Long-term outcomes of once weekly v. twice weekly sessions of cognitive behavioral therapy and interpersonal psychotherapy for depression.

BACKGROUND: Twice weekly sessions of cognitive behavioral therapy (CBT) and interpersonal psychotherapy (IPT) for major depressive disorder (MDD) lead to less drop-out and quicker and better response compared to once weekly sessions at posttreatment, but it is unclear whether these effects hold over the long run. AIMS: Compare the effects of twice weekly v. weekly sessions of CBT and IPT for depression up to 24 months since the start of treatment. METHODS: Using a 2 × 2 factorial design, this multicentre study randomized 200 adults with MDD to once or twice weekly sessions of CBT or IPT over 16-24 weeks, up to a maximum of 20 sessions. Main outcome measures were depression severity, measured with the Beck Depression Inventory-II and the Longitudinal Interval Follow-up Evaluation. Intention-to-treat analyses were conducted. RESULTS: Compared with patients who received once weekly sessions, patients who received twice weekly sessions showed a significant decrease in depressive symptoms up through month 9, but this effect was no longer apparent at month 24. Patients who received CBT showed a significantly larger decrease in depressive symptoms up to month 24 compared to patients who received IPT, but the between-group effect size at month 24 was small. No differential effects between session frequencies or treatment modalities were found in response or relapse rates. CONCLUSIONS: Although a higher session frequency leads to better outcomes in the acute phase of treatment, the difference in depression severity dissipated over time and there was no significant difference in relapse.

Cost-effectiveness of twice-weekly versus once-weekly sessions of cognitive-behavioural therapy and interpersonal psychotherapy for depression at 12 months after start of treatment: randomised controlled trial.

BACKGROUND: Cost-effective treatments are needed to reduce the burden of depression. One way to improve the cost-effectiveness of psychotherapy might be to increase session frequency, but keep the total number of sessions constant. AIM: To evaluate the cost-effectiveness of twice-weekly compared with once-weekly psychotherapy sessions after 12 months, from a societal perspective. METHOD: An economic evaluation was conducted alongside a randomised controlled trial comparing twice-weekly versus once-weekly sessions of psychotherapy (cognitive-behavioural therapy or interpersonal psychotherapy) for depression. Missing data were handled by multiple imputation. Statistical uncertainty was estimated with bootstrapping and presented with cost-effectiveness acceptability curves. RESULTS: Differences between the two groups in depressive symptoms, physical and social functioning, and quality-adjusted life-years (QALY) at 12-month follow-up were small and not statistically significant. Total societal costs in the twice-weekly session group were higher, albeit not statistically significantly so, than in the once-weekly session group (mean difference €2065, 95% CI -686 to 5146). The probability that twice-weekly sessions are cost-effective compared with once-weekly sessions was 0.40 at a ceiling ratio of €1000 per point improvement in Beck Depression Inventory-II score, 0.32 at a ceiling ratio of €50 000 per QALY gained, 0.23 at a ceiling ratio of €1000 per point improvement in physical functioning score and 0.62 at a ceiling ratio of €1000 per point improvement in social functioning score. CONCLUSIONS: Based on the current results, twice-weekly sessions of psychotherapy for depression are not cost-effective over the long term compared with once-weekly sessions.

The role of subclinical psychopathic traits on experimentally induced self- and other-compassion.

