| Title | The mHealth App Usability Questionnaire (MAUQ): Development and Validation Study. |
| Authors | Zhou, L; Bao, J; Setiawan, IMA; Saptono, A; Parmanto, B |
| Journal | JMIR mHealth and uHealth |
| Publication Date | 11 Apr 2019 |
| Date Added to PubMed | 12 Apr 2019 |
| Abstract | After a mobile health (mHealth) app is created, an important step is to evaluate the usability of the app before it is released to the public. There are multiple ways of conducting a usability study, one of which is collecting target users' feedback with a usability questionnaire. Different groups have used different questionnaires for mHealth app usability evaluation: The commonly used questionnaires are the System Usability Scale (SUS) and Post-Study System Usability Questionnaire (PSSUQ). However, the SUS and PSSUQ were not designed to evaluate the usability of mHealth apps. Self-written questionnaires are also commonly used for evaluation of mHealth app usability but they have not been validated. The goal of this project was to develop and validate a new mHealth app usability questionnaire. An mHealth app usability questionnaire (MAUQ) was designed by the research team based on a number of existing questionnaires used in previous mobile app usability studies, especially the well-validated questionnaires. MAUQ, SUS, and PSSUQ were then used to evaluate the usability of two mHealth apps: an interactive mHealth app and a standalone mHealth app. The reliability and validity of the new questionnaire were evaluated. The correlation coefficients among MAUQ, SUS, and PSSUQ were calculated. In this study, 128 study participants provided responses to the questionnaire statements. Psychometric analysis indicated that the MAUQ has three subscales and their internal consistency reliability is high. The relevant subscales correlated well with the subscales of the PSSUQ. The overall scale also strongly correlated with the PSSUQ and SUS. Four versions of the MAUQ were created in relation to the type of app (interactive or standalone) and target user of the app (patient or provider). A website has been created to make it convenient for mHealth app developers to use this new questionnaire in order to assess the usability of their mHealth apps. The newly created mHealth app usability questionnaire-MAUQ-has the reliability and validity required to assess mHealth app usability. |
| Link | http://doi.org/10.2196/11500 |
| Title | eHealth Literacy Instruments: Systematic Review of Measurement Properties. |
| Authors | Lee, J; Lee, EH; Chae, D |
| Journal | Journal of medical Internet research |
| Publication Date | 15 Nov 2021 |
| Date Added to PubMed | 16 Nov 2021 |
| Abstract | The internet is now a major source of health information. With the growth of internet users, eHealth literacy has emerged as a new concept for digital health care. Therefore, health professionals need to consider the eHealth literacy of consumers when providing care utilizing digital health technologies. This study aimed to identify currently available eHealth literacy instruments and evaluate their measurement properties to provide robust evidence to researchers and clinicians who are selecting an eHealth literacy instrument. We conducted a systematic review and meta-analysis of self-reported eHealth literacy instruments by applying the updated COSMIN (COnsensus-based Standards for the selection of health Measurement INstruments) methodology. This study included 7 instruments from 41 articles describing 57 psychometric studies, as identified in 4 databases (PubMed, CINAHL, Embase, and PsycInfo). No eHealth literacy instrument provided evidence for all measurement properties. The eHealth literacy scale (eHEALS) was originally developed with a single-factor structure under the definition of eHealth literacy before the rise of social media and the mobile web. That instrument was evaluated in 18 different languages and 26 countries, involving diverse populations. However, various other factor structures were exhibited: 7 types of two-factor structures, 3 types of three-factor structures, and 1 bifactor structure. The transactional eHealth literacy instrument (TeHLI) was developed to reflect the broader concept of eHealth literacy and was demonstrated to have a sufficient low-quality and very low-quality evidence for content validity (relevance, comprehensiveness, and comprehensibility) and sufficient high-quality evidence for structural validity and internal consistency; however, that instrument has rarely been evaluated. The eHealth literacy scale was the most frequently investigated instrument. However, it is strongly recommended that the instrument's content be updated to reflect recent advancements in digital health technologies. In addition, the transactional eHealth literacy instrument needs improvements in content validity and further psychometric studies to increase the credibility of its synthesized evidence. |
