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Background: As numerous studies highlighted the importance of maintaining proper foot care (FC) behaviours among individuals with diabetes to prevent complications, we sought to assess FC behaviours among patients with diabetes and to identify the factors associated with the practice of diabetic FC. Methods: We used a cross-sectional design and collected data through self-reported questionnaires administered to a sample of 586 patients from five medical centres. We conducted descriptive and inferential analyses to explore the relationships between potential risk and protective factors and FC behaviours. Results: Overall, 429 individuals (73.2%) had good FC behaviours, while 157 (26.8%) displayed poor FC behaviours. Furthermore, we identified eight influencing factors on FC behaviours, including smoking status, the availability of a caregiver, the presence of diabetic foot ulcers, amputation history, FC knowledge, subjective norms in diabetes self-care behaviour, diabetes-related stress, and quality of life index values. The logistic regression analysis showed that current smokers were 60% less likely to practice good FC compared to non-smokers (odds ratio (OR) = 0.40; 95%; confidence interval (CI) = 0.22-0.73). Having a caregiver decreased the likelihood of practicing good FC by 50% (OR = 0.52; 95% CI = 0.33-0.84), while having diabetic foot ulcers doubled it (OR = 2.65; 95% CI = 1.26-5.54). Additionally, more FC knowledge increased the likelihood by 20% (OR = 1.21; 95% CI = 1.10-1.33), and higher diabetes-related stress increased it by 1.03 times (OR = 1.03; 95% CI = 1.02-1.05). Conclusions: Our findings underscore the interplay of various factors influencing FC behaviours among individuals with diabetes and call for targeted interventions and tailored strategies to improve FC practices in this vulnerable population.
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Diabetes Mellitus Tipo 2 , Pé Diabético , Humanos , Estudos Transversais , Masculino , Feminino , Pé Diabético/psicologia , Pessoa de Meia-Idade , Diabetes Mellitus Tipo 2/terapia , Diabetes Mellitus Tipo 2/psicologia , Idoso , Autocuidado , Inquéritos e Questionários , Comportamentos Relacionados com a Saúde , Adulto , Conhecimentos, Atitudes e Prática em Saúde , Fatores de RiscoRESUMO
BACKGROUND: To investigate the impacts of the COVID-19 pandemic on the health workforce, we aimed to develop a framework that synergizes natural language processing (NLP) techniques and human-generated analysis to reduce, organize, classify, and analyze a vast volume of publicly available news articles to complement scientific literature and support strategic policy dialogue, advocacy, and decision-making. OBJECTIVE: This study aimed to explore the possibility of systematically scanning intelligence from media that are usually not captured or best gathered through structured academic channels and inform on the impacts of the COVID-19 pandemic on the health workforce, contributing factors to the pervasiveness of the impacts, and policy responses, as depicted in publicly available news articles. Our focus was to investigate the impacts of the COVID-19 pandemic and, concurrently, assess the feasibility of gathering health workforce insights from open sources rapidly. METHODS: We conducted an NLP-assisted media content analysis of open-source news coverage on the COVID-19 pandemic published between January 2020 and June 2022. A data set of 3,299,158 English news articles on the COVID-19 pandemic was extracted from the World Health Organization Epidemic Intelligence through Open Sources (EIOS) system. The data preparation phase included developing rules-based classification, fine-tuning an NLP summarization model, and further data processing. Following relevancy evaluation, a deductive-inductive approach was used for the analysis of the summarizations. This included data extraction, inductive coding, and theme grouping. RESULTS: After processing and classifying the initial data set comprising 3,299,158 news articles and reports, a data set of 5131 articles with 3,007,693 words was devised. The NLP summarization model allowed for a reduction in the length of each article resulting in 496,209 words that facilitated agile analysis performed by humans. Media content analysis yielded results in 3 sections: areas of COVID-19 impacts and their pervasiveness, contributing factors to COVID-19-related impacts, and responses to the impacts. The results suggest that insufficient remuneration and compensation packages have been key disruptors for the health workforce during the COVID-19 pandemic, leading to industrial actions and mental health burdens. Shortages of personal protective equipment and occupational risks have increased infection and death risks, particularly at the pandemic's onset. Workload and staff shortages became a growing disruption as the pandemic progressed. CONCLUSIONS: This study demonstrates the capacity of artificial intelligence-assisted media content analysis applied to open-source news articles and reports concerning the health workforce. Adequate remuneration packages and personal protective equipment supplies should be prioritized as preventive measures to reduce the initial impact of future pandemics on the health workforce. Interventions aimed at lessening the emotional toll and workload need to be formulated as a part of reactive measures, enhancing the efficiency and maintainability of health delivery during a pandemic.
