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NPJ Digital Medicine Sep 2023Skin diseases affect one-third of the global population, posing a major healthcare burden. Deep learning may optimise healthcare workflows through processing skin images... (Review)
Review
Skin diseases affect one-third of the global population, posing a major healthcare burden. Deep learning may optimise healthcare workflows through processing skin images via neural networks to make predictions. A focus of deep learning research is skin lesion triage to detect cancer, but this may not translate to the wider scope of >2000 other skin diseases. We searched for studies applying deep learning to skin images, excluding benign/malignant lesions (1/1/2000-23/6/2022, PROSPERO CRD42022309935). The primary outcome was accuracy of deep learning algorithms in disease diagnosis or severity assessment. We modified QUADAS-2 for quality assessment. Of 13,857 references identified, 64 were included. The most studied diseases were acne, psoriasis, eczema, rosacea, vitiligo, urticaria. Deep learning algorithms had high specificity and variable sensitivity in diagnosing these conditions. Accuracy of algorithms in diagnosing acne (median 94%, IQR 86-98; n = 11), rosacea (94%, 90-97; n = 4), eczema (93%, 90-99; n = 9) and psoriasis (89%, 78-92; n = 8) was high. Accuracy for grading severity was highest for psoriasis (range 93-100%, n = 2), eczema (88%, n = 1), and acne (67-86%, n = 4). However, 59 (92%) studies had high risk-of-bias judgements and 62 (97%) had high-level applicability concerns. Only 12 (19%) reported participant ethnicity/skin type. Twenty-four (37.5%) evaluated the algorithm in an independent dataset, clinical setting or prospectively. These data indicate potential of deep learning image analysis in diagnosing and monitoring common skin diseases. Current research has important methodological/reporting limitations. Real-world, prospectively-acquired image datasets with external validation/testing will advance deep learning beyond the current experimental phase towards clinically-useful tools to mitigate rising health and cost impacts of skin disease.
PubMed: 37758829
DOI: 10.1038/s41746-023-00914-8 -
Digital Health 2023Although the pedometer- and accelerometer-based interventions (PABI) have demonstrated efficacy in improving physical activity (PA) and health-related outcomes, the... (Review)
Review
Effectiveness of pedometer- and accelerometer-based interventions in improving physical activity and health-related outcomes among college students: A systematic review and meta-analysis.
BACKGROUND
Although the pedometer- and accelerometer-based interventions (PABI) have demonstrated efficacy in improving physical activity (PA) and health-related outcomes, the dearth of empirical evidence in college students warrants further investigation.
OBJECTIVE
This systematic review and meta-analysis aim to examine the effects of PABI on improving PA and health-related outcomes among college students.
METHODS
PubMed, Web of Science, Embase, Cochrane Library, and PsycINFO were searched for relevant literature from inception to 20 February 2022. Randomized controlled trials (RCTs) conducted among college students with PABI to increase objectively measured PA as the primary outcome were included in this study.
RESULTS
A total of nine RCTs with 527 participants were included in this study. The combined results showed that PABI significantly improved PA (standardized mean difference = 0.41, 95% confidence interval (CI): 0.08, 0.74, = 0.016) and significantly contributed to weight loss (mean differences (MD) = -1.56 kg, 95% CI: -2.40 kg, -0.73 kg, < 0.01), and lower body mass index (MD = -0.33 kg/m, 95% CI: -0.66 kg/m, 0.00 kg/m, = 0.05) compared to the control group, but no significant effects were observed on improvements of body fat (%) and exercise self-efficacy. Interventions in the group of step, general students, pedometer-based intervention, theory, and developed region were significantly more effective in subgroup analyses.
CONCLUSIONS
PABI was found to be effective in promoting PA and weight loss among college students. Future research is needed to further explore the long-term effects of PABI and the characteristics of multiple intervention models.
PubMed: 37492032
DOI: 10.1177/20552076231188213 -
Frontiers in Digital Health 2023The electronic health record (EHR) has been widely implemented internationally as a tool to improve health and healthcare delivery. However, EHR implementation has been... (Review)
Review
BACKGROUND
The electronic health record (EHR) has been widely implemented internationally as a tool to improve health and healthcare delivery. However, EHR implementation has been comparatively slow amongst hospitals in the Arabian Gulf countries. This gradual uptake may be linked to prevailing opinions amongst medical practitioners. Until now, no systematic review has been conducted to identify the impact of EHRs on doctor-patient relationships and attitudes in the Arabian Gulf countries.
OBJECTIVE
To understand the impact of EHR use on patient-doctor relationships and communication in the Arabian Gulf countries.
DESIGN
A systematic review of English language publications was performed using PRISMA chart guidelines between 1990 and 2023.