| Link | http://doi.org/10.2196/30644 |
| Title | Factors Influencing Adherence to mHealth Apps for Prevention or Management of Noncommunicable Diseases: Systematic Review. |
| Authors | Jakob, R; Harperink, S; Rudolf, AM; Fleisch, E; Haug, S; Mair, JL; Salamanca-Sanabria, A; Kowatsch, T |
| Journal | Journal of medical Internet research |
| Publication Date | 25 May 2022 |
| Date Added to PubMed | 26 May 2022 |
| Abstract | Mobile health (mHealth) apps show vast potential in supporting patients and health care systems with the increasing prevalence and economic costs of noncommunicable diseases (NCDs) worldwide. However, despite the availability of evidence-based mHealth apps, a substantial proportion of users do not adhere to them as intended and may consequently not receive treatment. Therefore, understanding the factors that act as barriers to or facilitators of adherence is a fundamental concern in preventing intervention dropouts and increasing the effectiveness of digital health interventions. This review aimed to help stakeholders develop more effective digital health interventions by identifying factors influencing the continued use of mHealth apps targeting NCDs. We further derived quantified adherence scores for various health domains to validate the qualitative findings and explore adherence benchmarks. A comprehensive systematic literature search (January 2007 to December 2020) was conducted on MEDLINE, Embase, Web of Science, Scopus, and ACM Digital Library. Data on intended use, actual use, and factors influencing adherence were extracted. Intervention-related and patient-related factors with a positive or negative influence on adherence are presented separately for the health domains of NCD self-management, mental health, substance use, nutrition, physical activity, weight loss, multicomponent lifestyle interventions, mindfulness, and other NCDs. Quantified adherence measures, calculated as the ratio between the estimated intended use and actual use, were derived for each study and compared with the qualitative findings. The literature search yielded 2862 potentially relevant articles, of which 99 (3.46%) were included as part of the inclusion criteria. A total of 4 intervention-related factors indicated positive effects on adherence across all health domains: personalization or tailoring of the content of mHealth apps to the individual needs of the user, reminders in the form of individualized push notifications, user-friendly and technically stable app design, and personal support complementary to the digital intervention. Social and gamification features were also identified as drivers of app adherence across several health domains. A wide variety of patient-related factors such as user characteristics or recruitment channels further affects adherence. The derived adherence scores of the included mHealth apps averaged 56.0% (SD 24.4%). This study contributes to the scarce scientific evidence on factors that positively or negatively influence adherence to mHealth apps and is the first to quantitatively compare adherence relative to the intended use of various health domains. As underlying studies mostly have a pilot character with short study durations, research on factors influencing adherence to mHealth apps is still limited. To facilitate future research on mHealth app adherence, researchers should clearly outline and justify the app's intended use; report objective data on actual use relative to the intended use; and, ideally, provide long-term use and retention data. |
| Link | http://doi.org/10.2196/35371 |
| Title | Children must co-design digital health research. |
| Authors | |
| Journal | The Lancet. Digital health |
| Publication Date | 1 May 2023 |
| Date Added to PubMed | 10 Apr 2023 |
| Abstract | |
| Link | http://doi.org/10.1016/S2589-7500(23)00071-7 |
| Title | A Multidimensional Tool Based on the eHealth Literacy Framework: Development and Initial Validity Testing of the eHealth Literacy Questionnaire (eHLQ). |
| Authors | Kayser, L; Karnoe, A; Furstrand, D; Batterham, R; Christensen, KB; Elsworth, G; Osborne, RH |
| Journal | Journal of medical Internet research |
| Publication Date | 12 Feb 2018 |
| Date Added to PubMed | 13 Feb 2018 |