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OBJECTIVE: To compare the clinical and cost effectiveness of the Collaborative Model of Care between Orthopaedics and Allied Healthcare Professionals (CONNACT), a community-based, stratified, multidisciplinary intervention consisting of exercise, education, psychological and nutrition delivered through a chronic care model to usual hospital care in adults with knee osteoarthritis (OA). METHODS: Pragmatic, parallel-arm, single-blinded superiority RCT trial. Community-dwelling, ambulant adults with knee OA (Kellgren-Lawrence grade > 1; Knee Injury and OA Outcome Score (KOOS4) ≤75) were enrolled. Primary outcome was KOOS4 at 12-months; secondary outcomes included: quality of life, physical performance measures, symptom satisfaction, psychological outcomes, dietary habits, and global perceived effect. Intention-to-treat analysis using generalized linear model (GLM) and regression modeling were conducted. Economic evaluation through a societal approach was embedded. RESULTS: 110 participants (55 control, 55 intervention) were randomized. No between-group difference found for the primary outcome (MD [95%CI]: -1.86 [-9.11. 5.38]), although both groups demonstrated within-group improvement over 12-months. Among the secondary outcomes, the CONNACT group demonstrated superior dietary change (12 months) and physical performance measures (3 months), and global perceived effect (6 months). While there was no between-group difference in total cost, significant productivity gains (reduced indirect cost) were seen in the CONNACT group. CONCLUSION: CONNACT was not superior to usual care at 1 year. Further efforts are needed to understand the underlying contextual and implementation factors in order to further improve and refine such community-based, stratified care models moving forward. TRIAL REGISTRATION: Clinicaltrials.gov Identifier: NCT03809975. Registered January 18, 2019. https://clinicaltrials.gov/ct2/show/NCT03809975.
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Análise Custo-Benefício , Osteoartrite do Joelho , Humanos , Feminino , Masculino , Osteoartrite do Joelho/terapia , Osteoartrite do Joelho/reabilitação , Pessoa de Meia-Idade , Idoso , Pessoal Técnico de Saúde , Método Simples-Cego , Ortopedia , Qualidade de Vida , Equipe de Assistência ao Paciente , Terapia por Exercício/métodosRESUMO
Objective: Sleep quality is a crucial concern, particularly among youth. The integration of health coaching with question-answering (QA) systems presents the potential to foster behavioural changes and enhance health outcomes. This study proposes a novel human-AI sleep coaching model, combining health coaching by peers and a QA system, and assesses its feasibility and efficacy in improving university students' sleep quality. Methods: In a four-week unblinded pilot randomised controlled trial, 59 university students (mean age: 21.9; 64% males) were randomly assigned to the intervention (health coaching and QA system; n = 30) or the control conditions (QA system; n = 29). Outcomes included efficacy of the intervention on sleep quality (Pittsburgh Sleep Quality Index; PSQI), objective and self-reported sleep measures (obtained from Fitbit and sleep diaries) and feasibility of the study procedures and the intervention. Results: Analysis revealed no significant differences in sleep quality (PSQI) between intervention and control groups (adjusted mean difference = -0.51, 95% CI: [-1.55-0.77], p = 0.40). The intervention group demonstrated significant improvements in Fitbit measures of total sleep time (adjusted mean difference = 32.5, 95% CI: [5.9-59.1], p = 0.02) and time in bed (adjusted mean difference = 32.3, 95% CI: [2.7-61.9], p = 0.03) compared to the control group, although other sleep measures were insignificant. Adherence was high, with the majority of the intervention group attending all health coaching sessions. Most participants completed baseline and post-intervention self-report measures, all diary entries, and consistently wore Fitbits during sleep. Conclusions: The proposed model showed improvements in specific sleep measures for university students and the feasibility of the study procedures and intervention. Future research may extend the intervention period to see substantive sleep quality improvements.