METHODS
Electronic database search (Ovid MEDLINE, Global Health, HMIC, EMRIM, and PsycINFO) and reference searching restricted to the six Arabian Gulf countries only. MeSH terms and keywords related to electronic health records, doctor-patient communication, and relationship were used. Newcastle-Ottawa Scale (NOS) quality assessment was performed.
RESULTS
18 studies fulfilled the criteria to be included in the systematic review. They were published between 1992 and 2023. Overall, a positive impact of EHR uptake was reported within the Gulf countries studied. This included improvement in the quality and performance of physicians, as well as improved accuracy in monitoring patient health. On the other hand, a notable negative impact was a general perception of physician attention shifted away from the patients themselves and towards data entry tasks (e.g., details of the patients and their education at the time of the consultation).
CONCLUSION
The implementation of EHR systems is beneficial for effective care delivery by doctors in Gulf countries despite some patients' perception of decreased attention. The use of EHR assists doctors with recording patient details, including medication and treatment procedures, as well as their outcomes. Based on this study, the authors conclude that widespread EHR implementation is highly recommended, yet specific training should be provided, and the subsequent effect on adoption rates by all users must be evaluated (particularly physicians). The COVID-19 Pandemic showed the great value of EHR in accessing information and consulting patients remotely.
PubMed: 37877127
DOI: 10.3389/fdgth.2023.1252227 -
Frontiers in Digital Health 2023This review focuses on studies about digital health interventions in sub-Saharan Africa. Digital health interventions in sub-Saharan Africa are increasingly adopting... (Review)
Review
BACKGROUND
This review focuses on studies about digital health interventions in sub-Saharan Africa. Digital health interventions in sub-Saharan Africa are increasingly adopting gender-transformative approaches to address factors that derail women's access to maternal healthcare services. However, there remains a paucity of synthesized evidence on gender-transformative digital health programs for maternal healthcare and the corresponding research, program and policy implications. Therefore, this systematic review aims to synthesize evidence of approaches to transformative gender integration in digital health programs (specifically mHealth) for maternal health in sub-Saharan Africa.
METHOD
The following key terms "mobile health", "gender", "maternal health", "sub-Saharan Africa" were used to conduct electronic searches in the following databases: PsycInfo, EMBASE, Medline (OVID), CINAHL, and Global Health databases. The method and results are reported as consistent with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). Data synthesis followed a convergent approach for mixed-method systematic review recommended by the JBI (Joanna Briggs Institute).
RESULTS
Of the 394 studies retrieved from the databases, 11 were included in the review. Out of these, six studies were qualitative in nature, three were randomized control trials, and two were mixed-method studies. Findings show that gender transformative programs addressed one or more of the following categories: (1) gender norms/roles/relations, (2) women's specific needs, (3) causes of gender-based health inequities, (4) ways to transform harmful gender norms, (5) promoting gender equality, (6) progressive changes in power relationships between women and men. The most common mHealth delivery system was text messages via short message service on mobile phones. The majority of mHealth programs for maternal healthcare were focused on reducing unintended pregnancies through the promotion of contraceptive use. The most employed gender transformative approach was a focus on women's specific needs.
CONCLUSION
Findings from gender transformative mHealth programs indicate positive results overall. Those reporting negative results indicated the need for a more explicit focus on gender in mHealth programs. Highlighting gender transformative approaches adds to discussions on how best to promote mHealth for maternal health through a gender transformative lens and provides evidence relevant to policy and research.
SYSTEMATIC REVIEW REGISTRATION
PROSPERO CRD42023346631.
PubMed: 38026837
DOI: 10.3389/fdgth.2023.1263488 -
Digital Health 2023Disparities in cancer care contribute to higher rates of cancer mortality. Online health information would be a resource for cancer patients to obtain knowledge and... (Review)
Review
UNLABELLED
Disparities in cancer care contribute to higher rates of cancer mortality. Online health information would be a resource for cancer patients to obtain knowledge and make health decisions. However, factors that hinder or facilitate online searching behaviours among patients remain unexplored. The current systematic review aims to identify and synthesise evidence of cancer patients' barriers to and facilitators of online health information-seeking behaviours. Electronic databases (PubMed, EMBASE, Scopus) were systematically searched, and a total of 123 full-text studies were reviewed of which 24 met the inclusion criteria. Thematic analysis was performed to identify barriers and facilitators of online health information-seeking behaviours. Seven key themes were identified: (1) socio-demographic characteristics (age, gender, education, income, ethnicity and language), (2) psychosocial aspects (psychological wellbeing, need for a face to face contact, motivation, support), (3) accessibility (Internet access, residence), (4) quality and quantity of information (amount, reliability), (5) cancer stage and symptoms (time since diagnosis, experiencing symptoms), (6) aspects related to healthcare professionals (relationship with the patients and opinions on online health information) and (7) digital literacy (computer skills and literacy). Findings underscore the significance of recognising the multifaceted nature of barriers and facilitators affecting cancer patients' online health information-seeking behaviours. A strong link between these factors and cancer patients' ability to make informed decisions and cope effectively with their diagnosis emerged. Consequently, addressing these barriers and leveraging the identified facilitators could lead to improvements in patient-centred care, ultimately contributing to better healthcare services and informed decision-making for cancer patients. Future research should prioritise exploring strategies for enhancing cancer care accessibility across all stakeholders involved.
