Search

BACKGROUND: Increasing an individual's ability to focus on concrete, specific detail, thus reducing the tendency toward overly broad, decontextualised generalisations about the self and world, is a target within cognitive behavioural therapy (CBT). However, empirical investigation of the impact of within-treatment specificity on treatment outcomes is scarce. We evaluated whether the specificity of patient dialogue predicted a) end-of-treatment symptoms and b) session completion for CBT for common mental health issues. METHODS: This preregistered (https://osf.io/agr4t) study trained a deep learning model to score the specificity of patient dialogue in transcripts from 353,614 internet-enabled CBT sessions for common mental health disorders, delivered on behalf of UK NHS services. Data were from obtained from 65,030 participants (n = 47,308 female, n = 241 unstated) aged 18-94 years (M = 34.69, SD = 12.35). Depressive disorders were the most common (39.1 %) primary diagnosis. Primary outcome was end-of-treatment score on the Patient Health Questionnaire-9 (PHQ-9). Secondary outcome was number of sessions attended. RESULTS: Linear mixed-effects models demonstrated that increased patient specificity significantly predicted lower post-treatment symptoms on the PHQ-9, although the size and direction of the effect varied depending on the type of therapeutic activity being completed. Effect sizes were consistently small. Higher patient specificity was associated with completing a greater number of sessions. LIMITATIONS: We are unable to infer causation from our data. CONCLUSIONS: Although effect sizes were small, an effect of specificity was observed across common mental health disorders. Further studies are needed to explore whether encouraging patient specificity during CBT may provide an enhancement of treatment attendance and treatment effects.

Individuals with depression typically remember their past in a generalised manner, at the cost of retrieving specific event memories. This may impair engagement with cognitive behavioural therapy (CBT) tasks that use concrete episodic information to challenge maladaptive beliefs, potentially limiting their therapeutic benefit. Study 1 demonstrated that an episodic specificity induction increased detail and specificity of autobiographical memory in people with major depression, relative to control conditions (N = 88). We therefore examined whether the induction enhanced the efficacy of CBT tasks that depend on episodic memory - cognitive reappraisal (Study 2, N = 30), evidence gathering (Study 2, N = 30), and planning behavioural experiments (Study 3a, N = 30). Across all three tasks, there were no significant differences in emotion- or belief-change between the specificity and control conditions. Although the induction temporarily enhanced specificity in depressed individuals, it did not significantly augment the efficacy of CBT tasks theorised to benefit from the use of specific mnemonic information.

Boundary extension is a memory phenomenon in which an individual reports seeing more of a scene than they actually did. We provide the first examination of boundary extension in individuals diagnosed with depression, hypothesising that an overemphasis on pre-existing schema may enhance boundary extension effects on emotional photographs. The relationship between boundary extension and overgeneralisation in autobiographical memory was also explored. Individuals with (n = 42) and without (n = 41) Major Depressive Disorder completed a camera paradigm task utilising positive, negative, and neutral stimuli. Across all participants, positive (d = 0.37) and negative (d = 0.66) stimuli were extended more than neutral stimuli. This effect did not differ between depressed and never-depressed participants. Across all participants, images containing objects were extended more than images containing faces. An association was also evident between extension effects in memory for perceptual space and extensions of autobiographical memory across time.

The ability to retrieve specific, single-incident autobiographical memories has been consistently posited as a predictor of recurrent depression. Elucidating the role of autobiographical memory specificity in patient-response to depressive treatments may improve treatment efficacy and facilitate use of science-driven interventions. We used recent methodological advances in individual patient data meta-analysis to determine a) whether memory specificity is improved following mindfulness-based cognitive therapy (MBCT), relative to control interventions, and b) whether pre-treatment memory specificity moderates treatment response. All bar one study evaluated MBCT for relapse prevention for depression. Our initial analysis therefore focussed on MBCT datasets only(n = 708), then were repeated including the additional dataset(n = 880). Memory specificity did not significantly differ from baseline to post-treatment for either MBCT and Control interventions. There was no evidence that baseline memory specificity predicted treatment response in terms of symptom-levels, or risk of relapse. Findings raise important questions regarding the role of memory specificity in depressive treatments.

Low-intensity psychological interventions that target cognitive risk factors for depressive relapse may improve access to relapse prevention programs and thereby reduce subsequent risk. This study provides the first evaluation of an autobiographical memory-based intervention for relapse prevention, to establish whether memory-training programs that are efficacious for acute depression may also aid those currently in remission. We also provide the longest follow-up to-date of the effects of autobiographical memory training on autobiographical memory processes themselves. This pre-registered randomized-controlled proof-of-concept trial (N = 74) compared an autobiographical Memory Flexibility (MemFlex) intervention to Psychoeducation about cognitive-behavioral mechanisms which maintain depression. Both interventions were primarily self-guided, and delivered via paper workbooks completed over four weeks. The key cognitive outcome was ability to retrieve and alternate between specific and general autobiographical memories. Co-primary clinical outcomes were time until depressive relapse and depression-free days in the twelve-months following intervention. Results indicated a small-moderate effect size (d = 0.35) in favor of MemFlex for the cognitive outcome. A small Hazard Ratio (1.08) was observed for time until depressive relapse, along with a negligible effect size for depression-free days (d = 0.11). Although MemFlex produced long-term improvement in memory retrieval skills, there was little support for MemFlex as a relapse prevention program for depression.

