| Title | Telemental health for clinical assessment and treatment. |
| Authors | Sugarman, DE; Busch, AB |
| Journal | BMJ (Clinical research ed.) |
| Publication Date | 16 Jan 2023 |
| Date Added to PubMed | 17 Jan 2023 |
| Abstract | Telemental health-the use of videoconferencing or audio only (telephone) in mental health care-has accelerated tremendously since the start of the covid-19 pandemic. Meta-analyses have examined the reliability (ie, concordance) of assessment and the efficacy/effectiveness of telemental health compared with in-person care. Results indicate that telemental health assessment and clinical outcomes are similar compared with in-person care but there is much unexplained variability, as well as evidence that patient clinical and demographic characteristics can influence these findings. Further, gaps exist in the literature regarding specific patient populations (eg, psychotic disorders, children/adolescents), treatment modalities (eg, group therapy), audio only telemedicine, and hybrid care that mixes in-person with telemental health care. These gaps provide important directions for the next generation of telemental health research. Comprehensive clinical guidelines from mental health organizations are available to telemental health practitioners and focus on five content themes: legal and regulatory issues, clinical considerations, standard operating procedures and protocols, technical requirements, and considerations of specific populations and settings. |
| Link | http://doi.org/10.1136/bmj-2022-072398 |
| Title | Development and validation of the Digital Health Acceptability Questionnaire. |
| Authors | Haydon, HM; Major, T; Kelly, JT; Catapan, SC; Caffery, LJ; Smith, AC; Gallegos-Rejas, V; Thomas, EE; Banbury, A; Snoswell, CL |
| Journal | Journal of telemedicine and telecare |
| Publication Date | 1 Dec 2023 |
| Date Added to PubMed | 26 Nov 2023 |
| Abstract | Acceptability (of healthcare services) is an important construct that lacks a consistent definition within research. Addressing this issue, a systematic review led to the Theoretical Framework of Acceptability. In this study, we describe the development (based on the Theoretical Framework of Acceptability) and validation of the Digital Health Acceptability Questionnaire. Nineteen items aligning with the Theoretical Framework of Acceptability were developed. Two versions of the questionnaire measuring telehealth acceptability by telephone (N = 644) and videoconference appointment (N = 425), were administered to a nationally representative survey of consumers in Australia. Two exploratory factor analyses (Oblimin rotation) were conducted for each scale (telephone/videoconference). Two-factor solutions (5 items each) were found for both (telephone/videoconference) acceptability questionnaires: (a) attitude toward the service as a means to address healthcare needs and affective attitude and (b) individual capacity and effort to use telehealth. Before rotation, Factor 1 of the telephone scale (α = 0.92) measured 56.18% of the variance and Factor 2 (α = 0.86) measured 14.17%. Factor 1 of the videoconference scale (α = 0.90) measured 56.68% of the variance and Factor 2 (α = 0.85) measured 10.63%. The full10-item acceptability questionnaire showed excellent internal consistency (telephone: α = 0.91 and videoconference: α = 0.92). The 2-dimensional Digital Health Acceptability Questionnaire is a brief survey based on research evidence and validated in a large Australian sample. |
| Link | http://doi.org/10.1177/1357633X231202279 |
| Title | Digital Health Applications for Pharmacogenetic Clinical Trials. |
| Authors | Naik, H; Palaniappan, L; Ashley, EA; Scott, SA |
| Journal | Genes |
| Publication Date | 26 Oct 2020 |
| Date Added to PubMed | 30 Oct 2020 |
| Abstract | Digital health (DH) is the use of digital technologies and data analytics to understand health-related behaviors and enhance personalized clinical care. DH is increasingly being used in clinical trials, and an important field that could potentially benefit from incorporating DH into trial design is pharmacogenetics. Prospective pharmacogenetic trials typically compare a standard care arm to a pharmacogenetic-guided therapeutic arm. These trials often require large sample sizes, are challenging to recruit into, lack patient diversity, and can have complicated workflows to deliver therapeutic interventions to both investigators and patients. Importantly, the use of DH technologies could mitigate these challenges and improve pharmacogenetic trial design and operation. Some DH use cases include (1) automatic electronic health record-based