Latent variable mixture modelling and individual treatment prediction

A person-centered, transdiagnostic schema and mode profile approach to predict outcome in time-limited schema group therapy

OBJECTIVE

This study employs a person-centered transdiagnostic approach to examine how schema and mode profiles predict symptom severity reduction in schema group therapy for patients with personality disorders and enduring clinical syndromes.

METHOD

We analyzed symptom reduction in 248 patients across three formats of manualized, time-limited schema group therapy. Latent profile analysis and mixed multilevel modeling were used to determine the extent to which schema/mode classes predict symptom reduction, and whether the inclusion of individual schemas and modes enhances these predictions.

RESULTS

No significant differences in treatment outcomes were found across the group modalities. A three latent profile solution for schemas and modes showed external validity with clinical variables and demonstrated that declines in symptom severity varied by schema and mode class, even after adjusting for baseline symptom severity. Adding the Vulnerability to Harm schema and Vulnerable Child mode to the model increased the explained variance.

CONCLUSION

Patients with more severe personality problems show more substantial symptom reduction. Both schema and mode profiles significantly contribute to predicting post-treatment symptom levels. Understanding these profiles may help therapists tailor interventions more effectively, consistent with Young's theoretical model.Trial registration: ISRCTN.org identifier: ISRCTN17262253.

The future of psychological treatments: The Marburg Declaration

Although psychological treatments are broadly recognized as evidence-based interventions for various mental disorders, challenges remain. For example, a substantial proportion of patients receiving such treatments do not fully recover, and many obstacles hinder the dissemination, implementation, and training of psychological treatments. These problems require those in our field to rethink some of our basic models of mental disorders and their treatments, and question how research and practice in clinical psychology should progress. To answer these questions, a group of experts of clinical psychology convened at a Think-Tank in Marburg, Germany, in August 2022 to review the evidence and analyze barriers for current and future developments. After this event, an overview of the current state-of-the-art was drafted and suggestions for improvements and specific recommendations for research and practice were integrated. Recommendations arising from our meeting cover further improving psychological interventions through translational approaches, improving clinical research methodology, bridging the gap between more nomothetic (group-oriented) studies and idiographic (person-centered) decisions, using network approaches in addition to selecting single mechanisms to embrace the complexity of clinical reality, making use of scalable digital options for assessments and interventions, improving the training and education of future psychotherapists, and accepting the societal responsibilities that clinical psychology has in improving national and global health care. The objective of the Marburg Declaration is to stimulate a significant change regarding our understanding of mental disorders and their treatments, with the aim to trigger a new era of evidence-based psychological interventions.

The addition of employment support alongside psychological therapy enhances the chance of recovery for clients most at risk of poor clinical outcomes

BACKGROUND

Many people achieve positive outcomes from psychological therapies for anxiety and depression. However, not everyone benefits and some may require additional support. Previous studies have examined the demographic and clinical characteristics of people starting treatment and identified a patient profile that is associated with poor clinical outcomes.

AIMS

To examine whether the addition of employment-related support alongside psychological therapy was associated with a greater chance of recovery for clients belonging to this patient profile.

METHOD

We analysed 302 clients across three services, who were offered employment-related support alongside psychological therapy. The rate of clinical recovery (falling below clinical thresholds on measures of both anxiety and depression) was compared between individuals who accepted the offer and those who declined, while adjusting for potential confounders.

RESULTS

Logistic regression showed that receiving employment support was significantly associated with clinical recovery after controlling for baseline anxiety and depression scores, the number of psychological treatment sessions, and other clinical and demographic variables. The odds of recovery were 2.54 times greater if clients received employment support; 47% of clients who received employment support alongside psychological therapy were classified as recovered, compared with 27% of those receiving psychological therapy only.

CONCLUSIONS

Providing employment support alongside therapy may be particularly helpful for clients belonging to this patient profile, who represent approximately 10% of referrals to NHS Talking Therapies for Anxiety and Depression services. Services could consider how to increase the provision and uptake of employment-focused support to enhance clients' clinical outcomes.

