Objective: The objective of this review is to assess and synthesize the available qualitative evidence on health professionals' experiences in screening for postpartum depression (PPD). Introduction: PPD is a significant public health problem. Clinical screening is essential to develop appropriate interventions to meet the needs of women and their families. The findings of this review have important implications for decision-making and policy development for continuous professional development programs that promote evidence-based PPD screening. Inclusion criteria: This review considered studies that explore the experiences of health professionals who screen for PPD in any geographic location at any health care facility, scenario, or setting. The review focused on qualitative data, including methods such as phenomenology, grounded theory, ethnography, action research, and feminist research. Methods: The review followed a 3-step search strategy in line with JBI methodology for systematic reviews of qualitative evidence. The databases searched included PubMed, CINAHL (EBSCOhost), Embase (Elsevier), Scopus, LILACS (BVS), ScienceDirect (Elsevier), PsycINFO (Ovid), Index Psi Journals (BVS-PSI), and PePsic (IPUSP). Unpublished studies were searched for in Google Scholar, Cybertesis, Dart-E, EthOS, and Open Access Theses and Dissertations (OATD). Two independent reviewers evaluated the included studies for methodological quality and extracted data using the JBI data extraction and synthesis tools. Studies published in English, Portuguese, and Spanish from database inception until October 2023 were included. Results: Twenty-four qualitative studies from 14 countries across 5 continents involving 392 health professionals were included. A total of 113 findings were extracted and grouped into 5 categories: i) education and training; ii) responsibility of PPD screening, referral, and follow-up: role of the job and work overload; iii) screening, referral, and follow-up; iv) disclosure, judgment, culture; v) and health system structure. Two synthesized findings evolved from these categories: i) The need for training and ongoing education, professional role, professional practice, and ways of caring in screening postpartum women for depressive symptoms; ii) External barriers, facilitating factors, and health system issues. Conclusions: Health professionals' experiences caring for women and families concerning PPD are influenced by their culture, practices, training, and worldview. Regular workshops and practical training sessions that emphasize the development of PPD-screening skills, particularly in recognizing subtle signs of depression and conducting culturally sensitive assessments, could be highly effective for health professionals. Policymakers should collaborate with health care professionals to develop and implement policies tailored to different contexts and cultures. Providing educational subsidies and ensuring monitoring and follow-up after PPD screening are fundamental for the sustainability of PPD screening and management.

This scoping review provides a broad overview of the existing literature on economic evaluations of preventive, screening, and treatment programmes for peripartum depression (PPD). PPD is one of the leading causes of disease-related disability among women. However, PPD often goes undiagnosed and untreated, with as many as half of cases not being identified. We followed the PICO-P (publication type) structure. Databases were searched from inception until 30 June 2023. The intervention stage in the studies was classified as prevention, screening, treatment, screening and treatment, and prevention and treatment. The health economics methods of the studies were divided into cost-effectiveness analysis, cost-utility analysis, cost-benefit analysis, cost-minimisation analysis, return of investment, and multiple. Ultimately, 38 studies were included for extraction and evaluation. Several interventions for PPD may be cost effective, including peer support, psychological therapies, and screening strategies using tools like the Edinburgh Postnatal Depression Scale (EPDS). However, study limitations include heterogeneity across studies, methodological limitations, and limited generalisability to diverse populations. The cost-effectiveness results of PPD interventions may differ across different health systems, partly due to differences in the amount and distribution of resources available. By implementing suggested policy recommendations, policymakers can significantly improve the identification, treatment, and prevention of PPD, ultimately improving the health and well-being of mothers, children, and families.