REGISTRATION
CRD42023408091.
PubMed: 38107979
DOI: 10.1177/20552076231210663 -
Digital Health 2023To review the evidence about the impact of digital technology on social connectedness among adults with one or more chronic health conditions. (Review)
Review
PURPOSE
To review the evidence about the impact of digital technology on social connectedness among adults with one or more chronic health conditions.
METHODS
PubMed, Embase, Social Sciences, CINAHL, and Compendex were systematically searched for full-text, peer-reviewed empirical evidence published between 2012 and 2023 and reported using the PRISMA flow diagram. Articles were critically appraised applying the Joanna Briggs Institute checklists. Specific data were extracted based on the framework for social identity and technology approaches for health outcomes and then analyzed and synthesized.
RESULTS
Thirty-four studies met study criteria. Evidence showed heterogeneity among research methodology, chronic health conditions, digital technology, and health outcomes. Technology use was influenced by factors such as usability, anonymity, availability, and control. More advanced digital technologies require higher digital literacy and improved accessibility features/modifications. Social support was the most measured aspect of social connectedness. The emotional and informational forms of social support were most reported; instrumental support was the least likely to be delivered. Self-efficacy for using technology was considered in seven articles. Sixteen articles reported health outcomes: 31.2% ( = 5) described mental health outcomes only, 18.8% ( = 3) reported physical health outcomes only, 31.2% ( = 5) detailed both physical and mental health outcomes, whereas 18.8% ( = 3) denoted well-being or quality-of-life outcomes. Most often, health outcomes were positive, with negative outcomes for selected groups also noted.
CONCLUSION
Leveraging digital technology to promote social connectedness has the potential to affect positive health outcomes. Further research is needed to better understand the social integration of technology among populations with different contexts and chronic health conditions to enhance and tailor digital interventions.
PubMed: 37799504
DOI: 10.1177/20552076231204746 -
The Lancet. Digital Health Dec 2023As the number and availability of digital mental health tools increases, patients and clinicians see benefit only when these tools are engaging and well integrated into... (Review)
Review
As the number and availability of digital mental health tools increases, patients and clinicians see benefit only when these tools are engaging and well integrated into care. Digital navigators-ie, members of health-care teams who are dedicated to supporting patient use of digital resources-offer one solution and continue to be piloted in behavioural health; however, little is known about the core features of this position. The aims of this systematic review were to assess how digital navigators are implemented in behavioural health, and to provide a standardised definition of this position. In January, 2023, we conducted a systematic literature search resulting in 48 articles included in this systematic review. Results showed high heterogeneity between four attributes of digital navigators: training specifications, educational background, frequency of communication, and method of communication with patients. Reported effect sizes for depression and anxiety were medium to large, but could not be synthesised due to study heterogeneity and small study sample size. This systematic review was registered with PROSPERO (CRD42023391696). Results suggest that digital navigator support can probably increase access to, engagement with, and clinical integration of digital health technology, with standards for training and defined responsibilities now emerging.
Topics: Humans; Mental Health; Anxiety Disorders; Communication; Biomedical Technology
PubMed: 38000876
DOI: 10.1016/S2589-7500(23)00152-8 -
Digital Health 2023Given the current shortage of blood donors in the USA, researchers have tried to identify different strategies to attract more young people and spread the voice of... (Review)
Review
OBJECTIVES
Given the current shortage of blood donors in the USA, researchers have tried to identify different strategies to attract more young people and spread the voice of donors' needs.
METHODS
A systematic literature review is conducted to investigate the current mobile applications used to track, attract, and retain donors. We also provide some preliminary results of a pilot study, based on a cross-sectional survey of 952 participants (aged 18 to 39), about the willingness of donors to use mobile apps as tools for encouraging blood donation. The data is collected using a 20-item questionnaire, which includes four constructs of the Theory of Planned Behavior to assess the respondents' willingness to donate blood. A range of statistical techniques, including univariate analysis, multivariate analysis, and structural equation modeling, were utilized to analyze the collected data.
