Can Remote Digital Health Interventions Improve Rehabilitation Following Major Trauma? Results of a Systematic Review.

The use of digital health (DH) interventions has increased over the past 2 decades, providing patients with alternative remote pathways for receiving health care services. Patients with major trauma frequently require long-term access to health care services to support their mental and physical health and their overall quality of life. DH interventions can help patients stay connected to rehabilitation services, thereby enhancing their health condition and helping them regain their independence, which will enable them to return to the workplace or regain a role in society. There is a need to explore existing evidence on the effectiveness of DH interventions for improving health-related outcomes in patients with major trauma. This review aims to identify DH interventions that support the physical, functional, or psychological rehabilitation of patients who have experienced major physical trauma. This review targets randomized controlled trials. Studies investigating DH interventions in adult patients with major traumatic physical injuries (end users of the interventions) are considered eligible for inclusion. Digital interventions that are delivered remotely and studies that report the impact of DH interventions on patients' health-related outcomes will be included. The search will be limited to publications since 2000 and peer-reviewed journals. No language restrictions will be applied, and articles not written in English will be translated. The search will be conducted in MEDLINE, Embase, AMED, CINAHL Plus, and PsycInfo. Grey literature and bibliographies of included studies and relevant reviews will also be searched for potentially relevant articles. A minimum of two reviewers will independently screen retrieved references. Data extraction will be conducted by 1 reviewer and independently checked by another reviewer. Quality assessment of the included studies will be conducted using the Cochrane Risk of Bias 2 tool. Any disagreements arising at any stage of the review will be resolved through discussion or by consulting a third reviewer, if required. A meta-analysis will be performed where possible, and a descriptive analysis of the included studies will be reported. As of January 2025, the systematic review is in the data extraction stage. Seven studies have been identified as eligible for inclusion. The findings are expected to be published in a peer-reviewed journal by December 2025. The review findings will help identify existing evidence regarding DH interventions used to support the physical, functional, or psychological rehabilitation needs of patients with major trauma. This would help guide practitioners and policy makers to implement effective interventions to better support patient outcomes. The evidence synthesized from this review will also identify existing gaps and direct future research. PROSPERO CRD42023485748; https://www.crd.york.ac.uk/PROSPERO/view/CRD42023485748. DERR1-10.2196/67675.

BackgroundDepression and anxiety disorders are common, and treatment often includes psychological interventions. Digital health interventions, delivered through technologies such as web-based programs and mobile apps, are increasingly used in mental health treatment. Acceptability, the extent to which an intervention is viewed positively, has been identified as contributing to patient adherence and engagement with digital health interventions. Acceptability, therefore, impacts the benefit derived from using digital health interventions in treatment. Understanding the acceptability of digital mental health interventions among patients with depression or anxiety disorders is essential to maximize the effectiveness of their treatment.ObjectiveThis review investigated the acceptability of technology-based interventions among patients with depression or anxiety disorders.MethodsA systematic review was performed based on PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and PROSPERO (International Prospective Register of Systematic Reviews) guidelines. We searched PubMed, Web of Science, and Ovid in May 2022. Studies were included if they evaluated digital interventions for the treatment of depression or anxiety disorders and investigated their acceptability among adult patients. Studies were excluded if they targeted only specific populations (eg, those with specific physical health conditions), investigated acceptability in healthy individuals or patients under the age of 18 years, involved no direct interaction between patients and technologies, used technology only as a platform for traditional care (eg, videoconferencing), had patients using technologies only in clinical or laboratory settings, or involved virtual reality technologies. Acceptability outcome data were narratively synthesized by the direction of acceptability using vote counting. Included studies were evaluated using levels of evidence from the Oxford Centre for Evidence-Based Medicine. The risk of bias was assessed using a tool designed for this review and GRADE (Grading of Recommendations, Assessment, Development, and Evaluation).ResultsA total of 143 articles met the inclusion criteria, comprising 67 (47%) articles on interventions for depression, 65 (45%) articles on interventions for anxiety disorders, and 11 (8%) articles on interventions for both. Overall, 90 (63%) were randomized controlled trials, 50 (35%) were other quantitative studies, and 3 (2%) were qualitative studies. Interventions used web-based programs, mobile apps, and computer programs. Cognitive behavioral therapy was the basis of 71% (102/143) of the interventions. Digital mental health interventions were generally acceptable among patients with depression or anxiety disorders, with 88% (126/143) indicating positive acceptability, 8% (11/143) mixed results, and 4% (6/143) insufficient information to categorize the direction of acceptability. The available research evidence was of moderate quality.ConclusionsDigital mental health interventions seem to be acceptable to patients with depression or anxiety disorders. Consistent use of validated measures for acceptability would enhance the quality of evidence. Careful design of acceptability as an evaluation outcome can further improve the quality of evidence and reduce the risk of bias.Trial RegistrationOpen Science Framework Y7MJ4; https://doi.org/10.17605/OSF.IO/SPR8M