Abstract This scoping review provides a broad overview of the existing literature on economic evaluations of preventive, screening, and treatment programmes for peripartum depression (PPD). PPD is one of the leading causes of disease-related disability among women. However, PPD often goes undiagnosed and untreated, with as many as half of cases not being identified. We followed the PICO-P (publication type) structure. Databases were searched from inception until 30 June 2023. The intervention stage in the studies was classified as prevention, screening, treatment, screening and treatment, and prevention and treatment. The health economics methods of the studies were divided into cost-effectiveness analysis, cost-utility analysis, cost-benefit analysis, cost-minimisation analysis, return of investment, and multiple. Ultimately, 38 studies were included for extraction and evaluation. Several interventions for PPD may be cost effective, including peer support, psychological therapies, and screening strategies using tools like the Edinburgh Postnatal Depression Scale (EPDS). However, study limitations include heterogeneity across studies, methodological limitations, and limited generalisability to diverse populations. The cost-effectiveness results of PPD interventions may differ across different health systems, partly due to differences in the amount and distribution of resources available. By implementing suggested policy recommendations, policymakers can significantly improve the identification, treatment, and prevention of PPD, ultimately improving the health and well-being of mothers, children, and families.

Background: The diagnosis of depression in dementia patients leads to an increase in the burden of the disease. To treat depression in this patient group, antidepressants are frequently used; however, there is not any proof of their therapeutic effectiveness, and their use may be potentially harmful. This narrative review aims to summarize the existing evidence regarding the role of antidepressants in treating depression in dementia patients. Main text: A search was conducted in the PubMed, Excerpta Medica database (EMBASE), and Cochrane databases for randomized controlled trials and meta-analyses wherein antidepressants were given to dementia sufferers to address depression. Fifteen randomized controlled trials and seven meta-analyses were identified. Most well-designed blinded placebo-controlled trials reported a lack of effectiveness of antidepressants in treating depression in dementia patients. Among the seven metanalyses, two reported good efficacy of Selective serotonin reuptake inhibitors (SSRIs). However, two major Cochrane reviews reported little or no effectiveness and increased side effects of antidepressants in dementia patients. Conclusion: There is robust evidence regarding the lack of efficacy of antidepressants in treating depression in dementia patients. However, further well-designed Randomized controlled trials (RCTs,) using scales with good validity and reliability to diagnose depression in dementia patients, sufficient sample sizes, and detailed adverse effect profiles may help determine the rationale for their use.

Objective: Non-invasive brain stimulation (NIBS) is beneficial to adult patients with depression, but its safety and efficacy in combination with antidepressants in children and adolescents with depression are not clear. We conducted a preliminary meta-analysis to objectively evaluate its clinical effect and provide information for future research and clinical practice. Methods: PubMed, Cochrane Library, Embase, and Web of Science were searched systematically to find clinical trials published in English before April 11, 2023. Stata software was used for meta-analysis, and random or fixed effect models were used to combine effect sizes. Results: Nine studies were eligible and included (n = 393). No articles about children were included in the analysis. The results showed that the remission rate was 40% (95% confidence interval [CI]: 13% to 71%). The scores of Children's Depression Rating Scale (CRDS) and Hamilton's depression scale (HAMD) significantly decreased compared to baseline value (MD = -27.04, 95% CI: -30.95, -23.12 and MD = -12.78, 95% CI: -19.55 to -6.01). In addition, the incidence of all adverse events was 13% (95% CI: 5%, 23%), and all were minor pain-related events. Conclusion: The combination of NIBS and antidepressants has been shown to notably alleviate depressive symptoms in adolescents, offering a considerable level of safety. This therapeutic synergy is particularly effective in patients with major depressive disorder, where repetitive transcranial magnetic stimulation augmented with antidepressants can enhance the amelioration of depressive symptoms. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023442215, PROSPERO CRD42023442215.

