally, as more health benefits are obtained, ease of use becomes greater. Perceived usefulness (PU; β=.415, t0.001;4999=3.442, P=.001), attitude toward using (β=.301, t0.01;499=2.299, P=.02), and promotion of health (β=.210, t0.05;499=2.108, P=.03) were found to have a statistically significant impact on behavior intention to use eHealth apps (R2=76.4%). Perceived ease of use (PEOU; β=.179, t0.01;499=2.623, P=.009) and PU (β=.755, t0.001;499=12.888, P<.001) were found to have a statistically significant impact on attitude toward using (R2>=78.2%). Furthermore, PEOU (β=.203, t0.01;499=2.810, P=.005), health benefits (β=.448, t0.001;499=4.010, P<.001), and promotion of health (β=.281, t0.01;499=2.393, P=.01) exerted a significant impact on PU (R2=72.7%). Finally, health benefits (β=.640, t0.001;499=14.948, P<.001) had a statistically significant impact on PEOU (R2=40.9%), while promotion of health (β=.865, t0.001;499=29.943, P<.001) significantly influenced health benefits (R2=74.7%).

CONCLUSIONS

mHealth apps could be used to predict the behavior of patients in the face of recommendations to prevent pandemics, such as COVID-19 or SARS, and to track users' symptoms while they stay at home. Gender is a determining factor that influences the intention to use mHealth apps, so perhaps different interfaces and utilities could be designed according to gender.

Improving service engagement in healthcare through internet of things based healthcare systems

Purpose

The purpose of the study was to empirically validate the linkages between IoT adoption and how it overarched influenced the patient care service engagement. This contributes to the body of knowledge and helps hospital managers to understand the relationship and relevance of IoT adoption; otherwise healthcare sector are late movers towards technology adoption. This gives a nuanced framework towards establishing empirically validated framework which will motivate healthcare services providers to be motivated to adopt and implement IoT enabled care delivery. The physician patient interaction and alignment during decision making will foster positive word of mouth, superior care service and reduce extra overheads for healthcare providers without compromise or rather with increment in service delivery proposition.

Design/methodology/approach

The study theoretically and empirically describes that with the adoption of internet of things (IoT) devices in health care, better services can be provided to patients by using partial least square – structure equation modelling-based robust technique and explains the better understanding of the health-care process with the help of information pervasiveness, physician-patient orientation and improved patient and physician involvement in the decision-making process.

Findings

This study shows that wearable IoT device adoption in health-care service delivery opens new opportunities and disrupts the conventional and traditional way of health-care service delivery by empowering the patient to take part in decision-making and enhancing their engagement in health-care service delivery.

Research limitations/implications

The study might influence by generalizability. Perception-based cross-examination knowledge from the patient’s perspective. It is likely that patients who use these devices will grow accustomed to using them and become more capable of using them. Thus, time-series tests have not been used to catch enhanced skills. New patients’ experiences will be altered over time. Regardless, non-response bias and traditional process bias received excessive interest.

Practical implications

The study aims at unravelling how the adoption of IoT enabled practices and usage of IoT devices bolsters the available data points in the context of healthcare especially with respect to patient care delivery. The study conceptualizes and empirically validates how the usage of IoT interface enabled technology enables better patient treatment and caregiver participation. The study puts forth a nuanced understanding regarding how pervasively available ubiquitous care information fosters shared decision making. This study further emphasizes that importance of ensuring a reliable computing environment devoid of privacy and security risks. The study attempts at Emphasizing empirically how the enhanced information pervasiveness catapults the patient-provider interactions, through health data exchange. Highlighting the importance of search feature in cloud storage and recovery mechanisms. The study not only fulfills the overarching linkage between enhanced service engagement with IoT adoption, it provides a mental map and ready to refer framework for hospital and healthcare experts to refer to, which prescribes thar care providers must build new methods aimed at empowerment of patients to participate and take more inclusive role. This unique confluence between patients and physicians will unravel the sync; helping not only avoid costly decision errors, but also improve patient care delivery environment. Patients should be permitted to participate in decision-making,inspire patients to be participatory.

Originality/value

The study efforts to empirically investigate and discover the link between how wearable sensor-based IoT enhances health-care service engagement is underway. Using primary data this linkage validation allows the community and readers at large to gain a nuanced understanding of how superior interaction is enabled by a digital-health-care process with the help of IoT-enabled information pervasiveness, physician-patient orientation and empowered involvement.

The Digital Therapeutic Alliance and Human-Computer Interaction

The therapeutic alliance (TA), the relationship that develops between a therapist and a client/patient, is a critical factor in the outcome of psychological therapy. As mental health care is increasingly adopting digital technologies and offering therapeutic interventions that may not involve human therapists, the notion of a TA in digital mental health care requires exploration. To date, there has been some incipient work on developing measures to assess the conceptualization of a digital TA for mental health apps. However, the few measures that have been proposed have more or less been derivatives of measures from psychology used to assess the TA in traditional face-to-face therapy. This conceptual paper explores one such instrument that has been proposed in the literature, the Mobile Agnew Relationship Measure, and examines it through a human-computer interaction (HCI) lens. Through this process, we show how theories from HCI can play a role in shaping or generating a more suitable, purpose-built measure of the digital therapeutic alliance (DTA), and we contribute suggestions on how HCI methods and knowledge can be used to foster the DTA in mental health apps.

In-Home Rehabilitation Using a Smartphone App Coupled With 3D Printed Functional Objects: Single-Subject Design Study

BACKGROUND

Stroke is a major cause of long-term disability. While there is potential for improvements long after stroke onset, there is little to support functional recovery across the lifespan. mHealth solutions can help fill this gap. mRehab was designed to guide individuals with stroke through a home program and provide performance feedback.

OBJECTIVE

To examine if individuals with chronic stroke can use mRehab at home to improve upper limb mobility. The secondary objective was to examine if changes in limb mobility transferred to standardized clinical assessments.

METHODS

mRehab consists of a smartphone coupled with 3D printed household items: mug, bowl, key, and doorknob. The smartphone custom app guides task-oriented activities and measures both time to complete an activity and quality of movement (smoothness/accuracy). It also provides performance-based feedback to aid the user in self-monitoring their performance. Task-oriented activities were categorized as (1) object transportation, (2) prehensile grip with supination/pronation, (3) fractionated finger movement, and (4) walking with object. A total of 18 individuals with stroke enrolled in the single-subject experimental design study consisting of pretesting, a 6-week mRehab home program, and posttesting. Pre- and posttesting included both in-laboratory clinical assessments and in-home mRehab recorded samples of task performance. During the home program, mRehab recorded performance data. A System Usability Scale assessed user's perception of mRehab.

RESULTS

A total of 16 participants completed the study and their data are presented in the results. The average days of exercise for each mRehab activity ranged from 15.93 to 21.19 days. This level of adherence was sufficient for improvements in time (t15=2.555, P=.02) and smoothness (t15=3.483, P=.003) in object transportation. Clinical assessments indicated improvements in functional performance (t15=2.675, P=.02) and hand dexterity (t15=2.629, P=.02). Participant's perception of mRehab was positive.

CONCLUSIONS

Despite heterogeneity in participants' use of mRehab, there were improvements in upper limb mobility. Smartphone-based portable technology can support home rehabilitation programs in chronic conditions such as stroke. The ability to record performance data from home rehabilitation offers new insights into the impact of home programs on outcomes.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04363944; https://clinicaltrials.gov/ct2/show/NCT04363944.