| Abstract | For people to be able to access, understand, and benefit from the increasing digitalization of health services, it is critical that services are provided in a way that meets the user's needs, resources, and competence. The objective of the study was to develop a questionnaire that captures the 7-dimensional eHealth Literacy Framework (eHLF). Draft items were created in parallel in English and Danish. The items were generated from 450 statements collected during the conceptual development of eHLF. In all, 57 items (7 to 9 items per scale) were generated and adjusted after cognitive testing. Items were tested in 475 people recruited from settings in which the scale was intended to be used (community and health care settings) and including people with a range of chronic conditions. Measurement properties were assessed using approaches from item response theory (IRT) and classical test theory (CTT) such as confirmatory factor analysis (CFA) and reliability using composite scale reliability (CSR); potential bias due to age and sex was evaluated using differential item functioning (DIF). CFA confirmed the presence of the 7 a priori dimensions of eHLF. Following item analysis, a 35-item 7-scale questionnaire was constructed, covering (1) using technology to process health information (5 items, CSR=.84), (2) understanding of health concepts and language (5 items, CSR=.75), (3) ability to actively engage with digital services (5 items, CSR=.86), (4) feel safe and in control (5 items, CSR=.87), (5) motivated to engage with digital services (5 items, CSR=.84), (6) access to digital services that work (6 items, CSR=.77), and (7) digital services that suit individual needs (4 items, CSR=.85). A 7-factor CFA model, using small-variance priors for cross-loadings and residual correlations, had a satisfactory fit (posterior productive P value: .27, 95% CI for the difference between the observed and replicated chi-square values: -63.7 to 133.8). The CFA showed that all items loaded strongly on their respective factors. The IRT analysis showed that no items were found to have disordered thresholds. For most scales, discriminant validity was acceptable; however, 2 pairs of dimensions were highly correlated; dimensions 1 and 5 (r=.95), and dimensions 6 and 7 (r=.96). All dimensions were retained because of strong content differentiation and potential causal relationships between these dimensions. There is no evidence of DIF. The eHealth Literacy Questionnaire (eHLQ) is a multidimensional tool based on a well-defined a priori eHLF framework with robust properties. It has satisfactory evidence of construct validity and reliable measurement across a broad range of concepts (using both CTT and IRT traditions) in various groups. It is designed to be used to understand and evaluate people's interaction with digital health services. |
| Link | http://doi.org/10.2196/jmir.8371 |
| Title | Timing, Indicators, and Approaches to Digital Patient Experience Evaluation: Umbrella Systematic Review. |
| Authors | Wang, T; Giunti, G; Goossens, R; Melles, M |
| Journal | Journal of medical Internet research |
| Publication Date | 5 Feb 2024 |
| Date Added to PubMed | 5 Feb 2024 |
| Abstract | The increasing prevalence of DH applications has outpaced research and practice in digital health (DH) evaluations. Patient experience (PEx) was reported as one of the challenges facing the health system by the World Health Organization. To generate evidence on DH and promote the appropriate integration and use of technologies, a standard evaluation of PEx in DH is required. This study aims to systematically identify evaluation timing considerations (ie, when to measure), evaluation indicators (ie, what to measure), and evaluation approaches (ie, how to measure) with regard to digital PEx. The overall aim of this study is to generate an evaluation guide for further improving digital PEx evaluation. This is a 2-phase study parallel to our previous study. In phase 1, literature reviews related to PEx in DH were systematically searched from Scopus, PubMed, and Web of Science databases. Two independent raters conducted 2 rounds of paper screening, including title and abstract screening and full-text screening, and assessed the interrater reliability for 20% (round 1: 23/115 and round 2: 12/58) random samples using the Fleiss-Cohen coefficient (round 1: k1=0.88 and round 2: k2=0.80). When reaching interrater reliability (k>0.60), TW conducted the rest of the screening process, leaving any uncertainties for group discussions. Overall, 38% (45/119) of the articles were considered eligible for further thematic analysis. In phase 2, to check if there were any meaningful novel insights that would change our conclusions, we performed an updated literature search in which we collected 294 newly published reviews, of which 102 (34.7%) were identified as eligible articles. We considered them to have no important changes to our original results on the research objectives. Therefore, they were not integrated into the synthesis of this review and were used as supplementary materials. Our review highlights 5 typical evaluation objectives that serve 5 stakeholder groups separately. We identified a set of key evaluation timing considerations and classified them into 3 categories: intervention maturity stages, timing of the evaluation, and timing of data collection. Information on evaluation indicators of digital PEx was identified and summarized into 3 categories (intervention outputs, patient outcomes, and health care system impact), 9 themes, and 22 subthemes. A set of evaluation theories, common study designs, data collection methods and instruments, and data analysis approaches was captured, which can be used or adapted to evaluate digital PEx. Our findings enabled us to generate an evaluation guide to help DH intervention researchers, designers, developers, and program evaluators evaluate digital PEx. Finally, we propose 6 directions for encouraging further digital PEx evaluation research and practice to address the challenge of poor PEx. |
