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The need for scalable delivery of mental health care services that are efficient and effective is now a major public health priority. Artificial intelligence (AI) tools have the potential to improve behavioral health care services by helping clinicians collect objective data on patients' progress, streamline their workflow, and automate administrative tasks. The aim of this study was to determine the feasibility, acceptability, and preliminary efficacy of an AI platform for behavioral health in facilitating better clinical outcomes for patients receiving outpatient therapy. The study was conducted at a community-based clinic in the United States. Participants were 47 adults referred for outpatient, individual cognitive behavioral therapy for a main diagnosis of a depressive or anxiety disorder. The platform provided by Eleos Health was compared to a treatment-as-usual (TAU) approach during the first 2 months of therapy. This AI platform summarizes and transcribes the therapy session, provides feedback to therapists on the use of evidence-based practices, and integrates these data with routine standardized questionnaires completed by patients. The information is also used to draft the session's progress note. Patients were randomized to receive either therapy provided with the support of an AI platform developed by Eleos Health or TAU at the same clinic. Data analysis was carried out based on an intention-to-treat approach from December 2022 to January 2023. The primary outcomes included the feasibility and acceptability of the AI platform. Secondary outcomes included changes in depression (Patient Health Questionnaire-9) and anxiety (Generalized Anxiety Disorder-7) scores as well as treatment attendance, satisfaction, and perceived helpfulness. A total of 72 patients were approached, of whom 47 (67%) agreed to participate. Participants were adults (34/47, 72% women and 13/47, 28% men; mean age 30.64, SD 11.02 years), with 23 randomized to the AI platform group, and 24 to TAU. Participants in the AI group attended, on average, 67% (mean 5.24, SD 2.31) more sessions compared to those in TAU (mean 3.14, SD 1.99). Depression and anxiety symptoms were reduced by 34% and 29% in the AI platform group versus 20% and 8% for TAU, respectively, with large effect sizes for the therapy delivered with the support of the AI platform. No group difference was found in 2-month treatment satisfaction and perceived helpfulness. Further, therapists using the AI platform submitted their progress notes, on average, 55 hours earlier than therapists in the TAU group (t=-0.73; P<.001). In this randomized controlled trial, therapy provided with the support of Eleos Health demonstrated superior depression and anxiety outcomes as well as patient retention, compared with TAU. These findings suggest that complementing the mental health services provided in community-based clinics with an AI platform specializing in behavioral treatment was more effective in reducing key symptoms than standard therapy. ClinicalTrials.gov NCT05745103; https://classic.clinicaltrials.gov/ct2/show/NCT05745103.

The efficacy of antidepressant medication has been shown empirically to be overestimated due to publication bias, but this has only been inferred statistically with regard to psychological treatment for depression. We assessed directly the extent of study publication bias in trials examining the efficacy of psychological treatment for depression. We identified US National Institutes of Health grants awarded to fund randomized clinical trials comparing psychological treatment to control conditions or other treatments in patients diagnosed with major depressive disorder for the period 1972-2008, and we determined whether those grants led to publications. For studies that were not published, data were requested from investigators and included in the meta-analyses. Thirteen (23.6%) of the 55 funded grants that began trials did not result in publications, and two others never started. Among comparisons to control conditions, adding unpublished studies (Hedges' g = 0.20; CI95% -0.11~0.51; k = 6) to published studies (g = 0.52; 0.37~0.68; k = 20) reduced the psychotherapy effect size point estimate (g = 0.39; 0.08~0.70) by 25%. Moreover, these findings may overestimate the \"true\" effect of psychological treatment for depression as outcome reporting bias could not be examined quantitatively. The efficacy of psychological interventions for depression has been overestimated in the published literature, just as it has been for pharmacotherapy. Both are efficacious but not to the extent that the published literature would suggest. Funding agencies and journals should archive both original protocols and raw data from treatment trials to allow the detection and correction of outcome reporting bias. Clinicians, guidelines developers, and decision makers should be aware that the published literature overestimates the effects of the predominant treatments for depression.

