Use of the FITT framework to understand patients' experiences using a real-time medication monitoring pill bottle linked to a mobile-based HIV self-management app: A qualitative study

Approaches to Evaluating Digital Health Technologies: Scoping Review

BACKGROUND

Profound scientific evaluation of novel digital health technologies (DHTs) is key to enhance successful development and implementation. As such, we previously developed the eHealth evaluation cycle. The eHealth evaluation cycle contains 5 consecutive study phases: conceptual, development, feasibility, effectiveness, and implementation.

OBJECTIVE

The aim of this study is to develop a better understanding of the daily practice of the eHealth evaluation cycle. Therefore, the objectives are to conduct a structured analysis of literature data to analyze the practice of the evaluation study phases and to determine which evaluation approaches are used in which study phase of the eHealth evaluation cycle.

METHODS

We conducted a systematic literature search in PubMed including the MeSH term "telemedicine" in combination with a wide variety of evaluation approaches. Original peer-reviewed studies published in the year 2019 (pre-COVID-19 cohort) were included. Nonpatient-focused studies were excluded. Data on the following variables were extracted and systematically analyzed: journal, country, publication date, medical specialty, primary user, functionality, evaluation study phases, and evaluation approach. RStudio software was used to summarize the descriptive data and to perform statistical analyses.

RESULTS

We included 824 studies after 1583 titles and abstracts were screened. The majority of the evaluation studies focused on the effectiveness (impact; 304/824, 36.9%) study phase, whereas uptake (implementation; 70/824, 8.5%) received the least focus. Randomized controlled trials (RCTs; 170/899, 18.9%) were the most commonly used DHT evaluation method. Within the effectiveness (impact) study phase, RCTs were used in one-half of the studies. In the conceptual and planning phases, survey research (27/78, 35%) and interview studies (27/78, 35%) were most frequently used. The United States published the largest amount of DHT evaluation studies (304/824, 36.9%). Psychiatry and mental health (89/840, 10.6%) and cardiology (75/840, 8.9%) had the majority of studies published within the field.

CONCLUSIONS

We composed the first comprehensive overview of the actual practice of implementing consecutive DHT evaluation study phases. We found that the study phases of the eHealth evaluation cycle are unequally studied and most attention is paid to the effectiveness study phase. In addition, the majority of the studies used an RCT design. However, in order to successfully develop and implement novel DHTs, stimulating equal evaluation of the sequential study phases of DHTs and selecting the right evaluation approach that fits the iterative nature of technology might be of the utmost importance.

Attributes, Methods, and Frameworks Used to Evaluate Wearables and Their Companion mHealth Apps: Scoping Review

BACKGROUND

Wearable devices, mobile technologies, and their combination have been accepted into clinical use to better assess the physical fitness and quality of life of patients and as preventive measures. Usability is pivotal for overcoming constraints and gaining users' acceptance of technology such as wearables and their companion mobile health (mHealth) apps. However, owing to limitations in design and evaluation, interactive wearables and mHealth apps have often been restricted from their full potential.

OBJECTIVE

This study aims to identify studies that have incorporated wearable devices and determine their frequency of use in conjunction with mHealth apps or their combination. Specifically, this study aims to understand the attributes and evaluation techniques used to evaluate usability in the health care domain for these technologies and their combinations.

METHODS

We conducted an extensive search across 4 electronic databases, spanning the last 30 years up to December 2021. Studies including the keywords "wearable devices," "mobile apps," "mHealth apps," "physiological data," "usability," "user experience," and "user evaluation" were considered for inclusion. A team of 5 reviewers screened the collected publications and charted the features based on the research questions. Subsequently, we categorized these characteristics following existing usability and wearable taxonomies. We applied a methodological framework for scoping reviews and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist.

RESULTS

A total of 382 reports were identified from the search strategy, and 68 articles were included. Most of the studies (57/68, 84%) involved the simultaneous use of wearables and connected mobile apps. Wrist-worn commercial consumer devices such as wristbands were the most prevalent, accounting for 66% (45/68) of the wearables identified in our review. Approximately half of the data from the medical domain (32/68, 47%) focused on studies involving participants with chronic illnesses or disorders. Overall, 29 usability attributes were identified, and 5 attributes were frequently used for evaluation: satisfaction (34/68, 50%), ease of use (27/68, 40%), user experience (16/68, 24%), perceived usefulness (18/68, 26%), and effectiveness (15/68, 22%). Only 10% (7/68) of the studies used a user- or human-centered design paradigm for usability evaluation.

