JustKiddo/KiddosVault huggingface dataset:
Psychoanalytic and cognitive-behavior therapy of chronic depression: study protocol for a randomized controlled trial.

Despite limited effectiveness of short-term psychotherapy for chronic depression, there is a lack of trials of long-term psychotherapy. Our study is the first to determine the effectiveness of controlled long-term psychodynamic and cognitive-behavioral (CBT) treatments and to assess the effects of preferential vs. randomized assessment. Patients are assigned to treatment according to their preference or randomized (if they have no clear preference). Up to 80 sessions of psychodynamic or psychoanalytically oriented treatments (PAT) or up to 60 sessions of CBT are offered during the first year in the study. After the first year, PAT can be continued according to the 'naturalistic' usual method of treating such patients within the system of German health care (normally from 240 up to 300 sessions over two to three years). CBT therapists may extend their treatment up to 80 sessions, but focus mainly maintenance and relapse prevention. We plan to recruit a total of 240 patients (60 per arm). A total of 11 assessments are conducted throughout treatment and up to three years after initiation of treatment. The primary outcome measures are the Quick Inventory of Depressive Symptoms (QIDS, independent clinician rating) and the Beck Depression Inventory (BDI) after the first year. We combine a naturalistic approach with randomized controlled trials(RCTs)to investigate how effectively chronic depression can be treated on an outpatient basis by the two forms of treatment reimbursed in the German healthcare system and we will determine the effects of treatment preference vs. randomization. http://www.controlled-trials.com/ISRCTN91956346.
A machine learning ensemble to predict treatment outcomes following an Internet intervention for depression.

Some Internet interventions are regarded as effective treatments for adult depression, but less is known about who responds to this form of treatment. An elastic net and random forest were trained to predict depression symptoms and related disability after an 8-week course of an Internet intervention, Deprexis, involving adults (N = 283) from across the USA. Candidate predictors included psychopathology, demographics, treatment expectancies, treatment usage, and environmental context obtained from population databases. Model performance was evaluated using predictive R2$\\lpar R_{{\\rm pred}}^2\\rpar\\comma $ the expected variance explained in a new sample, estimated by 10 repetitions of 10-fold cross-validation. An ensemble model was created by averaging the predictions of the elastic net and random forest. Model performance was compared with a benchmark linear autoregressive model that predicted each outcome using only its baseline. The ensemble predicted more variance in post-treatment depression (8.0% gain, 95% CI 0.8-15; total $R_{{\\rm pred}}^2 \\; $= 0.25), disability (5.0% gain, 95% CI -0.3 to 10; total $R_{{\\rm pred}}^2 \\; $= 0.25), and well-being (11.6% gain, 95% CI 4.9-19; total $R_{{\\rm pred}}^2 \\; $= 0.29) than the benchmark model. Important predictors included comorbid psychopathology, particularly total psychopathology and dysthymia, low symptom-related disability, treatment credibility, lower access to therapists, and time spent using certain Deprexis modules. A number of variables predict symptom improvement following an Internet intervention, but each of these variables makes relatively small contributions. Machine learning ensembles may be a promising statistical approach for identifying the cumulative contribution of many weak predictors to psychosocial depression treatment response.
The role of early symptom trajectories and pretreatment variables in predicting treatment response to cognitive behavioral therapy.

Research has focused on 2 different approaches to answering the question, "Which clients will respond to cognitive behavioral therapy (CBT) for depression?" One approach focuses on rates of symptom change within the 1st few weeks of treatment, whereas the 2nd approach looks to pretreatment client variables (e.g., hopelessness) to identify clients who are more or less likely to respond. The current study simultaneously examines these 2 lines of research (i.e., early symptom change and pretreatment variables) on the prediction of treatment outcome to determine the incremental utility of each potential predictor. The sample consists of 173 clients (66.47% female, 92.49% Caucasian), 18-64 years of age (M = 27.94, SD = 11.42), receiving treatment for depression and anxiety disorders in a CBT-oriented psychology training clinic. The rate of change in depressive symptom severity from baseline over the 1st 5 treatment sessions significantly predicted treatment outcome. A contemplative orientation to change and medication status positively predicted early symptom change, whereas student status negatively predicted early symptom change. Higher levels of baseline anxiety, precontemplative readiness to change, and global functioning predicted lower levels of depressive symptom severity at termination. The findings suggest achieving rapid symptom change early in treatment may be integral to overall success. As such, therapists may wish to target factors such as readiness to change to potentially maximize rapid rate of symptom change and subsequent treatment outcome.
Defining and Predicting Patterns of Early Response in a Web-Based Intervention for Depression.