To investigate the effects of digital health interventions for improving adherence to oral iron supplementation in pregnant women. Five databases were searched from their inception to October 2023 with no date restrictions. Randomized controlled trials (RCTs) that assessed the effects of digital health interventions on adherence to oral iron supplementation (e.g., tablets and capsules) compared to non-digital health interventions for pregnant women were eligible. We calculated standardized mean differences (SMDs) and mean differences (MDs) with 95% confidence intervals (CIs) for continuous variables using the inverse variance method. We calculated odds ratios (OR) with 95%CI for categorical variables using the Mantel-Haenszel model. The certainty of the evidence was assessed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. The risk of bias of the included RCTs was assessed using the Cochrane risk of bias tool 2.0. Ten trials with 1,633 participants were included. Based on 7 trials, digital health interventions can improve objective adherence rate comparing with non-digital health interventions (1,289 participants, OR = 4.07 [2.19, 7.57], p < 0.001, I2 = 69%) in pregnant women. Digital health interventions can improve subjective adherence behavior comparing with non-digital health interventions (3 trials, 434 participants, SMD = 0.82 [0.62, 1.01], p < 0.001, I2 = 0%) in pregnant women. Based on 3 trials, digital health interventions can improve tablets consumption comparing with non-digital health interventions (333 participants, SMD = 1.00 [0.57, 1.42], p < 0.001, I2 = 66%) in pregnant women. Digital health interventions can improve hemoglobin level comparing with non-digital health interventions (7 trials, 1,216 participants, MD = 0.59 [0.31, 0.88], p < 0.001, I2 = 93%) in pregnant women. Digital health interventions were effective at improving adherence to oral iron supplementation and hemoglobin levels in pregnant women.

BACKGROUND Digital Health Interventions (DHIs) are widely used to manage users' health in everyday life through digital devices. The use of DHIs generates various data, such as records of intervention usage and the status of target symptoms, providing researchers with data-driven insights for improving these interventions even after deployment. Although DHI researchers have investigated this data, existing analysis practices have been carried out in a fragmented manner, limiting the comprehensive understanding of the data. OBJECTIVE We proposed an analysis task model to help DHI researchers analyze observational data from a holistic perspective. This model was then used to prototype an interactive visual analytics tool. Our objective is to evaluate the model’s suitability for DHI data analysis and explore task support through a visual analytics tool. METHODS We constructed an analysis task model based on data analysis practices from existing DHI research. Moreover, we designed 'Maum Health Analytics,' an initial prototype of an interactive visual analytics tool that supports the tasks included in the proposed model. To investigate whether our model adequately covers the DHI data analysis process, we conducted a preliminary user study with five groups of DHI researchers (n=15). During this process, we had them use Maum Health Analytics within given data analysis scenarios, providing analyzed results from in-the-wild data collected in a non-experimental setting through a mobile DHI service targeting depressive symptoms. After using the analytics tool, we interviewed the DHI researchers to determine whether the analysis tasks were appropriate and how the information provided by the tool could be utilized in practice. RESULTS Our analysis task model was created using three key components (i.e., user grouping criteria) for DHI data analysis: user characteristics, user engagement with DHIs, and the effectiveness of DHIs on the target symptom via pre-post comparisons. Furthermore, the prototype of interactive visual analytics was designed, with each feature mapped one-to-one to an analysis task described in the model. From the interview sessions, DHI researchers valued group-level analysis that enabled identifying users who need care, improving intervention content and recommendations, and understanding the effectiveness of DHIs in connection with user characteristics and engagement levels. They also noted several benefits of the model and tool, such as simplifying analysis tasks and supporting communication among diverse experts. CONCLUSIONS We proposed an analysis task model and designed an interactive visual analytics tool to support DHI researchers. Our user study showed that the model allows a holistic investigation of DHI data by integrating key analysis components, and the prototype tool simplifies analytic tasks and enhances communication among researchers. As DHIs grow, our model and tool could effectively meet the data analysis needs of researchers and improve efficiency.

