Attrition in Conversational Agent-Delivered Mental Health Interventions: Systematic Review and Meta-Analysis.

BACKGROUND: Conversational agents (CAs) or chatbots are computer programs that mimic human conversation. They have the potential to improve access to mental health interventions through automated, scalable, and personalized delivery of psychotherapeutic content. However, digital health interventions, including those delivered by CAs, often have high attrition rates. Identifying the factors associated with attrition is critical to improving future clinical trials. OBJECTIVE: This review aims to estimate the overall and differential rates of attrition in CA-delivered mental health interventions (CA interventions), evaluate the impact of study design and intervention-related aspects on attrition, and describe study design features aimed at reducing or mitigating study attrition. METHODS: We searched PubMed, Embase (Ovid), PsycINFO (Ovid), Cochrane Central Register of Controlled Trials, and Web of Science, and conducted a gray literature search on Google Scholar in June 2022. We included randomized controlled trials that compared CA interventions against control groups and excluded studies that lasted for 1 session only and used Wizard of Oz interventions. We also assessed the risk of bias in the included studies using the Cochrane Risk of Bias Tool 2.0. Random-effects proportional meta-analysis was applied to calculate the pooled dropout rates in the intervention groups. Random-effects meta-analysis was used to compare the attrition rate in the intervention groups with that in the control groups. We used a narrative review to summarize the findings. RESULTS: The systematic search retrieved 4566 records from peer-reviewed databases and citation searches, of which 41 (0.90%) randomized controlled trials met the inclusion criteria. The meta-analytic overall attrition rate in the intervention group was 21.84% (95% CI 16.74%-27.36%; I2=94%). Short-term studies that lasted ≤8 weeks showed a lower attrition rate (18.05%, 95% CI 9.91%- 27.76%; I2=94.6%) than long-term studies that lasted >8 weeks (26.59%, 95% CI 20.09%-33.63%; I2=93.89%). Intervention group participants were more likely to attrit than control group participants for short-term (log odds ratio 1.22, 95% CI 0.99-1.50; I2=21.89%) and long-term studies (log odds ratio 1.33, 95% CI 1.08-1.65; I2=49.43%). Intervention-related characteristics associated with higher attrition include stand-alone CA interventions without human support, not having a symptom tracker feature, no visual representation of the CA, and comparing CA interventions with waitlist controls. No participant-level factor reliably predicted attrition. CONCLUSIONS: Our results indicated that approximately one-fifth of the participants will drop out from CA interventions in short-term studies. High heterogeneities made it difficult to generalize the findings. Our results suggested that future CA interventions should adopt a blended design with human support, use symptom tracking, compare CA intervention groups against active controls rather than waitlist controls, and include a visual representation of the CA to reduce the attrition rate. TRIAL REGISTRATION: PROSPERO International Prospective Register of Systematic Reviews CRD42022341415; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022341415.

Conversational Agents in Health Care: Expert Interviews to Inform the Definition, Classification, and Conceptual Framework.

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.

Scope, Characteristics, Behavior Change Techniques, and Quality of Conversational Agents for Mental Health and Well-Being: Systematic Assessment of Apps.

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.

Evaluating Conversational Agents for Mental Health: Scoping Review of Outcomes and Outcome Measurement Instruments.

