Psychotherapy effectiveness for major depression: a randomized trial in a Finnish community

A systematic meta-review of patient-level predictors of psychological therapy outcome in major depressive disorder

BACKGROUND

Psychological therapies are effective for treating major depressive disorder, but current clinical guidelines do not provide guidance on the personalization of treatment choice. Established predictors of psychotherapy treatment response could help inform machine learning models aimed at predicting individual patient responses to different therapy options. Here we sought to comprehensively identify known predictors.

METHODS

EMBASE, Medline, PubMed, PsycINFO were searched for systematic reviews with or without meta-analysis published until June 2020 to identify individual patient-level predictors of response to psychological treatments. 3113 abstracts were identified and 300 articles assessed. We qualitatively synthesized our findings by predictor category (sociodemographic; symptom profile; social support; personality features; affective, cognitive, and behavioural; comorbidities; neuroimaging; genetics) and treatment type. We used the AMSTAR 2 to evaluate the quality of included reviews.

RESULTS

Following screening and full-text assessment, 27 systematic reviews including 12 meta-analyses were eligible for inclusion. 74 predictors emerged for various psychological treatments, primarily cognitive behavioural therapy, interpersonal therapy, and mindfulness-based cognitive therapy.

LIMITATIONS

A paucity of studies examining predictors of psychological treatment outcome, as well as methodological heterogeneities and publication biases limit the strength of the identified predictors.

CONCLUSIONS

The synthesized predictors could be used to supplement clinical decision-making in selecting psychological therapies based on individual patient characteristics. These predictors could also be used as a priori input features for machine learning models aimed at predicting a given patient's likelihood of response to different treatment options for depression, and may contribute toward the development of patient-specific treatment recommendations in clinical guidelines.

The 2020 Royal Australian and New Zealand College of Psychiatrists clinical practice guidelines for mood disorders

OBJECTIVES

To provide advice and guidance regarding the management of mood disorders, derived from scientific evidence and supplemented by expert clinical consensus to formulate s that maximise clinical utility.

METHODS

Articles and information sourced from search engines including PubMed, EMBASE, MEDLINE, PsycINFO and Google Scholar were supplemented by literature known to the mood disorders committee (e.g. books, book chapters and government reports) and from published depression and bipolar disorder guidelines. Relevant information was appraised and discussed in detail by members of the mood disorders committee, with a view to formulating and developing consensus-based recommendations and clinical guidance. The guidelines were subjected to rigorous consultation and external review involving: expert and clinical advisors, key stakeholders, professional bodies and specialist groups with interest in mood disorders.

RESULTS

The Royal Australian and New Zealand College of Psychiatrists mood disorders clinical practice guidelines 2020 (MDcpg²⁰²⁰) provide up-to-date guidance regarding the management of mood disorders that is informed by evidence and clinical experience. The guideline is intended for clinical use by psychiatrists, psychologists, primary care physicians and others with an interest in mental health care.

CONCLUSION

The MDcpg²⁰²⁰ builds on the previous 2015 guidelines and maintains its joint focus on both depressive and bipolar disorders. It provides up-to-date recommendations and guidance within an evidence-based framework, supplemented by expert clinical consensus.

MOOD DISORDERS COMMITTEE

Gin S Malhi (Chair), Erica Bell, Darryl Bassett, Philip Boyce, Richard Bryant, Philip Hazell, Malcolm Hopwood, Bill Lyndon, Roger Mulder, Richard Porter, Ajeet B Singh and Greg Murray.

Interventions to improve return to work in depressed people

BACKGROUND

Work disability such as sickness absence is common in people with depression.

OBJECTIVES

To evaluate the effectiveness of interventions aimed at reducing work disability in employees with depressive disorders.

SEARCH METHODS

We searched CENTRAL (The Cochrane Library), MEDLINE, Embase, CINAHL, and PsycINFO until April 4th 2020.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) and cluster-RCTs of work-directed and clinical interventions for depressed people that included days of sickness absence or being off work as an outcome. We also analysed the effects on depression and work functioning.