Psychopathic traits come with high levels of anger and aggression. Since previous studies showed that compassion can mitigate both anger and aggression, the current research puts compassion forward as a possible target to alleviate psychopathy's destructive patterns. Specifically, the present study explored the influence of subclinical psychopathic traits-as well as their three subcomponents egocentricity, callousness, and antisociality-on the efficacy of experimentally induced self-compassion (SC) and other-compassion (OC). This manuscript is part of a larger study in which student and community participants (N = 230, M age = 27.41, 65.2% female) completed a psychopathic trait questionnaire to assess their dimensional level of psychopathy, filled out state SC and OC questionnaires, and were randomized to participate in an experimental self- or other-compassion induction. It was expected that psychopathic traits would positively relate to increases in SC but negatively relate to increases in OC. Baseline levels of both SC and OC negatively related to psychopathy. Overall, as expected, the results on change scores show that subclinical psychopathic traits positively related to a stronger increase in SC, irrespective of the type of compassion induction. This positive relation between a stronger increase in SC and psychopathy total and callousness was more pronounced after the SC induction, rather than after the OC induction. Psychopathic traits did not differentially influence changes in OC. One implication of this study is that high psychopathic and callousness traits predispose to profit extra from targeting SC. Furthermore, psychopathic traits do not hinder increasing compassion for others. These findings suggest that compassion is a promising intervention to improve the wellbeing of people with elevated subclinical psychopathic traits and those around them. Although further research is needed to assess the impact of compassion on anger and aggression specifically, and on clinical psychopathy, the current study suggests that both SC and OC may be useful intervention targets in case of elevated psychopathic traits.

Does psychological process change during psychotherapy predict long-term depression outcome after successful cognitive therapy or interpersonal psychotherapy? Secondary analysis of a randomized trial.

Objective Psychotherapies for depression are similarly effective, but the processes through which these therapies work have not been identified. We focus on psychological process changes during therapy as predictors of long-term depression outcome in treatment responders. Method: Secondary analysis of a randomized trial comparing cognitive therapy (CT) and interpersonal psychotherapy (IPT) that focuses on 85 treatment responders. Using mixed-effects models, changes during therapy (0-7 months) on nine process variables were associated with depression severity (BDI-II) at follow-up (7-24 months). Results: A decrease in dysfunctional attitudes was associated with a decrease in depression scores over time. Improved self-esteem was associated with less depression at follow-up (borderline significant). More improvement in both work and social functioning and interpersonal problems was associated with better depression outcomes in IPT relative to CT, while less improvement in work and social functioning and interpersonal problems was associated with better outcomes in CT relative to IPT. Conclusions: Less negative thinking during therapy is associated with lower depression severity in time, while changes during therapy in work and social functioning and interpersonal problems appear to predict different long-term outcomes in CT vs. IPT. If replicated, these findings can be used to guide clinical decision-making during psychotherapy.

Impact of Comorbid Personality Disorders on Depression Treatment in Routine Outpatient Care.

OBJECTIVE: The impact of personality disorder on treatment effectiveness for depression has been debated, and study results have been inconsistent. However, studies that report a negative impact of personality disorders on depression treatment outcomes are often characterized by uncontrolled treatment designs. Within such contexts, individuals with depression and personality disorders are at risk to receive suboptimal treatment. The aim of this retrospective observational study was to investigate whether and to what extent comorbid personality disorders were associated with the type and amount of depression treatment received in routine outpatient care. METHODS: Retrospectively extracted data from electronic records of 1,455 outpatients treated for depression at several sites of a nationwide mental health provider in the Netherlands were included. The type and number of treatment sessions and visits were analyzed by using regression models. RESULTS: Individuals with depression and comorbid personality disorders received more psychotherapy sessions than individuals without personality disorders, irrespective of depression severity. The number of pharmacotherapy sessions and supportive and crisis visits did not differ between individuals with and without comorbid personality disorders. CONCLUSIONS: Individuals with depression and personality disorders received more intensive treatment than individuals without comorbid personality disorders. These results conflict with treatment guidelines and recommendations from high-quality studies and may be indicative of overtreatment among this large group of patients.

Impact of Comorbid Personality Disorders on Depression Treatment in Routine Outpatient Care.