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BACKGROUND: Health apps are increasingly recognized as crucial tools for enhancing health care delivery. Many countries, particularly those in sub-Saharan Africa, can substantially benefit from using health apps to support self-management and thus help to achieve universal health coverage and the third sustainable development goal. However, most health apps published in app stores are of unknown or poor quality, which poses a risk to patient safety. Regulatory standards and guidance can help address this risk and promote patient safety. OBJECTIVE: This review aims to assess the regulatory standards and guidance for health apps supporting evidence-based best practices in sub-Saharan Africa with a focus on self-management. METHODS: A methodological framework for scoping reviews was applied. A search strategy was built and applied across the following databases, gray literature sources, and institutional websites: PubMed, Scopus, World Health Organization (WHO) African Index Medicus, OpenGrey, WHO Regional Office for Africa Library, ICTworks, WHO Directory of eHealth policies, HIS Strengthening Resource Center, International Telecommunication Union, Ministry of Health websites, and Google. The search covered the period between January 2005 and January 2024. The findings were analyzed using a deductive descriptive content analysis. The policy analysis framework was adapted and used to organize the findings. The Reporting Items for Stakeholder Analysis tool guided the identification and mapping of key stakeholders based on their roles in regulating health apps for self-management. RESULTS: The study included 49 documents from 31 sub-Saharan African countries. While all the documents were relevant for stakeholder identification and mapping, only 3 regulatory standards and guidance contained relevant information on regulation of health apps. These standards and guidance primarily aimed to build mutual trust; promote integration, inclusion, and equitable access to services; and address implementation issues and poor coordination. They provided guidance on systems quality, software acquisition and maintenance, security measures, data exchange, interoperability and integration, involvement of relevant stakeholders, and equitable access to services. To enhance implementation, the standards highlight that legal authority, coordination of activities, building capacity, and monitoring and evaluation are required. A number of stakeholders, including governments, regulatory bodies, funders, intergovernmental and nongovernmental organizations, academia, and the health care community, were identified to play key roles in regulating health apps. CONCLUSIONS: Health apps have huge potential to support self-management in sub-Saharan Africa, but the lack of regulatory standards and guidance constitutes a major barrier. Hence, for these apps to be safely and effectively integrated into health care, more attention should be given to regulation. Learning from countries with effective regulations can help sub-Saharan Africa build a more robust and responsive regulatory system, ensuring the safe and beneficial use of health apps across the region. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2018-025714.
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Autogestão , Humanos , Bases de Dados Factuais , Governo , Literatura Cinzenta , África SubsaarianaRESUMO
ABSTRACT: With the rise of generative artificial intelligence (AI) and AI-powered chatbots, the landscape of medicine and healthcare is on the brink of significant transformation. This perspective delves into the prospective influence of AI on medical education, residency training and the continuing education of attending physicians or consultants. We begin by highlighting the constraints of the current education model, challenges in limited faculty, uniformity amidst burgeoning medical knowledge and the limitations in 'traditional' linear knowledge acquisition. We introduce 'AI-assisted' and 'AI-integrated' paradigms for medical education and physician training, targeting a more universal, accessible, high-quality and interconnected educational journey. We differentiate between essential knowledge for all physicians, specialised insights for clinician-scientists and mastery-level proficiency for clinician-computer scientists. With the transformative potential of AI in healthcare and service delivery, it is poised to reshape the pedagogy of medical education and residency training.
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Educação Médica , Médicos , Humanos , Inteligência Artificial , Estudos Prospectivos , Educação ContinuadaRESUMO
BACKGROUND: Depression is a common issue among university students and has been particularly exacerbated during the COVID-19 pandemic. However, limited research has specifically focused on depression among university entrants. OBJECTIVES: This study aimed to determine the prevalence of depression severity and identify associated factors during different phases of the COVID-19 pandemic using health screening questionnaires completed by matriculated university students in Singapore. METHODS: A repeated cross-sectional study was conducted at a public university in Singapore. Data from health screening questionnaires administered in 2020 and 2021, involving 15,630 newly enrolled university students, were analyzed. The questionnaires covered students' sociodemographic information, physical health status, own and family medical history, lifestyle behaviours, and the Patient Health Questionnaire (PHQ-9). The PHQ-9 was used to measure the severity of depressive symptoms, categorizing into moderate to severe depressive symptoms (MSDS), mild depressive symptoms (MDS), or no depressive symptom (NDS). Multinomial logistic regression was used to assess the sociodemographic, physical and behavioural correlates of depression. RESULTS: The prevalence of MSDS was 1% in both 2020 and 2021, while the rates for MDS were 1.93% in 2020 and 1.64% in 2021. In the 2020 cohort, male freshmen who reported better health had a lower likelihood of experiencing depression. Conversely, students of Malay ethnicity, those majoring in Engineering, those with multiple chronic diseases, monthly alcohol consumers, current smokers, and those with a family history of mental disorder had a higher likelihood of experiencing depression. Moreover, students who lived on-campus in the 2021 cohort were less likely to experience depression than those living off-campus. However, the associations between academic majors, alcohol consumption, and smoking with depression were not significant in the 2021 cohort. CONCLUSIONS: This study reported a low prevalence of both MSDS and MDS among university entrants in Singapore. The study further identified three categories of factors associated with depression: sociodemographic, physical, and behavioural. This study suggests policy interventions to enhance targeted social support that address each student group's specific requirements and susceptibilities. A more extensive and comprehensive study is warranted to assess the changes in student mental health status post-COVID-19 pandemic.