DATA COLLECTION AND ANALYSIS

Two review authors independently extracted the data and rated the certainty of the evidence using GRADE. We used standardised mean differences (SMDs) or risk ratios (RR) with 95% confidence intervals (CI) to pool study results in studies we judged to be sufficiently similar.  MAIN RESULTS: In this update, we added 23 new studies. In total, we included 45 studies with 88 study arms, involving 12,109 participants with either a major depressive disorder or a high level of depressive symptoms. Risk of bias The most common types of bias risk were detection bias (27 studies) and attrition bias (22 studies), both for the outcome of sickness absence. Work-directed interventions Work-directed interventions combined with clinical interventions A combination of a work-directed intervention and a clinical intervention probably reduces days of sickness absence within the first year of follow-up (SMD -0.25, 95% CI -0.38 to -0.12; 9 studies; moderate-certainty evidence). This translates back to 0.5 fewer (95% CI -0.7 to -0.2) sick leave days in the past two weeks or 25 fewer days during one year (95% CI -37.5 to -11.8). The intervention does not lead to fewer persons being off work beyond one year follow-up (RR 0.96, 95% CI 0.85 to 1.09; 2 studies, high-certainty evidence). The intervention may reduce depressive symptoms (SMD -0.25, 95% CI -0.49 to -0.01; 8 studies, low-certainty evidence) and probably has a small effect on work functioning (SMD -0.19, 95% CI -0.42 to 0.06; 5 studies, moderate-certainty evidence) within the first year of follow-up.  Stand alone work-directed interventions A specific work-directed intervention alone may increase the number of sickness absence days compared with work-directed care as usual (SMD 0.39, 95% CI 0.04 to 0.74; 2 studies, low-certainty evidence) but probably does not lead to more people being off work within the first year of follow-up (RR 0.93, 95% CI 0.77 to 1.11; 1 study, moderate-certainty evidence) or beyond (RR 1.00, 95% CI 0.82 to 1.22; 2 studies, moderate-certainty evidence). There is probably no effect on depressive symptoms (SMD -0.10, 95% -0.30 CI to 0.10; 4 studies, moderate-certainty evidence) within the first year of follow-up and there may be no effect on depressive symptoms beyond that time (SMD 0.18, 95% CI -0.13 to 0.49; 1 study, low-certainty evidence). The intervention may also not lead to better work functioning (SMD -0.32, 95% CI -0.90 to 0.26; 1 study, low-certainty evidence) within the first year of follow-up.   Psychological interventions A psychological intervention, either face-to-face, or an E-mental health intervention, with or without professional guidance, may reduce the number of sickness absence days, compared with care as usual (SMD -0.15, 95% CI -0.28 to -0.03; 9 studies, low-certainty evidence). It may also reduce depressive symptoms (SMD -0.30, 95% CI -0.45 to -0.15, 8 studies, low-certainty evidence). We are uncertain whether these psychological interventions improve work ability (SMD -0.15 95% CI -0.46 to 0.57; 1 study; very low-certainty evidence). Psychological intervention combined with antidepressant medication Two studies compared the effect of a psychological intervention combined with antidepressants to antidepressants alone. One study combined psychodynamic therapy with tricyclic antidepressant (TCA) medication and another combined telephone-administered cognitive behavioural therapy (CBT) with a selective serotonin reuptake inhibitor (SSRI). We are uncertain if this intervention reduces the number of sickness absence days (SMD -0.38, 95% CI -0.99 to 0.24; 2 studies, very low-certainty evidence) but found that there may be no effect on depressive symptoms (SMD -0.19, 95% CI -0.50 to 0.12; 2 studies, low-certainty evidence). Antidepressant medication only Three studies compared the effectiveness of SSRI to selective norepinephrine reuptake inhibitor (SNRI) medication on reducing sickness absence and yielded highly inconsistent results. Improved care Overall, interventions to improve care did not lead to fewer days of sickness absence, compared to care as usual (SMD -0.05, 95% CI -0.16 to 0.06; 7 studies, moderate-certainty evidence). However, in studies with a low risk of bias, the intervention probably leads to fewer days of sickness absence in the first year of follow-up (SMD -0.20, 95% CI -0.35 to -0.05; 2 studies; moderate-certainty evidence). Improved care probably leads to fewer depressive symptoms (SMD -0.21, 95% CI -0.35 to -0.07; 7 studies, moderate-certainty evidence) but may possibly lead to a decrease in work-functioning (SMD 0.5, 95% CI 0.34 to 0.66; 1 study; moderate-certainty evidence). Exercise Supervised strength exercise may reduce sickness absence, compared to relaxation (SMD -1.11; 95% CI -1.68 to -0.54; one study, low-certainty evidence). However, aerobic exercise probably is not more effective than relaxation or stretching (SMD -0.06; 95% CI -0.36 to 0.24; 2 studies, moderate-certainty evidence). Both studies found no differences between the two conditions in depressive symptoms.

AUTHORS' CONCLUSIONS

A combination of a work-directed intervention and a clinical intervention probably reduces the number of sickness absence days, but at the end of one year or longer follow-up, this does not lead to more people in the intervention group being at work. The intervention may also reduce depressive symptoms and probably increases work functioning more than care as usual. Specific work-directed interventions may not be more effective than usual work-directed care alone. Psychological interventions may reduce the number of sickness absence days, compared with care as usual. Interventions to improve clinical care probably lead to lower sickness absence and lower levels of depression, compared with care as usual. There was no evidence of a difference in effect on sickness absence of one antidepressant medication compared to another. Further research is needed to assess which combination of work-directed and clinical interventions works best.

