EHealth tools for the self-testing of visual acuity: a scoping review.
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ABSTRACT:
SUBMITTER: Yeung WK
PROVIDER: S-EPMC6706420 | biostudies-literature | 2019
REPOSITORIES: biostudies-literature
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eHealth tools for the self-testing of visual acuity: a scoping review.
Yeung Wai Kent WK Dawes Piers P Pye Annie A Neil Malcolm M Aslam Tariq T Dickinson Christine C Leroi Iracema I
NPJ digital medicine 20190822
Uncorrected refractive error is a major cause of vision impairment, and is indexed by visual acuity. Availability of vision assessment is limited in low/middle-income countries and in minority groups in high income countries. eHealth tools offer a solution; two-thirds of the globe own mobile devices. This is a scoping review of the number and quality of tools for self-testing visual acuity. Software applications intended for professional clinical use were excluded. Keyword searches were conducte ...[more]
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Project description:IntroductionNumerous digital tools to self-assess visual acuity have been introduced. The recent COVID-19 pandemic underlined the need for high-quality remote care. This review gives a current overview of digital tools for remotely assessing visual function and reports on their accuracy.MethodsWe searched the databases of Embase and Pubmed, and systematically reviewed the literature, conforming to PRISMA guidelines. Two preliminary papers were added from medRxiv.org. The main outcome was the agreement of the digital tools with conventional clinical charts, as expressed by mean differences and 95% limits of agreement (95% LoA).ResultsSeventeen publications included studies reported on 13 different digital tools. Most of the tools focus on distance visual acuity. The mean differences of the digital tools ranged from - 0.08 to 0.10 logMAR, when compared to traditional clinical assessments. The 95% LoA differed considerably between studies: from ± 0.08 logMAR to ± 0.47 logMAR, though the variability was less pronounced for higher visual acuities.ConclusionThe low mean differences between digital visual acuity assessments and reference charts suggest clinical equivalence, though the wide 95% LoA identify a lower precision of digital self-assessments. This effect diminishes in individuals with better visual acuities, which is a common feature of visual acuity assessments. There is great potential for the digital tools to increase access to eye care and we expect the accuracy of the current tools to improve with every iteration in technology development.
| S-EPMC8225487 | biostudies-literature
Project description:ObjectiveeHealth-mediated interventions have been proposed as one option to support self-management in those with musculoskeletal disorders (MSDs). This scoping review aimed to chart the evidence regarding eHealth modalities, musculoskeletal diagnosis, and outcomes of eHealth-mediated self-management support interventions in persons with MSDs and identify any gaps within the literature.MethodsSix electronic databases (MEDLINE, CINAHL, PsycINFO, Embase, Scopus, and the Cochrane Database of Systematic Reviews), 7 grey literature sources (eg, OpenGrey), and reference and citation lists of included studies were searched from database inception to July 2020. Published studies of adult participants with a MSD utilizing an eHealth intervention to support self-management were included. Studies were limited to those published in English. Two reviewers independently screened all studies. Data were extracted by 1 reviewer and reviewed by another reviewer.ResultsAfter screening 3377 titles and abstracts followed by 176 full texts, 87 studies fulfilled the eligibility criteria. The majority were published in the last 5 years (n = 48; 55%), with almost one-third originating in the United States (n = 28; 32%). The most common eHealth modality type was internet based (n = 22; 35%), with almost one-half (n = 41; 47%) of the included studies involving participants with widespread musculoskeletal symptoms. The most commonly reported outcomes were related to body functions (ie, pain intensity) (n = 67; 45%), closely followed by activities and participation (ie, function) (n = 65; 44%), with environmental factors (ie, health care utilization) the least commonly reported (n = 17; 20%).ConclusionsThere is considerable variation within the eHealth-mediated self-management support intervention literature. Research is needed on the role of eHealth-mediated self-management support interventions across a broad range of MSDs to guide clinical practice.ImpactThis scoping review has identified gaps in the literature relating to specific eHealth modalities, musculoskeletal diagnoses, and health care utilization data, which should guide future research.