OBJECTIVE: The impact of personality disorder on treatment effectiveness for depression has been debated, and study results have been inconsistent. However, studies that report a negative impact of personality disorders on depression treatment outcomes are often characterized by uncontrolled treatment designs. Within such contexts, individuals with depression and personality disorders are at risk to receive suboptimal treatment. The aim of this retrospective observational study was to investigate whether and to what extent comorbid personality disorders were associated with the type and amount of depression treatment received in routine outpatient care. METHODS: Retrospectively extracted data from electronic records of 1,455 outpatients treated for depression at several sites of a nationwide mental health provider in the Netherlands were included. The type and number of treatment sessions and visits were analyzed by using regression models. RESULTS: Individuals with depression and comorbid personality disorders received more psychotherapy sessions than individuals without personality disorders, irrespective of depression severity. The number of pharmacotherapy sessions and supportive and crisis visits did not differ between individuals with and without comorbid personality disorders. CONCLUSIONS: Individuals with depression and personality disorders received more intensive treatment than individuals without comorbid personality disorders. These results conflict with treatment guidelines and recommendations from high-quality studies and may be indicative of overtreatment among this large group of patients.

The relation between therapy quality, therapy processes and outcomes and identifying for whom therapy quality matters in CBT and IPT for depression.

BACKGROUND: Research on which therapy processes are crucial for whom is necessary to optimize treatment outcomes for major depressive disorder (MDD) but may be impeded by a lack of variation in therapy quality and because of individual differences in therapy response. The present study used a dataset with large variation in therapy quality to investigate the impact of therapy quality on change in therapy processes and outcome. Machine-learning techniques were used to explore individual differences in these relationships. METHOD: Data come from a multicenter trial that randomized patients with MDD into weekly versus twice weekly sessions of cognitive behavioral therapy (CBT) or interpersonal psychotherapy (IPT). Correlations between quality of therapy, change in therapy processes and depressive symptoms were calculated. Using elastic net regression, a prognostic model was developed that investigated individual differences. RESULTS: There were no significant correlations between therapy quality and change in therapy process variables or between therapy quality and therapy outcome, except between therapy quality and dysfunctional thinking and IPT skills. Improvement in therapy processes played a larger role in patients whose therapy outcome was poorly predicted by their baseline characteristics. CONCLUSIONS: In this study, in which therapy quality varied considerably, we found that therapy quality was not related to change in therapy processes or outcome. In addition, this study provides a first demonstration of proposed methods to identify individual responses to change in therapy processes. Results suggested that the importance of certain therapy processes might differ between patients. Future research into the relation between therapy quality, change in therapy processes and outcome should take into account the variation of therapy quality, focus on improved measurement of therapy quality and use a combination of machine learning techniques and experimental lab studies to determine to which extent and for whom therapy quality and change in therapy processes matter.

Cross-trial prediction in psychotherapy: External validation of the Personalized Advantage Index using machine learning in two Dutch randomized trials comparing CBT versus IPT for depression.

Objective: Optimizing treatment selection may improve treatment outcomes in depression. A promising approach is the Personalized Advantage Index (PAI), which predicts the optimal treatment for a given individual. To determine the generalizability of the PAI, models needs to be externally validated, which has rarely been done. Method: PAI models were developed within each of two independent trials, with substantial between-study differences, that both compared CBT and IPT for depression (STEPd: n = 151 and FreqMech: n = 200). Subsequently, both PAI models were tested in the other dataset. Results: In the STEPd study, post-treatment depression was significantly different between individuals assigned to their PAI-indicated treatment versus those assigned to their non-indicated treatment (d = .57). In the FreqMech study, post-treatment depression was not significantly different between patients receiving their indicated treatment versus those receiving their non-indicated treatment (d = .20). Cross-trial predictions indicated that post-treatment depression was not significantly different between those receiving their indicated treatment and those receiving their non-indicated treatment (d = .16 and d = .27). Sensitivity analyses indicated that cross-trial prediction based on only overlapping variables didn't improve the results. Conclusion: External validation of the PAI has modest results and emphasizes between-study differences and many other challenges.

Selecting the optimal treatment for a depressed individual: Clinical judgment or statistical prediction?