CONCLUSIONS

Our scoping review identified the types and categories of wearable devices and mHealth apps, their frequency of use in studies, and their implementation in the medical context. In addition, we examined the usability evaluation of these technologies: methods, attributes, and frameworks. Within the array of available wearables and mHealth apps, health care providers encounter the challenge of selecting devices and companion apps that are effective, user-friendly, and compatible with user interactions. The current gap in usability and user experience in health care research limits our understanding of the strengths and limitations of wearable technologies and their companion apps. Additional research is necessary to overcome these limitations.

Key Features of Smart Medication Adherence Products: Updated Scoping Review

BACKGROUND

Older adults often face challenges in self-managing their medication owing to physical and cognitive limitations, complex medication regimens, and packaging of medications. Emerging smart medication dispensing and adherence products (SMAPs) offer the options of automated dispensing, tracking medication intake in real time, and reminders and notifications. A 2021 review identified 51 SMAPs owing to the rapid influx of digital technology; an update to this review is required.

OBJECTIVE

This review aims to identify new products and summarize and compare the key features of SMAPs.

METHODS

Gray and published literature and videos were searched using Google, YouTube, PubMed, Embase, and Scopus. The first 10 pages of Google and the first 100 results of YouTube were screened using 4 and 5 keyword searches, respectively. SMAPs were included if they were able to store and allowed for the dispensation of medications, tracked real-time medication intake data, and could automatically analyze data. Products were excluded if they were stand-alone software applications, not marketed in English, not for in-home use, or only used in clinical trials. In total, 5 researchers independently screened and extracted the data.

RESULTS

This review identified 114 SMAPs, including 80 (70.2%) marketed and 34 (29.8%) prototypes, grouped into 15 types. Among the marketed products, 68% (54/80) were available for consumer purchase. Of these products, 26% (14/54) were available worldwide and 78% (42/54) were available in North America. There was variability in the hardware, software, data collection and management features, and cost of the products. Examples of hardware features include battery life, medication storage capacity, availability of types and number of alarms, locking features, and additional technology required for use of the product, whereas software features included reminder and notification capabilities and availability of manufacturer support. Data capture methods included the availability of sensors to record the use of the product and data-syncing capabilities with cloud storage with short-range communications. Data were accessible to users via mobile apps or web-based portals. Some SMAPs provided data security assurance with secure log-ins (use of personal identification numbers or facial recognition), whereas other SMAPs provided data through registered email addresses. Although some SMAPs were available at set prices or free of cost to end users, the cost of other products varied based on availability, shipping fees, and subscription fees.

CONCLUSIONS

An expanding market for SMAPs with features specific to at-home patient use is emerging. Health care professionals can use these features to select and suggest products that meet their patients' unique requirements.

Piloting an online telecoaching community-based exercise intervention with adults living with HIV: protocol for a mixed-methods implementation science study

INTRODUCTION

Our aim is to evaluate the implementation of an online telecoaching community-based exercise (CBE) intervention with the goal of reducing disability and enhancing physical activity and health among adults living with HIV.

METHODS AND ANALYSIS

We will conduct a prospective longitudinal mixed-methods two-phased intervention study to pilot the implementation of an online CBE intervention with ~30 adults (≥18 years) living with HIV who consider themselves safe to participate in exercise. In the intervention phase (0-6 months), participants will take part in an online CBE intervention involving thrice weekly exercise (aerobic, resistance, balance and flexibility), with supervised biweekly personal training sessions with a fitness instructor, YMCA membership providing access to online exercise classes, wireless physical activity monitor to track physical activity and monthly online educational sessions on topics related to HIV, physical activity and health. In the follow-up phase (6-12 months), participants will be encouraged to continue independent exercise thrice weekly. Quantitative assessment: Bimonthly, we will assess cardiopulmonary fitness, strength, weight, body composition and flexibility, followed by administering self-reported questionnaires to assess disability, contextual factor outcomes (mastery, engagement in care, stigma, social support), implementation factors (cost, feasibility, technology), health status and self-reported physical activity. We will conduct a segmented regression analyses to describe the change in level and trend between the intervention and follow-up phases. Qualitative assessment: We will conduct online interviews with a subsample of ~10 participants and 5 CBE stakeholders at baseline (month 0), postintervention (month 6) and end of follow-up (month 12) to explore experiences, impact and implementation factors for online CBE. Interviews will be audiorecorded and analysed using content analytical techniques.