Digital health interventions (DHIs) are widely used to manage users' health in everyday life through digital devices. The use of DHIs generates various data, such as records of intervention use and the status of target symptoms, providing researchers with data-driven insights for improving these interventions even after deployment. Although DHI researchers have investigated these data, existing analysis practices have been fragmented, limiting a comprehensive understanding of the data. We proposed an analysis task model to help DHI researchers analyze observational data from a holistic perspective. This model was then used to prototype an interactive visual analytics tool. We aimed to evaluate the suitability of the model for DHI data analysis and explore task support using a visual analytics tool. We constructed a data analysis task model using 3 key components (ie, user grouping criteria) for DHI data analysis: user characteristics, user engagement with DHIs, and the effectiveness of DHIs on target symptoms based on comparisons before and after the intervention. On the basis of this model, we designed Maum Health Analytics, a medium-fidelity prototype of an interactive visual analytics tool. Each feature of the prototype was mapped one-to-one to the analysis task described in the model. To investigate whether the proposed model adequately reflects real-world DHI analysis needs, we conducted a preliminary user study with 5 groups of researchers (N=15). Participants explored the tool through scenario-based analysis tasks using in-the-wild data collected from a mobile DHI service targeting depressive symptoms. Following the session, we conducted interviews to assess the appropriateness of the defined tasks and the usability and practical utility of the visual analytics tool. DHI researchers responded positively to both the analysis task model and the visual analytics tool. In the interviews, participants noted that the tool supported the identification of users who needed additional care, informed content recommendations, and helped analyze intervention effectiveness in relation to user characteristics and engagement levels. They also appreciated the tool's role in simplifying analytic tasks and supporting communication across multidisciplinary teams. Additional suggestions included improvements for continuity across tasks and more detailed engagement metrics. We proposed an analysis task model and designed an interactive visual analytics tool to support DHI researchers. Our user study showed that the model allows a holistic investigation of DHI data by integrating key analysis components and that the prototype tool simplifies analytic tasks and enhances communication among researchers. As DHIs grow, the proposed model and tool can effectively meet the data analysis requirements of researchers and improve efficiency.

BackgroundPoor mental health among university students remains a pressing public health issue. Over the past few years, digital health interventions have been developed and considered promising in increasing psychological wellbeing among university students. Therefore, this umbrella review aims to synthesize evidence on digital health interventions targeting university students and to evaluate their effectiveness.MethodsA systematic literature search was performed in April 2021 searching PubMed, Psychology and Behavioural Science Collection, Web of Science, ERIC, and Scopus for systematic reviews and meta-analyses on digital mental health interventions targeting university students. The review protocol was registered in the International Prospective Register of Systematic Reviews PROSPERO [CRD42021234773].ResultsThe initital literature search resulted in 806 records of which seven remained after duplicates were removed and evaluated against the inclusion criteria. Effectiveness was reported and categorized into the following six delivery types: (a) web-based, online/computer-delivered interventions (b) computer-based Cognitive Behavior Therapy (CBT), (c) mobile applications and short message service (d) virtual reality interventions (e) skills training (f) relaxation and exposure-based therapy. Results indicated web-based online/computer delivered-interventions were effective or at least partially effective at decressing depression, anxiety, stress and eating disorder symptoms. This was similar for skills-training interventions, CBT-based intervention and mobile applications. However, digital mental health interventions using virtual reality and relaxation, exposure-based therapy was inconclusive. Due to the variation in study settings and inconsistencies in reporting, effectiveness was greatly dependent on the delivery format, targeted mental health problem and targeted purpose group.ConclusionThe findings provide evidence for the beneficial effect of digital mental health interventions for university students. However, this review calls for a more systematic approach in testing and reporting the effectiveness of digital mental health interventions.