| S-EPMC8994513 | biostudies-literature
Project description:BackgroundAs eHealth and use of information and communication technologies (ICT) within healthcare becomes widespread, it is important to ensure that these forms of healthcare are accessible to the users. One factor that is key to accessing eHealth is digital health literacy.ObjectivesThis scoping review assesses available tools that can be used to evaluate digital health literacy.MethodsA systematic literature search was made in MEDLINE, CINAHL, APA PsychInfo, Ageline, AMED, and APA PsychArticles to present the tools currently in use to assess digital health literacy. A qualitative synthesis of the evidence was carried out using a data charting form created for this review. Extracted data included details of the population of investigation and digital health literacy tool used. A report was produced following PRISMA-ScR guidelines.ResultsIn total, 53 papers with adult participants and 3 with adolescent participants (aged between 12 and 19 years) were included in the scoping review. 5 questionnaires were identified that measured digital health literacy or attitudes towards the internet, of which the eHealth Literacy Scale (eHEALS) was the most commonly used questionnaire for both adults and children. Two children's questionnaires were often accompanied by a second task to verify the accuracy of the responses to the eHEALS questions.ConclusionseHEALS is the most commonly used method to assess digital health literacy and assess whether an individual is able to engage actively with eHealthcare or virtual resources. However, care needs to be taken to ensure that its administration does not exclude digitally disadvantaged groups from completing it. Future research would benefit from assessing whether digital health literacy tools are appropriate for use in clinical settings, working to ensure that any scales developed in this area are practical and can be used to support the allocation of resources to ensure that people are able to access healthcare equitably.
| S-EPMC9449566 | biostudies-literature
Project description:BackgroundCompassion is closely linked to psychological well-being, and several assessment tools have been developed and studied to assess the level of compassion in different populations and for more precise measurement. There is currently a scarcity of comprehensive knowledge about compassion-related assessment tools, and our research provides an overview of these tools.AimsTo identify scales used to measure compassion from different flows, and to assess their measurement properties and quality.MethodsFocusing on compassion assessment tools, the authors conducted a thorough search of 10 Chinese and English databases from their establishment until August 14, 2022. Data extracted included the author, year, country, objectives, target population, as well as the primary evaluation content. Using the COSMIN checklist, the methodological quality and measurement properties of the included studies were appraised. This scoping review was registered with the Open Science Framework and followed the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) checklist.ResultsThere were 15,965 papers searched, and 36 compassion-related measurement tools were identified in this study. None of the 36 studies provided possessed all nine psychometric properties, as outlined by the COSMIN criteria. On the basis of a systematic evaluation of quality, measurement qualities were ranked. The results for internal consistency and content validity were relatively favorable, whereas the results for structural validity were variable and the results for the remaining attributes were either uncertain or negative. A Venn diagram was used to illustrate the overlapping groups of compassion measurement tools based on the three-way flow of compassion. An overview of the reference instrument and theoretical basis for the included studies was provided, and half of them did not contain any theoretical or scale-based evidence.ConclusionIn this study, 36 compassion-related measuring instruments were identified, and the methodological quality and measurement properties of the included studies were acceptable. The included measurements were consistent with flows of compassion. A further focus of further research should be on developing theories in the compassion domain and developing instruments for measuring compassion that are multidimensional, multi-populations, and culturally relevant.