patient screening and recruitment; (2) interactive websites for participant engagement; (3) home- and tele-health visits for patient convenience (e.g., samples for lab tests, physical exams, medication administration); (4) healthcare apps to collect patient-reported outcomes, adverse events and concomitant medications, and to deliver therapeutic information to patients; and (5) wearable devices to collect vital signs, electrocardiograms, sleep quality, and other discrete clinical variables. Given that pharmacogenetic trials are inherently challenging to conduct, future pharmacogenetic utility studies should consider implementing DH technologies and trial methodologies into their design and operation. |
| Link | http://doi.org/10.3390/genes11111261 |
| Title | Cost-Effectiveness of Digital Health Interventions for Asthma or COPD: Systematic Review. |
| Authors | Ferreira, MAM; Dos Santos, AF; Sousa-Pinto, B; Taborda-Barata, L |
| Journal | Clinical and experimental allergy : journal of the British Society for Allergy and Clinical Immunology |
| Publication Date | 1 Sep 2024 |
| Date Added to PubMed | 13 Aug 2024 |
| Abstract | Digital interventions such as remote monitoring of symptoms and physiological measurements have the potential to reduce the economic burden of asthma and chronic obstructive pulmonary disease (COPD) but their cost-effectiveness remains unclear. This systematic review of randomised controlled trials (RCT) aims to assess whether digital health interventions can be cost-effective in these patients. Systematic review of RCTs. Study quality was assessed using RoB2 tool. Systematic search in three databases: PubMed, Scopus and Web of Science. Studies were eligible if they were RCTs with health economic evaluations assessing participants with asthma and/or COPD and comparing a digital health intervention to standard of care. We included 35 RCTs, of which 21 were related to COPD, 13 to asthma and one to both diseases. Overall, studies assessed four categories of digital health interventions: (i) Electronic patient diaries (n = 4), (ii) real-time monitoring (n = 19), (iii) teleconsultations (n = 6) and (iv) others (n = 6). Eleven studies performed a full economic evaluation analysis, while 24 studies performed a partial economic analysis. Most studies involving real-time monitoring or teleconsultations presented economic results in favour of digital health interventions (indicating them to be cost-effective or less expensive than the standard of care). Mixed results were obtained for electronic patient diaries. In the studies that conducted a full economic analysis, the incremental cost-effectiveness ratio (ICER) ranged from 3530,93€/QALY and 286,369,28€/QALY. In the studies that conducted a partial economic analysis, the cost differences between the intervention group and the control group ranged from 0,12€ and 85,217,86€. Half studies with low risk of bias concluded that the intervention was economically favourable. Although costs varied based on intervention type, follow-up period and country, most studies report digital health interventions to be affordable or associated with decreased costs. PROSPERO: CRD42023439195. |
| Link | http://doi.org/10.1111/cea.14547 |
| Title | Digital health technologies: opportunities and challenges in rheumatology. |
| Authors | Solomon, DH; Rudin, RS |
| Journal | Nature reviews. Rheumatology |
| Publication Date | 1 Sep 2020 |
| Date Added to PubMed | 28 Jul 2020 |
| Abstract | The past decade in rheumatology has seen tremendous innovation in digital health technologies, including the electronic health record, virtual visits, mobile health, wearable technology, digital therapeutics, artificial intelligence and machine learning. The increased availability of these technologies offers opportunities for improving important aspects of rheumatology, including access, outcomes, adherence and research. However, despite its growth in some areas, particularly with non-health-care consumers, digital health technology has not substantially changed the delivery of rheumatology care. This Review discusses key barriers and opportunities to improve application of digital health technologies in rheumatology. Key topics include smart design, voice enablement and the integration of electronic patient-reported outcomes. Smart design involves active engagement with the end users of the technologies, including patients and clinicians through focus groups, user testing sessions and prototype review. Voice enablement using voice assistants could be critical for enabling patients with hand arthritis to effectively use smartphone apps and might facilitate