JustKiddo/KiddosVault huggingface dataset:
Back to basics: could behavioural therapy be a good treatment option for youth depression? A critical review.

Recent findings from systematic reviews and primary research studies have shown more modest effects of cognitive behavioural therapy (CBT) for youth depression than previously shown, highlighting the need to further enhance the effectiveness of this intervention, or components of this intervention. Therefore, the aim of this review is to summarize the work that has been done to identify the different components of CBT and their varying effectiveness for young people with depression. Narrative overview of English language reviews/meta-analyses and primary intervention studies retrieved from searches of computerized databases as well as ancestry searches. Reviews of intervention studies of adults as well as young people with depression have shown that behavioural approaches are equally as effective as cognitive approaches in reducing depression symptoms. Post-hoc analyses of large studies in youth depression have also shown that behavioural approaches might be more suitable for young people. Behaviourally based approaches appear promising in treating youth depression; however, further research is required. This research will represent an essential step towards refining interventions for youth depression, and enabling interventions to be targeted to particular subgroups, to optimize their effectiveness.
Predictors and moderators of response to internet-delivered Interpersonal Psychotherapy and Cognitive Behavior Therapy for depression.

By identifying which predictors and moderators lead to beneficial outcomes, accurate selection of the best initial treatment will have significant benefits for depressed individuals. An automated, fully self-guided randomized controlled internet-delivered noninferiority trial was conducted comparing two new interventions (Interpersonal Psychotherapy [IPT; n=620] and Cognitive Behavioral Therapy [CBT; n=610]) to an active control intervention (MoodGYM; n=613) over a period of 4 weeks to spontaneous visitors of an internet-delivered therapy website (e-couch). A range of putative predictors and moderators (socio-demographic characteristics [age, gender, marital status, education level], clinical characteristics [depression/anxiety symptoms, disability, quality of life, medication use], skills [mastery and dysfunctional attitudes] and treatment preference) were assessed using internet-delivered self-report measures at baseline and immediately following treatment and at six months follow-up. Analyses were conducted using Mixed Model Repeated Measures (MMRM). Female gender, lower mastery and lower dysfunctional attitudes predicted better outcome at post-test and/or follow-up regardless of intervention. No overall differential effects for condition on depression as a function of outcome were found. However, based on time-specific estimates, a significant interaction effect of age was found. For younger people, internet-delivered IPT may be the preferred treatment choice, whereas older participants derive more benefits from internet-delivered CBT programs. Although the sample of participants was large, power to detect moderator effects was still lacking. Different e-mental health programs may be more beneficial for specific age groups. The findings raise important possibilities for increasing depression treatment effectiveness and improving clinical practice guidelines for depression treatment of different age groups.
Effectiveness of a self-management training for patients with chronic and treatment resistant anxiety or depressive disorders on quality of life, symptoms, and empowerment: results of a randomized controlled trial.

Anxiety and depressive disorders are common mental disorders. A substantial part of patients does not achieve symptomatic remission after treatment in specialized services. Current care as usual (CAU) for these patients consists of long-term supportive contacts. Termination of CAU is often not considered to be an option due to persistent symptoms, a low level of functioning, and the absence of further treatment options. A new intervention, ZemCAD, offers a program focused on rehabilitation and self-management, followed by referral back to primary care. This multicenter randomized controlled trial was carried out in twelve specialized outpatient mental health care services in the Netherlands. Consenting and eligible patients were invited for the MINI interview and the baseline questionnaire. Assessments were done at 6 (T1), 12 (T2) and 18 (T3) months post baseline. We used linear mixed model analysis (LMM) to ascertain the effectiveness of the ZemCAD group relative to the CAU group on quality of life, symptom severity and empowerment. In total 141 patients were included. The results at 18-month follow-up regarding to quality of life and symptom severity, showed no significant differences between the ZemCAD group and the CAU group, except on the 'social relationships'-domain (d=0.37). With regard to empowerment a significant difference between both groups was observed in the total empowerment score and one empowerment dimension (d=0.45 and d=0.39, respectively). After the ZemCAD intervention, more patients went from specialized outpatient mental health services back to a less specialized health care setting with less intensive treatment, such as primary care. The findings in this study suggest that patients with chronic and treatment-resistant anxiety and depression using the ZemCAD intervention improve on empowerment but not on symptom severity or quality of life. Since little is known about the effects of rehabilitation and self-management in patients with chronic and treatment resistant anxiety and depressive disorders, this is a first attempt to provide a proof-of-concept study in this under-researched but important field. Netherlands Trial Register: NTR3335 , registered 7 March 2012.
Predicting remission after internet-delivered psychotherapy in patients with depression using machine learning and multi-modal data.