BackgroundThere is a high prevalence of children and young people (CYP) experiencing mental health (MH) problems. Owing to accessibility, affordability, and scalability, an increasing number of digital health interventions (DHIs) have been developed and incorporated into MH treatment. Studies have shown the potential of DHIs to improve MH outcomes. However, the modes of delivery used to engage CYP in digital MH interventions may differ, with implications for the extent to which findings pertain to the level of engagement with the DHI. Knowledge of the various modalities could aid in the development of interventions that are acceptable and feasible.ObjectiveThis review aimed to (1) identify modes of delivery used in CYP digital MH interventions, (2) explore influencing factors to usage and implementation, and (3) investigate ways in which the interventions have been evaluated and whether CYP engage in DHIs.MethodsA literature search was performed in the Cochrane Library, Excerpta Medica dataBASE (EMBASE), Medical Literature Analysis and Retrieval System Online (MEDLINE), and PsycINFO databases using 3 key concepts “child and adolescent mental health,” “digital intervention,” and “engagement.” Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed using rigorous inclusion criteria and screening by at least two reviewers. The selected articles were assessed for quality using the mixed methods appraisal tool, and data were extracted to address the review aims. Data aggregation and synthesis were conducted and presented as descriptive numerical summaries and a narrative synthesis, respectively.ResultsThis study identified 6 modes of delivery from 83 articles and 71 interventions for engaging CYP: (1) websites, (2) games and computer-assisted programs, (3) apps, (4) robots and digital devices, (5) virtual reality, and (6) mobile text messaging. Overall, 2 themes emerged highlighting intervention-specific and person-specific barriers and facilitators to CYP’s engagement. These themes encompassed factors such as suitability, usability, and acceptability of the DHIs and motivation, capability, and opportunity for the CYP using DHIs. The literature highlighted that CYP prefer DHIs with features such as videos, limited text, ability to personalize, ability to connect with others, and options to receive text message reminders. The findings of this review suggest a high average retention rate of 79% in studies involving various DHIs.ConclusionsThe development of DHIs is increasing and may be of interest to CYP, particularly in the area of MH treatment. With continuous technological advancements, it is important to know which modalities may increase engagement and help CYP who are facing MH problems. This review identified the existing modalities and highlighted the influencing factors from the perspective of CYP. This knowledge provides information that can be used to design and evaluate new interventions and offers important theoretical insights into how and why CYP engage in DHIs.

Digital health technologies have been enhancing the capacity of healthcare providers and, thereby, the delivery of targeted health services. The Southeast Asia Region (SEAR) has invested in strengthening digital public health. Many digital health interventions have been implemented in public health settings but are rarely assessed using the holistic health technology assessment (HTA) approach. A systematic literature review was performed to provide an overview of evaluations of digital public health interventions in the World Health Organization (WHO) SEAR. Searches were conducted on four electronic databases. Screening title abstracts and full texts was independently conducted by two reviewers, followed by data extraction. Dimensions of HTA were analyzed against the EUnetHTA Core Model 3.0. Quality assessment of included articles was conducted using the JBI Checklist for Economic Evaluation and Consolidated Health Economic Evaluation Reporting Standards 2022 checklist to assess the reporting quality. The findings are presented using systematic evidence tables and bar charts. Of the forty-three studies screened at the full-text stage, thirteen studies conducted across six countries were included in the analysis. Telemedicine and m-health interventions were assessed in ten studies. Nine studies conducted cost-effectiveness analysis, and five assessments were conducted from a societal perspective. Four studies utilized more than one perspective for the assessment. Health problem definition and current use of technology, description and technical characteristics of the technology, clinical effectiveness, costs, economic evaluation, and organizational aspects were assessed by all the studies, whereas legal aspects were least assessed. The lack of HTAs on digital public health interventions in the region highlights the need for capacity-building efforts.