Web-based interventions for individuals with depressive disorders have been a recent focus of research and may be an effective adjunct to face-to-face psychotherapy or pharmacological treatment. The aim of our study was to examine the early change patterns in Web-based interventions to identify differential effects. We applied piecewise growth mixture modeling (PGMM) to identify different latent classes of early change in individuals with mild-to-moderate depression (n=409) who underwent a CBT-based web intervention for depression. Overall, three latent classes were identified (N=409): Two early response classes (n=158, n=185) and one early deterioration class (n=66). Latent classes differed in terms of outcome (P<.001) and adherence (P=.03) in regard to the number of modules (number of modules with a duration of at least 10 minutes) and the number of assessments (P<.001), but not in regard to the overall amount of time using the system. Class membership significantly improved outcome prediction by 24.8% over patient intake characteristics (P<.001) and significantly added to the prediction of adherence (P=.04). These findings suggest that in Web-based interventions outcome and adherence can be predicted by patterns of early change, which can inform treatment decisions and potentially help optimize the allocation of scarce clinical resources.
Activity and subsequent depression levels: a causal analysis of behavioural activation group treatment with weekly assessments over 8 weeks.

Research on behavioural activation (BA) for depression assumes that increasing the rate of rewarding activities leads to reduced depressive mood. Although the efficacy of BA treatment has been convincingly demonstrated, assumptions referring to the mechanisms underlying this effect have not been tested decisively yet. The Behavioural Activation Scale for Depression and the Beck Depression Inventory II were administered over 8 weeks in 161 reliably diagnosed patients with unipolar depression who underwent BA treatment in groups. Time-lagged associations between behavioural activity on depression at subsequent assessment (1 week later) and vice versa were modelled (a) with multilevel models and (b) dynamic panel models that eliminate shared constant factors and allow for reverse causation (e.g., depression affecting subsequent activation in the model for activation on depression). Both activation and depression changed significantly (model-based within effect sizes for activation = .70 and for depression = -.75). Higher activation and lower depression predict each other over time (mixed-effects, time-lagged model), but this association disappears in dynamic causal models. Change patterns were only analysed within a time frame of 1 week; smaller time intervals were not investigated. There were no objective observational data of activity patterns. In the present study, increased behavioural activity and reduced depressive mood co-occur on the week scale. They predict each other across time, but this may be due to shared causes only.
Exercise and internet-based cognitive-behavioural therapy for depression: multicentre randomised controlled trial with 12-month follow-up.

Evidence-based treatment of depression continues to grow, but successful treatment and maintenance of treatment response remains limited. To compare the effectiveness of exercise, internet-based cognitive-behavioural therapy (ICBT) and usual care for depression. A multicentre, three-group parallel, randomised controlled trial was conducted with assessment at 3 months (post-treatment) and 12 months (primary end-point). Outcome assessors were masked to group allocation. Computer-generated allocation was performed externally in blocks of 36 and the ratio of participants per group was 1:1:1. In total, 945 adults with mild to moderate depression aged 18-71 years were recruited from primary healthcare centres located throughout Sweden. Participants were randomly assigned to one of three 12-week interventions: supervised group exercise, clinician-supported ICBT or usual care by a physician. The primary outcome was depression severity assessed by the Montgomery-Åsberg Depression Rating Scale (MADRS). The response rate at 12-month follow-up was 84%. Depression severity reduced significantly in all three treatment groups in a quadratic trend over time. Mean differences in MADRS score at 12 months were 12.1 (ICBT), 11.4 (exercise) and 9.7 (usual care). At the primary end-point the group × time interaction was significant for both exercise and ICBT. Effect sizes for both interventions were small to moderate. The long-term treatment effects reported here suggest that prescribed exercise and clinician-supported ICBT should be considered for the treatment of mild to moderate depression in adults.
Long-term effects of Internet-delivered cognitive behavioral therapy for depression in primary care - the PRIM-NET controlled trial.