Trajectories of depression and anxiety symptom severity during psychological therapy for common mental health problems

BACKGROUND

There is substantial variation in patient symptoms following psychological therapy for depression and anxiety. However, reliance on endpoint outcomes ignores additional interindividual variation during therapy. Knowing a patient's likely symptom trajectories could guide clinical decisions. We aimed to identify latent classes of patients with similar symptom trajectories over the course of psychological therapy and explore associations between baseline variables and trajectory class.

METHODS

Patients received high-intensity psychological treatment for common mental health problems at National Health Service Improving Access to Psychological Therapies services in South London (N = 16 258). To identify trajectories, we performed growth mixture modelling of depression and anxiety symptoms over 11 sessions. We then ran multinomial regressions to identify baseline variables associated with trajectory class membership.

RESULTS

Trajectories of depression and anxiety symptoms were highly similar and best modelled by four classes. Three classes started with moderate-severe symptoms and showed (1) no change, (2) gradual improvement, and (3) fast improvement. A final class (4) showed initially mild symptoms and minimal improvement. Within the moderate-severe baseline symptom classes, patients in the two showing improvement as opposed to no change tended not to be prescribed psychotropic medication or report a disability and were in employment. Patients showing fast improvement additionally reported lower baseline functional impairment on average.

CONCLUSIONS

Multiple trajectory classes of depression and anxiety symptoms were associated with baseline characteristics. Identifying the most likely trajectory for a patient at the start of treatment could inform decisions about the suitability and continuation of therapy, ultimately improving patient outcomes.

Predicting Youth and Young Adult Treatment Engagement in a Transdiagnostic Remote Intensive Outpatient Program: Latent Profile Analysis

BACKGROUND

The youth mental health crisis in the United States continues to worsen, and research has shown poor mental health treatment engagement. Despite the need for personalized engagement strategies, there is a lack of research involving youth. Due to complex youth developmental milestones, there is a need to better understand clinical presentation and factors associated with treatment engagement to effectively identify and tailor beneficial treatments.

OBJECTIVE

This quality improvement investigation sought to identify subgroups of clients attending a remote intensive outpatient program (IOP) based on clinical acuity data at intake, to determine the factors associated with engagement outcomes for clients who present in complex developmental periods and with cooccurring conditions. The identification of these subgroups was used to inform programmatic decisions within this remote IOP system.

METHODS

Data were collected as part of ongoing quality improvement initiatives at a remote IOP for youth and young adults. Participants included clients (N=2924) discharged between July 2021 and February 2023. A latent profile analysis was conducted using 5 indicators of clinical acuity at treatment entry, and the resulting profiles were assessed for associations with demographic factors and treatment engagement outcomes.

RESULTS

Among the 2924 participants, 4 profiles of clinical acuity were identified: a low-acuity profile (n=943, 32.25%), characterized by minimal anxiety, depression, and self-harm, and 3 high-acuity profiles defined by moderately severe depression and anxiety but differentiated by rates of self-harm (high acuity+low self-harm: n=1452, 49.66%; high acuity+moderate self-harm: n=203, 6.94%; high acuity+high self-harm: n=326, 11.15%). Age, gender, transgender identity, and sexual orientation were significantly associated with profile membership. Clients identified as sexually and gender-marginalized populations were more likely to be classified into high-acuity profiles than into the low-acuity profile (eg, for clients who identified as transgender, high acuity+low self-harm: odds ratio [OR] 2.07, 95% CI 1.35-3.18; P<.001; high acuity+moderate self-harm: OR 2.85, 95% CI 1.66-4.90; P<.001; high acuity+high self-harm: OR 3.67, 95% CI 2.45-5.51; P<.001). Race was unrelated to the profile membership. Profile membership was significantly associated with treatment engagement: youth and young adults in the low-acuity and high-acuity+low-self-harm profiles attended an average of 4 fewer treatment sessions compared with youth in the high-acuity+moderate-self-harm and high-acuity+high-self-harm profiles (ꭓ23=27.6, P<.001). Individuals in the high-acuity+low-self-harm profile completed treatment at a significantly lower rate relative to the other 2 high-acuity profiles (ꭓ23=13.4, P=.004). Finally, those in the high-acuity+high-self-harm profile were significantly less likely to disengage early relative to youth in all other profiles (ꭓ23=71.12, P<.001).