BACKGROUND: Optimizing treatment selection is a way to enhance treatment success in major depressive disorder (MDD). In clinical practice, treatment selection heavily depends on clinical judgment. However, research has consistently shown that statistical prediction is as accurate - or more accurate - than predictions based on clinical judgment. In the context of new technological developments, the current aim was to compare the accuracy of clinical judgment versus statistical predictions in selecting cognitive therapy (CT) or interpersonal psychotherapy (IPT) for MDD. METHODS: Data came from a randomized trial comparing CT (n=76) with IPT (n=75) for MDD. Prior to randomization, therapists' recommendations were formulated during multidisciplinary staff meetings. Statistical predictions were based on Personalized Advantage Index models. Primary outcomes were post-treatment and 17-month follow-up depression severity. Secondary outcome was treatment dropout. RESULTS: Individuals receiving treatment according to their statistical prediction were less depressed at post-treatment and follow-up compared to those receiving their predicted non-indicated treatment. This difference was not found for recommended versus non-recommended treatments based on clinical judgment. Moreover, for individuals with an IPT recommendation by therapists, higher post-treatment and follow-up depression severity was found for those that actually received IPT compared to those that received CT. Recommendations based on statistical prediction and clinical judgment were not associated with differences in treatment dropout. LIMITATIONS: Information on the clinical reasoning behind therapist recommendations was not collected, and statistical predictions were not externally validated. CONCLUSIONS: Statistical prediction outperforms clinical judgment in treatment selection for MDD and has the potential to personalize treatment strategies.

Precision medicine for long-term depression outcomes using the Personalized Advantage Index approach: cognitive therapy or interpersonal psychotherapy?

BACKGROUND: Psychotherapies for depression are equally effective on average, but individual responses vary widely. Outcomes can be improved by optimizing treatment selection using multivariate prediction models. A promising approach is the Personalized Advantage Index (PAI) that predicts the optimal treatment for a given individual and the magnitude of the advantage. The current study aimed to extend the PAI to long-term depression outcomes after acute-phase psychotherapy. METHODS: Data come from a randomized trial comparing cognitive therapy (CT, n = 76) and interpersonal psychotherapy (IPT, n = 75) for major depressive disorder (MDD). Primary outcome was depression severity, as assessed by the BDI-II, during 17-month follow-up. First, predictors and moderators were selected from 38 pre-treatment variables using a two-step machine learning approach. Second, predictors and moderators were combined into a final model, from which PAI predictions were computed with cross-validation. Long-term PAI predictions were then compared to actual follow-up outcomes and post-treatment PAI predictions. RESULTS: One predictor (parental alcohol abuse) and two moderators (recent life events; childhood maltreatment) were identified. Individuals assigned to their PAI-indicated treatment had lower follow-up depression severity compared to those assigned to their PAI-non-indicated treatment. This difference was significant in two subsets of the overall sample: those whose PAI score was in the upper 60%, and those whose PAI indicated CT, irrespective of magnitude. Long-term predictions did not overlap substantially with predictions for acute benefit. CONCLUSIONS: If replicated, long-term PAI predictions could enhance precision medicine by selecting the optimal treatment for a given depressed individual over the long term.

Interpersonal Psychotherapy Versus Cognitive Therapy for Depression: How They Work, How Long, and for Whom-Key Findings From an RCT.