Objective: To consolidate existing evidence on experiences and perspectives of healthcare providers involved in telemedicine services in long-term residential care. Methods: A scoping review was conducted. A systematic search for articles published in 2000-2021 was performed in CINAHL, Web of Science, PubMed, EMBASE and Scopus; further, relevant journals and grey literature websites were hand searched. Key search terms included 'telemedicine', 'telehealth' and 'nursing homes'. Results: Twenty-six articles were included. A narrative synthesis of evidence was conducted. The review identified four themes: (1) Presence of multidisciplinary care, (2) perceived usefulness of telemedicine, (3) perceived ease of use and (4) expanded role of nursing home staff. The presence of multidisciplinary care providers provided a wide range of telemedicine services to residents and promoted interprofessional collaboration between acute and long-term care. Telemedicine was perceived to increase timely onsite management by remote specialists, which enabled care quality improvement. However, technical problems associated with equipment usage reduced the ease of use of telemedicine. Concerns emerged from the expanded role of nursing home staff, which could negatively affect clinical decision-making and create medico-legal risks. Conclusion and implications: Telemedicine is valuable in distance-based care, especially in the current 2019 coronavirus pandemic, for supporting continuity of care to nursing home residents. This review provided evidence from multiple healthcare providers' perspectives. Further research can elucidate their specific roles and responsibilities in telemedicine and challenges in work processes, which will facilitate developing evidence-based competencies and improving technical infrastructure, thus contributing to personal and organisational readiness for telemedicine integration.

Aim: This meta-analysis aimed to compare the efficacy of in-person and digital mental health interventions in addressing Postpartum Depression. Methods: Following PRISMA guidelines, the protocol for this meta-analysis was registered at the Open Science Framework (Retrieved from osf.io/wy3s4). This meta analysis included Randomized Controlled Trials (RCTs) conducted between 2013 and 2023. A comprehensive literature search identified 35 eligible RCTs from various electronic databases. Inclusion criteria focused on pregnant women over 18 years old, encompassing antenatal depression and up to two years postpartum. Diagnostic interviews or Edinburgh Postnatal Depression Scale (EPDS) were used to establish PPD. Digital interventions included telephonic, app-based, or internet-based approaches, while in-person interventions involved face-to-face sessions. Results: The meta-analysis revealed a moderate overall effect size of -0.69, indicating that psychological interventions are effective for PPD. Digital interventions (g = -0.86) exhibited a higher mean effect size than in-person interventions (g = -0.55). Both types of interventions displayed substantial heterogeneity (digital: I2 = 99%, in-person: I2 = 92%), suggesting variability in intervention content, delivery methods, and participant characteristics. Conclusion: Digital mental health interventions show promise in addressing PPD symptoms, with a potentially greater effect size compared to in-person interventions. However, the high heterogeneity observed in both modalities underscores the need for further research to identify key drivers of success and tailor interventions to diverse populations. Additionally, the choice between digital and in-person interventions should consider individual needs and preferences. Ongoing research should further investigate and optimise intervention modalities to better serve pregnant women at risk of PPD.

The Psychiatric Pediatric Issues Task Force of the International League Against Epilepsy (ILAE) aimed to develop recommendations for the diagnosis and treatment of anxiety and depression in children and adolescents with epilepsy. The Task Force conducted a systematic review and identified two studies that assessed the accuracy of four screening measures for depression and anxiety symptoms compared with a psychiatric interview. Nine studies met the eligibility criteria for treatment of anxiety and depressive disorders or symptoms. The risk of bias and certainty of evidence were assessed. The evidence generated by this review followed by consensus where evidence was missing generated 47 recommendations. Those with a high level of agreement (≥80%) are summarized. Diagnosis: (1) Universal screening for anxiety and depression is recommended. Closer surveillance is recommended for children after 12 years, at higher risk (e.g., suicide-related behavior), with subthreshold symptoms, and experiencing seizure worsening or therapeutic modifications. (2) Multiple sources of ascertainment and a formal screening are recommended. Clinical interviews are recommended whenever possible. The healthcare provider must always explain that symptom recognition is essential to optimize treatment outcomes and reduce morbidity. (3) Questioning about the relationship between symptoms of anxiety or depression with seizure worsening/control and behavioral adverse effects of antiseizure medications is recommended. Treatment: (1) An individualized treatment plan is recommended. (2) For mild depression, active monitoring must be considered. (3) Referral to a mental health care provider must be considered for moderate to severe depression and anxiety. (4) Clinical care pathways must be developed. (5) Psychosocial interventions must be tailored and age-appropriate. (6) Healthcare providers must monitor children with epilepsy who are prescribed antidepressants, considering symptoms and functioning that may not improve simultaneously. (7) Caregiver education is essential to ensure treatment adherence. (8) A shared-care model involving all healthcare providers is recommended for children and adolescents with epilepsy and mental health disorders. We identified clinical decisions in the management of depression and anxiety that lack solid evidence and provide consensus-based guidance to address the care of children and adolescents with epilepsy.