| S-EPMC10668436 | biostudies-literature
Project description:BackgroundeHealth is the use of information and communication technologies to enable and improve health and health care services. It is crucial that medical students receive adequate training in eHealth as they will work in clinical environments that are increasingly being enabled by technology. This trend is especially accelerated by the COVID-19 pandemic as it complicates traditional face-to-face medical consultations and highlights the need for innovative approaches in health care.ObjectiveThis review aims to evaluate the extent and nature of the existing literature on medical student training in eHealth. In detail, it aims to examine what this education consists of, the barriers, enhancing factors, and propositions for improving the medical curriculum. This review focuses primarily on some key technologies such as mobile health (mHealth), the internet of things (IoT), telehealth, and artificial intelligence (AI).MethodsSearches were performed on 4 databases, and articles were selected based on the eligibility criteria. Studies had to be related to the training of medical students in eHealth. The eligibility criteria were studies published since 2014, from a peer-reviewed journal, and written in either English or French. A grid was used to extract and chart data.ResultsThe search resulted in 25 articles. The most studied aspect was mHealth. eHealth as a broad concept, the IoT, AI, and programming were least covered. A total of 52% (13/25) of all studies contained an intervention, mostly regarding mHealth, electronic health records, web-based medical resources, and programming. The findings included various barriers, enhancing factors, and propositions for improving the medical curriculum.ConclusionsTrends have emerged regarding the suboptimal present state of eHealth training and barriers, enhancing factors, and propositions for optimal training. We recommend that additional studies be conducted on the following themes: barriers, enhancing factors, propositions for optimal training, competencies that medical students should acquire, learning outcomes from eHealth training, and patient care outcomes from this training. Additional studies should be conducted on eHealth and each of its aspects, especially on the IoT, AI, programming, and eHealth as a broad concept. Training in eHealth is critical to medical practice in clinical environments that are increasingly being enabled by technology. The need for innovative approaches in health care during the COVID-19 pandemic further highlights the relevance of this training.
| S-EPMC7519432 | biostudies-literature
Project description:BACKGROUND:Dyadic psychosocial interventions have been found beneficial both for people coping with mental or physical health conditions as well as their family members and friends who provide them with support. Delivering these interventions via electronic health (eHealth) may help increase their scalability. OBJECTIVE:This scoping review aimed to provide the first comprehensive overview of dyadic eHealth interventions for individuals of all ages affected by mental or physical illness and their family members or friends who support them. The goal was to understand how dyadic eHealth interventions have been used and to highlight areas of research needed to advance dyadic eHealth intervention development and dissemination. METHODS:A comprehensive electronic literature search of PubMed, EMBASE, Cochrane, Cumulative Index to Nursing and Allied Health Literature, and PsycINFO was conducted for articles published in the English language through March 2019. Eligible records described a psychosocial eHealth intervention that intervened with both care recipients and their support person. RESULTS:A total of 7113 records were reviewed of which 101 met eligibility criteria. There were 52 unique dyadic eHealth interventions identified, which were tested across 73 different trials. Of the unique interventions, 33 were conducted among dyads of children and their supporting parent, 1 was conducted with an adolescent-young adult care recipient population, and the remaining 18 were conducted among adult dyads. Interventions targeting pediatric dyads most commonly addressed a mental health condition (n=10); interventions targeting adult dyads most commonly addressed cancer (n=9). More than three-fourths of interventions (n=40) required some human support from research staff or clinicians. Most studies (n=64) specified one or more primary outcomes for care recipients, whereas less than one-fourth (n=22) specified primary outcomes for support persons. Where specified, primary outcomes were most commonly self-reported psychosocial or health factors for both care recipients (n=43) and support persons (n=18). Results of the dyadic eHealth intervention tended to be positive for care recipients, but evidence of effects for support persons was limited because of few studies specifying primary outcomes for supporters. Trials of dyadic eHealth interventions were most commonly randomized controlled trials (RCTs; n=44), and RCTs most commonly compared the dyadic eHealth intervention to usual care alone (n=22). CONCLUSIONS:This first comprehensive review of dyadic eHealth interventions demonstrates that there is substantial, diverse, and growing literature supporting this interventional approach. However, several significant gaps were identified. Few studies were designed to evaluate the unique effects of dyadic interventions relative to individual interventions. There was also limited assessment and reporting of outcomes for support persons, and there were no interventions meeting our eligibility criteria specifically targeting the needs of older adult dyads. Findings highlight areas of research opportunities for developing dyadic eHealth interventions for novel populations and for increasing access to dyadic care.