A Randomized Clinical Trial Showing Persisting Reductions in Depressive Symptoms in HIV-Infected Rural Adults Following Brief Telephone-Administered Interpersonal Psychotherapy

Background

Rural areas account for 5% to 7% of all HIV infections in the USA, and rural people living with HIV (PLHIV) are 1.3 times more likely to receive a depression diagnosis than their urban counterparts. A previous analysis from our randomized clinical trial found that nine weekly sessions of telephone-administered interpersonal psychotherapy (tele-IPT) reduced depressive symptoms and interpersonal problems in rural PLHIV from preintervention through postintervention significantly more than standard care but did not increase perceived social support compared to standard care.

Purpose

To assess tele-IPT's enduring effects at 4- and 8-month follow-up in this cohort.

Methods

Tele-IPT's long-term depression treatment efficacy was assessed through Beck Depression Inventory self-administrations at 4 and 8 months. Using intention-to-treat and completer-only approaches, mixed models repeated measures, and Cohen's d assessed maintenance of acute treatment gains.

Results

Intention-to-treat analyses found fewer depressive symptoms in tele-IPT patients than standard care controls at 4 (d = .41; p < .06) and 8-month follow-up (d =.47; p < .05). Completer-only analyses found similar patterns, with larger effect sizes. Tele-IPT patients used crisis hotlines less frequently than standard care controls at postintervention and 4-month follow-up (ps < .05).

Conclusions

Tele-IPT provides longer term depression relief in depressed rural PLHIV. This is also the first controlled trial to find that IPT administered over the telephone provides long-term depressive symptom relief to any clinical population.

Trial Registration

ClinicalTrials.gov Identifier: NCT02299453.

Identification of Patients in Need of Advanced Care for Depression Using Data Extracted From a Statewide Health Information Exchange: A Machine Learning Approach

Background

As the most commonly occurring form of mental illness worldwide, depression poses significant health and economic burdens to both the individual and community. Different types of depression pose different levels of risk. Individuals who suffer from mild forms of depression may recover without any assistance or be effectively managed by primary care or family practitioners. However, other forms of depression are far more severe and require advanced care by certified mental health providers. However, identifying cases of depression that require advanced care may be challenging to primary care providers and health care team members whose skill sets run broad rather than deep.

Objective

This study aimed to leverage a comprehensive range of patient-level diagnostic, behavioral, and demographic data, as well as past visit history data from a statewide health information exchange to build decision models capable of predicting the need of advanced care for depression across patients presenting at Eskenazi Health, the public safety net health system for Marion County, Indianapolis, Indiana.

Methods

Patient-level diagnostic, behavioral, demographic, and past visit history data extracted from structured datasets were merged with outcome variables extracted from unstructured free-text datasets and were used to train random forest decision models that predicted the need of advanced care for depression across (1) the overall patient population and (2) various subsets of patients at higher risk for depression-related adverse events; patients with a past diagnosis of depression; patients with a Charlson comorbidity index of ≥1; patients with a Charlson comorbidity index of ≥2; and all unique patients identified across the 3 above-mentioned high-risk groups.

Results

The overall patient population consisted of 84,317 adult (aged ≥18 years) patients. A total of 6992 (8.29%) of these patients were in need of advanced care for depression. Decision models for high-risk patient groups yielded area under the curve (AUC) scores between 86.31% and 94.43%. The decision model for the overall patient population yielded a comparatively lower AUC score of 78.87%. The variance of optimal sensitivity and specificity for all decision models, as identified using Youden J Index, is as follows: sensitivity=68.79% to 83.91% and specificity=76.03% to 92.18%.

Conclusions

This study demonstrates the ability to automate screening for patients in need of advanced care for depression across (1) an overall patient population or (2) various high-risk patient groups using structured datasets covering acute and chronic conditions, patient demographics, behaviors, and past visit history. Furthermore, these results show considerable potential to enable preventative care and can be easily integrated into existing clinical workflows to improve access to wraparound health care services.

Is psychotherapy effective? A re-analysis of treatments for depression

AimsThe aim of this study was to reanalyse the data from Cuijpers et al.'s (2018) meta-analysis, to examine Eysenck's claim that psychotherapy is not effective. Cuijpers et al., after correcting for bias, concluded that the effect of psychotherapy for depression was small (standardised mean difference, SMD, between 0.20 and 0.30), providing evidence that psychotherapy is not as effective as generally accepted.

METHODS

The data for this study were the effect sizes included in Cuijpers et al. (2018). We removed outliers from the data set of effects, corrected for publication bias and segregated psychotherapy from other interventions. In our study, we considered wait-list (WL) controls as the most appropriate estimate of the natural history of depression without intervention.

RESULTS

The SMD for all interventions and for psychotherapy compared to WL controls was approximately 0.70, a value consistent with past estimates of the effectiveness of psychotherapy. Psychotherapy was also more effective than care-as-usual (SMD = 0.31) and other control groups (SMD = 0.43).

CONCLUSIONS

The re-analysis reveals that psychotherapy for adult patients diagnosed with depression is effective.