BackgroundAn estimated 1 in 5 adolescents experience a mental health disorder each year; yet because of barriers to accessing and seeking care, most remain undiagnosed and untreated. Furthermore, the early emergence of psychopathology contributes to a lifelong course of challenges across a broad set of functional domains, so addressing this early in the life course is essential. With increasing digital connectivity, including in low- and middle-income countries, digital health technologies are considered promising for addressing mental health among adolescents and young people. In recent years, a growing number of digital health interventions, including more than 2 million web-based mental health apps, have been developed to address a range of mental health issues.ObjectiveThis review aims to synthesize the current evidence on digital health interventions targeting adolescents and young people with mental health conditions, aged between 10-24 years, with a focus on effectiveness, cost-effectiveness, and generalizability to low-resource settings (eg, low- and middle-income countries).MethodsWe searched MEDLINE, PubMed, PsycINFO, and Cochrane databases between January 2010 and June 2020 for systematic reviews and meta-analyses on digital mental health interventions targeting adolescents and young people aged between 10-24 years. Two authors independently screened the studies, extracted data, and assessed the quality of the reviews.ResultsIn this systematic overview, we included 18 systematic reviews and meta-analyses. We found evidence on the effectiveness of computerized cognitive behavioral therapy on anxiety and depression, whereas the effectiveness of other digital mental health interventions remains inconclusive. Interventions with an in-person element with a professional, peer, or parent were associated with greater effectiveness, adherence, and lower dropout than fully automatized or self-administered interventions. Despite the proposed utility of digital interventions for increasing accessibility of treatment across settings, no study has reported sample-specific metrics of social context (eg, socioeconomic background) or focused on low-resource settings.ConclusionsAlthough digital interventions for mental health can be effective for both supplementing and supplanting traditional mental health treatment, only a small proportion of existing digital platforms are evidence based. Furthermore, their cost-effectiveness and effectiveness, including in low- and middle-income countries, have been understudied. Widespread adoption and scale-up of digital mental health interventions, especially in settings with limited resources for health, will require more rigorous and consistent demonstrations of effectiveness and cost-effectiveness vis-à-vis the type of service provided, target population, and the current standard of care.

Access to quality healthcare remains a challenge in low-and middle-income countries. Vulnerable populations with unmet needs face the greatest challenge in accessing primary care for appropriate and timely healthcare. The use of digital technologies can not only strengthen health systems but also improve access to health care, particularly for the vulnerable. This scoping review aims to assess the various digital health technologies and interventions available for improving access to primary care for the vulnerable in India. This scoping review employed the Joanna Brigg Institute's (JBI) guidelines and Arksey and O'Malley's methodological framework. The literature search was conducted in Medline/PubMed, Embase, Web of Science-Core Collection, Scopus, AgeLine, PsycINFO, CINAHL, ERIC, Cochrane CENTRAL, and Cochrane Effective Practice and Organisation of Care (EPOC) Group Specialised Register databases, using the keywords, such as 'Access', 'Healthcare', 'Assistive technology', 'Digital health' 'Vulnerable', 'India' and 'Healthcare technology'. A two-staged screening of titles and abstracts, followed by full-text was conducted independently by two reviewers, using the Rayyan software. Subsequently, the data was extracted from selected studies using a pre-designed and approved extraction form. The data was then synthesised and analysed narratively. The protocol for this review has been registered with open science forum (OSF) registries (https://osf.io/63pjw/). The search yielded about 3840 records, 3544 records were eligible for screening of titles and abstracts. We included seven studies after a two-round screening and identified seven different technological innovations developed to bridge gaps in access to primary care. The commonly used digital health interventions for improving access to primary care were virtual tele-health systems and mHealth applications in-built within an android smartphone or a tablet. Digital health interventions was either used as a standalone tele-health aid or a collaborative system for community workers, primary care physicians as well as the health service users. The purpose of these innovations was to increase awareness and knowledge to access support for specific aspects of healthcare. Virtual primary health care with the specialist in the hub supporting general physicians at the primary health centres in blocks and districts was another such model used for improving access to primary care. Digital health interventions was also used for mass community screening of disabilities, such as persons with hearing disability. To re-imagine a digitally empowered health systems in India, also inclusive of the vulnerable, it is important to inclusively conceptualise, systematically develop and rigorously evaluate any public health interventions including those that are enabled by digital health interventions to bridge the gaps in access to primary care in India. Such a strategy could address the paucity of evidence in public health interventions and provide sustainable strategies to strengthen health systems in India. Trial registration: Open Science Framework-Registration Link: https://osf.io/63pjw/.