ETHICS AND DISSEMINATION

Protocol approved by the University of Toronto Research Ethics Board (Protocol # 40410). Knowledge translation will occur in the form of presentations and publications in open-access peer-reviewed journals.

TRIAL REGISTRATION NUMBER

NCT05006391.

Efficacy of an mHealth self-management intervention for persons living with HIV: the WiseApp randomized clinical trial

IMPORTANCE

Progression of HIV disease, the transmission of the disease, and premature deaths among persons living with HIV (PLWH) have been attributed foremost to poor adherence to HIV medications. mHealth tools can be used to improve antiretroviral therapy (ART) adherence in PLWH and have the potential to improve therapeutic success.

OBJECTIVE

To determine the efficacy of WiseApp, a user-centered design mHealth intervention to improve ART adherence and viral suppression in PLWH.

DESIGN, SETTING, AND PARTICIPANTS

A randomized (1:1) controlled efficacy trial of the WiseApp intervention arm (n = 99) versus an attention control intervention arm (n = 101) among persons living with HIV who reported poor adherence to their treatment regimen and living in New York City.

INTERVENTIONS

The WiseApp intervention includes the following components: testimonials of lived experiences, push-notification reminders, medication trackers, health surveys, chat rooms, and a "To-Do" list outlining tasks for the day. Both study arms also received the CleverCap pill bottle, with only the intervention group linking the pill bottle to WiseApp.

RESULTS

We found a significant improvement in ART adherence in the intervention arm compared to the attention control arm from day 1 (69.7% vs 48.3%, OR = 2.5, 95% CI 1.4-3.5, P = .002) to day 59 (51.2% vs 37.2%, OR = 1.77, 95% CI 1.0-1.6, P = .05) of the study period. From day 60 to 120, the intervention arm had higher adherence rates, but the difference was not significant. In the secondary analyses, no difference in change from baseline to 3 or 6 months between the 2 arms was observed for all secondary outcomes.

CONCLUSIONS

The WiseApp intervention initially improved ART adherence but did not have a sustained effect on outcomes.

Leveraging mHealth for the Treatment and Management of PLHIV

Objective

The objective of this systematic review was to analyze published literature from the last five years to assess facilitators and barriers to the adoption of mHealth as interventions to treat and manage HIV for PLHIV (people living with HIV). The primary outcomes were physical and mental conditions. The secondary outcomes were behavior based (substance use, care engagement, and healthy habits).

Methods

Four databases (PubMed, CINAHL, Web of Science, and ScienceDirect) were queried on 9/2/2022 for peer-reviewed studies on the treatment and management of PLHIV with mHealth as the intervention. The review was conducted in accordance with the Kruse Protocol and reported in accordance with PRISMA 2020.

Results

Five mHealth interventions were identified across 32 studies that resulted in improvements in physical health, mental health, care engagement, and behavior change. mHealth interventions offer both convenience and privacy, meet a digital preference, increase health knowledge, decrease healthcare utilization, and increase quality of life. Barriers are cost of technology and incentives, training of staff, security concerns, digital literacy gap, distribution of technology, technical issues, usability, and visual cues are not available over the phone.

Conclusion

mHealth offers interventions to improve physical health, mental health, care engagement, and behavior for PLHIV. There are many advantages to this intervention and very few barriers to its adoption. The barriers are strong, however, and should be addressed through policy. Further research should focus on specific apps for younger versus older PLHIV, based on preferences and the digital literacy gap.