| Link | http://doi.org/10.2196/46308 |
| Title | Digital Health Interventions to Enhance Tuberculosis Treatment Adherence: Scoping Review. |
| Authors | Lee, S; Rajaguru, V; Baek, JS; Shin, J; Park, Y |
| Journal | JMIR mHealth and uHealth |
| Publication Date | 4 Dec 2023 |
| Date Added to PubMed | 6 Dec 2023 |
| Abstract | Digital health technologies are widely used for disease management, with their computing platforms, software, and sensors being used for health care. These technologies are developed to manage chronic diseases and infectious bacterial diseases, including tuberculosis (TB). This study aims to comprehensively review the literature on the use of digital health interventions (DHIs) for enhancing TB treatment adherence and identify major strategies for their adoption. We conducted a literature search in the PubMed, Cochrane Library, Ovid Embase, and Scopus databases for relevant studies published between January 2012 and March 2022. Studies that focused on web-based or mobile phone-based interventions, medication adherence, digital health, randomized controlled trials, digital interventions, or mobile health and ubiquitous health technology for TB treatment and related health outcomes were included. We identified 27 relevant studies and classified them according to the intervention method, a significant difference in treatment success, and health outcomes. The following interventions were emphasized: SMS text messaging interventions (8/27, 30%), medicine reminders (6/27, 22%), and web-based direct observation therapy (9/27, 33%). Digital health technology significantly promoted disease management among individuals and health care professionals. However, only a few studies addressed 2-way communication therapies, such as interactive SMS text messaging and feedback systems. This scoping review classified studies on DHIs for patients with TB and demonstrated their potential for the self-management of TB. DHIs are still being developed, and evidence on the impact of digital technologies on enhancing TB treatment adherence remains limited. However, it is necessary to encourage patients' participation in TB treatment and self-management through bidirectional communication. We emphasize the importance of developing a communication system. |
| Link | http://doi.org/10.2196/49741 |
| Title | Digital Health Technologies in Pediatric Trials. |
| Authors | Sacks, L; Kunkoski, E; Noone, M |
| Journal | Therapeutic innovation & regulatory science |
| Publication Date | 1 Nov 2022 |
| Date Added to PubMed | 29 Mar 2022 |
| Abstract | Advances in the miniaturization of sensors and other technologies provide opportunities to collect physiological and/or functional data directly from patients participating in clinical trials. The use of such technologies in children is particularly promising. Objective, quantifiable measurements made by these technologies, often on a continuous or frequent basis, may provide more robust data than the episodic reports from caregivers that are used in traditional pediatric trials. We reviewed the pros and cons of these technologies for use in a variety of pediatric diseases, including seizure and neuromuscular disorders, cardiorespiratory diseases, and metabolic disorders. Correlation between sensor measurements and patient observations or traditional clinical measurements varied depending on the disease being evaluated. There was a notable dearth of reports on the use of digital health technology in pediatric patients. Given the range of sensors and measurements that can be made by DHTs, selection of the design, metrics and types of sensors best suited to disease evaluation presents challenges for adoption of these technologies in clinical trials. Traditional measurements of drug effects are often deficient, particularly in the evaluation of infants and young children. The opportunity to make objective, frequent measurements may increase our power to detect and quantify responses to therapy in these populations. Further research and evaluation are needed to realize the full scientific potential of remote monitoring in pediatric clinical trials. |
| Link | http://doi.org/10.1007/s43441-021-00374-w |
| Title | Digital Health for Geriatric Oncology. |
| Authors | Fallahzadeh, R; Rokni, SA; Ghasemzadeh, H; Soto-Perez-de-Celis, E; Shahrokni, A |
| Journal | JCO clinical cancer informatics |
| Publication Date | 1 Dec 2018 |
| Date Added to PubMed | 18 Jan 2019 |
