This study examined therapist–patient interactions during clinical management with antidepressant medication and pill-placebo.

The sample consisted of 80 patients on active medication and 40 patients in a pill-placebo condition from a randomized controlled trial for moderate to severe depression. Pharmacotherapist–patient interactions were characterized using observer ratings of the therapeutic alliance, pharmacotherapist-offered facilitative conditions, pharmacotherapist adherence to clinical management treatment guidelines and pharmacotherapist competence. Patients, therapists and raters were blind to treatment condition and outcome.

Provision of greater non-specific support (facilitative conditions) in early sessions predicted less subsequent improvement in depressive symptoms for patients receiving pill-placebo but not those receiving active medications, for which none of the process ratings predicted subsequent change. Early symptom change predicted later alliance and adherence in both conditions and therapist competence in the active condition.

Higher levels of support in early sessions predict poorer subsequent response among placebo patients. It remains unclear whether patients who are likely to be refractory elicit greater non-specific support or whether the provision of such support has a deleterious effect in unmedicated patients. Differences in treatment process variables between conditions late in treatment are likely to be largely a consequence of symptom relief produced by active medications.

Meta-analyses suggest that reboxetine may be less effective than other antidepressants. Such comparisons may be biased by lower adherence to reboxetine and subsequent handling of missing outcome data. This study illustrates how to adjust for differential non-adherence and hence derive an unbiased estimate of the efficacy of reboxetine compared with citalopram in primary care patients with depression.

A structural mean modelling (SMM) approach was used to generate adherence-adjusted estimates of the efficacy of reboxetine compared with citalopram using GENetic and clinical Predictors Of treatment response in Depression (GENPOD) trial data. Intention-to-treat (ITT) analyses were performed to compare estimates of effectiveness with results from previous meta-analyses.

At 6 weeks, 92% of those randomized to citalopram were still taking their medication, compared with 72% of those randomized to reboxetine. In ITT analysis, there was only weak evidence that those on reboxetine had a slightly worse outcome than those on citalopram [adjusted difference in mean Beck Depression Inventory (BDI) scores: 1.19, 95% confidence interval (CI) –0.52 to 2.90, p = 0.17]. There was no evidence of a difference in efficacy when differential non-adherence was accounted for using the SMM approach for mean BDI (–0.29, 95% CI –3.04 to 2.46, p = 0.84) or the other mental health outcomes.

There was no evidence of a difference in the efficacy of reboxetine and citalopram when these drugs are taken and tolerated by depressed patients. The SMM approach can be implemented in standard statistical software to adjust for differential non-adherence and generate unbiased estimates of treatment efficacy for comparisons of two (or more) active interventions.

Oral histories from 9/11 responders to the World Trade Center (WTC) attacks provide rich narratives about distress and resilience. Artificial Intelligence (AI) models promise to detect psychopathology in natural language, but they have been evaluated primarily in non-clinical settings using social media. This study sought to test the ability of AI-based language assessments to predict PTSD symptom trajectories among responders.

Participants were 124 responders whose health was monitored at the Stony Brook WTC Health and Wellness Program who completed oral history interviews about their initial WTC experiences. PTSD symptom severity was measured longitudinally using the PTSD Checklist (PCL) for up to 7 years post-interview. AI-based indicators were computed for depression, anxiety, neuroticism, and extraversion along with dictionary-based measures of linguistic and interpersonal style. Linear regression and multilevel models estimated associations of AI indicators with concurrent and subsequent PTSD symptom severity (significance adjusted by false discovery rate).

Cross-sectionally, greater depressive language (β = 0.32; p = 0.049) and first-person singular usage (β = 0.31; p = 0.049) were associated with increased symptom severity. Longitudinally, anxious language predicted future worsening in PCL scores (β = 0.30; p = 0.049), whereas first-person plural usage (β = −0.36; p = 0.014) and longer words usage (β = −0.35; p = 0.014) predicted improvement.

This is the first study to demonstrate the value of AI in understanding PTSD in a vulnerable population. Future studies should extend this application to other trauma exposures and to other demographic groups, especially under-represented minorities.

Previous research has shown an association between subjective wellbeing and incident diabetes. Less is known about the role of wellbeing for subclinical disease trajectories as captured via glycated hemoglobin (HbA1c). We aimed to explore the association between subjective wellbeing and future HbA1c levels, and the role of sociodemographic, behavioral and clinical factors in this association.

We used data from the English Longitudinal Study of Ageing for this study (N = 2161). Subjective wellbeing (CASP-19) was measured at wave 2 and HbA1c was measured 8 years later at wave 6. Participants were free from diabetes at baseline. We conducted a series of analyses to examine the extent to which the association was accounted for by a range of sociodemographic, behavioral and clinical factors in linear regression models.

Models showed that subjective wellbeing (CASP-19 total score) was inversely associated with HbA1c 8 years later after controlling for depressive symptoms, age, sex, and baseline HbA1c (B = −0.035, 95% CI −0.060 to –0.011, p = 0.005). Inclusion of sociodemographic variables and behavioral factors in models accounted for a large proportion (17.0% and 24.5%, respectively) of the relationship between wellbeing and later HbA1c; clinical risk factors explained a smaller proportion of the relationship (3.4%).