| S-EPMC7081137 | biostudies-literature
Project description:BackgroundVisual analytics (VA) promotes the understanding of data with visual, interactive techniques, using analytic and visual engines. The analytic engine includes automated techniques, whereas common visual outputs include flow maps and spatiotemporal hot spots.ObjectiveThis scoping review aims to address a gap in the literature, with the specific objective to synthesize literature on the use of VA tools, techniques, and frameworks in interrelated health care areas of population health and health services research (HSR).MethodsUsing the 2018 PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines, the review focuses on peer-reviewed journal articles and full conference papers from 2005 to March 2019. Two researchers were involved at each step, and another researcher arbitrated disagreements. A comprehensive abstraction platform captured data from diverse bodies of the literature, primarily from the computer and health sciences.ResultsAfter screening 11,310 articles, findings from 55 articles were synthesized under the major headings of visual and analytic engines, visual presentation characteristics, tools used and their capabilities, application to health care areas, data types and sources, VA frameworks, frameworks used for VA applications, availability and innovation, and co-design initiatives. We found extensive application of VA methods used in areas of epidemiology, surveillance and modeling, health services access, use, and cost analyses. All articles included a distinct analytic and visualization engine, with varying levels of detail provided. Most tools were prototypes, with 5 in use at the time of publication. Seven articles presented methodological frameworks. Toward consistent reporting, we present a checklist, with an expanded definition for VA applications in health care, to assist researchers in sharing research for greater replicability. We summarized the results in a Tableau dashboard.ConclusionsWith the increasing availability and generation of big health care data, VA is a fast-growing method applied to complex health care data. What makes VA innovative is its capability to process multiple, varied data sources to demonstrate trends and patterns for exploratory analysis, leading to knowledge generation and decision support. This is the first review to bridge a critical gap in the literature on VA methods applied to the areas of population health and HSR, which further indicates possible avenues for the adoption of these methods in the future. This review is especially important in the wake of COVID-19 surveillance and response initiatives, where many VA products have taken center stage.International registered report identifier (irrid)RR2-10.2196/14019.
| S-EPMC7716797 | biostudies-literature
Project description:BackgroundAcross eHealth intervention studies involving children, adolescents, and their parents, researchers have measured user experience to assist with intervention development, refinement, and evaluation. To date, no widely accepted definitions or measures of user experience exist to support a standardized approach for evaluation and comparison within or across interventions.ObjectiveWe conduct a scoping review with subsequent Delphi consultation to identify how user experience is defined and measured in eHealth research studies, characterize the measurement tools used, and establish working definitions for domains of user experience that could be used in future eHealth evaluations.MethodsWe systematically searched electronic databases for published and gray literature available from January 1, 2005, to April 11, 2019. We included studies assessing an eHealth intervention that targeted any health condition and was designed for use by children, adolescents, and their parents. eHealth interventions needed to be web-, computer-, or mobile-based, mediated by the internet with some degree of interactivity. We required studies to report the measurement of user experience as first-person experiences, involving cognitive and behavioral factors reported by intervention users. We appraised the quality of user experience measures in included studies using published criteria: well-established, approaching well-established, promising, or not yet established. We conducted a descriptive analysis of how user experience was defined and measured in each study. Review findings subsequently informed the survey questions used in the Delphi consultations with eHealth researchers and adolescent users for how user experience should be defined and measured.ResultsOf the 8634 articles screened for eligibility, 129 articles and 1 erratum were included in the review. A total of 30 eHealth researchers and 27 adolescents participated in the Delphi consultations. On the basis of the literature and consultations, we proposed working definitions for 6 main user experience domains: acceptability, satisfaction, credibility, usability, user-reported adherence, and perceived impact. Although most studies incorporated a study-specific measure, we identified 10 well-established measures to quantify 5 of the 6 domains of user experience (all except for self-reported adherence). Our adolescent and researcher participants ranked perceived impact as one of the most important domains of user experience and usability as one of the least important domains. Rankings between adolescents and researchers diverged for other domains.ConclusionsFindings highlight the various ways in which user experience has been defined and measured across studies and what aspects are most valued by researchers and adolescent users. We propose incorporating the working definitions and available measures of user experience to support consistent evaluation and reporting of outcomes across studies. Future studies can refine the definitions and measurement of user experience, explore how user experience relates to other eHealth outcomes, and inform the design and use of human-centered eHealth interventions.