INTRODUCTION: Trauma-focused cognitive behavioural therapies are the first-line treatment for posttraumatic stress disorder (PTSD) in children and adolescents. Nevertheless, open questions remain with respect to efficacy: why does this first-line treatment not work for everyone? For whom does it work best? Individual clinical trials often do not provide sufficient statistical power to examine and substantiate moderating factors. To overcome the issue of limited power, an individual participant data meta-analysis of randomised trials evaluating forms of trauma-focused cognitive behavioural therapy in children and adolescents aged 6-18 years will be conducted. METHODS AND ANALYSIS: We will update the National Institute for Health and Care Excellence guideline literature search from 2018 with an electronic search in the databases PsycINFO, MEDLINE, Embase, Cochrane Central Register of Controlled Trials and CINAHL with the terms (trauma* OR stress*) AND (cognitive therap* OR psychotherap*) AND (trial* OR review*). Electronic searches will be supplemented by a comprehensive grey literature search in archives and trial registries. Only randomised trials that used any manualised psychological treatment-that is a trauma-focused cognitive behavioural therapy for children and adolescents-will be included. The primary outcome variable will be child-reported posttraumatic stress symptoms (PTSS) post-treatment. Proxy-reports (teacher, parent and caregiver) will be analysed separately. Secondary outcomes will include follow-up assessments of PTSS, PTSD diagnosis and symptoms of comorbid disorders such as depression, anxiety-related and externalising problems. Random-effects models applying restricted maximum likelihood estimation will be used for all analyses. We will use the Revised Cochrane Risk of Bias tool to measure risk of bias. ETHICS AND DISSEMINATION: Contributing study authors need to have permission to share anonymised data. Contributing studies will be required to rem

Anxiety disorders are prevalent and disabling yet understudied from a genetic standpoint, compared with other major psychiatric disorders such as bipolar disorder and schizophrenia. The fact that they are more common, diverse and perceived as embedded in normal life may explain this relative oversight. In addition, as for other psychiatric disorders, there are technical challenges related to the identification and validation of candidate genes and peripheral biomarkers. Human studies, particularly genetic ones, are susceptible to the issue of being underpowered, because of genetic heterogeneity, the effect of variable environmental exposure on gene expression, and difficulty of accrual of large, well phenotyped cohorts. Animal model gene expression studies, in a genetically homogeneous and experimentally tractable setting, can avoid artifacts and provide sensitivity of detection. Subsequent translational integration of the animal model datasets with human genetic and gene expression datasets can ensure cross-validatory power and specificity for illness. We have used a pharmacogenomic mouse model (involving treatments with an anxiogenic drug--yohimbine, and an anti-anxiety drug--diazepam) as a discovery engine for identification of anxiety candidate genes as well as potential blood biomarkers. Gene expression changes in key brain regions for anxiety (prefrontal cortex, amygdala and hippocampus) and blood were analyzed using a convergent functional genomics (CFG) approach, which integrates our new data with published human and animal model data, as a translational strategy of cross-matching and prioritizing findings. Our work identifies top candidate genes (such as FOS, GABBR1, NR4A2, DRD1, ADORA2A, QKI, RGS2, PTGDS, HSPA1B, DYNLL2, CCKBR and DBP), brain-blood biomarkers (such as FOS, QKI and HSPA1B), pathways (such as cAMP signaling) and mechanisms for anxiety disorders--notably signal transduction and reactivity to environment, with a prominent role for the hippocam

Anxiety disorders are prevalent and disabling yet understudied from a genetic standpoint, compared with other major psychiatric disorders such as bipolar disorder and schizophrenia. The fact that they are more common, diverse and perceived as embedded in normal life may explain this relative oversight. In addition, as for other psychiatric disorders, there are technical challenges related to the identification and validation of candidate genes and peripheral biomarkers. Human studies, particularly genetic ones, are susceptible to the issue of being underpowered, because of genetic heterogeneity, the effect of variable environmental exposure on gene expression, and difficulty of accrual of large, well phenotyped cohorts. Animal model gene expression studies, in a genetically homogeneous and experimentally tractable setting, can avoid artifacts and provide sensitivity of detection. Subsequent translational integration of the animal model datasets with human genetic and gene expression datasets can ensure cross-validatory power and specificity for illness. We have used a pharmacogenomic mouse model (involving treatments with an anxiogenic drug--yohimbine, and an anti-anxiety drug--diazepam) as a discovery engine for identification of anxiety candidate genes as well as potential blood biomarkers. Gene expression changes in key brain regions for anxiety (prefrontal cortex, amygdala and hippocampus) and blood were analyzed using a convergent functional genomics (CFG) approach, which integrates our new data with published human and animal model data, as a translational strategy of cross-matching and prioritizing findings. Our work identifies top candidate genes (such as FOS, GABBR1, NR4A2, DRD1, ADORA2A, QKI, RGS2, PTGDS, HSPA1B, DYNLL2, CCKBR and DBP), brain-blood biomarkers (such as FOS, QKI and HSPA1B), pathways (such as cAMP signaling) and mechanisms for anxiety disorders--notably signal transduction and reactivity to environment, with a prominent role for the hippocam