BACKGROUND: Rapid proliferation of mental health interventions delivered through conversational agents (CAs) calls for high-quality evidence to support their implementation and adoption. Selecting appropriate outcomes, instruments for measuring outcomes, and assessment methods are crucial for ensuring that interventions are evaluated effectively and with a high level of quality. OBJECTIVE: We aimed to identify the types of outcomes, outcome measurement instruments, and assessment methods used to assess the clinical, user experience, and technical outcomes in studies that evaluated the effectiveness of CA interventions for mental health. METHODS: We undertook a scoping review of the relevant literature to review the types of outcomes, outcome measurement instruments, and assessment methods in studies that evaluated the effectiveness of CA interventions for mental health. We performed a comprehensive search of electronic databases, including PubMed, Cochrane Central Register of Controlled Trials, Embase (Ovid), PsychINFO, and Web of Science, as well as Google Scholar and Google. We included experimental studies evaluating CA mental health interventions. The screening and data extraction were performed independently by 2 review authors in parallel. Descriptive and thematic analyses of the findings were performed. RESULTS: We included 32 studies that targeted the promotion of mental well-being (17/32, 53%) and the treatment and monitoring of mental health symptoms (21/32, 66%). The studies reported 203 outcome measurement instruments used to measure clinical outcomes (123/203, 60.6%), user experience outcomes (75/203, 36.9%), technical outcomes (2/203, 1.0%), and other outcomes (3/203, 1.5%). Most of the outcome measurement instruments were used in only 1 study (150/203, 73.9%) and were self-reported questionnaires (170/203, 83.7%), and most were delivered electronically via survey platforms (61/203, 30.0%). No validity evidence was cited for more than half of the outcome measurement instruments (107/203, 52.7%), which were largely created or adapted for the study in which they were used (95/107, 88.8%). CONCLUSIONS: The diversity of outcomes and the choice of outcome measurement instruments employed in studies on CAs for mental health point to the need for an established minimum core outcome set and greater use of validated instruments. Future studies should also capitalize on the affordances made available by CAs and smartphones to streamline the evaluation and reduce participants' input burden inherent to self-reporting.

Conversational Agents in Health Care: Scoping Review of Their Behavior Change Techniques and Underpinning Theory.

BACKGROUND: Conversational agents (CAs) are increasingly used in health care to deliver behavior change interventions. Their evaluation often includes categorizing the behavior change techniques (BCTs) using a classification system of which the BCT Taxonomy v1 (BCTTv1) is one of the most common. Previous studies have presented descriptive summaries of behavior change interventions delivered by CAs, but no in-depth study reporting the use of BCTs in these interventions has been published to date. OBJECTIVE: This review aims to describe behavior change interventions delivered by CAs and to identify the BCTs and theories guiding their design. METHODS: We searched PubMed, Embase, Cochrane's Central Register of Controlled Trials, and the first 10 pages of Google and Google Scholar in April 2021. We included primary, experimental studies evaluating a behavior change intervention delivered by a CA. BCTs coding followed the BCTTv1. Two independent reviewers selected the studies and extracted the data. Descriptive analysis and frequent itemset mining to identify BCT clusters were performed. RESULTS: We included 47 studies reporting on mental health (n=19, 40%), chronic disorders (n=14, 30%), and lifestyle change (n=14, 30%) interventions. There were 20/47 embodied CAs (43%) and 27/47 CAs (57%) represented a female character. Most CAs were rule based (34/47, 72%). Experimental interventions included 63 BCTs, (mean 9 BCTs; range 2-21 BCTs), while comparisons included 32 BCTs (mean 2 BCTs; range 2-17 BCTs). Most interventions included BCTs 4.1 "Instruction on how to perform a behavior" (34/47, 72%), 3.3 "Social support" (emotional; 27/47, 57%), and 1.2 "Problem solving" (24/47, 51%). A total of 12/47 studies (26%) were informed by a behavior change theory, mainly the Transtheoretical Model and the Social Cognitive Theory. Studies using the same behavior change theory included different BCTs. CONCLUSIONS: There is a need for the more explicit use of behavior change theories and improved reporting of BCTs in CA interventions to enhance the analysis of intervention effectiveness and improve the reproducibility of research.

Designing, Developing, Evaluating, and Implementing a Smartphone-Delivered, Rule-Based Conversational Agent (DISCOVER): Development of a Conceptual Framework.