Addressing Health Inequities in Digital Clinical Trials: A Review of Challenges and Solutions From the Field of HIV Research

Clinical trials are considered the gold standard for establishing efficacy of health interventions, thus determining which interventions are brought to scale in health care and public health programs. Digital clinical trials, broadly defined as trials that have partial to full integration of technology across implementation, interventions, and/or data collection, are valued for increased efficiencies as well as testing of digitally delivered interventions. Although recent reviews have described the advantages and disadvantages of and provided recommendations for improving scientific rigor in the conduct of digital clinical trials, few to none have investigated how digital clinical trials address the digital divide, whether they are equitably accessible, and if trial outcomes are potentially beneficial only to those with optimal and consistent access to technology. Human immunodeficiency virus (HIV), among other health conditions, disproportionately affects socially and economically marginalized populations, raising questions of whether interventions found to be efficacious in digital clinical trials and subsequently brought to scale will sufficiently and consistently reach and provide benefit to these populations. We reviewed examples from HIV research from across geographic settings to describe how digital clinical trials can either reproduce or mitigate health inequities via the design and implementation of the digital clinical trials and, ultimately, the programs that result. We discuss how digital clinical trials can be intentionally designed to prevent inequities, monitor ongoing access and utilization, and assess for differential impacts among subgroups with diverse technology access and use. These findings can be generalized to many other health fields and are practical considerations for donors, investigators, reviewers, and ethics committees engaged in digital clinical trials.

Health outcomes and healthcare utilization of Native Hawaiians and other Pacific Islanders living with HIV in Hawai'i: A mixed-methods study

OBJECTIVES

Past research shows mixed outcomes in terms of HIV-related disparities among Native Hawaiians and Pacific Islanders (NHOPI). This study investigates HIV-related disparities among NHOPI living with HIV in Hawai'i.

DESIGN

An explanatory sequential design was utilized. The quantitative portion analyzed survey data from a statewide Ryan White Needs Assessment (N = 398) to examine the differences in viral suppression and satisfaction with care between NHOPI and other ethnic groups. Utilizing the behavioral model for vulnerable populations (BMVP), semi-structured interviews (N = 16) were conducted next to explain what factors play a role in satisfaction with care and viral suppression when it comes to NHOPI living with HIV in Hawai'i.

RESULTS

Among the 398 participants 13% were NHOPI. NHOPI were more likely to have a viral load of ≥10,000 copies/mL compared to those who didn't identify as NHOPI. However, there were no significant differences for other viral load levels (20-199 or 200-9999), and only 20 participants (5.2%) had a viral load of 10,000 copies/mL or more. No significant ethnic differences were found in satisfaction with medical care. In the qualitative phase, factors from all domains of the BMVP were represented within the four themes identified: (1) Care coordination is essential- with AIDs service organizations taking the lead; (2) HIV care, as well as overall health, is defined by the effectiveness of medication; (3) Initial diagnosis is a critical moment for intervention; and (4) Aspects of culture are intangible.

CONCLUSION

Among NHOPI in Hawai'i who are engaged in case management, there appears to be no substantial disparities in either viral load or satisfaction with care compared to other ethnic groups. Despite this, qualitative findings provide insights on how ethnicity and culture may still be playing a role. Addressing all domains of the BMVP is crucial to addressing this.

A Smoking Cessation Mobile App for Persons Living With HIV: Preliminary Efficacy and Feasibility Study

BACKGROUND

The prevalence of smoking in the United States general population has gradually declined to the lowest rate ever recorded; however, this has not been true for persons with HIV.

OBJECTIVE

We conducted a pilot test to assess the feasibility and efficacy of the Lumme Quit Smoking mobile app and smartwatch combination with sensing capabilities to improve smoking cessation in persons with HIV.

METHODS

A total of 40 participants were enrolled in the study and randomly assigned 1:1 to the control arm, which received an 8-week supply of nicotine replacement therapy, a 30-minute smoking cessation counseling session, and weekly check-in calls with study staff, or to the intervention arm, which additionally received the Lumme Quit Smoking app and smartwatch.

RESULTS

Of the 40 participants enrolled, 37 completed the follow-up study assessments and 16 used the app every day during the 56-day period. During the 6-month recruitment and enrollment period, 122 people were screened for eligibility, with 67.2% (82/122) deemed ineligible. Smoking criteria and incompatible tech were the major reasons for ineligibility. There was no difference in the proportion of 7-day point prevalence abstinence by study arm and no significant decrease in exhaled carbon monoxide for the intervention and control arms separately. However, the average exhaled carbon monoxide decreased over time when analyzing both arms together (P=.02).