Poorer subjective wellbeing is associated with greater HbA1c over 8 years of follow-up and this relationship can in part be explained by sociodemographic, behavioral and clinical factors among older adults.

Age effects may be important for improving models for the prediction of conversion to psychosis for individuals in the clinical high risk (CHR) state. This study aimed to explore whether adolescent CHR individuals (ages 9–17 years) differ significantly from adult CHR individuals (ages 18–45 years) in terms of conversion rates and predictors.

Consecutive CHR individuals (N = 517) were assessed for demographic and clinical characteristics and followed up for 3 years. Individuals with CHR were classified as adolescent (n = 244) or adult (n = 273) groups. Age-specific prediction models of psychosis were generated separately using Cox regression.

Similar conversion rates were found between age groups; 52 out of 216 (24.1%) adolescent CHR individuals and 55 out of 219 (25.1%) CHR adults converted to psychosis. The conversion outcome was best predicted by negative symptoms compared to other clinical variables in CHR adolescents (χ2 = 7.410, p = 0.006). In contrast, positive symptoms better predicted conversion in CHR adults (χ2 = 6.585, p = 0.01).

Adolescent and adult CHR individuals may require a different approach to early identification and prediction. These results can inform the development of more precise prediction models based on age-specific approaches.

Major depressive disorder (MDD) is clinically documented to co-occur with multiple gastrointestinal disorders (GID), but the potential causal relationship between them remains unclear. We aimed to evaluate the potential causal relationship of MDD with 4 GID [gastroesophageal reflux disease (GERD), irritable bowel syndrome (IBS), peptic ulcer disease (PUD), and non-alcoholic fatty liver disease (NAFLD)] using a two-sample Mendelian randomization (MR) design.

We obtained genome-wide association data for MDD from a meta-analysis (N = 480 359), and for GID from the UK Biobank (N ranges: 332 601–486 601) and FinnGen (N ranges: 187 028–218 792) among individuals of European ancestry. Our primary method was inverse-variance weighted (IVW) MR, with a series of sensitivity analyses to test the hypothesis of MR. Individual study estimates were pooled using fixed-effect meta-analysis.

Meta-analyses IVW MR found evidence that genetically predicted MDD may increase the risk of GERD, IBS, PUD and NAFLD. Additionally, reverse MR found evidence of genetically predicted GERD or IBS may increase the risk of MDD.

Genetically predicted MDD may increase the risk of GERD, IBS, PUD and NAFLD. Genetically predicted GERD or IBS may increase the risk of MDD. The findings may help elucidate the mechanisms underlying the co-morbidity of MDD and GID. Focusing on GID symptoms in patients with MDD and emotional problems in patients with GID is important for the clinical management.

Overgeneralised self-blame and worthlessness are key symptoms of major depressive disorder (MDD) and have previously been associated with self-blame-selective changes in connectivity between right superior anterior temporal lobe (rSATL) and subgenual frontal cortices. Another study showed that remitted MDD patients were able to modulate this neural signature using functional magnetic resonance imaging (fMRI) neurofeedback training, thereby increasing their self-esteem. The feasibility and potential of using this approach in symptomatic MDD were unknown.

This single-blind pre-registered randomised controlled pilot trial probed a novel self-guided psychological intervention with and without additional rSATL-posterior subgenual cortex (BA25) fMRI neurofeedback, targeting self-blaming emotions in people with insufficiently recovered MDD and early treatment-resistance (n = 43, n = 35 completers). Participants completed three weekly self-guided sessions to rebalance self-blaming biases.

As predicted, neurofeedback led to a training-induced reduction in rSATL-BA25 connectivity for self-blame v. other-blame. Both interventions were safe and resulted in a 46% reduction on the Beck Depression Inventory-II, our primary outcome, with no group differences. Secondary analyses, however, revealed that patients without DSM-5-defined anxious distress showed a superior response to neurofeedback compared with the psychological intervention, and the opposite pattern in anxious MDD. As predicted, symptom remission was associated with increases in self-esteem and this correlated with the frequency with which participants employed the psychological strategies in daily life.

These findings suggest that self-blame-rebalance neurofeedback may be superior over a solely psychological intervention in non-anxious MDD, although further confirmatory studies are needed. Simple self-guided strategies tackling self-blame were beneficial, but need to be compared against treatment-as-usual in further trials. https://doi.org/10.1186/ISRCTN10526888

This study investigates the extent to which the GHQ-12 exhibits configural, metric and scalar invariance across six ethnic groups in Britain and Northern Ireland, using the UK Household Longitudinal Study (N = 35 410).

A confirmatory factor analysis was carried out on a white British group in order to establish an adequate measurement model. Secondly, a multi-group confirmatory factor analysis was conducted in order to assess measurement invariance. A sensitivity analysis comparing summated and latent means across groups was carried out. Finally, revised estimates of scale reliability were derived using two different methods.