Introduction: Depression and anxiety are significant contributors to maternal perinatal morbidity and a range of negative child outcomes. This systematic review and meta-analysis aimed to review and assess the diagnostic test accuracy of selected screening tools (Edinburgh Postnatal Depression Scale [EPDS], EPDS-3A, Patient Health Questionnaire [PHQ-9]-, PHQ-2, Matthey Generic Mood Question [MGMQ], Generalized Anxiety Disorder scale [GAD-7], GAD-2, and the Whooley questions) used to identify women with antenatal depression or anxiety in Western countries. Material and methods: On January 16, 2023, we searched 10 databases (CINAHL, Cochrane Library, CRD Database, Embase, Epistemonikos, International HTA Database, KSR Evidence, Ovid MEDLINE, PROSPERO and PsycINFO); the references of included studies were also screened. We included studies of any design that compared case-identification with a relevant screening tool to the outcome of a diagnostic interview based on the Diagnostic and Statistical Manual of Mental Disorders, fourth or fifth edition (DSM-IV or DSM-5), or the International Statistical Classification of Diseases and Related Health Problems, 10th revision (ICD-10). Diagnoses of interest were major depressive disorder and anxiety disorders. Two authors independently screened abstracts and full-texts for relevance and evaluated the risk of bias using QUADAS-2. Data extraction was performed by one person and checked by another team member for accuracy. For synthesis, a bivariate model was used. The certainty of evidence was assessed using Grading of Recommendations Assessment, Development and Evaluation (GRADE). Registration: PROSPERO CRD42021236333. Results: We screened 8276 records for eligibility and included 16 original articles reporting on diagnostic test accuracy: 12 for the EPDS, one article each for the GAD-2, MGMQ, PHQ-9, PHQ-2, and Whooley questions, and no articles for the EPDS-3A or GAD-7. Most of the studies had moderate to high risk of bias. Ten of the EPDS articles provided data for synthesis at cutoffs ≥10 to ≥14 for diagnosing major depressive disorder. Cutoff ≥10 gave the optimal combined sensitivity (0.84, 95% confidence interval [CI]: 0.75-0.90) and specificity (0.87, 95% CI: 0.79-0.92). Conclusions: Findings from the meta-analysis suggest that the EPDS alone is not perfectly suitable for detection of major depressive disorder during pregnancy. Few studies have evaluated the other instruments, therefore, their usefulness for identification of women with depression and anxiety during pregnancy remains very uncertain. At present, case-identification with any tool may best serve as a complement to a broader dialogue between healthcare professionals and their patients.

ObjectiveInternet-based cognitive behavior therapy (ICBT) may provide an accessible alternative to face-to-face treatment, but the evidence base in adolescents is limited. This systematic review and meta-analysis aims to comprehensively assess the efficacy of ICBT in addressing depression among adolescents.MethodsFour electronic databases were searched on June 8, 2023. Randomized controlled trials (RCTs) evaluating the efficacy of ICBT for depression in adolescents were included. The quality of the studies was assessed using the risk of bias tool recommended by the Cochrane Handbook. Furthermore, the GRADE approach was employed to gauge the certainty of the obtained evidence. Meta-analysis was conducted using RevMan 5.4, and Egger's test was implemented through Stata for assessment of potential publication bias.ResultsA total of 18 RCTs involving 1683 patients were included. In comparison to control groups like attention control, waiting list, and treatment as usual, our meta-analysis findings elucidate a significant reduction in depression scores (SMD = −0.42, 95 % CI: [−0.74, −0.11], p .05).ConclusionResults provide evidence of the efficacy of ICBT to reduce depressive and anxiety symptoms in adolescents. These research findings are of vital significance for the establishment of evidence-based treatment guidelines in the digital era.Trial registrationPROSPERO registration: CRD42021277562