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COVID-19 , Humanos , Masculino , COVID-19/epidemiologia , Depressão/epidemiologia , Estudos Transversais , Prevalência , Universidades , Pandemias , Singapura/epidemiologia , Estudantes/psicologiaRESUMO
BACKGROUND: Conversational agents (CAs), or chatbots, are computer programs that simulate conversations with humans. The use of CAs in health care settings is recent and rapidly increasing, which often translates to poor reporting of the CA development and evaluation processes and unreliable research findings. We developed and published a conceptual framework, designing, developing, evaluating, and implementing a smartphone-delivered, rule-based conversational agent (DISCOVER), consisting of 3 iterative stages of CA design, development, and evaluation and implementation, complemented by 2 cross-cutting themes (user-centered design and data privacy and security). OBJECTIVE: This study aims to perform in-depth, semistructured interviews with multidisciplinary experts in health care CAs to share their views on the definition and classification of health care CAs and evaluate and validate the DISCOVER conceptual framework. METHODS: We conducted one-on-one semistructured interviews via Zoom (Zoom Video Communications) with 12 multidisciplinary CA experts using an interview guide based on our framework. The interviews were audio recorded, transcribed by the research team, and analyzed using thematic analysis. RESULTS: Following participants' input, we defined CAs as digital interfaces that use natural language to engage in a synchronous dialogue using ≥1 communication modality, such as text, voice, images, or video. CAs were classified by 13 categories: response generation method, input and output modalities, CA purpose, deployment platform, CA development modality, appearance, length of interaction, type of CA-user interaction, dialogue initiation, communication style, CA personality, human support, and type of health care intervention. Experts considered that the conceptual framework could be adapted for artificial intelligence-based CAs. However, despite recent advances in artificial intelligence, including large language models, the technology is not able to ensure safety and reliability in health care settings. Finally, aligned with participants' feedback, we present an updated iteration of the conceptual framework for health care conversational agents (CHAT) with key considerations for CA design, development, and evaluation and implementation, complemented by 3 cross-cutting themes: ethics, user involvement, and data privacy and security. CONCLUSIONS: We present an expanded, validated CHAT and aim at guiding researchers from a variety of backgrounds and with different levels of expertise in the design, development, and evaluation and implementation of rule-based CAs in health care settings.
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Inteligência Artificial , Voz , Humanos , Reprodutibilidade dos Testes , Comunicação , IdiomaRESUMO
BACKGROUND: Diabetic foot ulcers (DFUs) cause significant morbidity affecting 19% to 34% of people living with diabetes mellitus. DFUs not only impair quality of life but may also result in limb loss and mortality. Patient education has been advocated to raise awareness of proper foot self-care and the necessity of seeking assistance when a foot wound occurs. Modern technologies, including mobile health (mHealth) interventions such as health apps, bring the potential for more cost-effective and scalable interventions. OBJECTIVE: This study aims to examine the feasibility and usability of a newly developed mHealth app called Well Feet, which is a diabetes and foot care education app for individuals at risk of developing DFU. METHODS: Well Feet was developed using an evidence-based and expert panel cocreation approach to deliver educational content available in 3 languages (ie, English, Chinese, and Malay) via animation videos and a range of additional features, including adaptive learning. A nonrandomized, single-arm feasibility study using a mixed methods approach with a series of validated questionnaires and focus group discussions will be conducted. In total, 40 patients and carers will be recruited from a tertiary hospital diabetes clinic to receive a 1-month mHealth intervention. The primary outcomes are the usability of the app and a qualitative perspective on user experience. Secondary outcomes include changes in foot care knowledge, self-management behaviors, and quality of life. RESULTS: Patient recruitment began in July 2023, and the intervention and data collection will be completed by the end of September 2023. This study has been approved by National Healthcare Group Domain Specific Review Board (2022/00614) on February 10, 2023. The expected results will be published in spring 2024. CONCLUSIONS: Through this feasibility study, the Well Feet DFU education app will undergo a comprehensive quantitative and qualitative evaluation of its usability and acceptance for future improvement in its design. With local contextualization, cultural adaptation, and its multilingual functionality, the app addresses a critical aspect of DFU health education and self-management in a multiethnic population. Findings from this study will refine and enhance the features of the app based on user feedback and shape the procedural framework for a subsequent randomized controlled trial to assess the effectiveness of Well Feet. TRIAL REGISTRATION: ClinicalTrials.gov NCT05564728; https://clinicaltrials.gov/study/NCT05564728. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/52036.