This study applied supervised machine learning with multi-modal data to predict remission of major depressive disorder (MDD) after psychotherapy. Genotyped adult patients (n=894, 65.5% women, age 18-75 years) diagnosed with mild-to-moderate MDD and treated with guided Internet-based Cognitive Behaviour Therapy (ICBT) at the Internet Psychiatry Clinic in Stockholm were included (2008-2016). Predictor types were demographic, clinical, process (e.g., time to complete online questionnaires), and genetic (polygenic risk scores). Outcome was remission status post ICBT (cut-off ≤10 on MADRS-S). Data were split into train (60%) and validation (40%) given ICBT start date. Predictor selection employed human expertise followed by recursive feature elimination. Model derivation was internally validated through cross-validation. The final random forest model was externally validated against a (i) null, (ii) logit, (iii) XGBoost, and (iv) blended meta-ensemble model on the hold-out validation set. Feature selection retained 45 predictors representing all four predictor types. With unseen validation data, the final random forest model proved reasonably accurate at classifying post ICBT remission (Accuracy 0.656 [0.604, 0.705], P vs null model = 0.004; AUC 0.687 [0.631, 0.743]), slightly better vs logit (bootstrap D=1.730, P=0.084) but not vs XGBoost (D=0.463, P=0.643). Transparency analysis showed model usage of all predictor types at both the group and individual patient level. A new, multi-modal classifier for predicting MDD remission status after ICBT treatment in routine psychiatric care was derived and empirically validated. The multi-modal approach to predicting remission may inform tailored treatment, and deserves further investigation to attain clinical usefulness.
Acceptance and Commitment Therapy (ACT) to reduce depression: A systematic review and meta-analysis.

The aim of this study is to investigate the effectiveness of ACT on depression reduction and further examine the relationship between different follow-up periods, different degree of depression, and different age of patients through subgroup analysis. Relevant electronic databases were searched from Jan 2010 to Aug 2018, including CNKI, WANFANG, PubMed, EMBASE, Cochrane Library, PsycINFO. Two reviewers independently screened for eligible studies, extracted data, and assessed risk of bias of the included studies. The Cochrane Collaboration's bias assessment tool was used to evaluate the risk of bias for included studies, and Review Manager 5.3 Software for the meta-analysis RESULTS: 18 studies with 1,088 participants were included in the review. Four studies were rated as high-quality studies, and the remaining 14 studies were rated as moderate quality studies. ACT significantly reduced depression as compared with the control group [SMD = 0.59, 95% CI (0.38, 0.81)]. The subgroup analysis found a significant difference between ACT and control group after post-intervention, three months follow up, mild depression group and adults group, [SMD= 0.62, 95% CI (0.35, 0.90), [SMD= 0.55, 95% CI (0.23, 0.87)], [SMD= 0.65, 95% CI (0.40, 0.91)], [SMD= 0.52, 95% CI (0.33, 0.71)] respectively. The heterogeneity between included studies results in heterogeneity of the results. Most of the specific methods for random sequence generation and allocation concealment were not clear. The search results had limitations since only the published studies in Chinese and English were searched and lacked a search for gray and paper documents. The current study suggested that ACT was significantly for reducing depressive symptoms compared with the control group, especially at three months of follow-up, adult group and mild depression. More research is needed to investigate the difference effects for minor group, moderate and severe depression and long-term follow-up.
Psychological treatment of depression in institutional settings: A meta-analytic review.

Many depressed patients are treated in institutional settings. The number of studies focusing on psychotherapies for depressed patients in institutional settingsis limited, and only a few up-to-date meta-analyses have integrated the results of these studies. We conducted a meta-analysis of 32 randomized trials with 37 comparisons between psychotherapy and control conditions, examining the effects of psychotherapy for adult patients in institutional settings with depressive disorders. We found that psychotherapy had a significant, small to moderate effect on depressive symptoms (g=0.42; 95% CI: 0.29~0.56), with low to moderate heterogeneity (I2=33; 95% CI: 0~55). The effects remained small but significant after adjustment for publication bias (g=0.27; 95% CI: 0.12~0.42) and in the studies with low risk of bias (g=0.32; 95% CI: 0.11~0.52). The effects were largely retained at 9 to 15 months follow-up and still significant, again after adjustment for publication bias and in studies with low risk of bias. We found no significant difference across types of institutional settings, including psychiatric inpatient settings and nursing homes, although no studies with a low risk of bias were available in nursing homes. We included different types of institutional settings, although we did not find a significant difference between settings. The number of studies was small and risk of bias was high in a considerable number of trials. This meta-analysis provides evidence for a small to moderate and sustained effect of psychotherapy in patients in institutional settings with depression.
Individual differences in response to once versus twice weekly sessions of CBT and IPT for depression.