CONCLUSIONS

This investigation represents a novel application for identifying subgroups of adolescents and young adults based on clinical acuity data at intake to identify patterns in treatment engagement outcomes. Identifying subgroups that differentially engage in treatment is a critical first step toward targeting engagement strategies for complex populations.

A randomized controlled trial on using predictive algorithm to adapt level of psychological care for community college students: STAND triaging and adapting to level of care study protocol

BACKGROUND

There is growing interest in using personalized mental health care to treat disorders like depression and anxiety to improve treatment engagement and efficacy. This randomized controlled trial will compare a traditional symptom severity decision-making algorithm to a novel multivariate decision-making algorithm for triage to and adaptation of mental health care. The stratified levels of care include a self-guided online wellness program, coach-guided online cognitive behavioral therapy, and clinician-delivered psychotherapy with or without pharmacotherapy. The novel multivariate algorithm will be comprised of baseline (for triage and adaptation) and time-varying variables (for adaptation) in four areas: social determinants of mental health, early adversity and life stressors, predisposing, enabling, and need influences on health service use, and comprehensive mental health status. The overarching goal is to evaluate whether the multivariate algorithm improves adherence to treatment, symptoms, and functioning above and beyond the symptom-based algorithm.

METHODS/DESIGN

This trial will recruit a total of 1000 participants over the course of 5 years in the greater Los Angeles Metropolitan Area. Participants will be recruited from a highly diverse sample of community college students. For the symptom severity approach, initial triaging to level of care will be based on symptom severity, whereas for the multivariate approach, the triaging will be based on a comprehensive set of baseline measures. After the initial triaging, level of care will be adapted throughout the duration of the treatment, utilizing either symptom severity or multivariate statistical approaches. Participants will complete computerized assessments and self-report questionnaires at baseline and up to 40 weeks. The multivariate decision-making algorithm will be updated annually to improve predictive outcomes.

DISCUSSION

Results will provide a comparison on the traditional symptom severity decision-making and the novel multivariate decision-making with respect to treatment adherence, symptom improvement, and functional recovery. Moreover, the developed multivariate decision-making algorithms may be used as a template in other community college settings. Ultimately, findings will inform the practice of level of care triage and adaptation in psychological treatments, as well as the use of personalized mental health care broadly.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05591937, submitted August 2022, published October 2022.

Associations between psychological therapy outcomes for depression and incidence of dementia

BACKGROUND

Depression is an important, potentially modifiable dementia risk factor. However, it is not known whether effective treatment of depression through psychological therapies is associated with reduced dementia incidence. The aim of this study was to investigate associations between reduction in depressive symptoms following psychological therapy and the subsequent incidence of dementia.

METHODS

National psychological therapy data were linked with hospital records of dementia diagnosis for 119808 people aged 65+. Participants received a course of psychological therapy treatment in Improving Access to Psychological Therapies (IAPT) services between 2012 and 2019. Cox proportional hazards models were run to test associations between improvement in depression following psychological therapy and incidence of dementia diagnosis up to eight years later.

RESULTS

Improvements in depression following treatment were associated with reduced rates of dementia diagnosis up to 8 years later (HR = 0.88, 95% CI 0.83-0.94), after adjustment for key covariates. Strongest effects were observed for vascular dementia (HR = 0.86, 95% CI 0.77-0.97) compared with Alzheimer's disease (HR = 0.91, 95% CI 0.83-1.00).