Innovative health promotion strategies are crucial for enhancing global quality of life and curbing premature deaths. Digital health promotion is particularly impactful for young individuals often using internet-connected devices. Collaborative methodologies in digital intervention research offer insights into supporting youth during key life stages, such as adolescence. This review sought to examine the literature on digital health interventions for youth co-designed via participatory frameworks. Following the Joanna Briggs Institute Manual and an adapted Arksey & O'Malley's 6-stage framework, this review utilised the PRISMA-ScR checklist for structured reporting. Peer-reviewed research where young individuals (15-35 years) contributed to digital health intervention design was analysed. Systematic synthesis adhered to Braun & Clarke's Thematic Analysis Guidelines, mapping data to research queries and thematic framework. Eighteen articles were systematically synthesised, revealing seven main themes: digital tool, inquiry field, report aim, participatory activities, intervention attributes and behavioural change support. Seventeen distinctive digital health interventions were assessed, mostly within risk mitigation and mental health domains. Predominantly, interventions were web-based, with mental wellness websites emerging as the prevalent tool. User experience testing stood out as the primary reported outcome. Several innovative digital health interventions targeting youth have been identified. Platforms including social media, specialised apps, websites and video games are instrumental for health advice and clinical support dissemination, overcoming access and cost barriers. Participatory techniques are integral for the efficacy of digital health resources, encompassing youth aspirations and anticipations. Continued efforts will enrich comprehension of optimal practices in digital health promotion and intervention formulation.

Digital health interventions (DHIs) have frequently been highlighted as one way to respond to increasing levels of mental health problems in children and young people. Whilst many are developed to address existing mental health problems, there is also potential for DHIs to address prevention and early intervention. However, there are currently limitations in the design and reporting of the development, evaluation and implementation of preventive DHIs that can limit their adoption into real-world practice. This scoping review aimed to examine existing evidence-based DHI interventions and review how well the research literature described factors that researchers need to include in their study designs and reports to support real-world implementation. A search was conducted for relevant publications published from 2013 onwards. Twenty-one different interventions were identified from 30 publications, which took a universal (n = 12), selective (n = 3) and indicative (n = 15) approach to preventing poor mental health. Most interventions targeted adolescents, with only two studies including children aged ≤10 years. There was limited reporting of user co-design involvement in intervention development. Barriers and facilitators to implementation varied across the delivery settings, and only a minority reported financial costs involved in delivering the intervention. This review found that while there are continued attempts to design and evaluate DHIs for children and young people, there are several points of concern. More research is needed with younger children and those from poorer and underserved backgrounds. Co-design processes with children and young people should be recognised and reported as a necessary component within DHI research as they are an important factor in the design and development of interventions, and underpin successful adoption and implementation. Reporting the type and level of human support provided as part of the intervention is also important in enabling the sustained use and implementation of DHIs.

ObjectiveTo assess the effect of digital health (DH), biomarker feedback (BF) and nurse or midwife-led counselling (NoMC) interventions on abstinence in pregnant smokers during pregnancy and postpartum.SettingsAny healthcare setting servicing...

IntroductionMental disorders such as depression are common, and an estimated 264 million people are affected by them throughout the world. In recent years, studies on digital health interventions to treat...

Background: Adolescents are at a critical developmental stage marked by rapid cognitive, emotional, and social changes, making them highly susceptible to mental health issues. Recently, digital health interventions (DHIs) have emerged as innovative and scalable tools for promoting mental well-being in this population. Methods: This integrative review was conducted based on comprehensive literature searches of major academic databases, including PubMed, Scopus, Web of Science, and PsycINFO. Studies published between January 2010 and December 2024 were identified using keywords such as “adolescent mental health,” “digital health intervention,” “behavior change model,” “e-health,” “mobile mental health,” and “digital therapeutics.” The inclusion criteria comprised peer-reviewed studies on digital mental health interventions for adolescents that applied, fully or partially, a behavior change approach. Studies targeting adults, interventions without digital technology, the gray literature, and duplicate publications were excluded. Results: We examined intervention strategies based on developmental stage prevention, early intervention, and recovery and highlighted key digital components such as accessibility, anonymity, personalization, and continuous monitoring. Furthermore, we analyzed case studies from various countries, including Korea, the United Kingdom, Australia, and Japan, to identify best practices and contextual challenges. Conclusions: DHIs rooted in sound psychological theory and ethical design can complement school- and community-based interventions by offering effective personalized support. The practical implications and future directions are discussed.