The Personalized Advantage Index (PAI) is a method to guide treatment selection by investigating which of two or more treatments is optimal for a given individual. Recently, it was shown that, on average, twice-weekly sessions of psychotherapy for depression lead to better outcomes compared to once-weekly sessions. The present study applied the PAI method to assess if subgroups of patients may have a differential response to psychotherapy frequency. Data came from a clinical trial (n = 200) randomizing depressed patients into different session frequencies: weekly sessions versus twice-weekly sessions. Machine-learning techniques were used to select pretreatment variables and develop a multivariable prediction model that calculated each patient's PAI. Differences in observed depression post-treatment scores (Beck Depression Inventory-II [BDI-II]) were tested between patients that received their PAI-indicated versus non-indicated session frequency. Between-group effect sizes (Cohen's d) were reported. We identified prognostic indicators generally associated with lower post-treatment BDI-II regardless of treatment assignment. In addition, we identified specific demographic and psychometric features associated with differential response to weekly- versus twice-weekly therapy sessions. Observed post-treatment BDI-II scores were significantly different between individuals receiving the PAI-indicated versus non-indicated session frequency (d = .37). Although a higher session frequency is more effective on average, different session frequencies seem beneficial for different patients. Future studies should externally validate these findings before they can be generalized to other settings. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
Defined symptom-change trajectories during acute-phase cognitive therapy for depression predict better longitudinal outcomes.

Acute-phase cognitive therapy (CT) is an efficacious treatment for major depressive disorder (MDD), but responders experience varying post-acute outcomes (e.g., relapse vs. recovery). Responders' symptom-change trajectories during response to acute-phase CT may predict longer term outcomes. We studied adult outpatients (N = 220) with recurrent MDD who responded to CT but had residual symptoms. Responders with linear (steady improvement), log-linear (quicker improvement earlier and slower later), one-step (a single, relatively large, stable improvement between adjacent assessments), or undefined (not linear, log-linear, or one-step) symptom trajectories were assessed every 4 months for 32 additional months. Defined (linear, log-linear, one-step) versus undefined acute-phase trajectories predicted lower depressive symptoms (d = 0.36), lower weekly probability of being in a major depressive episode (OR = 0.46), higher weekly probabilities of remission (OR = 1.93) and recovery (OR = 2.35), less hopelessness (d = 0.41), fewer dysfunctional attitudes (d = 0.31), and better social adjustment (d = 0.32) for 32 months after acute-phase CT. Differences among defined trajectory groups were nonsignificant. Responding to acute-phase CT with a defined trajectory (orderly pattern) of symptom reduction predicts better longer term outcomes, but which defined trajectory (linear, log-linear, or one-step) appears unimportant. Frequent measurement of depressive symptoms to identify un/defined CT response trajectories may clarify need for continued clinical monitoring and treatment.
Using moderator-based algorithms and electronic medical records to achieve optimal outcomes in depression.

Moderator-based treatment algorithms for depression are available to assist clinicians by providing a highly structured approach for the monitoring and assessment of medication efficacy and risks. Algorithm-based treatment strategies provide consistent care and improve outcomes, and patients treated with measurement-based care experience greater reduction of symptoms, faster remission rates, and better overall efficacy than care as usual. Additionally, electronic medical records have the potential to provide interactive guidance on optimal treatment choices during patient follow-up visits. This Webcast focuses on evaluating predictors of treatment response within the context of using algorithms and integrating this information into clinical practice via electronic medical records.
Evidence-based treatments for depression and anxiety versus treatment-as-usual: a meta-analysis of direct comparisons.

The aim of this study was to examine the relative efficacy of evidence-based treatments (EBTs) versus treatment-as-usual (TAU) in routine care for anxiety and depression in adults. A computerized search of studies that directly compared an EBT with a TAU was conducted. Meta-analytic methods were used to estimate effectiveness of EBTs relative to TAU and to model how various confounding variables impacted the results of this comparative research. A total of 14 studies were included in the final meta-analysis. There was significant heterogeneity in the TAU conditions, which ranged from unknown and/or minimal mental health treatment to psychotherapeutic interventions provided by trained professionals. Although the effect for EBT vs. TAU was significantly greater than zero, the effect for EBT vs. TAUs that were psychotherapeutic interventions was not statistically different from zero. Heterogeneity of TAU conditions in this meta-analysis highlight the importance of clarifying the research questions being asked when investigating and drawing conclusions from EBT-TAU comparisons. Researchers need to clarify if they are comparing an EBT to psychotherapeutic services in routine care or to minimal mental health services. Extant research on EBT versus TAU reveals that there is insufficient evidence to recommend the transportation of EBTs for anxiety and depression to routine care, particularly when the routine care involves psychotherapeutic services.
Evaluation of the online-based self-help programme "Selfapy" in patients with unipolar depression: study protocol for a randomized, blinded parallel group dismantling study.