Objective: Internet-based cognitive behavior therapy (ICBT) may provide an accessible alternative to face-to-face treatment, but the evidence base in adolescents is limited. This systematic review and meta-analysis aims to comprehensively assess the efficacy of ICBT in addressing depression among adolescents. Methods: Four electronic databases were searched on June 8, 2023. Randomized controlled trials (RCTs) evaluating the efficacy of ICBT for depression in adolescents were included. The quality of the studies was assessed using the risk of bias tool recommended by the Cochrane Handbook. Furthermore, the GRADE approach was employed to gauge the certainty of the obtained evidence. Meta-analysis was conducted using RevMan 5.4, and Egger's test was implemented through Stata for assessment of potential publication bias. Results: A total of 18 RCTs involving 1683 patients were included. In comparison to control groups like attention control, waiting list, and treatment as usual, our meta-analysis findings elucidate a significant reduction in depression scores (SMD = -0.42, 95 % CI: [-0.74, -0.11], p .05). Conclusion: Results provide evidence of the efficacy of ICBT to reduce depressive and anxiety symptoms in adolescents. These research findings are of vital significance for the establishment of evidence-based treatment guidelines in the digital era. Trial registration: PROSPERO registration: CRD42021277562.

OBJECTIVE: To evaluate the effectiveness of VR therapy (VRT) for symptoms related to social anxiety disorder (SAD), namely fear and avoidance of social interactions and performance situations (FASIP), fear of negative evaluation (FNE), anxiety and depression, a systematic review and meta-analysis were performed. METHODS: Medline, PubMed, Science Direct, Web of Science, CINAHL, PsychINFO and Scopus were searched to include randomised controlled trials of VRT for SAD that met the criteria. A total of 15 RCTs with 720 participants published between 1998 and 2022 were included. Hedge's g with a 95 % confidence interval (CI) was adopted to compute the effect sizes. RESULTS: Results showed no difference between the effect of VRT and CBT on FASIP, FNE, anxiety and depression and a large effect size for VRT versus the waitlist control group on FASIP (g = -1.170, 95 % CI: -2.056-0.283; p < 0.010). The moderator analysis demonstrated that VRT was superior to the controlled group in addressing FASIP, FNE and anxiety when the sample size was smaller than 50 and the number of sessions was five or fewer. LIMITATIONS: Differences in hardware, software and intervention duration for VRT across studies. CONCLUSION: This study confirmed the feasibility of VRT in alleviating the FASIP in patients with SAD, with the waitlist control group as a comparison. However, the effectiveness of VRT was not significant in FASIP, FNE, anxiety and depression compared to cognitive behavioural therapy (CBT). Additional social interaction scenarios should be developed in VRT, standardised hardware should be used and the proper length of exposure time to VR should be determined to enhance the efficacy of VRT.

Introduction: Personalization is a much-discussed approach to improve adherence and outcomes for Digital Mental Health interventions (DMHIs). Yet, major questions remain open, such as (1) what personalization is, (2) how prevalent it is in practice, and (3) what benefits it truly has. Methods: We address this gap by performing a systematic literature review identifying all empirical studies on DMHIs targeting depressive symptoms in adults from 2015 to September 2022. The search in Pubmed, SCOPUS and Psycinfo led to the inclusion of 138 articles, describing 94 distinct DMHIs provided to an overall sample of approximately 24,300 individuals. Results: Our investigation results in the conceptualization of personalization as purposefully designed variation between individuals in an intervention's therapeutic elements or its structure. We propose to further differentiate personalization by what is personalized (i.e., intervention content, content order, level of guidance or communication) and the underlying mechanism [i.e., user choice, provider choice, decision rules, and machine-learning (ML) based approaches]. Applying this concept, we identified personalization in 66% of the interventions for depressive symptoms, with personalized intervention content (32% of interventions) and communication with the user (30%) being particularly popular. Personalization via decision rules (48%) and user choice (36%) were the most used mechanisms, while the utilization of ML was rare (3%). Two-thirds of personalized interventions only tailored one dimension of the intervention. Discussion: We conclude that future interventions could provide even more personalized experiences and especially benefit from using ML models. Finally, empirical evidence for personalization was scarce and inconclusive, making further evidence for the benefits of personalization highly needed.