Cognitive therapy and antidepressant medication are both effective treatments for depression. Derubeis and colleagues propose common and divergent neural changes that might underlie the antidepressant effects of both types of treatment and that could explain the enduring, relapse-preventing effects of cognitive therapy. An interview with Rob DeRubeis for Neuropod is available for download . Depression is one of the most prevalent and debilitating of the psychiatric disorders. Studies have shown that cognitive therapy is as efficacious as antidepressant medication at treating depression, and it seems to reduce the risk of relapse even after its discontinuation. Cognitive therapy and antidepressant medication probably engage some similar neural mechanisms, as well as mechanisms that are distinctive to each. A precise specification of these mechanisms might one day be used to guide treatment selection and improve outcomes.

Depression is a common, debilitating, and costly disorder. Many patients request psychological therapy, but the best-evidenced therapy—cognitive behavioural therapy (CBT)—is complex and costly. A simpler therapy—behavioural activation (BA)—might be as effective and cheaper than is CBT. We aimed to establish the clinical efficacy and cost-effectiveness of BA compared with CBT for adults with depression. In this randomised, controlled, non-inferiority trial, we recruited adults aged 18 years or older meeting Diagnostic and Statistical Manual of Mental Disorders IV criteria for major depressive disorder from primary care and psychological therapy services in Devon, Durham, and Leeds (UK). We excluded people who were receiving psychological therapy, were alcohol or drug dependent, were acutely suicidal or had attempted suicide in the previous 2 months, or were cognitively impaired, or who had bipolar disorder or psychosis or psychotic symptoms. We randomly assigned participants (1:1) remotely using computer-generated allocation (minimisation used; stratified by depression severity [Patient Health Questionnaire 9 (PHQ-9) score of <19 vs ≥19], antidepressant use, and recruitment site) to BA from junior mental health workers or CBT from psychological therapists. Randomisation done at the Peninsula Clinical Trials Unit was concealed from investigators. Treatment was given open label, but outcome assessors were masked. The primary outcome was depression symptoms according to the PHQ-9 at 12 months. We analysed all those who were randomly allocated and had complete data (modified intention to treat [mITT]) and also all those who were randomly allocated, had complete data, and received at least eight treatment sessions (per protocol [PP]). We analysed safety in the mITT population. The non-inferiority margin was 1·9 PHQ-9 points. This trial is registered with the ISCRTN registry, number ISRCTN27473954. Between Sept 26, 2012, and April 3, 2014, we randomly allocated 221 (50%) participants to BA and 219 (50%) to CBT. 175 (79%) participants were assessable for the primary outcome in the mITT population in the BA group compared with 189 (86%) in the CBT group, whereas 135 (61%) were assessable in the PP population in the BA group compared with 151 (69%) in the CBT group. BA was non-inferior to CBT (mITT: CBT 8·4 PHQ-9 points [SD 7·5], BA 8·4 PHQ-9 points [7·0], mean difference 0·1 PHQ-9 points [95% CI −1·3 to 1·5], p=0·89; PP: CBT 7·9 PHQ-9 points [7·3]; BA 7·8 [6·5], mean difference 0·0 PHQ-9 points [–1·5 to 1·6], p=0·99). Two (1%) non-trial-related deaths (one [1%] multidrug toxicity in the BA group and one [1%] cancer in the CBT group) and 15 depression-related, but not treatment-related, serious adverse events (three in the BA group and 12 in the CBT group) occurred in three [2%] participants in the BA group (two [1%] patients who overdosed and one [1%] who self-harmed) and eight (4%) participants in the CBT group (seven [4%] who overdosed and one [1%] who self-harmed). We found that BA, a simpler psychological treatment than CBT, can be delivered by junior mental health workers with less intensive and costly training, with no lesser effect than CBT. Effective psychological therapy for depression can be delivered without the need for costly and highly trained professionals. National Institute for Health Research.