CONCLUSIONS

Reliable improvement in depression across psychological therapy was associated with reduced incidence of future dementia. Results are consistent with at least two possibilities. Firstly, psychological interventions to improve symptoms of depression may have the potential to contribute to dementia risk reduction efforts. Secondly, psychological therapies may be less effective in people with underlying dementia pathology or they may be more likely to drop out of therapy (reverse causality). Tackling the under-representation of older people in psychological therapies and optimizing therapy outcomes is an important goal for future research.

Trajectories of depression and generalised anxiety symptoms over the course of cognitive behaviour therapy in primary care: an observational, retrospective cohort

BACKGROUND

Cognitive-behavioural therapy (CBT) has been shown to be an effective treatment for depression and anxiety. However, most research has focused on the sum scores of symptoms. Relatively little is known about how individual symptoms respond.

METHODS

Longitudinal models were used to explore how depression and generalised anxiety symptoms behave over the course of CBT in a retrospective, observational cohort of patients from primary care settings (n = 5306). Logistic mixed models were used to examine the probability of being symptom-free across CBT appointments, using the 9-item Patient Health Questionnaire and the 7-item Generalised Anxiety Disorder scale as measures.

RESULTS

All symptoms improve across CBT treatment. The results suggest that low mood/hopelessness and guilt/worthlessness improved quickest relative to other depressive symptoms, with sleeping problems, appetite changes, and psychomotor retardation/agitation improving relatively slower. Uncontrollable worry and too much worry were the anxiety symptoms that improved fastest; irritability and restlessness improved the slowest.

CONCLUSIONS

This research suggests there is a benefit to examining symptoms rather than sum scores alone. Investigations of symptoms provide the potential for precision psychiatry and may explain some of the heterogeneity observed in clinical outcomes when only sum scores are considered.

Understanding the psychological therapy treatment outcomes for young adults who are not in education, employment, or training (NEET), moderators of outcomes, and what might be done to improve them

BACKGROUND

To determine: whether young adults (aged 18-24) not in education, employment or training (NEET) have different psychological treatment outcomes to other young adults; any socio-demographic or treatment-related moderators of differential outcomes; and whether service-level changes are associated with better outcomes for those who are NEET.

METHODS

A cohort was formed of 20 293 young adults treated with psychological therapies in eight Improving Access to Psychological Therapies services. Pre-treatment characteristics, outcomes, and moderators of differential outcomes were compared for those who were and were not NEET. Associations between outcomes and the following were assessed for those that were NEET: missing fewer sessions, attending more sessions, having a recorded diagnosis, and waiting fewer days between referral and starting treatment.

RESULTS

Those who were NEET had worse outcomes: odds ratio (OR) [95% confidence interval (CI)] for reliable recovery = 0.68 (0.63-0.74), for deterioration = 1.41 (1.25-1.60), and for attrition = 1.31 (1.19-1.43). Ethnic minority participants that were NEET had better outcomes than those that were White and NEET. Living in deprived areas was associated with worse outcomes. The intensity of treatment (high or low) did not moderate outcomes, but having more sessions was associated with improved outcomes for those that were NEET: odds (per one-session increase) of reliable recovery = 1.10 (1.08-1.12), deterioration = 0.94 (0.91-0.98), and attrition = 0.68 (0.66-0.71).

CONCLUSIONS

Earlier treatment, supporting those that are NEET to attend sessions, and in particular, offering them more sessions before ending treatment might be effective in improving clinical outcomes. Additional support when working with White young adults that are NEET and those in more deprived areas may also be important.

Personalised psychotherapy in primary care: evaluation of data-driven treatment allocation to cognitive-behavioural therapy versus counselling for depression

BACKGROUND

Various effective psychotherapies exist for the treatment of depression; however, only approximately half of patients recover after treatment. In efforts to improve clinical outcomes, research has focused on personalised psychotherapy - an attempt to match patients to treatments they are most likely to respond to.