| S-EPMC8686463 | biostudies-literature
Project description:ObjectiveThere has been substantial growth in eHealth over the past decade, driven by expectations of improved healthcare system performance. Despite substantial eHealth investment, little is known about the monitoring and evaluation strategies for gauging progress in eHealth availability and use. This scoping review aims to map the existing literature and depict the predominant approaches and methodological recommendations to national and regional monitoring and evaluation of eHealth availability and use, to advance national strategies for monitoring and evaluating eHealth.MethodsPeer-reviewed and grey literature on monitoring and evaluation of eHealth availability and use published between January 1, 2009, and March 11, 2019, were eligible for inclusion. A total of 2354 publications were identified and 36 publications were included after full-text review. Data on publication type (eg, empirical research), country, level (national or regional), publication year, method (eg, survey), and domain (eg, provider-centric electronic record) were charted.ResultsThe majority of publications monitored availability alone or applied a combination of availability and use measures. Surveys were the most common data collection method (used in 86% of the publications). Organization for Economic Co-operation and Development (OECD), European Commission, Canada Health Infoway, and World Health Organization (WHO) have developed comprehensive eHealth monitoring and evaluation methodology recommendations.DiscussionEstablishing continuous national eHealth monitoring and evaluation, based on international approaches and recommendations, could improve the ability for cross-country benchmarking and learning. This scoping review provides an overview of the predominant approaches to and recommendations for national and regional monitoring and evaluation of eHealth. It thereby provides a starting point for developing national eHealth monitoring strategies.
| S-EPMC7309231 | biostudies-literature
Project description:Assessment of visual acuity is a well standardized procedure at least for expert opinions and clinical trials. It is often recommended not giving patients feedback on the correctness of their responses. As this viewpoint has not been quantitatively examined so far, we quantitatively assessed possible effects of feedback on visual acuity testing. In 40 normal participants we presented Landolt Cs in 8 orientations using the automated Freiburg Acuity Test (FrACT, <michaelbach.de/fract. Over a run comprising 24 trials, the acuity threshold was measured with an adaptive staircase procedure. In an ABCDDCBA scheme, trial-by-trial feedback was provided in 2 x 4 conditions: (A) no feedback, (B) acoustic signals indicating correctness, (C)visual indication of correct orientation, and (D) a combination of (B) and (C). After each run the participants judged comfort. Main outcome measures were absolute visual acuity (logMAR), its test-retest agreement (limits of agreement) and participants' comfort estimates on a 5-step symmetric Likert scale. Feedback influenced acuity outcome significantly (p = 0.02), but with a tiny effect size: 0.02 logMAR poorer acuity for (D) compared to (A), even weaker effects for (B) and (C). Test-retest agreement was high (limits of agreement: ± 1.0 lines) and did not depend on feedback (p>0.5). The comfort ranking clearly differed, by 2 steps on the Likert scale: the condition (A)-no feedback-was on average "slightly uncomfortable", the other three conditions were "slightly comfortable" (p<0.0001). Feedback affected neither reproducibility nor the acuity outcome to any relevant extent. The participants, however, reported markedly greater comfort with any kind of feedback. We conclude that systematic feedback (as implemented in FrACT) offers nothing but advantages for routine use.
| S-EPMC4732607 | biostudies-literature