| Abstract | In this review, we describe state-of-the-art digital health solutions for geriatric oncology and explore the potential application of emerging remote health-monitoring technologies in the context of cancer care. We also discuss the benefits and motivations behind adopting technology for symptom monitoring of older adults with cancer. We provide an overview of common symptoms and of the digital solutions-designed remote symptom assessment. We describe state-of-the-art systems for this purpose and highlight the limitations and challenges for the full-scale adoption of such solutions in geriatric oncology. With rapid advances in Internet-of-things technologies, many remote assessment systems have been developed in recent years. Despite showing potential in several health care domains and reliable functionality, few of these solutions have been designed for or tested in older patients with cancer. As a result, the geriatric oncology community lacks a consensus understanding of a possible correlation between remote digital assessments and health-related outcomes. Although the recent development of digital health solutions has been shown to be reliable and effective in many health-related applications, there exists an unmet need for development of systems and clinical trials specifically designed for remote cancer management of older adults with cancer, including developing advanced remote technologies for cancer-related symptom assessment and psychological behavior monitoring at home and developing outcome-oriented study protocols for accurate evaluation of existing or emerging systems. We conclude that perhaps the clearest path to future large-scale use of remote digital health technologies in cancer research is designing and conducting collaborative studies involving computer scientists, oncologists, and patient advocates. |
| Link | http://doi.org/10.1200/CCI.17.00133 |
| Title | Digital Patient Experience: Umbrella Systematic Review. |
| Authors | Wang, T; Giunti, G; Melles, M; Goossens, R |
| Journal | Journal of medical Internet research |
| Publication Date | 4 Aug 2022 |
| Date Added to PubMed | 5 Aug 2022 |
| Abstract | The adoption and use of technology have significantly changed health care delivery. Patient experience has become a significant factor in the entire spectrum of patient-centered health care delivery. Digital health facilitates further improvement and empowerment of patient experiences. Therefore, the design of digital health is served by insights into the barriers to and facilitators of digital patient experience (PEx). This study aimed to systematically review the influencing factors and design considerations of PEx in digital health from the literature and generate design guidelines for further improvement of PEx in digital health. We performed an umbrella systematic review following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology. We searched Scopus, PubMed, and Web of Science databases. Two rounds of small random sampling (20%) were independently reviewed by 2 reviewers who evaluated the eligibility of the articles against the selection criteria. Two-round interrater reliability was assessed using the Fleiss-Cohen coefficient (k1=0.88 and k2=0.80). Thematic analysis was applied to analyze the extracted data based on a small set of a priori categories. The search yielded 173 records, of which 45 (26%) were selected for data analysis. Findings and conclusions showed a great diversity; most studies presented a set of themes (19/45, 42%) or descriptive information only (16/45, 36%). The digital PEx-related influencing factors were classified into 9 categories: patient capability, patient opportunity, patient motivation, intervention technology, intervention functionality, intervention interaction design, organizational environment, physical environment, and social environment. These can have three types of impacts: positive, negative, or double edged. We captured 4 design constructs (personalization, information, navigation, and visualization) and 3 design methods (human-centered or user-centered design, co-design or participatory design, and inclusive design) as design considerations. We propose the following definition for digital PEx: "Digital patient experience is the sum of all interactions affected by a patient's behavioral determinants, framed by digital technologies, and shaped by organizational culture, that influence patient perceptions across the continuum of care channeling digital health." In this study, we constructed a design and evaluation framework that contains 4 phases-define design, define evaluation, design ideation, and design evaluation-and 9 design guidelines to help digital health designers and developers address digital PEx throughout the entire design process. Finally, our review suggests 6 directions for future digital PEx-related research. |
| Link | http://doi.org/10.2196/37952 |