BACKGROUND: Conversational agents (CAs), also known as chatbots, are computer programs that simulate human conversations by using predetermined rule-based responses or artificial intelligence algorithms. They are increasingly used in health care, particularly via smartphones. There is, at present, no conceptual framework guiding the development of smartphone-based, rule-based CAs in health care. To fill this gap, we propose structured and tailored guidance for their design, development, evaluation, and implementation. OBJECTIVE: The aim of this study was to develop a conceptual framework for the design, evaluation, and implementation of smartphone-delivered, rule-based, goal-oriented, and text-based CAs for health care. METHODS: We followed the approach by Jabareen, which was based on the grounded theory method, to develop this conceptual framework. We performed 2 literature reviews focusing on health care CAs and conceptual frameworks for the development of mobile health interventions. We identified, named, categorized, integrated, and synthesized the information retrieved from the literature reviews to develop the conceptual framework. We then applied this framework by developing a CA and testing it in a feasibility study. RESULTS: The Designing, Developing, Evaluating, and Implementing a Smartphone-Delivered, Rule-Based Conversational Agent (DISCOVER) conceptual framework includes 8 iterative steps grouped into 3 stages, as follows: design, comprising defining the goal, creating an identity, assembling the team, and selecting the delivery interface; development, including developing the content and building the conversation flow; and the evaluation and implementation of the CA. They were complemented by 2 cross-cutting considerations-user-centered design and privacy and security-that were relevant at all stages. This conceptual framework was successfully applied in the development of a CA to support lifestyle changes and prevent type 2 diabetes. CONCLUSIONS: Drawing on published evidence, the DISCOVER conceptual framework provides a step-by-step guide for developing rule-based, smartphone-delivered CAs. Further evaluation of this framework in diverse health care areas and settings and for a variety of users is needed to demonstrate its validity. Future research should aim to explore the use of CAs to deliver health care interventions, including behavior change and potential privacy and safety concerns.

Evaluation of chatbot-delivered interventions for self-management of depression: Content analysis.

BACKGROUND: Conversational agents (CAs) or chatbots are increasingly used for depression, anxiety, and wellbeing management. CAs are considered acceptable and helpful. However, little is known about the adequacy of CA responses. This study assessed the structure, content, and user-customization of mental health CA dialogues with users with depression or at risk of suicide. METHODS: We used content analysis to examine the dialogues of CAs previously included in three assessments of mental health apps (depression education, self-guided cognitive behavioural therapy, and suicide prevention) performed between 2019 and 2020. Two standardized user personas with depression were developed to interact with the CA. All conversations were saved as screenshots, transcribed verbatim, and coded inductively. RESULTS: Nine CAs were included. Seven CAs (78%) had Android and iOS versions; five CAs (56%) had at least 500,000 downloads. The analysis generated eight categories: self-introduction, personalization, appropriateness of CA responses, conveying empathy, guiding users through mood-boosting activities, mood monitoring, suicide risk management, and others. CAs could engage in empathic, non-judgemental conversations with users, offer support, and guide psychotherapeutic exercises. LIMITATIONS: CA evaluations were performed using standardized personas, not real-world users. CAs were included for evaluation only if retrieved in the search strategies associated with the previous assessment studies. CONCLUSION: Assessed CAs offered anonymous, empathic, non-judgemental interactions that align with evidence for face-to-face psychotherapy. CAs from app stores are not suited to provide comprehensive suicide risk management. Further research should evaluate the effectiveness of CA-led interventions in mental health care and in enhancing suicide risk management strategies.

The Use of Telegram in Surgical Education: Exploratory Study.

BACKGROUND: The COVID-19 pandemic has disrupted medical education, shifting learning online. Social media platforms, including messaging apps, are well integrated into medical education. However, Telegram's role in medical education remains relatively unexplored. OBJECTIVE: This study aims to explore the perceptions of medical students regarding the role of messaging apps in medical education and their experience of using Telegram for surgical education. METHODS: A Telegram channel "Telegram Education for Surgery Learning and Application (TESLA)" was created to supplement medical students' learning. We invited 13 medical students who joined the TESLA channel for at least a month to participate in individual semistructured interviews. Interviews were conducted via videoconferencing using an interview guide and were then transcribed and analyzed by 2 researchers using inductive thematic content analysis. RESULTS: Two themes were identified: (1) learning as a medical student and (2) the role of mobile learning (mLearning) in medical education. Students shared that pandemic-related safety measures, such as reduced clinic allocations and the inability to cross between wards, led to a decrease in clinical exposure. Mobile apps, which included proprietary study apps and messaging apps, were increasingly used by students to aid their learning. Students favored Telegram over other messaging apps and reported the development of TESLA as beneficial, particularly for revision and increasing knowledge. CONCLUSIONS: The use of apps for medical education increased during the COVID-19 pandemic. Medical students commonly used apps to consolidate their learning and revise examination topics. They found TESLA useful, relevant, and trustworthy.