BACKGROUND: Older adults experience symptoms of depression, leading to suffering and increased morbidity and mortality. Although we have effective depression therapies, physical distancing and other public health measures have severely limited access to in-person interventions. OBJECTIVE: To describe the efficacy of virtual interventions for reducing symptoms of depression in community-dwelling older adults. DESIGN: Systematic review. SETTING: We searched MEDLINE, EMBASE, Cochrane Libraries, PsycINFO, and gray literature from inception to July 5, 2021. PARTICIPANTS AND INTERVENTIONS: We included randomized trials (RCTs) comparing the efficacy of virtual interventions to any other virtual intervention or usual care in community-dwelling adults ≥60 years old experiencing symptoms of depression or depression as an outcome. MEASUREMENTS: The primary outcome was change in symptoms of depression measured by any depression scale. RESULTS: We screened 12,290 abstracts and 830 full text papers. We included 15 RCTs (3100 participants). Five RCTs examined persons with depression symptoms at baseline and ten examined depression as an outcome only. Included studies demonstrated feasibility of interventions such as internet or telephone cognitive behavioral therapy with some papers showing statistically significant improvement in depressive symptoms. CONCLUSIONS: There is a paucity of studies examining virtual interventions in older adults with depression. Given difficulty in accessing in-person therapies in a pandemic and poor access for people living in rural and remote regions, there is an urgent need to explore efficacy, effectiveness, and implementation of virtual therapies.

Background: At the inter of old age and illness, older adults with life-threatening illnesses (LTI) are a group who often show resilience and seek validation of life, acceptance, and integration of past and now, even under the fear of loss, suffering, and dying evoked by life adversities. Life review has been widely conducted to help older adults enhance well-being and cope with burdens. Spirituality is an important part of an older adult' overall well-being, especially for those with LTI. However, few review studies examined the effectiveness of life review interventions on psychospiritual outcomes among this population. The aim of the study was to examine the effectiveness of life review on psychospiritual well-being among older adults with LTI.Methods: A systematic review with meta-analysis following the recommendations of the Cochrane Collaboration was conducted. Database searches included PubMed, PsycINFO, the Cochrane Library, the Campbell Library, EBSCO, CNKI, and the Airiti Library up to March 2020. Gray literature and reference lists from relevant articles were also searched and reviewed.Results: In total, 34 studies were included in the systematic review and the meta-analysis for outcomes of depression (n = 24), quality-of-life (QOL) (n = 10), anxiety (n = 5), life satisfaction (n = 3), mood (n = 3), apathy (n = 2), and general well-being (n = 2). Other psychospiritual outcome measures included spirituality, self-esteem, meaning in life, hope, and some multi-dimensional instruments. The studies greatly varied in program design, content, format, length, and more. Although with high heterogeneity, meta-analysis results demonstrated standardized mean differences in favor of life review in decreasing depression, anxiety, negative mood, and increasing positive mood and QOL compared with the control group.Conclusion: This review calls for including more psycho-spiritual well-being measures among interventions for older adults with LTI, as well as studies with rigorous designs in future research.