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Objective: Wound image analysis tools hold promise in helping patients to monitor their wounds. We aim to perform a novel feasibility study on the efficacy of a patient-owned wound surveillance system for diabetic foot ulcer (DFU) care. Methods: This two-institutional, prospective, single-arm pilot study examined patients with DFU. An artificial intelligence-enabled image analysis app calculating the wound surface area was installed and patients or caregivers were instructed to take pictures of wounds during dressing changes. Patients were followed until wound deterioration, wound healing, or wound stability at 6 months occurred and the outcomes of interest included study adherence, algorithm performance, and user experience. Results: Between January 2021 and December 2021, 39 patients were enrolled in the study, with a mean age of 61.6 ± 8.6 years, and 69% (n = 27) of subjects were male. All patients had documented diabetes and 85% (n = 33) of them had peripheral arterial disease. A mean follow-up for those completing the study was 12.0 ± 8.5 weeks. At the conclusion of the study, 80% of patients (n = 20) had primary wound healing whilst 20% (n = 5) had wound deterioration. The study completion rate was 64% (n = 25). Usage of the app for surveillance of DFU healing, as compared to physician evaluation, yielded a sensitivity of 100%, specificity of 20%, positive predictive value of 83%, and negative predictive value of 100%. Of those who provided user experience feedback, 59% (n = 10) felt the app was easy to use, 47% (n = 8) would recommend the wound analysis app to others but only 6% would pay for the app out of pocket (n = 1). Conclusion: Implementation of a patient-owned wound surveillance system is feasible. Most patients were able to effectively monitor wounds using a smartphone app-based solution. The image analysis algorithm demonstrates strong performance in identifying wound healing and is capable of detecting deterioration prior to interval evaluation by a physician. Patients generally found the app easy to use but were reluctant to pay for the use of the solution out of pocket.
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Digital health technologies have been in use for many years in a wide spectrum of healthcare scenarios. This narrative review outlines the current use and the future strategies and significance of digital health technologies in modern healthcare applications. It covers the current state of the scientific field (delineating major strengths, limitations, and applications) and envisions the future impact of relevant emerging key technologies. Furthermore, we attempt to provide recommendations for innovative approaches that would accelerate and benefit the research, translation and utilization of digital health technologies.
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Tecnologia Biomédica , Atenção à SaúdeRESUMO
In low- and middle-income countries (LMICs), the fields of medicine and public health grapple with numerous challenges that continue to hinder patients' access to healthcare services. ChatGPT, a publicly accessible chatbot, has emerged as a potential tool in aiding public health efforts in LMICs. This viewpoint details the potential benefits of employing ChatGPT in LMICs to improve medicine and public health encompassing a broad spectrum of domains ranging from health literacy, screening, triaging, remote healthcare support, mental health support, multilingual capabilities, healthcare communication and documentation, medical training and education, and support for healthcare professionals. Additionally, we also share potential concerns and limitations associated with the use of ChatGPT and provide a balanced discussion on the opportunities and challenges of using ChatGPT in LMICs.
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BACKGROUND: Type 2 diabetes (T2D) is a growing global health concern, including in Singapore. Diabetes education programs have been shown to be effective in improving health outcomes and diabetes self-management skills. Mobile health apps have emerged as useful tools for diabetes education; however, their use and acceptance by the target population remain inconsistent. Therefore, end-user participation in the design and development of a mobile health app is crucial for designing an acceptable app that can improve outcomes for populations with a chronic disease. OBJECTIVE: The objective of this study was to apply an end-user participatory approach to co-design a diabetes education app prototype for people living with T2D by exploring their perceptions, acceptance, and usability of an app prototype, as well as their diabetes experience and perspectives on digital diabetes education. METHODS: A total of 8 people with T2D, who were recruited from diabetes management Facebook groups, participated in 4 web-based surveys via Qualtrics and 2 structured interviews via Zoom (Zoom Video Communications, Inc) between August 20, 2021, and January 28, 2022. Descriptive statistics and thematic analyses of the discussion and iterative feedback on the app prototype were used to assess the participants' perceptions of living with T2D, attitudes toward digital diabetes education, and acceptance of the prototype. RESULTS: Analyses of the surveys and interview data revealed 3 themes: challenges of living with T2D; validation, acceptability, and usability of the diabetes education app prototype; and perspectives on digital diabetes education. In the first theme, participants highlighted the importance of solitary accountability, translating knowledge into practice, and developing pragmatic self-consciousness. The second theme indicated that the diabetes education app prototype was acceptable, with information and appearance being key; revealed ambivalent and polarized opinions toward the chatbot; and confirmed potential impact of the app on diabetes self-management skills and practice. The third theme comprised the necessity of using a variety of information-seeking strategies and recommendations for desired content and app qualities, including accessibility, adaptability, autonomy, evidence-based design and content, gamification, guidance, integration, personalization, and up-to-date content. The findings were used to reiterate the app design. CONCLUSIONS: Despite a small sample size, the study demonstrated the feasibility of engaging and empowering people living with T2D to consider digital therapeutics for diabetes self-management skills and practice. Participants gave rather positive feedback on the design and content of the app prototype, with some recommendations for improvements. The findings suggest that incorporating end-user feedback into app design can lead to the creation of feasible and acceptable tools for diabetes education, potentially improving outcomes for populations with a chronic disease. Further research is needed to test the impact of the refined diabetes education app prototype on diabetes self-management skills and practice and quality of life.