The Healthy Activity Programme (HAP), a brief behavioural intervention delivered by lay counsellors, enhanced remission over 3 months among primary care attendees with depression in peri-urban and rural settings in India. We evaluated the sustainability of the effects after treatment termination, the cost-effectiveness of HAP over 12 months, and the effects of the hypothesized mediator of activation on clinical outcomes. Primary care attendees aged 18-65 years screened with moderately severe to severe depression on the Patient Health Questionnaire 9 (PHQ-9) were randomised to either HAP plus enhanced usual care (EUC) (n = 247) or EUC alone (n = 248), of whom 95% completed assessments at 3 months, and 91% at 12 months. Primary outcomes were severity on the Beck Depression Inventory-II (BDI-II) and remission on the PHQ-9. HAP participants maintained the gains they showed at the end of treatment through the 12-month follow-up (difference in mean BDI-II score between 3 and 12 months = -0.34; 95% CI -2.37, 1.69; p = 0.74), with lower symptom severity scores than participants who received EUC alone (adjusted mean difference in BDI-II score = -4.45; 95% CI -7.26, -1.63; p = 0.002) and higher rates of remission (adjusted prevalence ratio [aPR] = 1.36; 95% CI 1.15, 1.61; p < 0.009). They also fared better on most secondary outcomes, including recovery (aPR = 1.98; 95% CI 1.29, 3.03; p = 0.002), any response over time (aPR = 1.45; 95% CI 1.27, 1.66; p < 0.001), higher likelihood of reporting a minimal clinically important difference (aPR = 1.42; 95% CI 1.17, 1.71; p < 0.001), and lower likelihood of reporting suicidal behaviour (aPR = 0.71; 95% CI 0.51, 1.01; p = 0.06). HAP plus EUC also had a marginal effect on WHO Disability Assessment Schedule score at 12 months (aPR = -1.58; 95% CI -3.33, 0.17; p = 0.08); other outcomes (days unable to work, intimate partner violence toward females) did not statistically significantly differ between the two arms. Economic analyses indicated that HAP plus EUC was dominant over EUC alone, with lower costs and better outcomes; uncertainty analysis showed that from this health system perspective there was a 95% chance of HAP being cost-effective, given a willingness to pay threshold of Intl$16,060-equivalent to GDP per capita in Goa-per quality-adjusted life year gained. Patient-reported behavioural activation level at 3 months mediated the effect of the HAP intervention on the 12-month depression score (β = -2.62; 95% CI -3.28, -1.97; p < 0.001). Serious adverse events were infrequent, and prevalence was similar by arm. We were unable to assess possible episodes of remission and relapse that may have occurred between our outcome assessment time points of 3 and 12 months after randomisation. We did not account for or evaluate the effect of mediators other than behavioural activation. HAP's superiority over EUC at the end of treatment was largely stable over time and was mediated by patient activation. HAP provides better outcomes at lower costs from a perspective covering publicly funded healthcare services and productivity impacts on patients and their families. ISRCTN registry ISRCTN95149997.

Various treatments are recommended as first-line options in practice guidelines for depression, but it is unclear which is most efficacious for a given person. Accurate individualized predictions of relative treatment effects are needed to optimize treatment recommendations for depression and reduce this disorder's vast personal and societal costs. We describe the protocol for a systematic review and individual participant data (IPD) network meta-analysis (NMA) to inform personalized treatment selection among five major empirically-supported depression treatments. We will use the METASPY database to identify randomized clinical trials that compare two or more of five treatments for adult depression: antidepressant medication, cognitive therapy, behavioral activation, interpersonal psychotherapy, and psychodynamic therapy. We will request IPD from identified studies. We will conduct an IPD-NMA and develop a multivariable prediction model that estimates individualized relative treatment effects from demographic, clinical, and psychological participant characteristics. Depressive symptom level at treatment completion will constitute the primary outcome. We will evaluate this model using a range of measures for discrimination and calibration, and examine its potential generalizability using internal-external cross-validation. We describe a state-of-the-art method to predict personalized treatment effects based on IPD from multiple trials. The resulting prediction model will need prospective evaluation in mental health care for its potential to inform shared decision-making. This study will result in a unique database of IPD from randomized clinical trials around the world covering five widely used depression treatments, available for future research.