patient engagement with many technologies. Tracking many rheumatic diseases requires frequent monitoring of patient-reported outcomes. Current practice only collects this information sporadically, and rarely between visits. Digital health technology could enable patient-reported outcomes to inform appropriate timing of face-to-face visits and enable improved application of treat-to-target strategies. However, best practice standards for digital health technologies do not yet exist. To achieve the potential of digital health technology in rheumatology, rheumatology professionals will need to be more engaged upstream in the technology design process and provide leadership to effectively incorporate the new tools into clinical care. |
| Link | http://doi.org/10.1038/s41584-020-0461-x |
| Title | Digital Health Interventions for Depression and Anxiety Among People With Chronic Conditions: Scoping Review. |
| Authors | Shah, A; Hussain-Shamsy, N; Strudwick, G; Sockalingam, S; Nolan, RP; Seto, E |
| Journal | Journal of medical Internet research |
| Publication Date | 26 Sep 2022 |
| Date Added to PubMed | 27 Sep 2022 |
| Abstract | Chronic conditions are characterized by their long duration (≥1 year), need for ongoing medical attention, and limitations in activities of daily living. These can often co-occur with depression and anxiety as common and detrimental comorbidities among the growing population living with chronic conditions. Digital health interventions (DHIs) hold promise in overcoming barriers to accessing mental health support for these individuals; however, the design and implementation of DHIs for depression and anxiety in people with chronic conditions are yet to be explored. This study aimed to explore what is known in the literature regarding DHIs for the prevention, detection, or treatment of depression and anxiety among people with chronic conditions. A scoping review of the literature was conducted using the Arksey and O'Malley framework. Searches of the literature published in 5 databases between 1990 and 2019 were conducted in April 2019 and updated in March 2021. To be included, studies must have described a DHI tested with, or designed for, the prevention, detection, or treatment of depression or anxiety in people with common chronic conditions (arthritis, asthma, diabetes mellitus, heart disease, chronic obstructive pulmonary disease, cancer, stroke, and Alzheimer disease or dementia). Studies were independently screened by 2 reviewers against the inclusion and exclusion criteria. Both quantitative and qualitative data were extracted, charted, and synthesized to provide a descriptive summary of the trends and considerations for future research. Database searches yielded 11,422 articles across the initial and updated searches, 53 (0.46%) of which were included in this review. DHIs predominantly sought to provide treatment (44/53, 83%), followed by detection (5/53, 9%) and prevention (4/53, 8%). Most DHIs were focused on depression (36/53, 68%), guided (32/53, 60%), tailored to chronic physical conditions (19/53, 36%), and delivered through web-based platforms (20/53, 38%). Only 2 studies described the implementation of a DHI. As a growing research area, DHIs offer the potential to address the gap in care for depression and anxiety among people with chronic conditions; however, their implementation in standard care is scarce. Although stepped care has been identified as a promising model to implement efficacious DHIs, few studies have investigated the use of DHIs for depression and anxiety among chronic conditions using such models. In developing stepped care, we outlined DHI tailoring, guidance, and intensity as key considerations that require further research. |
| Link | http://doi.org/10.2196/38030 |
| Title | Agile, Easily Applicable, and Useful eHealth Usability Evaluations: Systematic Review and Expert-Validation. |
| Authors | Sinabell, I; Ammenwerth, E |
| Journal | Applied clinical informatics |
| Publication Date | 1 Jan 2022 |
| Date Added to PubMed | 10 Mar 2022 |