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BACKGROUND: Mental disorders cause substantial health-related burden worldwide. Mobile health interventions are increasingly being used to promote mental health and well-being, as they could improve access to treatment and reduce associated costs. Behavior change is an important feature of interventions aimed at improving mental health and well-being. There is a need to discern the active components that can promote behavior change in such interventions and ultimately improve users' mental health. OBJECTIVE: This study systematically identified mental health conversational agents (CAs) currently available in app stores and assessed the behavior change techniques (BCTs) used. We further described their main features, technical aspects, and quality in terms of engagement, functionality, esthetics, and information using the Mobile Application Rating Scale. METHODS: The search, selection, and assessment of apps were adapted from a systematic review methodology and included a search, 2 rounds of selection, and an evaluation following predefined criteria. We conducted a systematic app search of Apple's App Store and Google Play using 42matters. Apps with CAs in English that uploaded or updated from January 2020 and provided interventions aimed at improving mental health and well-being and the assessment or management of mental disorders were tested by at least 2 reviewers. The BCT taxonomy v1, a comprehensive list of 93 BCTs, was used to identify the specific behavior change components in CAs. RESULTS: We found 18 app-based mental health CAs. Most CAs had <1000 user ratings on both app stores (12/18, 67%) and targeted several conditions such as stress, anxiety, and depression (13/18, 72%). All CAs addressed >1 mental disorder. Most CAs (14/18, 78%) used cognitive behavioral therapy (CBT). Half (9/18, 50%) of the CAs identified were rule based (ie, only offered predetermined answers) and the other half (9/18, 50%) were artificial intelligence enhanced (ie, included open-ended questions). CAs used 48 different BCTs and included on average 15 (SD 8.77; range 4-30) BCTs. The most common BCTs were 3.3 "Social support (emotional)," 4.1 "Instructions for how to perform a behavior," 11.2 "Reduce negative emotions," and 6.1 "Demonstration of the behavior." One-third (5/14, 36%) of the CAs claiming to be CBT based did not include core CBT concepts. CONCLUSIONS: Mental health CAs mostly targeted various mental health issues such as stress, anxiety, and depression, reflecting a broad intervention focus. The most common BCTs identified serve to promote the self-management of mental disorders with few therapeutic elements. CA developers should consider the quality of information, user confidentiality, access, and emergency management when designing mental health CAs. Future research should assess the role of artificial intelligence in promoting behavior change within CAs and determine the choice of BCTs in evidence-based psychotherapies to enable systematic, consistent, and transparent development and evaluation of effective digital mental health interventions.
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Aplicativos Móveis , Autogestão , Telemedicina , Humanos , Saúde Mental , Inteligência Artificial , Terapia Comportamental/métodos , Autogestão/métodos , Telemedicina/métodosRESUMO
Objective: Digital health has recently gained a foothold in monitoring and improving diabetes care. We aim to explore the views of patients, carers and healthcare providers (HCPs) regarding the use of a novel patient-owned wound surveillance application as part of outpatient management of patients with diabetic foot ulcers (DFUs). Methods: Semi-structured online interviews were conducted with patients, carers and HCPs in wound care for DFUs. The participants were recruited from a primary care polyclinic network and two tertiary hospitals in Singapore, within the same healthcare cluster. Purposive maximum variation sampling was used to select participants with differing attributes to ensure heterogeneity. Common themes relating to the wound imaging app were captured. Results: A total of 20 patients, 5 carers and 20 HCPs participated in the qualitative study. None of the participants have used a wound imaging app before. Regarding a patient-owned wound surveillance app, all were open and receptive to the system and workflow for use in DFU care. Four major themes emerged from patients and carers: (1) technology, (2) application features and usability, (3) feasibility of using the wound imaging application and (4) logistics of care. Four major themes were identified from HCPs: (1) attitudes towards wound imaging app, (2) preferences regarding functionality, (3) perceived challenges for patients/carers and (4) perceived barriers for HCPs. Conclusion: Our study highlighted several barriers and facilitators from patients, carers and HCPs regarding the use of a patient-owned wound surveillance app. These findings demonstrate the potential of digital health and areas to improve and tailor a DFU wound app suitable for implementation in the local population.