BACKGROUND: Patient education is a cardiac rehabilitation core component and is associated with improvements in self-management of patients with coronary heart disease (CHD). However, the efficacy of such interventions on psychosocial outcomes and relative impact of duration is less clear. OBJECTIVES: This study aimed to assess the efficacy of patient education for secondary prevention related to behaviour change and risk factor modification on psychological outcomes in CHD patients. DESIGN: A systematic review and meta-analysis. DATA SOURCES: PsycINFO, CINAHL, Embase, EmCare, MEDLINE, PubMed, and the Cochrane Central Register of Controlled Trials were searched from inception to February 2021. ELIGIBILITY CRITERIA FOR STUDY SELECTION: Randomized controlled trials (RCTs) evaluating patient education in CHD patients, or following myocardial infarction, or revascularization compared with usual care were identified. Outcomes included depression and anxiety at <6 and 6–12 months of follow-up. RESULTS: A total of 39 RCTs and 8748 participants were included. Patient education significantly improved participants’ depressive symptoms at <6 (SMD −0.82) and 6–12 months (SMD −0.38) of follow-up and anxiety level at <6 (SMD −0.90), and 6–12 months (SMD −0.32) of follow-up. Patient education also reduced the risk for having clinical depression by 35% and anxiety by 60%. Longer patient education of ≥3 months, resulted in more improvement in depressive symptoms at 6–12 months (coefficient −0.210) compared to shorter duration. CONCLUSIONS: Patient education for secondary prevention reduces anxiety and depressive symptoms in CHD patients. Regardless of intensity, longer patient education improves depression more than short duration. More information is needed on the relative impact of other intervention components.

Objectives: This study aimed to conduct a systematic review of cost-utility studies of internet-based and face-to-face cognitive behavioral therapy (CBT) for depression from childhood to adulthood and to examine their reporting and methodological quality. Methods: A structured search for cost-utility studies concerning CBT for depression was performed in 7 comprehensive databases from their inception to July 2020. Two reviewers independently screened the literature, abstracted data, and assessed quality using the Consolidated Health Economic Evaluation Reporting Standards and Quality of Health Economic Studies checklists. The primary outcome was the incremental cost-effectiveness ratio (ICER) across all studies. To make a relevant comparison of the ICERs across the identified studies, cost data were inflated to the year 2020 and converted into US dollars. Results: Thirty-eight studies were included in this review, of which 26 studies (68%) were deemed of high methodological quality and 12 studies (32%) of fair quality. Despite differences in study designs and settings, the conclusions of most included studies for adult depression were general agreement; they showed that face-to-face CBT monotherapy or combination therapy compared with antidepressants and usual care for adult depression were cost-effective from the societal, health system, or payer perspective (ICER $241 212.4/quality-adjusted life-year [QALY] to $33 032.47/QALY, time horizon 12-60 months). Internet-based CBT regardless of guided or unguided also has a significant cost-effectiveness advantage (ICER $37 717.52/QALY to $73 841.34/QALY, time horizon 3-36 months). In addition, CBT was cost-effective in preventing depression (ICER $23 932.07/QALY to $26 092.02/QALY, time horizon 9-60 months). Nevertheless, the evidence for the cost-effectiveness of CBT for children and adolescents was still ambiguous. Conclusions: Fair or high-quality evidence showed that CBT monotherapy or combination therapy for adult depression was cost-effective; whether CBT-related therapy was cost-effective for children and adolescents depression remains inconclusive.

Depression is one of the most prevalent mental disorders in older adults and leads to considerable decreases in health, well-being, and impaired functioning. Intervention studies have focused on the effects on symptomatic recovery, and most do not include functional recovery as an outcome. Reduction of functional limitations as a treatment goal in old-age psychiatry aligns with the values of older persons. The objective of this review was therefore to evaluate the effectiveness of late-life depression interventions on functional limitations. This systematic review identified 15 randomized controlled trials in which the effectiveness of different interventions on functional limitations was evaluated in patients with late-life depression. The interventions were categorized into four categories: psychological interventions, drug treatment, physical exercise, and collaborative care. Multicomponent and collaborative-care interventions appear to be the most promising for improvement of functional limitations, particularly in primary care and community-dwelling populations of older persons with symptoms of depression. There is, however, a lack of evidence regarding studies in specialized mental health care.