| Abstract | Electronic health (eHealth) usability evaluations of rapidly developed eHealth systems are difficult to accomplish because traditional usability evaluation methods require substantial time in preparation and implementation. This illustrates the growing need for fast, flexible, and cost-effective methods to evaluate the usability of eHealth systems. To address this demand, the present study systematically identified and expert-validated rapidly deployable eHealth usability evaluation methods. Identification and prioritization of eHealth usability evaluation methods suitable for agile, easily applicable, and useful eHealth usability evaluations. The study design comprised a systematic iterative approach in which expert knowledge was contrasted with findings from literature. Forty-three eHealth usability evaluation methods were systematically identified and assessed regarding their ease of applicability and usefulness through semi-structured expert interviews with 10 European usability experts and systematic literature research. The most appropriate eHealth usability evaluation methods were selected stepwise based on the experts' judgements of their ease of applicability and usefulness. Of these 43 eHealth usability evaluation methods identified as suitable for agile, easily applicable, and useful eHealth usability evaluations, 10 were recommended by the experts based on their usefulness for rapid eHealth usability evaluations. The three most frequently recommended eHealth usability evaluation methods were Remote User Testing, Expert Review, and Rapid Iterative Test and Evaluation Method. Eleven usability evaluation methods, such as Retrospective Testing, were not recommended for use in rapid eHealth usability evaluations. We conducted a systematic review and expert-validation to identify rapidly deployable eHealth usability evaluation methods. The comprehensive and evidence-based prioritization of eHealth usability evaluation methods supports faster usability evaluations, and so contributes to the ease-of-use of emerging eHealth systems. |
| Link | http://doi.org/10.1055/s-0041-1740919 |
| Title | Digital health interventions in dermatology-Mapping technology and study parameters of systematically identified publications. |
| Authors | Reinders, P; Augustin, M; Kirsten, N; Fleyder, A; Otten, M |
| Journal | Journal of the European Academy of Dermatology and Venereology : JEADV |
| Publication Date | 1 Dec 2023 |
| Date Added to PubMed | 2 Aug 2023 |
| Abstract | Digital health interventions (DHI) potentially improve the efficiency and effectiveness of dermatological care. Currently, an overview clustering and characterizing the evidence on DHIs is missing. This systematic mapping of the literature aims to analyse published research on DHIs in dermatology to identify trends and gaps in research. For this purpose, a systematic search of the MEDLINE database was conducted in August 2022 to identify original publications on DHIs in dermatology. Data on country, targeted audience, DHI category, indication, outcome parameter and study design were extracted. Out of 12,009 records identified in MEDLINE, 403 studies were included in the final analysis. Studies on DHIs mainly performed in western countries, headed by the United States (n = 133), Germany (n = 32) and Spain (n = 23). Of all identified DHIs, 261 targeted healthcare providers (HCP), 66 clients (e.g. patients, caregivers, healthy individuals) and 67 both clients and HCPs. A majority of DHIs focussed on establishing a diagnosis (n = 254). Every other study analysed store-and-forward teledermatology (n = 187), followed by artificial intelligence applications for image analysis (n = 65). The most often analysed DHI category for clients was a support of health behaviour change (n = 31). Monitoring of clients was targeted by 77 studies. Skin cancer (n = 148), wounds (n = 29) and psoriasis (n = 29) were the most targeted indications by DHIs. Most studies analysed diagnostic performance (n = 166), fewer studies analysed acceptance (n = 92) and effectiveness (n = 98). Usability (n = 32) and efficiency (n = 36) were investigated only to a small extent. Studies on DHIs in dermatology have focused on teledermatology and AI applications, with an emphasis on skin cancer diagnosis. Apart from that, a range of DHIs for different user groups, purposes and indications were identified, demonstrating the broad potential for DHIs in dermatology. Further research with a wider set of outcome parameters is needed to fully understand the potential of DHIs and ensure their sustainable implementation into dermatological care. |
| Link | http://doi.org/10.1111/jdv.19392 |
| Title | Integrating Behavioral Science and Design Thinking to Develop Mobile Health Interventions: Systematic Scoping Review. |
| Authors | Voorheis, P; Zhao, A; Kuluski, K; Pham, Q; Scott, T; Sztur, P; Khanna, N; Ibrahim, M; Petch, J |
| Journal | JMIR mHealth and uHealth |
| Publication Date | 16 Mar 2022 |
| Date Added to PubMed | 17 Mar 2022 |