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Background: Non-communicable diseases (NCDs) and common mental disorders (CMDs) are the leading causes of death and disability worldwide. Lifestyle interventions via mobile apps and conversational agents present themselves as low-cost, scalable solutions to prevent these conditions. This paper describes the rationale for, and development of, "LvL UP 1.0â³, a smartphone-based lifestyle intervention aimed at preventing NCDs and CMDs. Materials and Methods: A multidisciplinary team led the intervention design process of LvL UP 1.0, involving four phases: (i) preliminary research (stakeholder consultations, systematic market reviews), (ii) selecting intervention components and developing the conceptual model, (iii) whiteboarding and prototype design, and (iv) testing and refinement. The Multiphase Optimization Strategy and the UK Medical Research Council framework for developing and evaluating complex interventions were used to guide the intervention development. Results: Preliminary research highlighted the importance of targeting holistic wellbeing (i.e., both physical and mental health). Accordingly, the first version of LvL UP features a scalable, smartphone-based, and conversational agent-delivered holistic lifestyle intervention built around three pillars: Move More (physical activity), Eat Well (nutrition and healthy eating), and Stress Less (emotional regulation and wellbeing). Intervention components include health literacy and psychoeducational coaching sessions, daily "Life Hacks" (healthy activity suggestions), breathing exercises, and journaling. In addition to the intervention components, formative research also stressed the need to introduce engagement-specific components to maximise uptake and long-term use. LvL UP includes a motivational interviewing and storytelling approach to deliver the coaching sessions, as well as progress feedback and gamification. Offline materials are also offered to allow users access to essential intervention content without needing a mobile device. Conclusions: The development process of LvL UP 1.0 led to an evidence-based and user-informed smartphone-based intervention aimed at preventing NCDs and CMDs. LvL UP is designed to be a scalable, engaging, prevention-oriented, holistic intervention for adults at risk of NCDs and CMDs. A feasibility study, and subsequent optimisation and randomised-controlled trials are planned to further refine the intervention and establish effectiveness. The development process described here may prove helpful to other intervention developers.
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BACKGROUND: Digital education has expanded since the COVID-19 pandemic began. A substantial amount of recent data on how students learn has become available for learning analytics (LA). LA denotes the "measurement, collection, analysis, and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs." OBJECTIVE: This scoping review aimed to examine the use of LA in health care professions education and propose a framework for the LA life cycle. METHODS: We performed a comprehensive literature search of 10 databases: MEDLINE, Embase, Web of Science, ERIC, Cochrane Library, PsycINFO, CINAHL, ICTP, Scopus, and IEEE Explore. In total, 6 reviewers worked in pairs and performed title, abstract, and full-text screening. We resolved disagreements on study selection by consensus and discussion with other reviewers. We included papers if they met the following criteria: papers on health care professions education, papers on digital education, and papers that collected LA data from any type of digital education platform. RESULTS: We retrieved 1238 papers, of which 65 met the inclusion criteria. From those papers, we extracted some typical characteristics of the LA process and proposed a framework for the LA life cycle, including digital education content creation, data collection, data analytics, and the purposes of LA. Assignment materials were the most popular type of digital education content (47/65, 72%), whereas the most commonly collected data types were the number of connections to the learning materials (53/65, 82%). Descriptive statistics was mostly used in data analytics in 89% (58/65) of studies. Finally, among the purposes for LA, understanding learners' interactions with the digital education platform was cited most often in 86% (56/65) of papers and understanding the relationship between interactions and student performance was cited in 63% (41/65) of papers. Far less common were the purposes of optimizing learning: the provision of at-risk intervention, feedback, and adaptive learning was found in 11, 5, and 3 papers, respectively. CONCLUSIONS: We identified gaps for each of the 4 components of the LA life cycle, with the lack of an iterative approach while designing courses for health care professions being the most prevalent. We identified only 1 instance in which the authors used knowledge from a previous course to improve the next course. Only 2 studies reported that LA was used to detect at-risk students during the course's run, compared with the overwhelming majority of other studies in which data analysis was performed only after the course was completed.