Education on Depression in Mental Health Apps: Systematic Assessment of Characteristics and Adherence to Evidence-Based Guidelines.

BACKGROUND: Suboptimal understanding of depression and mental health disorders by the general population is an important contributor to the wide treatment gap in depression. Mental health literacy encompasses knowledge and beliefs about mental disorders and supports their recognition, management, and prevention. Besides knowledge improvement, psychoeducational interventions reduce symptoms of depression, enhance help-seeking behavior, and decrease stigma. Mental health apps often offer educational content, but the trustworthiness of the included information is unclear. OBJECTIVE: The aim of this study is to systematically evaluate adherence to clinical guidelines on depression of the information offered by mental health apps available in major commercial app stores. METHODS: A systematic assessment of the educational content regarding depression in the apps available in the Apple App Store and Google Play was conducted in July 2020. A systematic search for apps published or updated since January 2019 was performed using 42matters. Apps meeting the inclusion criteria were downloaded and assessed using two smartphones: an iPhone 7 (iOS version 14.0.1) and a Sony XPERIA XZs (Android version 8.0.0). The 156-question assessment checklist comprised general characteristics of apps, appraisal of 38 educational topics and their adherence to evidence-based clinical guidelines, as well as technical aspects and quality assurance. The results were tabulated and reported as a narrative review, using descriptive statistics. RESULTS: The app search retrieved 2218 apps, of which 58 were included in the analysis (Android apps: n=29, 50%; iOS apps: n=29, 50%). Of the 58 included apps, 37 (64%) apps offered educational content within a more comprehensive depression or mental health management app. Moreover, 21% (12/58) of apps provided non-evidence-based information. Furthermore, 88% (51/58) of apps included up to 20 of the educational topics, the common ones being listing the symptoms of depression (52/58, 90%) and available treatments (48/58, 83%), particularly psychotherapy. Depression-associated stigma was mentioned by 38% (22/58) of the apps, whereas suicide risk was mentioned by 71% (41/58), generally as an item in a list of symptoms. Of the 58 included apps, 44 (76%) highlighted the importance of help seeking, 29 (50%) emphasized the importance of involving the user's support network. In addition, 52% (30/58) of apps referenced their content, and 17% (10/58) included advertisements. CONCLUSIONS: Information in mental health and depression apps is often brief and incomplete, with 1 in 5 apps providing non-evidence-based information. Given the unmet needs and stigma associated with the disease, it is imperative that apps seize the opportunity to offer quality, evidence-based education or point the users to relevant resources. A multistakeholder consensus on a more stringent development and publication process for mental health apps is essential.

Choice of Behavioral Change Techniques in Health Care Conversational Agents: Protocol for a Scoping Review.