CONCLUSIONS

Results suggest excellent feasibility and acceptability of using a smoking sensor app among this smoking population. The knowledge gained from this research will enable the scientific community, clinicians, and community stakeholders to improve tobacco cessation outcomes for persons with HIV.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04808609; https://clinicaltrials.gov/ct2/show/NCT04808609.

Technologies for Medication Adherence Monitoring and Technology Assessment Criteria: Narrative Review

BACKGROUND

Accurate measurement and monitoring of patient medication adherence is a global challenge because of the absence of gold standard methods for adherence measurement. Recent attention has been directed toward the adoption of technologies for medication adherence monitoring, as they provide the opportunity for continuous tracking of individual medication adherence behavior. However, current medication adherence monitoring technologies vary according to their technical features and data capture methods, leading to differences in their respective advantages and limitations. Overall, appropriate criteria to guide the assessment of medication adherence monitoring technologies for optimal adoption and use are lacking.

OBJECTIVE

This study aims to provide a narrative review of current medication adherence monitoring technologies and propose a set of technology assessment criteria to support technology development and adoption.

METHODS

A literature search was conducted on PubMed, Scopus, CINAHL, and ProQuest Technology Collection (2010-present) using the combination of keywords medication adherence, measurement technology, and monitoring technology. The selection focused on studies related to medication adherence monitoring technology and its development and use. The technological features, data capture methods, and potential advantages and limitations of the identified technology applications were extracted. Methods for using data for adherence monitoring were also identified. Common recurring elements were synthesized as potential technology assessment criteria.

RESULTS

Of the 3865 articles retrieved, 98 (2.54%) were included in the final review, which reported a variety of technology applications for monitoring medication adherence, including electronic pill bottles or boxes, ingestible sensors, electronic medication management systems, blister pack technology, patient self-report technology, video-based technology, and motion sensor technology. Technical features varied by technology type, with common expectations for using these technologies to accurately monitor medication adherence and increase adoption in patients' daily lives owing to their unobtrusiveness and convenience of use. Most technologies were able to provide real-time monitoring of medication-taking behaviors but relied on proxy measures of medication adherence. Successful implementation of these technologies in clinical settings has rarely been reported. In all, 28 technology assessment criteria were identified and organized into the following five categories: development information, technology features, adherence to data collection and management, feasibility and implementation, and acceptability and usability.

CONCLUSIONS

This narrative review summarizes the technical features, data capture methods, and various advantages and limitations of medication adherence monitoring technology reported in the literature and the proposed criteria for assessing medication adherence monitoring technologies. This collection of assessment criteria can be a useful tool to guide the development and selection of relevant technologies, facilitating the optimal adoption and effective use of technology to improve medication adherence outcomes. Future studies are needed to further validate the medication adherence monitoring technology assessment criteria and construct an appropriate technology assessment framework.

Demand analysis of an intelligent medication administration system for older adults with chronic diseases based on the Kano model

Objectives

Gerontechnology has great potential in promoting older adults’ well-being. With the accelerated aging process, gerontechnology has a promising market prospect. However, most technological developers and healthcare professionals attached importance to products’ effectiveness, and ignored older adults’ demands and user experience, which reduced older adults' adoption intention of gerontechnology use. The inclusion of older adults in the design process of technologies is essential to maximize the effect. This study explored older adults’ demands for a self-developed intelligent medication administration system and proposed optimization schemes, thus providing reference to developing geriatric-friendly technologies and products.

Methods

A cross-sectional survey was conducted to explore older adults’ technological demands for the self-developed intelligent medication administration system, and data were analyzed based on the Kano model. A self-made questionnaire was administered from July 2020 to October 2020 after participants used this system for two weeks. The study was registered with the Chinese Clinical Trial Registry (ChiCTR2000040644).

Results

A total of 354 older adults participated in the survey. Four items, namely larger font size, simpler operation process, scheduled medication reminders and reliable hardware, were classified as must-be attributes; three items, namely searching drug instructions through WeChat, more sensitive system and longer battery life, as attractive attributes; one item, viewing disease-related information through WeChat, as the one-dimensional attribute; and the rest were indifferent attributes, including simple and beautiful displays, blocking advertisements automatically, providing user privacy protection protocol, viewing personal medical information only by logged-in users, recording all the medications, ordering medications through WeChat. The satisfaction values were between 0.24 and 0.69, and dissatisfaction values were between 0.06 and 0.94.