OBJECTIVE: Although the effectiveness of interpersonal psychotherapy (IPT) and cognitive therapy (CT) for major depression has been established, little is known about how and for whom they work and how they compare in the long term. The latter is especially relevant for IPT because research on its long-term effects has been limited. This overview paper summarizes findings from a Dutch randomized controlled trial on the effects and mechanisms of change of IPT versus CT for major depression. METHODS: Adult outpatients with depression (N=182) were randomly assigned to CT (N=76), IPT (N=75), or a 2-month waitlist control group followed by patient's treatment of choice (N=31). The primary outcome was depression severity. Other outcomes were quality of life, social and general psychological functioning, and scores on various mechanism measures. Interventions were compared at the end of treatment and up to 17 months follow-up. RESULTS: On average, IPT and CT were both superior to waitlist, and their outcomes did not differ significantly from one another. However, the pathway through which change occurred appeared to differ. For a majority of participants, one of the interventions was predicted to be more beneficial than the other. No support for the theoretical models of change was found. CONCLUSIONS: Outcomes of IPT and CT did not appear to differ significantly. IPT may have an enduring effect not different from that of CT. The field would benefit from further refinement of study methods to disentangle mechanisms of change and from advances in the field of personalized medicine (i.e., person-specific analyses and treatment selection methods).

The effects of once- versus twice-weekly sessions on psychotherapy outcomes in depressed patients.

BACKGROUND: It is unclear what session frequency is most effective in cognitive-behavioural therapy (CBT) and interpersonal psychotherapy (IPT) for depression. AIMS: Compare the effects of once weekly and twice weekly sessions of CBT and IPT for depression. METHOD: We conducted a multicentre randomised trial from November 2014 through December 2017. We recruited 200 adults with depression across nine specialised mental health centres in the Netherlands. This study used a 2 × 2 factorial design, randomising patients to once or twice weekly sessions of CBT or IPT over 16-24 weeks, up to a maximum of 20 sessions. Main outcome measures were depression severity, measured with the Beck Depression Inventory-II at baseline, before session 1, and 2 weeks, 1, 2, 3, 4, 5 and 6 months after start of the intervention. Intention-to-treat analyses were conducted. RESULTS: Compared with patients who received weekly sessions, patients who received twice weekly sessions showed a statistically significant decrease in depressive symptoms (estimated mean difference between weekly and twice weekly sessions at month 6: 3.85 points, difference in effect size d = 0.55), lower attrition rates (n = 16 compared with n = 32) and an increased rate of response (hazard ratio 1.48, 95% CI 1.00-2.18). CONCLUSIONS: In clinical practice settings, delivery of twice weekly sessions of CBT and IPT for depression is a way to improve depression treatment outcomes.

Measuring Patients' Acquisition of Therapy Skills in Psychotherapy for Depression: Assessing the CCTS-SR and the IPSS-SR.

Using data from 202 patients with depression, the authors conducted a psychometric evaluation of the Dutch translation of the Competencies of Cognitive Therapy Scale-Self-Report and an initial psychometric evaluation of the newly developed Interpersonal Psychotherapy Skills Scale-Self-Report.

A prognostic index for long-term outcome after successful acute phase cognitive therapy and interpersonal psychotherapy for major depressive disorder.

BACKGROUND: Major depressive disorder (MDD) has a highly recurrent nature. After successful treatment, it is important to identify individuals who are at risk of an unfavorable long-term course. Despite extensive research, there is no consensus yet on the clinically relevant predictors of long-term outcome in MDD, and no prediction models are implemented in clinical practice. The aim of this study was to create a prognostic index (PI) to estimate long-term depression severity after successful and high quality acute treatment for MDD. METHODS: Data come from responders to cognitive therapy (CT) and interpersonal psychotherapy (IPT) in a randomized clinical trial (n = 85; CT = 45, IPT = 40). Primary outcome was depression severity, assessed with the Beck Depression Inventory II, measured throughout a 17-month follow-up phase. We examined 29 variables as potential predictors, using a model-based recursive partitioning method and bootstrap resampling in conjunction with backwards elimination. The selected predictors were combined into a PI. Individual PI scores were estimated using a cross-validation approach. RESULTS: A total of three post-treatment predictors were identified: depression severity, hopelessness, and self-esteem. Cross-validated PI scores evidenced a strong correlation (r = 0.60) with follow-up depression severity. CONCLUSION: Long-term predictions of MDD are multifactorial, involving a combination of variables that each has a small prognostic effect. If replicated and validated, the PI can be implemented to predict follow-up depression severity for each individual after acute treatment response, and to personalize long-term treatment strategies.