BACKGROUND: Conversational agents or chatbots are computer programs that simulate conversations with users. Conversational agents are increasingly used for delivery of behavior change interventions in health care. Behavior change is complex and comprises the use of one or several components collectively known as behavioral change techniques (BCTs). OBJECTIVE: The objective of this scoping review is to identify the BCTs that are used in behavior change-focused interventions delivered via conversational agents in health care. METHODS: This scoping review will be performed in line with the Joanna Briggs Institute methodology and will be reported according to the PRISMA extension for scoping reviews guidelines. We will perform a comprehensive search of electronic databases and grey literature sources, and will check the reference lists of included studies for additional relevant studies. The screening and data extraction will be performed independently and in parallel by two review authors. Discrepancies will be resolved through consensus or discussion with a third review author. We will use a data extraction form congruent with the key themes and aims of this scoping review. BCTs employed in the included studies will be coded in line with BCT Taxonomy v1. We will analyze the data qualitatively and present it in diagrammatic or tabular form, alongside a narrative summary. RESULTS: To date, we have designed the search strategy and performed the search on April 26, 2021. The first round of screening of retrieved articles is planned to begin soon. CONCLUSIONS: Using appropriate BCTs in the design and delivery of health care interventions via conversational agents is essential to improve long-term outcomes. Our findings will serve to inform the development of future interventions in this area. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/30166.

Self-guided Cognitive Behavioral Therapy Apps for Depression: Systematic Assessment of Features, Functionality, and Congruence With Evidence.

BACKGROUND: Mental health disorders affect 1 in 10 people globally, of whom approximately 300 million are affected by depression. At least half of the people affected by depression remain untreated. Although cognitive behavioral therapy (CBT) is an effective treatment, access to mental health specialists, habitually challenging, has worsened because of the COVID-19 pandemic. Internet-based CBT is an effective and feasible strategy to increase access to treatment for people with depression. Mental health apps may further assist in facilitating self-management for people affected by depression; however, accessing the correct app may be cumbersome given the large number and wide variety of apps offered by public app marketplaces. OBJECTIVE: This study aims to systematically assess the features, functionality, data security, and congruence with evidence of self-guided CBT-based apps targeting users affected by depression that are available in major app stores. METHODS: We conducted a systematic assessment of self-guided CBT-based apps available in Google Play and the Apple App Store. Apps launched or updated since August 2018 were identified through a systematic search in the 42matters database using CBT-related terms. Apps meeting the inclusion criteria were downloaded and assessed using a Samsung Galaxy J7 Pro (Android 9) and iPhone 7 (iOS 13.3.1). Apps were appraised using a 182-question checklist developed by the research team, assessing their general characteristics, technical aspects and quality assurance, and CBT-related features, including 6 evidence-based CBT techniques (ie, psychoeducation, behavioral activation, cognitive restructuring, problem solving, relaxation, and exposure for comorbid anxiety) as informed by a CBT manual, CBT competence framework, and a literature review of internet-based CBT clinical trial protocols. The results were reported as a narrative review using descriptive statistics. RESULTS: The initial search yielded 3006 apps, of which 98 met the inclusion criteria and were systematically assessed. There were 20 well-being apps; 65 mental health apps, targeting two or more common mental health disorders, including depression; and 13 depression apps. A total of 28 apps offered at least four evidence-based CBT techniques, particularly depression apps. Cognitive restructuring was the most common technique, offered by 79% (77/98) of the apps. Only one-third of the apps offered suicide risk management resources, whereas 17% (17/98) of the apps offered COVID-19-related information. Although most apps included a privacy policy, only a third of the apps presented it before account creation. In total, 82% (74/90) of privacy policies stated sharing data with third-party service providers. Half of the app development teams included academic institutions or health care providers. CONCLUSIONS: Only a few self-guided CBT-based apps offer comprehensive CBT programs or suicide risk management resources. Sharing of users' data is widespread, highlighting shortcomings in health app market governance. To fulfill their potential, self-guided CBT-based apps should follow evidence-based clinical guidelines, be patient centered, and enhance users' data security.

Digital health professions education on chronic wound management: A systematic review.