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COVID-19 , Pandemias , Humanos , COVID-19/prevenção & controle , Aprendizagem , Atenção à Saúde , Poder PsicológicoRESUMO
OBJECTIVE: Venous leg ulcers (VLUs) are both chronic and recurrent. The treatment of such ulcers often require multiple outpatient visits and dressing changes. Several reports on the costs of treating such VLUs have been reported in the west. We prospectively evaluated the clinical and economic burden of VLUs in a population of Asian patients in the tropics. METHODS: Patients from a prospective two-center study conducted at two tertiary hospitals in Singapore, as a part of the Wound Care Innovation in the Tropics program, between August 2018 and September 2021 were recruited. The patients were followed up for 12 weeks (visit 1 to visit 12), until index ulcer healing, death, or lost to follow-up (whichever came first). These patients were then followed up 12 weeks later to determine the longer term outcome of the wound (healed, recurrence, remained unhealed). The itemized costs derived from the medical service were retrieved from the relevant departments of the study sites. The patients' health-related quality of life was assessed at baseline and the last visit of the 12-week follow-up period (or until index ulcer healing), using the official Singapore version of the EuroQol five-dimension-5L questionnaire, which also includes a visual analog scale (EQ-VAS). RESULTS: A total of 116 patients were enrolled; 63% were men, and the mean patient age was 64.7 years. Of the 116 patients, 85 (73%) had a healed ulcer at 24 weeks (mean duration to ulcer healing, 49 days), and 11 (12.9%) had experienced ulcer recurrence within the study period. Within the 6-month follow-up period, the mean direct healthcare cost per patient was USD$1998. The patients with healed ulcers had significantly lower costs per patient compared with those with unhealed ulcers (USD$1713 vs USD$2780). Regarding health-related quality of life, 71% of the patients had a lower quality of life at baseline, which had improved at 12 weeks of follow-up, with only 58% of the patients reported to have a lower quality of life. Also, the patients with healed ulcers scored higher for both utilities (societal preference weights) and EQ-VAS at follow-up (P < .001). In contrast, patients with unhealed ulcers only scored higher EQ-VAS at follow-up (P = .003). CONCLUSIONS: The findings from this exploratory study provide information on the clinical, quality of life, and economic burden of VLUs in an Asian population and suggest the importance of healing VLUs to reduce the effects on patients. The present study provides data as a basis for economic evaluation as a consideration for the treatment of VLUs.
Assuntos
Úlcera da Perna , Úlcera Varicosa , Masculino , Humanos , Pessoa de Meia-Idade , Feminino , Estudos Prospectivos , Úlcera , Qualidade de Vida , Estresse Financeiro , Úlcera Varicosa/terapia , Úlcera Varicosa/tratamento farmacológico , Úlcera da Perna/terapiaRESUMO
BACKGROUND: Knee osteoarthritis (OA) is a leading cause of global disability. The understanding of the role of psychosocial factors in knee OA outcomes is still evolving particularly in an Asian context. The primary aim of this study is to explore psychosocial factors that prognosticate short and long-term clinical outcomes, productivity, and healthcare utilization in patients with knee OA. Secondary aims are to explore the mediation and directional relationships and the role it plays in predicting the discordance between self-reported measures (SRM), physical-performance measures (PPMs) and objective clinical parameters. METHODS: A multi-centre prospective cohort study of community ambulant knee OA patients seeking treatment in the tertiary healthcare institutions in Singapore will be conducted. Patients with secondary arthritis, significant cognitive impairment, severe medical comorbidities or previous knee arthroplasty will be excluded. Primary clinical outcome measure is the Knee injury and OA Outcome Score-12 (KOOS-12). Baseline characteristics include sociodemographic status, arthritis status including symptom duration and radiographic severity, comorbidities and functional status through Charlson Comorbidities Index (CCI), Barthel Index (BI) and Parker Mobility Score (PMS). Psychosocial variables include social support, kinesiophobia, negative affect, self-efficacy, injustice, chronic illness shame and the built environment. Clinical outcomes include quality of life, physical performance, global assessment, satisfaction and physical activity levels. Productivity and healthcare utilization will be assessed by a modified OA Cost and Consequences Questionnaire (OCC-Q) and the Work Productivity and Activity Impairment Questionnaire (WPAI). Variables will be collected at baseline, 4, 12 months and yearly thereafter. Regression, mediation and structural equation modelling will be used for analysis. DISCUSSION: Results will allow contextualization, identification, and phenotyping of the critical (and potentially modifiable) psychosocial parameters that predict positive clinical outcomes in the OA population to guide optimization and refinement of healthcare and community. This will facilitate: 1. identification of high-risk knee OA subpopulations that will likely experience poor outcomes and 2. formulation of targeted multidisciplinary comprehensive approaches to address these psychosocial factors to optimize non-surgical treatment care, maximize functional outcomes and create more value-based care model for knee OA. ETHICS AND DISSEMINATION: The study has been registered under clinicaltrials.gov registry (Identifier: NCT04942236).