BACKGROUND: Mental health difficulties in children and adolescents are highly prevalent; however, only a minority receive adequate mental health care. Internet-delivered interventions offer a promising opportunity to increase access to mental health treatment. Research has demonstrated their effectiveness as a treatment for depression and anxiety in adults. This work provides an up-to-date examination of the available intervention options and their effectiveness for children and young people (CYP). OBJECTIVE: In this systematic review and meta-analysis, we aimed to determine the evidence available for the effectiveness of internet-delivered interventions for treating anxiety and depression in CYP. METHODS: Systematic literature searches were conducted throughout November 2020 using PubMed, PsycINFO, and EBSCO academic search complete electronic databases to find outcome trials of internet-delivered interventions treating symptoms of anxiety and/or depression in CYP by being either directly delivered to the CYP or delivered via their parents. Studies were eligible for meta-analysis if they were randomized controlled trials. Risk of bias and publication biases were evaluated, and Hedges g between group effect sizes evaluating intervention effects after treatment were calculated. Meta-analyses used random-effects models as per protocol. RESULTS: A total of 23 studies met the eligibility criteria for the systematic review, of which 16 were included in the meta-analyses, including 977 participants in internet-delivered treatment conditions and 1008 participants in control conditions across 21 comparisons. Random-effects models detected a significant small effect for anxiety symptoms (across 20 comparisons; Hedges g=-0.25, 95% CI -0.38 to -0.12; P<.001) and a small but not significant effect for depression (across 13 comparisons; Hedges g=-0.27, 95% CI -0.55 to 0.01; P=.06) in favor of internet-delivered interventions compared with control groups. Regarding secondary outcomes, there was a small effect of treatment across 9 comparisons for impaired functioning (Hedges g=0.52, 95% CI 0.24-0.80; P<.001), and 5 comparisons of quality of life showed no effect (Hedges g=-0.01, 95% CI -0.23 to 0.21; P=.94). CONCLUSIONS: The results show that the potential of internet-delivered interventions for young people with symptoms of anxiety or depression has not been tapped into to date. This review highlights an opportunity for the development of population-specific interventions and their research to expand our current knowledge and build an empirical base for digital interventions for CYP.

BACKGROUND: In this modern era, depression is one of the most prevalent mental disorder from which millions of individuals are affected today. The symptoms of depression are heterogeneous and often coincide with other disorders such as bipolar disorder, Parkinson's, schizophrenia, etc. It is a serious mental illness that may lead to other health problems if left untreated. Currently, identifying individuals with depression is totally based on the expertise of the clinician's experience. In order to assist clinicians in identifying the characteristics and classifying depressed people, different types of data modalities and machine learning techniques have been incorporated by researchers in this field. This study aims to find the answers of some important questions related to the trend of publications, data modality, machine learning models, dataset usage, pre-processing techniques and feature extraction and selection techniques that are prevalent and guide the direction of future research on depression diagnosis. METHODS: This systematic review was conducted using a broad range of articles from two major databases: IEEE Xplore and PubMed. Studies ranging from the years 2011 to April 2021 were retrieved from the databases resulting in a total of 590 articles (53 articles from IEEE Xplore database and 537 articles from PubMed database). Out of those, the articles which satisfied the defined inclusion criteria were investigated for further analysis. RESULTS: A total of 135 articles were identified and analysed for this review. A high growth in the number of publications has been observed in recent years. Furthermore, a significant diversity in the use of data modalities and machine learning classifiers has also been noted in this study. fMRI data with SVM classifier was found to be the most popular choice among researchers. In most of the studies, data scarcity and small sample size, particularly for neuroimaging data are major concerns. The use of identical data pre-processing tools for similar data modality can be seen. This study also provides statistical analysis of the current framework with respect to the modality, machine learning classifier, sample size and accuracy by applying one-way ANOVA and the Tukey - Kramer test. CONCLUSION: The results indicate that an effective fusion of machine learning techniques with a potential data modality has a promising future for assisting clinicians in automatic depression diagnosis.