Ben Lorimer

To investigate if Sessions 1-4 Patient Health Questionnaire-9 (PHQ-9) scores are associated with treatment outcome and if there is a differential effect between person-centered experiential therapy (PCET) and cognitive behavioral therapy (CBT). A secondary data analysis of a prospectively registered and ethically approved pragmatic, noninferiority randomized controlled trial comparing PCET and CBT for the treatment of moderate or severe depression. Latent growth curve modeling was applied to data from 274 patients who received ≥ five sessions of therapy to investigate the association between change in Sessions 1-4 PHQ-9 scores on a binary end-of-treatment outcome (i.e., reliable and clinically significant improvement; RCSI) and on final-session PHQ-9 scores. Estimated power was 80%. Change in Sessions 1-4 PHQ-9 scores was significantly associated with the probability of RCSI in the PCET condition (p = .002) but not the CBT condition (p = .156). Specifically, greater early treatment improvement and higher PHQ-9 scores at Session 1 were significantly associated with obtaining RCSI in PCET, but not in CBT; this relationship differed significantly between conditions (p = .007). Greater early treatment improvement was also significantly associated with lower final-session PHQ-9 scores (p < .001), but this relationship did not significantly differ across conditions (p = .121). Early session scores are associated with final-session depression scores, though PCET and CBT manifest distinctively different trajectories for patients achieving RCSI. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Background: Some patients return for further psychological treatment in routine services, although it is unclear how common this is, as scarce research is available on this topic.Aims: To estimate the treatment return rate and describe the clinical characteristics of patients who return for anxiety and depression treatment.Method: A large dataset (N=21,029) of routinely collected clinical data (2010–2015) from an English psychological therapy service was analysed using descriptive statistics.Results: The return rate for at least one additional treatment episode within 1–5 years was 13.7%. Furthermore, 14.5% of the total sessions provided by the service were delivered to treatment-returning patients. Of those who returned, 58.0% continued to show clinically significant depression and/or anxiety symptoms at the end of their first treatment, while 32.0% had experienced a demonstrable relapse before their second treatment.Conclusions: This study estimates that approximately one in seven patients return to the same service for additional psychological treatment within 1–5 years. Multiple factors may influence the need for additional treatment, and this may have a major impact on service activity. Future research needs to further explore and better determine the characteristics of treatment returners, prioritise enhancement of first treatment recovery, and evaluate relapse prevention interventions.

Severe mental ill health (SMI) is associated with excess mortality, and poor diet is one associated modifiable risk factor. This study investigated factors associated with low consumption of fruit and vegetables among people with SMI (N = 9914). A total of 8.4% of participants ate no portions per day, while only 15% ate 5 + portions. Individuals who never consumed fruit and vegetables or ate < 5 portions per day were more likely to be male, younger than 65, unemployed, experience poorer general health, or perceive health as unimportant. Poor diet is common among people with SMI and tailored dietary improvement interventions are required.

Cognitive behavioural therapy (CBT) is an effective psychological treatment for anxiety-related disorders (anxiety disorders, post-traumatic stress disorder, and obsessive-compulsive disorder). However, relapse of anxiety symptoms is common following completion of treatment. This study aimed to identify predictors of relapse of anxiety after CBT for adult (18+) patients to enable the identification of “at-risk” patients who could potentially benefit from relapse prevention interventions. A systematic review and meta-analysis were conducted, including studies found in PsycINFO, PubMed, Scopus, and Web of Science, and through hand-searches of references lists and reverse citations. Nine studies met eligibility criteria (N = 532 patients). On average, 23.8% of patients experienced relapse following completion of CBT. A total of 21 predictors were identified and grouped into seven categories: residual symptoms; personality disorders; medication; clinical features; stressful life-events; degree of improvement; and demographics. A meta-analysis of residual symptoms as a predictor of relapse yielded a moderate but non-significant-pooled effect size (r = 0.35; 95% CI −0.21, 0.74, p =.08). Further research with adequately powered samples and standardised operationalisations of relapse are required to identify robust predictors.

We examined the relation between maternal responsiveness and children's acquisition of mental and non-mental state vocabulary in 59 pairs of mothers and children aged 10 to 26 months as they engaged in a free-play episode. Children wore a head camera and responsiveness was defined as maternal talk that commented on the child's actions (e.g., when the child reached for or manipulated an object visible in the head camera). As hypothesized, maternal responsiveness correlated with both mental and non-mental state vocabulary acquisition in younger children (approximately 18 months and younger) but not older children. We posit a diminishing role for maternal responsiveness in language acquisition as children grow older.

Objective: Low-intensity cognitive behavioural therapy (LiCBT) can help to alleviate acute symptoms of depression and anxiety, but some patients relapse after completing treatment. Little is known regarding relapse risk factors, limiting our ability to predict its occurrence. Therefore, this study aimed to develop a dynamic prediction tool to identify cases at high risk of relapse. Method: Data from a longitudinal cohort study of LiCBT patients was analysed using a machine learning approach (XGBoost). The sample included n = 317 treatment completers who were followed-up monthly for 12 months (n = 223 relapsed; 70%). An ensemble of XGBoost algorithms was developed in order to predict and adjust the estimated risk of relapse (vs maintained remission) in a dynamic way, at four separate time-points over the course of a patient’s journey. Results: Indices of predictive accuracy in a cross-validation design indicated adequate generalizability (AUC range = 0.72–0.84; PPV range = 71.2–75.3%; NPV range = 56.0–74.8%). Younger age, unemployment, (non-)linear treatment responses, and residual symptoms were identified as important predictors. Discussion: It is possible to identify cases at risk of relapse and predictive accuracy improves over time as new information is collected. Early identification coupled with targeted relapse prevention could considerably improve the longer-term effectiveness of LiCBT.

Objective: Many patients relapse within one year of completing effective cognitive behavioural therapy (CBT) for depression and anxiety. Residual symptoms at treatment completion have been demonstrated to predict relapse, and so this study used network analyses to improve specificity regarding which residual anxiety and depression symptoms predict relapse. Method: A cohort study identified relapse cases following low- and high-intensity CBT in a stepped care psychological therapy service. The sample included N = 867 “recovered” treatment completers that attended a six-month follow-up review. At follow-up, N = 93 patients had relapsed and N = 774 remained in-remission. Networks of final treatment session depression (PHQ-9) and anxiety (GAD-7) symptoms were estimated for both sub-groups. Results: Qualitatively similar symptom networks were found. Difficulty concentrating was a highly central symptom in the relapse network, whilst of only average centrality in the remission network. In contrast, trouble relaxing was highly central in the remission network, whilst of only average centrality in the relapse network. Discussion: Identification of central residual symptoms holds promise in improving the specificity of prognostic models and the design of evidence-based relapse prevention strategies. The small sample of relapse cases limits this study’s ability to draw firm conclusions.