Depression is an eminently treatable disorder, although estimates of treatment efficacy have been inflated by publication bias. Patients with less severe depressions respond to even nonspecific interventions, whereas patients with more severe depressions require treatments that mobilize specific mechanisms. The cognitive and behavior therapies can be as efficacious as medications in the treatment of severe depression and have an enduring effect that medications lack. Medications may interfere with those enduring effects when added in combination and may prolong the life of the underlying episode when used alone. Thus the cognitive behavioral interventions might be the optimal first-line treatments for depression.

The randomized controlled trial (RCT) provides critical support for evidence-based practice using psychological interventions. The control condition is the principal method of removing the influence of unwanted variables in RCTs. There is little agreement or consistency in the design and construction of control conditions. Because control conditions have variable effects, the results of RCTs can depend as much on control condition selection as on the experimental intervention. The aim of this paper is to present a framework for the selection and design of control conditions for these trials. Threats to internal validity arising from modern RCT methodology are reviewed and reconsidered. The strengths and weaknesses of several categories of control conditions are examined, including the ones that are under experimental control, the ones that are under the control of clinical service providers, and no-treatment controls. Considerations in the selection of control conditions are discussed and several recommendations are proposed. The aim of this paper is to begin to define principles by which control conditions can be selected or developed in a manner that can assist both investigators and grant reviewers.

Situational factors can influence cognitive performance and should be considered for conducting cognitive assessments. The objective of this project was to develop a checklist for Cognitive Assessment Requirements (CARE) to identify these situational factors before conducting cognitive assessments and account for them. This study employed a four-round Delphi approach involving 22 experts to identify situational factors that can impact cognitive assessment results. The development of a robust and well-balanced checklist was guided by a consensus-driven approach, which considered metrics such as Interquartile Deviation (IQD) (> 1.00), Percentage of Positive Responses (PPR, above 60%), and mean importance ratings (< 3 on a 5-point Likert scale) to assess both degree of agreement and item importance. Consensus was reached, leading to a 14-item checklist to evaluate cognitive assessment requirements. These items were categorized into six groups: Acute Illness or Physical Discomfort, Medication Effects and Substance Use, Sleep Quality and Fatigue, Emotional State, Language factors, and Environmental factors. The CARE can be employed prior to cognitive assessments to identify situational factors of relevance to the individual client, thereby creating a more favorable environment for cognitive evaluation, and enhancing the reliability of the assessment findings. Furthermore, the CARE can help determine the level of confidence in the results by assessing whether the conditions are conducive to testing or if situational factors may undermine the validity of the evaluation.

Prior studies have independently reported associations between major depressive disorder (MDD), elevated cortisol concentrations, early adverse events and region-specific decreases in grey matter volume, but the relationships among these variables are unclear. In the present study, we sought to evaluate the relationships between grey matter volume, early adverse events and cortisol levels in MDD. Grey matter volume was compared between 19 controls and 19 individuals with MDD using voxel-based morphometry. A history of early adverse events was assessed using the Childhood Trauma Questionnaire. Subjects also provided salivary cortisol samples. Depressed patients showed decreased grey matter volume in the rostral ACC as compared to controls. Rostral ACC volume was inversely correlated with both cortisol and early adverse events. These findings suggest a key relationship between ACC morphology, a history of early adverse events and circulating cortisol in the pathophysiology of MDD.