Patients with mild to moderate depressive symptoms can have limited access to regular treatment; to ensure appropriate care, low-threshold treatment is needed. Effective online interventions could increase the supply of low-threshold treatment. Further research is needed to evaluate the effectiveness of online interventions. This study aims to evaluate the online-based self-help programme "Selfapy" on a sample of depressive subjects and compares the impact of the programme's unaccompanied version with its therapeutic accompanied version. A sample of 400 subjects that have a mild to severe depressive episode (Becks Depression Inventory - II and Hamilton Depression Scale) will be used. Subjects are randomly assigned to immediate access to an unaccompanied course (no support from psychologist via weekly phone calls), immediate access to an accompanied course (support from a psychologist via weekly phone calls) or a waiting list control group (access to the intervention after 24weeks). The intervention will last for a period of 12weeks. Depressive symptoms as a primary parameter, as well as various secondary parameters, such as life satisfaction, therapeutic relationships, social activation, self-esteem, attitudes towards Internet interventions and drop-out rates, are recorded at four different points in time: at baseline (T1), 6weeks after the start of the intervention (T2), 12weeks after the start of the intervention (T3) and 3months after completion of the treatment follow-up (T4). This randomized and controlled, blinded study will make use of a "dismantled" approach to adequately compare the accompanied and unaccompanied versions of the intervention. Positive and meaningful results are expected that could influence the acceptance and implementation of online interventions. German Clinical Trials Register DRKS00017191. Registered on 14 June 2019.
Arts for the Blues - a new creative psychological therapy for depression: a pilot workshop report.

Research over the last decade has identified both strengths and limitations in the use of routinely prescribed psychological therapies for depression. More recently, a focus on how creative art therapies and 'arts on prescription' are developing a growing recognition of their potential additional therapeutic mechanisms for depression. In an attempt to develop a new therapeutic intervention for depression, this research aligned both the evidence base surrounding the arts on prescription movement, collating these with client-reported helpful factors and preferences for therapeutic interventions. We developed a framework for a new pluralistic 'meta-approach' of therapy for depression, based on; an interdisciplinary thematic synthesis of active ingredients, considered specific features implemented in therapy, and client-reported helpful factors considered to be the broad features or experiences in therapy from both talking therapies and creative approaches. This framework contributed to the development of a pilot workshop entitled Arts for the Blues - A New Creative Psychological Therapy for Depression. An outline of, and evaluation from this workshop is presented in this article. Workshop participants were recruited via a voluntary workshop taking place at a North West Higher Education Institution Arts and Health conference ( N=15). The workshop was evaluated using quantitative measures, with results indicating around a 70% overall satisfaction, followed up with qualitative commentary around areas of good practice and areas for development. These included the positive reflection on the application of creative arts and the multimodal nature of the approach, while others reflected on the potential overwhelming nature of utilising multimodal methods for individuals with depression. Overall feedback from the pilot workshop is discussed in relation to prior research, giving credence to the potential for incorporating arts into therapy.
Computer-Assisted Cognitive-Behavior Therapy for Depression: A Systematic Review and Meta-Analysis.

To evaluate the efficacy of computer-assisted forms of cognitive-behavior therapy for major depressive disorder (MDD) and examine the role of clinician support and other factors that might affect outcomes. Ovid MEDLINE, PsycINFO, PubMed, and Scopus from their beginnings to July 18, 2016. Keywords were "randomized, controlled trials of computer-assisted cognitive-behavior therapy for depression" and "randomized, controlled trials of mobile apps for cognitive-behavior therapy of depression." Of 223 studies identified in the search, 183 were excluded yielding a sample of 40 randomized, controlled investigations of computer-assisted cognitive-behavior therapy (CCBT) for depression. Data were abstracted independently by two authors, and consensus was reached by discussion with a third author. The overall mean effect size for CCBT compared to control conditions was g = 0.502, a moderately large effect. Studies that provided support from a clinician or other person yielded significantly larger effects (g = 0.673) than studies in which no support was provided (g = 0.239). Completion rate and study setting also influenced outcomes. Lower mean effect sizes were observed in studies with lower completion rates and in studies conducted in primary care practices. CCBT with a modest amount of support from a clinician or other helping person was found to be efficacious with relatively large mean effect sizes on measures of depressive symptoms. Self-guided CCBT for depression was considerably less effective. Future research should focus on enhancing the implementation of CCBT, including evaluating the amount and type of support needed for effective delivery, methods to improve engagement with computer-assisted therapies, and ways to improve treatment outcome in primary care settings.