AIM

The present research aimed to evaluate the benefit of a data-driven model to support clinical decision-making in differential treatment allocation to cognitive-behavioural therapy versus counselling for depression.

METHOD

The present analysis used electronic healthcare records from primary care psychological therapy services for patients receiving cognitive-behavioural therapy (n = 14 544) and counselling for depression (n = 4725). A linear regression with baseline sociodemographic and clinical characteristics was used to differentially predict post-treatment Patient Health Questionnaire (PHQ-9) scores between the two treatments. The benefit of differential prescription was evaluated in a held-out validation sample.

RESULTS

On average, patients who received their model-indicated optimal treatment saw a greater improvement (by 1.78 PHQ-9 points). This translated into 4-10% more patients achieving clinically meaningful changes. However, for individual patients, the estimated differences in benefits of treatments were small and rarely met the threshold for minimal clinically important differences.

CONCLUSION

Precision prescription of psychotherapy based on sociodemographic and clinical characteristics is unlikely to produce large benefits for individual patients. However, the benefits may be meaningful from an aggregate public health perspective when applied at scale.

A next-generation approach to mental health outcomes: Treatment, time, and trajectories

Over the last several decades, inpatient psychiatric length of stay (LOS) has been greatly reduced to the detriment of patients. Latent variable mixture modeling, can be used to improve the quality of care for patients by identifying unobserved subgroups and optimize treatment variables, including LOS. This study had three objectives (1) to replicate the findings made by Oh et al. in a distinct sample, (2) to examine demographic differences related to inpatient treatment trajectories, and (3) to relate additional variables to each trajectory. We collected data on six key mental illness factors and information on felonies, misdemeanors, history of stopping psychiatric medication and psychotherapy, length of time in psychotherapy, and the number of therapists and psychiatrists from 489 patients at an inpatient psychiatric hospital. We derived latent mental illness scores after applying growth mixture modeling to these data. We identified three distinct trajectories of mental illness change: High-Risk, Rapid Improvement (HR-RI), Low-Risk, Partial Response (LR-PR), and High-Risk, Gradual Improvement (HR-GI). The HR-GI group was more likely to have patients who were female, Asian, younger, Yearly Income (YI) <$20,000, that spent more time in psychotherapy throughout their life, and had the longest LOS while inpatient. The LR-PR group had was more likely to be male, Hispanic/Latino and multiracial, older, YI >$500,000, have a history of misdemeanors, and this group had the shortest LOS (p < .05). These findings replicate and extend our previous findings in Oh et al. (2020a) and highlight the clinical utility of agnostically determining the treatment trajectories.

Symptom-specific effects of counselling for depression compared to cognitive-behavioural therapy

BACKGROUND

Cognitive-behavioural therapy (CBT) and counselling for depression (CfD) are recommended first-line treatments for depression. While they approach change differently, there is little understanding of the impact those approaches have on change during treatment.

OBJECTIVES

This study aimed to identify whether CBT and CfD target different symptoms and explore the implications of modelling choices when quantifying change during treatment.

METHODS

Symptom-specific effects of treatment were identified using moderated network modelling. This was a retrospective cohort study of 12 756 individuals who received CBT or CfD for depression in primary/community care psychological therapy services in England. Change was modelled several ways within the whole sample and a propensity score matched sample (n=3446).

FINDINGS

CBT for depression directly affected excessive worry, trouble relaxing and apprehensive expectation and had a stronger influence on changes between suicidal ideation and concentration. CfD had a stronger direct influence on thoughts of being a failure and on the associated change between being an easily annoyed and apprehensive of expectation. There were inconsistencies when modelling change using the first and second appointments as the baseline. Residual score models produced more conservative findings than models using difference scores.

CONCLUSIONS

CfD and CBT for depression have differential effects on symptoms demonstrating specific mechanisms of change.