A one-factor model including correlated error terms on the negatively phrased items showed superior fit in all ethnic groups. Tests for equal factor loadings and intercepts also showed adequate fit demonstrating metric and scalar invariance. Latent and summated scale estimates of mean group differences were similar for all groups. Scale reliability using McDonald's ω is lower than when using the more conventional Cronbach's α. Reliability across groups is reasonably consistent.

We find that the GHQ-12 does not display obvious bias in regard to ethnic groups in the UK and that valid comparisons across these groups can be made for the purposes of population research. Caution is needed when using as a screening tool for individuals.

A short, effective therapy for posttraumatic stress disorder (PTSD) could decrease barriers to implementation and uptake, reduce dropout, and ameliorate distressing symptoms in military personnel and veterans. This non-inferiority RCT evaluated the efficacy of 2-week massed prolonged exposure (MPE) therapy compared to standard 10-week prolonged exposure (SPE), the current gold standard treatment, in reducing PTSD severity in both active serving and veterans in a real-world health service system.

This single-blinded multi-site non-inferiority RCT took place in 12 health clinics across Australia. The primary outcome was PTSD symptom severity measured by the Clinician-Administered PTSD Scale for DSM-5 (CAPS-5) at 12 weeks. 138 military personnel and veterans with PTSD were randomised. 71 participants were allocated to SPE, with 63 allocated to MPE.

The intention-to-treat sample included 138 participants, data were analysed for 134 participants (88.1% male, M = 46 years). The difference between the mean MPE and SPE group PTSD scores from baseline to 12 weeks-post therapy was 0.94 [95% confidence interval (CI) −4.19 to +6.07]. The upper endpoint of the 95% CI was below +7, indicating MPE was non-inferior to SPE. Significant rates of loss of PTSD diagnosis were found for both groups (MPE 53.8%, SPE 54.1%). Dropout rates were 4.8% (MPE) and 16.9% (SPE).

MPE was non-inferior to SPE in significantly reducing symptoms of PTSD. Significant reductions in symptom severity, low dropout rates, and loss of diagnosis indicate MPE is a feasible, accessible, and effective treatment. Findings demonstrate novel methods to deliver gold-standard treatments for PTSD should be routinely considered.

This study aimed to examine the efficacy of combining paroxetine and mirtazapine v. switching to mirtazapine, for patients with major depressive disorder (MDD) who have had an insufficient response to SSRI monotherapy (paroxetine) after the first 2 weeks of treatment.

This double-blind, randomized, placebo-controlled, three-arm study recruited participants from five hospitals in China. Eligible participants were aged 18–60 years with MDD of at least moderate severity. Participants received paroxetine during a 2-week open-label phase and patients who had not achieved early improvement were randomized to paroxetine, mirtazapine or paroxetine combined with mirtazapine for 6 weeks. The primary outcome was improvement on the Hamilton Rating Scale for Depression 17-item (HAMD-17) scores 6 weeks after randomization.

A total of 204 patients who showed early non-response to paroxetine monotherapy were randomly assigned to receive either mirtazapine and placebo (n = 68), paroxetine and placebo (n = 68) or mirtazapine and paroxetine (n = 68), with 164 patients completing the outcome assessment. At week 8, the least squares (LS) mean change of HAMD-17 scores did not significantly differ among the three groups, (12.98 points) in the mirtazapine group, (12.50 points) in the paroxetine group and (13.27 points) in the mirtazapine plus paroxetine combination group. Participants in the paroxetine monotherapy group were least likely to experience adverse effects.

After 8 weeks follow-up, paroxetine monotherapy, mirtazapine monotherapy and paroxetine/mirtazapine combination therapy were equally effective in non-improvers at 2 weeks. The results of this trial do not support a recommendation to routinely offer additional treatment or a switch in treatment strategies for MDD patients who do not show early improvement after 2 weeks of antidepressant treatment.

Can core genetic liabilities for suicidal behavior be indexed using psychological and neural indicators combined? The current work addressed this question by examining phenotypic and genetic associations of two biobehavioral traits, threat sensitivity (THT) and disinhibition (DIS) – operationalized as psychoneurometric variables (i.e., composites of psychological-scale and neurophysiological measures) – with suicidal behaviors in a sample of adult twins.

Participants were 444 identical and fraternal twins recruited from an urban community. THT was assessed using a psychological-scale measure of fear/fearlessness combined with physiological indicators of reactivity to aversive pictures, and DIS was assessed using scale measures of disinhibitory tendencies combined with indicators of brain response from lab performance tasks. Suicidality was assessed using items from structured interview and questionnaire protocols.

THT and DIS each contributed uniquely to prediction of suicidality when assessed psychoneurometrically (i.e., as composites of scale and neurophysiological indicators). In addition, these traits predicted suicidality interactively, with participants high on both reporting the greatest degree of suicidal behaviors. Biometric (twin-modeling) analyses revealed that a high percentage of the predictive association for each psychoneurometric trait (83% for THT, 68% for DIS) was attributable to genetic variance in common with suicidality.

Findings indicate that psychoneurometric assessments of biobehavioral traits index genetic liability for suicidal behavior, and as such, can serve as innovative targets for research on core biological processes contributing to severe psychopathology, including suicidal proclivities and actions.