The influence of comorbid anxiety on the effectiveness of Cognitive Therapy and Interpersonal Psychotherapy for Major Depressive Disorder.

BACKGROUND: Anxious depression is an important subtype of Major Depressive Disorder (MDD) defined by both syndromal (anxiety disorders) and dimensional (anxiety symptoms) criteria. A debated question is how anxiety affects MDD treatment. This study examined the impact of comorbid anxiety disorders and symptoms on the effectiveness of and dropout during Cognitive Therapy (CT) and Interpersonal Psychotherapy (IPT) for MDD. METHODS: Depressed individuals were randomized to CT (n = 76) or IPT (n = 75). Outcome was depression severity measured with the Beck Depression Inventory-II (BDI-II) at the start of each therapy session, post treatment, and monthly up to five months follow-up. Anxiety disorders were assessed with the Structured Clinical Interview for DSM-IV Axis I disorders, (phobic) anxiety symptoms were assessed with Brief Symptom Inventory subscales. RESULTS: Approximately one third of participants had a comorbid anxiety disorder. Comorbid anxiety disorders and anxiety symptoms were associated with less favorable depression change during IPT as compared to CT in the treatment phase, but not in the trial follow-up phase. Individuals with a comorbid anxiety disorder had significantly higher treatment dropout during both treatments. LIMITATIONS: Not all therapists and participants were blind to the assessment of comorbid anxiety disorders and the assessments were performed by one rater. CONCLUSIONS: A preference for CT over IPT for MDD is justifiable when comorbid anxiety is present, although long-term differences are not established and replication of this finding is needed. Clinicians should be aware of the risk of dropout for depressed individuals with an anxiety disorder.

Validity of the Maudsley Staging Method in Predicting Treatment-Resistant Depression Outcome Using the Netherlands Study of Depression and Anxiety.

OBJECTIVE: We investigated if the degree of treatment resistance of depression, as measured by the Maudsley Staging Method (MSM), is predictive of a worse depression outcome by using a large naturalistic cohort of depressed patients. METHODS: 643 subjects from the general population, primary care, and secondary care who suffered from current depressive disorder were included from the Netherlands Study of Depression and Anxiety baseline assessment. The diagnostic criterion was major depressive disorder (MDD) in the last month, based on the Composite Interview Diagnostic Instrument (CIDI), or a CIDI diagnosis of MDD in the past 6 months with an Inventory of Depressive Symptomatology Self-Report score > 24 at baseline. In these subjects, composite scores of the MSM, based on duration, severity, and treatment history of current episode, were determined retrospectively. We then determined if the MSM score prospectively predicted the 2-year course of depression after baseline. The primary outcomes were percentage of follow-up time spent in a depressive episode and being "mostly depressed" (≥ 50% of the follow-up) between baseline and 2-year follow-up. RESULTS: The MSM predicted "percentage of follow-up time with depression" (P < .001) and was associated with being "mostly depressed" (OR = 1.40; 95% CI, 1.23-1.60; P < .001). These effects were not modified by having received treatment. CONCLUSIONS: The current study shows that the MSM is a promising tool to predict worse depression outcomes in depressed patients. In this study that adds to previous work, we show the applicability of MSM in a wider range of primary and secondary care patients with depression.

The impact of personality disorder pathology on the effectiveness of Cognitive Therapy and Interpersonal Psychotherapy for Major Depressive Disorder.