BACKGROUND: Continuing education is crucial for healthcare professionals to keep up with research but attending classroom lectures is a major barrier. Chronic wound management is increasingly relevant for continuous professional training. Digital education offers learning tailored to individual needs and could be an effective alternative to healthcare professionals' training. However, the effectiveness of digital education for chronic wound management training has not been explored. OBJECTIVES: To assess the effectiveness of digital education in improving healthcare professionals' knowledge, attitudes, practical skills and behaviour change on chronic wound management, and their satisfaction with the intervention. DESIGN: This systematic review follows Cochrane methodology and is one of a series of reviews on the use of digital education for health professions education. Protocol registration: PROSPERO CRD42018109971 DATA SOURCES: Searches were conducted in MEDLINE, Embase, Web of Science, ERIC, PsycINFO, CINAHL, CENTRAL, and ProQuest Dissertation and Theses Database. REVIEW METHODS: We included randomised control trials, cluster randomised control trials and quasi-randomised control trials comparing digital or blended education with traditional learning, no intervention or other forms of digital or blended education for pre- or post-registration healthcare professionals in chronic wound management. A narrative summary of findings is presented. RESULTS: Seven studies (1,404 participants) were included. All studies investigated interventions for nursing students or professionals working in hospitals or community settings, and all but one study focused on pressure ulcers. Five studies (935 participants) assessed post-intervention knowledge, and indicated that digital education was more effective than no intervention, while blended learning was superior to exclusive digital education. Three studies (543 participants) assessed post-intervention skills and reported mixed results. One study (140 participants) compared post-intervention behaviour change and satisfaction with blended and online digital education, and reported no difference in behaviour between the groups, and higher satisfaction with blended education. For knowledge retention up to six months, digital education was more effective than no intervention, while blended learning was superior to digital education. The risk of bias in included studies was mostly high or unclear. CONCLUSIONS: Digital education on chronic wound management appears to be less effective than blended education and more effective than no intervention in improving knowledge among nurses and nursing students. Data for other outcomes is scarce and inconclusive. Future studies should assess participants' skills, attitudes, satisfaction and behaviour change; cost-effectiveness and potential untoward effects of digital education, compare digital education to other learning modalities and include other healthcare professionals in diverse clinical settings.

Suicide prevention and depression apps' suicide risk assessment and management: a systematic assessment of adherence to clinical guidelines.

BACKGROUND: There are an estimated 800,000 suicides per year globally, and approximately 16,000,000 suicide attempts. Mobile apps may help address the unmet needs of people at risk. We assessed adherence of suicide prevention advice in depression management and suicide prevention apps to six evidence-based clinical guideline recommendations: mood and suicidal thought tracking, safety plan development, recommendation of activities to deter suicidal thoughts, information and education, access to support networks, and access to emergency counseling. METHODS: A systematic assessment of depression and suicide prevention apps available in Google Play and Apple's App Store was conducted. Apps were identified by searching 42matters in January 2019 for apps launched or updated since January 2017 using the terms "depression," "depressed," "depress," "mood disorders," "suicide," and "self-harm." General characteristics of apps, adherence with six suicide prevention strategies identified in evidence-based clinical guidelines using a 50-question checklist developed by the study team, and trustworthiness of the app based on HONcode principles were appraised and reported as a narrative review, using descriptive statistics. RESULTS: The initial search yielded 2690 potentially relevant apps. Sixty-nine apps met inclusion criteria and were systematically assessed. There were 20 depression management apps (29%), 3 (4%) depression management and suicide prevention apps, and 46 (67%) suicide prevention apps. Eight (12%) depression management apps were chatbots. Only 5/69 apps (7%) incorporated all six suicide prevention strategies. Six apps (6/69, 9%), including two apps available in both app stores and downloaded more than one million times each, provided an erroneous crisis helpline number. Most apps included emergency contact information (65/69 apps, 94%) and direct access to a crisis helpline through the app (46/69 apps, 67%). CONCLUSIONS: Non-existent or inaccurate suicide crisis helpline phone numbers were provided by mental health apps downloaded more than 2 million times. Only five out of 69 depression and suicide prevention apps offered all six evidence-based suicide prevention strategies. This demonstrates a failure of Apple and Google app stores, and the health app industry in self-governance, and quality and safety assurance. Governance levels should be stratified by the risks and benefits to users of the app, such as when suicide prevention advice is provided.

Digital Education for the Management of Chronic Wounds in Health Care Professionals: Protocol for a Systematic Review by the Digital Health Education Collaboration.