CLINICAL IMPLICATIONS

CBT was uniquely associated with changes in symptoms associated with anxiety and may be better suited to those with anxiety symptoms comorbid to their depression. When assessing change, the baseline should be the first therapy session, not the pretreatment assessment. Residual change scores should be preferred over difference score methods.

Riuscire a ottenere un beneficio di massa tramite l'offerta di terapie psicologiche: l'esperienza del programma inglese

Viene pubblicata la trascrizione della relazione tenuta al Convegno "Le terapie psicologiche per l'ansia e la depressione: nuove forme di integrazione clinica e organizzativa" (Isola di San Servolo, Venezia, 26 ottobre 2022). Dopo la descrizione delle principali caratteristiche del programma inglese Improving Access to Psychological Therapies (IAPT), viene sottolineata l'importanza di alcuni aspetti tra cui i seguenti: l'affidabilità delle linee-guida; un programma nazionale di training in cui si valuta accuratamente anche la competenza raggiunta dai terapeuti; la raccolta di tutti i risultati e la loro pubblicazione, che ha permesso di capire molti problemi (come ridurre le differenze nei risultati di gruppi etnici diversi, come migliorare i Servizi in aree povere, etc.); il benessere e la motivazione degli operatori (circa 10.000 terapeuti), che devono avere figure di leadership innovative che non danno solo importanza al risultato ma che sanno anche creare un ambiente di lavoro stimolante in cui si lavora volentieri e col piacere di apprendere sempre nuove cose.

Are students less likely to respond to routinely delivered psychological treatment? A retrospective cohort analysis

BACKGROUND

Depression and anxiety disorders are increasingly prevalent among university students, making the provision of effective treatment in this population a priority. Whilst campus-based services provide some psychological treatments, many students are treated by routine adult psychological treatment services which have no focus or adaptations to treatment for student populations. We aimed to compare psychological treatment outcomes between university students and young adults (aged 18-25) in employment to explore whether routinely delivered psychological interventions are equally effective for these groups, or whether students report poorer outcomes.

METHODS

A retrospective cohort was formed of 19,707 patients treated by eight National Health Service (NHS) Improving Access to Psychological Therapies (IAPT) services in England. Associations between student status (compared to same-age employed adults) and psychological treatment outcomes were explored using logistic regression models. Models were adjusted for important treatment, clinical and demographic characteristics, and propensity score matching was used to explore the robustness of effects.

RESULTS

Students and the employed comparison group were similar on baseline characteristics at assessment, but students were less likely to reliably recover (OR = 0.90 [95% CI = 0.83;0.96]) and reliably improve (OR = 0.91 [95% CI = 0.84;0.98]) by the end of treatment in fully adjusted models. Students and the employed group did not differ regarding the likelihood of deterioration (OR = 0.89 [95% CI = 0.78;1.02]) or treatment dropout (OR = 1.01 [95% CI = 0.93;1.11]).

CONCLUSIONS

Students appear at risk of poorer outcomes compared to employed younger adults when treated in routine psychological treatment services. Students may require additional support and treatment adaptations that account for student-specific stressors as this might improve psychological treatment outcomes.

Understanding differences in mental health service use by men: an intersectional analysis of routine data

PURPOSE

Rates of help-seeking for common mental health problems are lower for men, but less is known about patterns of engagement once they are in contact with services. Previous research has been limited in its ability to understand the intersection between service user characteristics and engagement. This study compared analytic approaches to investigate intersectional associations between sociodemographic and socioeconomic indicators and use of psychological treatment services by men.

METHOD

Data from 9,904 male service users attending two psychological treatment services in London were analysed. The association between ethnicity, sexual orientation, religious affiliation and employment status of service users and service use outcomes was explored using multinomial logistic regression and latent class analysis (LCA).