RESULTS
The 37 research articles, selected after applying several exclusion criteria, are classified into five main categories. The majority of the research (44.1%) is about using mobile apps to find blood donors and blood centers, followed by publications on using mobile apps to encourage blood donation (26.4%) and to recruit blood donors (14.7%). The remaining studies are about retaining blood donors (8.8%) and using mobile apps for scheduling donations (5.8%). Our pilot case study suggests that 73% of participants have favorable perceptions toward a blood donation mobile app.
CONCLUSIONS
Many efforts have been undertaken to employ mobile apps to make blood donations more convenient and create communities around donating blood. The case study findings suggest a high level of readiness of using mobile apps for blood donation among the younger generation.
PubMed: 37822963
DOI: 10.1177/20552076231203603 -
Digital Health 2024Smartphone apps (apps) are widely recognised as promising tools for improving access to mental healthcare. However, a key challenge is the development of digital... (Review)
Review
OBJECTIVE
Smartphone apps (apps) are widely recognised as promising tools for improving access to mental healthcare. However, a key challenge is the development of digital interventions that are acceptable to end users. Co-production with providers and stakeholders is increasingly positioned as the gold standard for improving uptake, engagement, and healthcare outcomes. Nevertheless, clear guidance around the process of co-production is lacking. The objectives of this review were to: (i) present an overview of the methods and approaches to co-production when designing, producing, and evaluating digital mental health interventions; and (ii) explore the barriers and facilitators affecting co-production in this context.
METHODS
A pre-registered (CRD42023414007) systematic review was completed in accordance with The Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines. Five databases were searched. A co-produced bespoke quality appraisal tool was developed with an expert by experience to assess the quality of the co-production methods and approaches. A narrative synthesis was conducted.
RESULTS
Twenty-six studies across 24 digital mental health interventions met inclusion criteria. App interventions were rarely co-produced with end users throughout all stages of design, development, and evaluation. Co-producing digital mental health interventions added value by creating culturally sensitive and acceptable interventions. Reported challenges included resource issues exacerbated by the digital nature of the intervention, variability across stakeholder suggestions, and power imbalances between stakeholders and researchers.
CONCLUSIONS
Variation in approaches to co-producing digital mental health interventions is evident, with inconsistencies between stakeholder groups involved, stage of involvement, stakeholders' roles and methods employed.
PubMed: 38665886
DOI: 10.1177/20552076241239172 -
Digital Health 2023The development of artificial intelligence (AI), machine learning (ML) and deep learning (DL) has advanced rapidly in the medical field, notably in trauma medicine. We... (Review)
Review
BACKGROUND
The development of artificial intelligence (AI), machine learning (ML) and deep learning (DL) has advanced rapidly in the medical field, notably in trauma medicine. We aimed to systematically appraise the efficacy of AI, ML and DL models for predicting outcomes in trauma triage compared to conventional triage tools.
METHODS
We searched PubMed, MEDLINE, ProQuest, Embase and reference lists for studies published from 1 January 2010 to 9 June 2022. We included studies which analysed the use of AI, ML and DL models for trauma triage in human subjects. Reviews and AI/ML/DL models used for other purposes such as teaching, or diagnosis were excluded. Data was extracted on AI/ML/DL model type, comparison tools, primary outcomes and secondary outcomes. We performed meta-analysis on studies reporting our main outcomes of mortality, hospitalisation and critical care admission.
RESULTS
One hundred and fourteen studies were identified in our search, of which 14 studies were included in the systematic review and 10 were included in the meta-analysis. All studies performed external validation. The best-performing AI/ML/DL models outperformed conventional trauma triage tools for all outcomes in all studies except two. For mortality, the mean area under the receiver operating characteristic (AUROC) score difference between AI/ML/DL models and conventional trauma triage was 0.09, 95% CI (0.02, 0.15), favouring AI/ML/DL models ( = 0.008). The mean AUROC score difference for hospitalisation was 0.11, 95% CI (0.10, 0.13), favouring AI/ML/DL models ( = 0.0001). For critical care admission, the mean AUROC score difference was 0.09, 95% CI (0.08, 0.10) favouring AI/ML/DL models ( = 0.00001).
CONCLUSIONS
This review demonstrates that the predictive ability of AI/ML/DL models is significantly better than conventional trauma triage tools for outcomes of mortality, hospitalisation and critical care admission. However, further research and in particular randomised controlled trials are required to evaluate the clinical and economic impacts of using AI/ML/DL models in trauma medicine.
PubMed: 37822960
DOI: 10.1177/20552076231205736