BACKGROUND: Despite extensive research, there is no consensus how Personality Disorders (PD) and PD features affect outcome for Major Depressive Disorder (MDD). The present study evaluated the effects of PD (features) on treatment continuation and effectiveness in Cognitive Therapy (CT) and Interpersonal Psychotherapy (IPT) for MDD. METHODS: Depressed outpatients were randomized to CT (n=72) and IPT (n=74). Primary outcome was depression severity measured repeatedly with the Beck Depression Inventory-II (BDI-II) at baseline, three months, at the start of each therapy session, at post-treatment and monthly during five months follow-up. RESULTS: Comorbid PD and PD features did not affect dropout. Multilevel and Cox regression models indicated no negative effect of PD on BDI-II change and remission rates during treatment and follow-up, irrespective of the treatment received. For both therapies, higher dependent PD features predicted overall lower BDI-II scores during treatment, however this effect did not sustain through follow-up. Cluster A PD features moderated treatment outcome during treatment and follow-up: individuals with high cluster A PD features had greater BDI-II reductions over time in CT as compared to IPT. LIMITATIONS: Not all therapists and participants were blind to the assessment of PD (features), and assessments were performed by one rater. Further research must investigate the state and trait dependent changes of PD and MDD over time. CONCLUSIONS: We found no negative impact of PD on the effectiveness and treatment retention of CT and IPT for MDD during treatment and follow-up. If replicated, cluster A PD features can be used to optimize treatment selection.

Indicators of patients with major depressive disorder in need of highly specialized care: A systematic review.

OBJECTIVES: Early identification of patients with major depressive disorder (MDD) that cannot be managed by secondary mental health services and who require highly specialized mental healthcare could enhance need-based patient stratification. This, in turn, may reduce the number of treatment steps needed to achieve and sustain an adequate treatment response. The development of a valid tool to identify patients with MDD in need of highly specialized care is hampered by the lack of a comprehensive understanding of indicators that distinguish patients with and without a need for highly specialized MDD care. The aim of this study, therefore, was to systematically review studies on indicators of patients with MDD likely in need of highly specialized care. METHODS: A structured literature search was performed on the PubMed and PsycINFO databases following PRISMA guidelines. Two reviewers independently assessed study eligibility and determined the quality of the identified studies. Three reviewers independently executed data extraction by using a pre-piloted, standardized extraction form. The resulting indicators were grouped by topical similarity, creating a concise summary of the findings. RESULTS: The systematic search of all databases yielded a total of 7,360 references, of which sixteen were eligible for inclusion. The sixteen papers yielded a total of 48 unique indicators. Overall, a more pronounced depression severity, a younger age of onset, a history of prior poor treatment response, psychiatric comorbidity, somatic comorbidity, childhood trauma, psychosocial impairment, older age, and a socioeconomically disadvantaged status were found to be associated with proxies of need for highly specialized MDD care. CONCLUSIONS: Several indicators are associated with the need for highly specialized MDD care. These indicators provide easily measurable factors that may serve as a starting point for the development of a valid tool to identify patients with MDD in need of highly specialized care.

Negative mood-induction modulates default mode network resting-state functional connectivity in chronic depression.

BACKGROUND: The aim of this study was to investigate the effects of sad mood on default mode network (DMN) resting-state connectivity in persons with chronic major depressive disorder (cMDD). METHODS: Participants with a diagnosis of cMDD (n=18) and age, gender and education level matched participants without a diagnosis of depression (n=18) underwent a resting-state fMRI scan, before and after a sad mood induction. The posterior cingulate cortex (PCC) was used as a seed for DMN functional connectivity across the two resting-state measurements. RESULTS: Mood ratings decreased in both groups following the sad mood induction procedure. PCC connectivity with the parahippocampal gyrus, the superior temporal gyrus and the anterior inferior temporal cortex increased in cMDD patients following the sad mood induction, whereas it decreased in non-patient controls. PCC connectivity with the anterior prefrontal cortex and the precuneus decreased in cMDD patients following the sad mood induction, whereas it increased in non-patient controls. LIMITATIONS: Limitations of this study include the relatively small sample size and lack of a clinical control group. CONCLUSIONS: These findings are in line with neurobiological models of depression suggesting that the observed changes in DMN connectivity following the sad mood induction might reflect a failure to exert cognitive control over negative memory retrieval in patients with cMDD.