RESULTS

Being from a minoritised ethnic background, of Muslim faith, being unemployed, and living in the most deprived neighbourhoods were associated with greater risk of not commencing or completing treatment. Seven classes were identified in LCA, with men predominately differentiated by self-reported ethnicity and religion. Compared with the 'White British, non-religious' class, the 'Asian Muslim' class and the 'minoritised ethnic, non-religious' class were at higher risk of disengagement, whilst the 'Asian, other religion' class were at higher risk of being referred elsewhere rather than completing initiated treatment.

CONCLUSIONS

There were significant inequalities in engagement by men associated with ethnicity, religion and socioeconomic status. Compared with the regression models, further nuance was apparent in LCA regarding the intersection of gender, religion and ethnicity. Identifying groups at greater risk of discontinuation of treatment could inform more personalised pathways through care.

Are subtypes of affective symptoms differentially associated with change in cognition over time: A latent class analysis

BACKGROUND

In the absence of disease-modifying treatments, identifying potential psychosocial risk factors for dementia is paramount. Depression and anxiety have been identified as potential risk factors. Studies however have yielded mixed findings, lending possibility to the fact that potential constellations of co-occurring depression and anxiety symptoms may better explain the link between affective symptoms and cognitive decline.

METHODS

Data from participants (aged 50 and above) of the PROTECT study was used. Latent Class Analysis (LCA) was conducted on 21,684 participants with baseline anxiety and depression measures. Multiple linear regressions models, using a subset of these participants (N = 6136) who had complete cognition data at baseline and at 2-year follow-up, were conducted to assess for associations between class membership and longitudinal changes in cognition.

RESULTS

The LCA identified a 5-class solution: "No Symptoms", "Sleep", "Sleep and Worry", "Sleep and Anhedonia", and "Co-morbid Depression and Anxiety". Class membership was significantly associated with longitudinal change in cognition. Furthermore, this association differed across different cognitive measures.

LIMITATIONS

Limitations included significant attrition and a generally healthy sample which may impact generalisability.

CONCLUSIONS

Substantial heterogeneity in affective symptoms could explain previous inconsistent findings concerning the association between affective symptoms and cognition. Clinicians should not focus solely on total symptom scores on a single affective domain, but instead on the presence and patterns of symptoms (even if sub-clinical) on measures across multiple affective domains. Identifying particular subgroups that are at greater risk of poor cognitive outcomes may support targeted prevention work.

Transdiagnostic symptom dynamics during psychotherapy

Psychotherapy is an effective treatment for many common mental health problems, but the mechanisms of action and processes of change are unclear, perhaps driven by the focus on a single diagnosis which does not reflect the heterogeneous symptom experiences of many patients. The objective of this study was to better understand therapeutic change, by illustrating how symptoms evolve and interact during psychotherapy. Data from 113,608 patients from psychological therapy services who completed depression and anxiety symptom measures across three to six therapy sessions were analysed. A panel graphical vector-autoregression model was estimated in a model development sample (N = 68,165) and generalizability was tested in a confirmatory model, fitted to a separate (hold-out) sample of patients (N = 45,443). The model displayed an excellent fit and replicated in the confirmatory holdout sample. First, we found that nearly all symptoms were statistically related to each other (i.e. dense connectivity), indicating that no one symptom or association drives change. Second, the structure of symptom interrelations which emerged did not change across sessions. These findings provide a dynamic view of the process of symptom change during psychotherapy and give rise to several causal hypotheses relating to structure, mechanism, and process.