Internet-delivered cognitive behavioral therapy (ICBT) is recommended as an efficient treatment alternative for depression in primary care. However, only few previous studies have been conducted at primary care centers (PCCs). We evaluated long-term effects of ICBT treatment for depression compared to treatment as usual (TAU) in primary care settings. Randomized controlled trial. Patients were enrolled at16 PCCs in south-west Sweden. Patients attending PCCs and diagnosed with depression (n=90). Patients were assessed by a primary care psychologist/psychotherapist and randomized to ICBT or TAU. The ICBT included an ICBT program consisting of seven modules and weekly therapist e-mail or telephone support during the 3-month treatment period. Questionnaires on depressive symptoms (BDI-II), quality of life (EQ-5D) and psychological distress (GHQ-12) were administered at baseline, with follow-ups at 3, 6 and 12 months. Antidepressants and sedatives use, sick leave and PCC contacts were registered. Intra-individual change in depressive symptoms did not differ between the ICBT group and the TAU group during the treatment period or across the follow-up periods. At 3-month follow-up, significantly fewer patients in ICBT were on antidepressants. However, the difference leveled out at later follow-ups. There were no differences between the groups concerning psychological distress, sick leave or quality of life, except for a larger improvement in quality of life in the TAU group during the 0- to 6-month period. ICBT with weekly minimal therapist support in primary care can be equally effective as TAU among depressed patients also over a 12-month period. The trial was registered in the Swedish Registry, researchweb.org, ID number 30511.
Personalized treatment of adult depression: medication, psychotherapy, or both? A systematic review.

Personalized medicine aims to identify which characteristics of an individual predict the outcome of a specific treatment, in order to get a better match between the individual and the treatment received. We conducted a systematic review and meta-analysis of randomized trials comparing two treatments directly in a group of patients with a specific characteristic. We searched relevant studies from bibliographical databases and included trials comparing (1) medication with psychotherapy, (2) medication with combined treatment, and (3) psychotherapy with combined treatment, in specific target groups (a) with a predefined sociodemographic characteristic, (b) a specific type of depression, (c) a comorbid mental or somatic disorder, or (d) from a specific setting (outpatients, primary care). We included 52 studies with 4,734 depressed patients. In these studies, 20 characteristics of the target groups were examined. The results showed that medication is probably the best treatment for dysthymia, and combined treatments are more effective in depressed outpatients, as well as in depressed older adults. However, in order to examine the 20 characteristics in the three categories of comparisons, 254 studies would be needed for having sufficient statistical power to show an effect size of g = 0.5. Currently, only 20.1% of these studies have been conducted. Although a considerable number of studies have compared medication, psychotherapy, and combined treatments, and some preliminary results are useful for deciding which treatment is best for which patient, the development of personalized treatment of depression has only just begun.
Economic evaluation of Internet-based problem-solving guided self-help treatment in comparison with enhanced usual care for depressed outpatients waiting for face-to-face treatment: A randomized controlled trial.

Previous studies have demonstrated the effectiveness of Internet-based interventions for depression in comparison with usual care. However, evidence on the cost-effectiveness of these interventions when delivered in outpatient clinics is lacking. The aim of this study was to estimate the cost-effectiveness of an Internet-based problem-solving guided self-help intervention in comparison with enhanced usual care for outpatients on a waiting list for face-to-face treatment for major depression. After the waiting list period, participants from both groups received the same treatment at outpatient clinics. An economic evaluation was performed alongside a randomized controlled trial with 12 months follow-up. Outcomes were improvement in depressive symptom severity (measured by CES-D), response to treatment and Quality-Adjusted Life-Years (QALYs). Statistical uncertainty around cost differences and incremental cost-effectiveness ratios were estimated using bootstrapping. Mean societal costs for the intervention group were €1579 higher than in usual care, but this was not statistically significant (95% CI - 1395 to 4382). Cost-effectiveness acceptability curves showed that the maximum probability of the intervention being cost-effective in comparison with usual care was 0.57 at a ceiling ratio of €15,000/additional point of improvement in CES-D, and 0.25 and 0.30 for an additional response to treatment and an extra QALY respectively, at a ceiling ratio of €30,000. Sensitivity analysis showed that from a mental healthcare provider perspective the probability of the intervention being cost-effective was 0.68 for a ceiling ratio of 0 €/additional unit of effect for the CES-D score, response to treatment and QALYs. As the ceiling ratio increased this probability decreased, because the mean costs in the intervention group were lower than the mean costs in the usual care group. The patients in the intervention group showed low adherence to the Internet-based treatment. It is possible that greater adherence would have led to larger clinical effects. Offering an Internet-based intervention to depressed outpatients on waiting list for face-to-face treatment was not considered cost-effective in comparison with enhanced usual care from a societal perspective. There was a high probability of the intervention being cost-effective in comparison with enhanced usual care from the perspective of the mental healthcare provider.
Online Mindfulness-Based Cognitive Behavioral Therapy Intervention for Youth With Major Depressive Disorders: Randomized Controlled Trial.