| Abstract | Mobile health (mHealth) interventions are increasingly being designed to facilitate health-related behavior change. Integrating insights from behavioral science and design science can help support the development of more effective mHealth interventions. Behavioral Design (BD) and Design Thinking (DT) have emerged as best practice approaches in their respective fields. Until now, little work has been done to examine how BD and DT can be integrated throughout the mHealth design process. The aim of this scoping review was to map the evidence on how insights from BD and DT can be integrated to guide the design of mHealth interventions. The following questions were addressed: (1) what are the main characteristics of studies that integrate BD and DT during the mHealth design process? (2) what theories, models, and frameworks do design teams use during the mHealth design process? (3) what methods do design teams use to integrate BD and DT during the mHealth design process? and (4) what are key design challenges, implementation considerations, and future directions for integrating BD and DT during mHealth design? This review followed the Joanna Briggs Institute reviewer manual and PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) checklist. Studies were identified from MEDLINE, PsycINFO, Embase, CINAHL, and JMIR by using search terms related to mHealth, BD, and DT. Included studies had to clearly describe their mHealth design process and how behavior change theories, models, frameworks, or techniques were incorporated. Two independent reviewers screened the studies for inclusion and completed the data extraction. A descriptive analysis was conducted. A total of 75 papers met the inclusion criteria. All studies were published between 2012 and 2021. Studies integrated BD and DT in notable ways, which can be referred to as "Behavioral Design Thinking." Five steps were followed in Behavioral Design Thinking: (1) empathize with users and their behavior change needs, (2) define user and behavior change requirements, (3) ideate user-centered features and behavior change content, (4) prototype a user-centered solution that supports behavior change, and (5) test the solution against users' needs and for its behavior change potential. The key challenges experienced during mHealth design included meaningfully engaging patient and public partners in the design process, translating evidence-based behavior change techniques into actual mHealth features, and planning for how to integrate the mHealth intervention into existing clinical systems. Best practices from BD and DT can be integrated throughout the mHealth design process to ensure that mHealth interventions are purposefully developed to effectively engage users. Although this scoping review clarified how insights from BD and DT can be integrated during mHealth design, future research is needed to identify the most effective design approaches. |
| Link | http://doi.org/10.2196/35799 |
| Title | The Digital Health Revolution and People with Disabilities: Perspective from the United States. |
| Authors | Jones, M; DeRuyter, F; Morris, J |
| Journal | International journal of environmental research and public health |
| Publication Date | 7 Jan 2020 |
| Date Added to PubMed | 16 Jan 2020 |
| Abstract | This article serves as the introduction to this special issue on Mobile Health and Mobile Rehabilitation for People with Disabilities. Social, technological and policy trends are reviewed. Needs, opportunities and challenges for the emerging fields of mobile health (mHealth, aka eHealth) and mobile rehabilitation (mRehab) are discussed. Healthcare in the United States (U.S.) is at a critical juncture characterized by: (1) a growing need for healthcare and rehabilitation services; (2) maturing technological capabilities to support more effective and efficient health services; (3) evolving public policies designed, by turns, to contain cost and support new models of care; and (4) a growing need to ensure acceptance and usability of new health technologies by people with disabilities and chronic conditions, clinicians and health delivery systems. Discussion of demographic and population health data, healthcare service delivery and a public policy primarily focuses on the U.S. However, trends identified (aging populations, growing prevalence of chronic conditions and disability, labor shortages in healthcare) apply to most countries with advanced economies and others. Furthermore, technologies that enable mRehab (wearable sensors, in-home environmental monitors, cloud computing, artificial intelligence) transcend national boundaries. Remote and mobile healthcare delivery is needed and inevitable. Proactive engagement is critical to ensure acceptance and effectiveness for all stakeholders. |
| Link | http://doi.org/10.3390/ijerph17020381 |