Conclusion

This study suggested that older adults had personalized technology demands. Including their technological demands and desire may assist in decreasing the digital divide and promoting the satisfaction of e-health and/or m-health. Based on older adults’ demands, our study proposed optimization schemes of the intelligent medication administration system, which may help developers design geriatric-friendly intelligent products and nurses to perform older adults-centered and efficient medication management.

What Works Best to Engage Participants in Mobile App Interventions and e-Health: A Scoping Review

Background:

Despite the growing popularity of mobile app interventions, specific engagement components of mobile apps have not been well studied.

Methods:

The objectives of this scoping review are to determine which components of mobile health intervention apps encouraged or hindered engagement, and examine how studies measured engagement.

Results:

A PubMed search on March 5, 2020 yielded 239 articles that featured the terms engagement, mobile app/mobile health, and adult. After applying exclusion criteria, only 54 studies were included in the final analysis.

Discussion:

Common app components associated with increased engagement included: personalized content/feedback, data visualization, reminders/push notifications, educational information/material, logging/self-monitoring functions, and goal-setting features. On the other hand, social media integration, social forums, poor app navigation, and technical difficulties appeared to contribute to lower engagement rates or decreased usage. Notably, the review revealed a great variability in how engagement with mobile health apps is measured due to lack of established processes.

Conclusion:

There is a critical need for controlled studies to provide guidelines and standards to help facilitate engagement and its measurement in research and clinical trial work using mobile health intervention apps.

Women's adoption of a web-based intervention for stress urinary incontinence: a qualitative study

Background

Stress urinary incontinence (SUI) is common among women and affects their quality of life. Pelvic floor muscle training is an effective conservative therapy, but only a minority of women seek help. E-health with pelvic floor muscle training is effective and increases access to care. To implement an e-Health intervention in a sustainable way, however, we need to understand what determines adoption. The aim is to investigate the barriers and facilitators to adopting an e-Health intervention among Dutch women with stress urinary incontinence.

Methods

Semi-structured telephonic interviews were carried out among participants of the Dutch e-Health intervention for women with stress urinary incontinence. Women were purposively sampled. The ‘Fit between Individuals, Task and Technology’ (FITT) framework was used for both the data collection and data analysis, to gain a more in-depth insight into the adoption of the intervention.

Results

Twenty women were interviewed, mean age 51 years and mostly highly educated. The adoption of e-Health for women with SUI mainly depends on the interaction between users and e-Health, and users and pelvic floor muscle training exercises. Facilitators for the adoption were the preference for an accessible self-management intervention, having a strong sense of self-discipline and having the ability to schedule the exercises routinely. Women needed to possess self-efficacy to do this intervention independently. Barriers to the adoption of e-Health were personal circumstances restricting time for scheduling pelvic floor muscle training and lacking skills to perform the exercises correctly. Despite guidance by technical features several women remained uncertain about their performance of the exercises and, therefore, wanted additional contact with a professional.

Conclusions

For stress urinary incontinence e-Health is an appropriate option for a target audience. Use of the FITT framework clearly demonstrates the conditions for optimal adoption. For a subgroup it was a suitable alternative for medical care in person. For others it identified the need for further support by a health care professional. This support could be provided by improvements of technical features and incorporating modes for digital communication. The additional value of integration of the e-Health intervention in primary care might be a logical next step.

Trial registration

The study was prospectively registered in the Netherlands Trial Registry (NTR) NTR6956.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-06585-z.

Reporting health data in waiting rooms with mobile technology: Patient expectation and confirmation

OBJECTIVES

Hospitals and medical staff use digital devices such as mobile phones and tablets to treat patients. Prior research has examined patient-reported outcomes, and the use of medical devices to do diagnosis and prognosis of patients, but not whether patients like using, and intend to use in future, mobile devices to self-report medical data. We address this research gap by developing a theoretical model based on the expectancy confirmation model (ECM) and testing it in an empirical study of patients using mobile technology to self-report data.

DESIGN

This study adopts a non-interventional cross-sectional research design. Randomly-selected patients provided data via survey and physical measurements. The target population comprises adults visiting a healthcare laboratory to get their blood drawn.