Approximately 70% of mental health disorders appear prior to 25 years of age and can become chronic when ineffectively treated. Individuals between 18 and 25 years old are significantly more likely to experience mental health disorders, substance dependencies, and suicidality. Treatment progress, capitalizing on the tendencies of youth to communicate online, can strategically address depressive disorders. We performed a randomized controlled trial (RCT) that compared online mindfulness-based cognitive behavioral therapy (CBT-M) combined with standard psychiatric care to standard psychiatric care alone in youth (18-30 years old) diagnosed with major depressive disorder. Forty-five participants were randomly assigned to CBT-M and standard care (n=22) or to standard psychiatric care alone (n=23). All participants were provided standard psychiatric care (ie, 1 session per month), while participants in the experimental group received an additional intervention consisting of the CBT-M online software program. Interaction with online workbooks was combined with navigation coaching delivered by phone and secure text messaging. In a two-level linear mixed-effects model intention-to-treat analysis, significant between-group differences were found for the Beck Depression Inventory-II score (difference -8.54, P=.01), Quick Inventory of Depressive Symptoms score (difference -4.94, P=.001), Beck Anxiety Inventory score (difference -11.29, P<.001), and Brief Pain Inventory score (difference -1.99, P=.03), while marginal differences were found for the Five Facet Mindfulness Questionnaire-Nonjudging subscale (difference -2.68, P=.05). These results confirm that youth depression can be effectively treated with online CBT-M that can be delivered with less geographic restriction. Clinical Trials.gov NCT03406052; https://www.clinicaltrials.gov/ct2/show/NCT03406052.
Family psychoeducation for major depressive disorder - study protocol for a randomized controlled trial.

Major depressive disorder has been shown to affect many domains of family life including family functioning. Conversely, the influence of the family on the course of the depression, including the risk of relapse, is one reason for targeting the family in interventions. The few studies conducted within this area indicate that family psychoeducation as a supplement to traditional treatment can effectively reduce the risk of relapse in patients with major depression as well as being beneficial for the relatives involved. However, the evidence is currently limited. This study will investigate the effect of family psychoeducation compared to social support on the course of the illness in patients with major depressive disorder. The study is designed as a dual center, two-armed, observer-blinded, randomized controlled trial. Relatives are randomized to participate in one of two conditions: either four sessions of manualized family psychoeducation or four sessions in a social support group led by a health care professional. Patients will not participate in the groups and will continue their treatment as usual. A total of 100 patients, each accompanied by one relative, will be recruited primarily from two outpatient clinics in the Capital Region of Denmark. The primary outcome is the occurrence of depressive relapse at 9-month follow-up defined as a score ≥7 on the Hamilton six-item subscale. Secondary outcomes will include time to relapse. It is hoped that the results from this study will help to clarify the mechanisms behind any beneficial changes due to family psychoeducation and provide information on the long-term effect of this intervention for both patient and relatives. If the results are positive, the family psychoeducation program may be suitable for implementation within a clinical setting. ClinicalTrials.gov Identifier: NCT02348827 , registered 5 January 2015.
Effectiveness of guided self-help in decreasing expressed emotion in family caregivers of people diagnosed with depression in Thailand: a randomised controlled trial.

High expressed emotion (EE) can extend the duration of illness and precipitate relapse; however, little evidence-based information is available to assist family caregivers of individuals with depression. In the present exploratory study, we examined the effectiveness of a cognitive behaviour therapy (CBT) based guided self-help (GSH) manual in decreasing EE in caregivers of people with depression, in Thailand. A parallel group randomised controlled trial was conducted, following CONSORT guidelines, with 54 caregivers who were allocated equally to GSH or control group (standard outpatient department support). In addition, both groups were contacted weekly by telephone. EE was assessed, using the Family Questionnaire (FQ), at baseline, post-test (Week 8) and follow-up (Week 12). FQ scores at baseline indicated that both groups had similar, though moderately high level of EE. However, between baseline and post-test EE scores decreased markedly in the intervention group, but in contrast, they increased slightly in the control group. Between post-test and follow-up, little change took place in the EE scores of either group. Overall, the intervention group recipients of GSH showed a significant decrease in EE whereas the control group recipients of standard outpatient department support reported a slight increase in EE. These findings provide preliminary evidence that GSH is beneficial in reducing EE in caregivers, which is advantageous to family members with depression and caregivers. The approach may be used as an adjunct to the limited outpatient department support given to caregivers by mental health professionals and, perhaps, to caregivers who do not attend these departments. Australian and New Zealand Clinical Trials Registry https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=366639. Registered 21 July 2014.