BACKGROUND: Digital education is "the act of teaching and learning by means of digital technologies." Digital education comprises a wide range of interventions that can be broadly divided into offline digital education, online digital education, digital game-based learning, massive open online courses (MOOCs), psychomotor skills trainers, virtual reality environments, virtual patient simulations, and m-learning. Chronic wounds pose an immense economic and psychosocial burden to patients and the health care system, as caring for them require highly specialized personnel. Current training strategies face significant barriers, such as lack of time due to work commitments, distance from provider centers, and costs. Therefore, there is an increased need to synthesize evidence on the effectiveness of digital education interventions on chronic wounds management in health care professionals. OBJECTIVE: Our main objective is to assess the effectiveness of digital education as a stand-alone approach or as part of a blended-learning approach in improving pre- and postregistration health care professionals' knowledge, attitudes, practical skills, and behavior in the management of chronic wounds, as well as their satisfaction with the intervention. Secondary objectives are to evaluate patient-related outcomes, cost-effectiveness of the interventions, and any unfavorable or undesirable outcomes that may arise. METHODS: This systematic review will follow the methodology as described in the Cochrane Handbook for Systematic Reviews of Interventions. As our systematic review is one of a series of reviews on digital education for health professionals' education, we will use a previously developed search strategy. This search includes the following databases: the Cochrane Central Register of Controlled Trials (CENTRAL) (Cochrane Library), MEDLINE (Ovid), Embase (Ovid), Web of Science, the Educational Resource Information Centre (ERIC) (Ovid), PsycINFO (Ovid), the Cumulative Index to Nursing and Allied Health Literature (CINAHL) (EBSCO), the ProQuest Dissertation and Theses database, and trial registries. Databases will be searched for studies published from January 1990 to August 2018. Two independent reviewers will screen the library for included studies. We will describe the screening process using a flowchart as per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We will extract the data using a previously developed, structured data extraction form. Included studies will be quality-assessed using the Risk of Bias tool from Cochrane. We will narratively summarize the data and, if possible, we will conduct a meta-analysis. We will use Cochrane's RevMan 5.3 software for data analysis. RESULTS: We have completed the screening of titles and abstracts for this systematic review and are currently selecting papers against our inclusion and exclusion criteria through full-text revision. We are expecting to complete our review by the end of April 2019. CONCLUSIONS: This systematic review will provide an in-depth analysis of digital education strategies to train health care providers in the management of chronic wounds. We consider this topic particularly relevant given the current challenges facing health care systems worldwide, including shortages of skilled personnel and a steep increase in the population of older adults as a result of a prolonged life expectancy. TRIAL REGISTRATION: PROSPERO CRD42018109971; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=109971. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/12488.

Prevalence of chronic wounds in the general population: systematic review and meta-analysis of observational studies.

PURPOSE: Chronic wounds are a major public health challenge, but little is known about the true burden with studies reporting different estimates because of disparities in study designs and measurement methods. This hampers efficient resource allocation, planning, and improvement of wound care. METHODS: Our study aimed to pool prevalence estimates from a global perspective by systematically carrying out searches in MEDLINE, EMBASE, Cochrane, CINAHL, Global Health, and PsycINFO databases for articles reporting the prevalence of chronic wounds in adults, from January 2000 to June 2018. The included publications had to define wound chronicity by duration (≥3 weeks), and/or labeling the wounds as chronic, complex, or hard-to-heal. RESULTS: Seventeen studies met the inclusion criteria, and 11 studies analyzing chronic wounds in the general population were included in random effects meta-analyses to calculate pooled prevalence. Chronic wounds of mixed etiologies (n = 3) showed a pooled prevalence of 2.21 per 1000 population, and for chronic leg ulcers (n = 9), the prevalence was estimated at 1.51 per 1000 population. CONCLUSIONS: Our findings, aligned to previous studies reporting point prevalence of chronic wounds identified within the healthcare system, showed that the vast majority of chronic wounds in epidemiological studies are made up by chronic leg ulcers.