MATERIALS AND METHODS

We surveyed 190 randomly-selected patients waiting for treatment in the clinic. They were surveyed at two points in time - before and after their blood was drawn - on their demographic characteristics, research variables concerning their use of mobile devices to provide medical information, and perceived clinical data (blood pressure, height and weight). The research model was tested using structural equation modeling.

RESULTS

The study found strong support for the research model, with seven of eight hypotheses being supported. Both self-disclosure effort and feedback expectation positively affect both perceived feedback quality and confirmation. Contrary to expectations, perceived feedback quality was not found to affect confirmation. Perceived feedback quality, along with confirmation, was found to positively affect satisfaction, which was found to affect intention to disclose medical data through mobile technology.

CONCLUSIONS

The study's findings support the proposed path from feedback expectation and self-disclosure effort to confirmation to satisfaction to disclosure intention. Although perceived feedback does not affect confirmation, it affects satisfaction. Overall, we believe the results provide novel insights to both scientific research community and practitioners about using mobile technologies for self-reporting medical data.

mHealth Interventions to Promote Anti-Retroviral Adherence in HIV: Narrative Review

Background

Antiretrovirals (ARVs) are key in the management of HIV. Although no cure exists, ARVs help patients live healthy lives and prevent transmission to others. Adherence to complex regimens is paramount to outcomes and in avoiding the emergence of drug-resistant viruses. The goal of therapy is to reach an undetectable viral load. However, adherence is a common problem, stemming from issues such as mental health, chaotic home situations, and busy work schedules. Mobile health (mHealth) represents a new approach in improving medication adherence, and multiple studies have been performed in this area.

Objective

This study aims to review the current implementation of mHealth in the management of HIV among different groups of patients.

Methods

We used PubMed, Academic Search Elite, and 1 journal database with various search terms to review the current implementation of mHealth in HIV care.

Results

Titles and abstracts were screened, and 61 papers were identified and fully reviewed. The literature was divided into lower- and higher-income nations, as defined by the United Nations. A total of 20 studies with quantitative results were identified, with 10 being text- and SMS-based interventions (the majority of these being in lower-income countries) and 8 being smartphone-based apps (primarily in higher-income countries). The majority of these studies determined whether there was an effect on adherence or biochemical parameters (viral load and CD4 count). Various qualitative studies have also been conducted, and many have focused on determining the specific design of interventions that were successful (frequency of messaging, types of messages, etc) as well as priorities for patients with regard to mHealth interventions.

Conclusions

There seems to be a role of mHealth in the management of HIV in lower-income nations; however, the optimal design of an intervention needs to be delineated. In higher-income countries, where the 2 significant risk factors were injection drugs and men who have sex with men, the benefit was less clear, and more research is needed.

Applying and Extending the FITT Framework to Identify the Challenges and Opportunities of Successful eHealth Services for Patient Self-Management: Qualitative Interview Study

Background

The number of public eHealth services that support patient self-management is rapidly increasing. However, the implementation of these eHealth services for self-management has encountered challenges.

Objective

The purpose of this paper was to analyze the challenges and opportunities of implementing eHealth services for self-management by focusing on the fit between the technical solution and clinical use.

Methods

We performed in-depth interviews with 10 clinical project coordinators and managers who were responsible for developing and implementing various eHealth services for self-management interventions in five university hospitals in Finland. The results were analyzed using content analysis and open coding. The Fit between Individuals, Task, and Technology (FITT) framework was used to interpret the findings.

Results

The implementation of self-management services involved many challenges related to technical problems, health professional acceptance, patient motivation, and health organization and management. The implementers identified practices to manage the identified challenges, including improving the design of the technology, supporting health professionals in the adoption of the eHealth services, changing the work processes and tasks, involving patients, and collectively planning the implementation inside an organization. The findings could be mostly attributed to the dimensions of the FITT framework.

Conclusions

The FITT framework helped to analyze the challenges related to the implementation, and most of them were related to poor fit. The importance of patients as stakeholders in eHealth services for patient self-management needs to be highlighted. Thus, we propose that patients should be added as a different type of individual dimension to the FITT framework. In addition, the framework could be extended to include organization and management in a new context dimension.