A Patient Stratification Approach to Identifying the Likelihood of Continued Chronic Depression and Relapse Following Treatment for Depression

Background: Subgrouping methods have the potential to support treatment decision making for patients with depression. Such approaches have not been used to study the continued course of depression or likelihood of relapse following treatment. Method: Data from individual participants of seven randomised controlled trials were analysed. Latent profile analysis was used to identify subgroups based on baseline characteristics. Associations between profiles and odds of both continued chronic depression and relapse up to one year post-treatment were explored. Differences in outcomes were investigated within profiles for those treated with antidepressants, psychological therapy, and usual care. Results: Seven profiles were identified; profiles with higher symptom severity and long durations of both anxiety and depression at baseline were at higher risk of relapse and of chronic depression. Members of profile five (likely long durations of depression and anxiety, moderately-severe symptoms, and past antidepressant use) appeared to have better outcomes with psychological therapies: antidepressants vs. psychological therapies (OR (95% CI) for relapse = 2.92 (1.24–6.87), chronic course = 2.27 (1.27–4.06)) and usual care vs. psychological therapies (relapse = 2.51 (1.16–5.40), chronic course = 1.98 (1.16–3.37)). Conclusions: Profiles at greater risk of poor outcomes could benefit from more intensive treatment and frequent monitoring. Patients in profile five may benefit more from psychological therapies than other treatments.

Treatment selection using prototyping in latent-space with application to depression treatment

Machine-assisted treatment selection commonly follows one of two paradigms: a fully personalized paradigm which ignores any possible clustering of patients; or a sub-grouping paradigm which ignores personal differences within the identified groups. While both paradigms have shown promising results, each of them suffers from important limitations. In this article, we propose a novel deep learning-based treatment selection approach that is shown to strike a balance between the two paradigms using latent-space prototyping. Our approach is specifically tailored for domains in which effective prototypes and sub-groups of patients are assumed to exist, but groupings relevant to the training objective are not observable in the non-latent space. In an extensive evaluation, using both synthetic and Major Depressive Disorder (MDD) real-world clinical data describing 4754 MDD patients from clinical trials for depression treatment, we show that our approach favorably compares with state-of-the-art approaches. Specifically, the model produced an 8% absolute and 23% relative improvement over random treatment allocation. This is potentially clinically significant, given the large number of patients with MDD. Therefore, the model can bring about a much desired leap forward in the way depression is treated today.

Profiles and trajectories of mental health service utilisation during early intervention in psychosis

BACKGROUND

Early intervention in psychosis services (EIS) support individuals experiencing a first episode of psychosis. Support required will vary in response to the remittance and reoccurrence of symptoms, including relapses. Characterising individuals who will need more intensive support can inform care planning. This study explores service utilisation profiles and their trajectories of service use in a sample of individuals referred to EIS.

METHOD

We analysed service utilisation during the 3 years following referral to EIS (n = 2363) in West London between 2011 and 2020. Mental health service utilisation data were submitted to model-based clustering. Latent growth models were then estimated for identified profiles. Profiles were compared regarding clinical and demographic characteristics and onward pathways of care.

RESULTS

Analyses revealed 5 profiles of individuals attending EIS based on their service utilisation over 3 years. 55.5% of the sample were members of a low utilisation and less clinically severe profile. The distinct service use patterns of these profiles were associated with Health of the Nations Outcome Scale scores at treatment initiation (at total, subscale, and individual item level), along with age and gender. These patterns of use were also associated with onward care and ethnicity.

CONCLUSIONS

Profiles and trajectories of service utilisation call for development of integrated care pathways and use of more personalised interventions. Services should consider patient symptoms and characteristics when making clinical decisions informing the provision of care. The profiles represent typical patterns of service use, and identifying factors associated with these subgroups might help optimise EIS support.

The contribution of depressive 'disorder characteristics' to determinations of prognosis for adults with depression: an individual patient data meta-analysis

BACKGROUND

This study aimed to investigate general factors associated with prognosis regardless of the type of treatment received, for adults with depression in primary care.

METHODS

We searched Medline, Embase, PsycINFO and Cochrane Central (inception to 12/01/2020) for RCTs that included the most commonly used comprehensive measure of depressive and anxiety disorder symptoms and diagnoses, in primary care depression RCTs (the Revised Clinical Interview Schedule: CIS-R). Two-stage random-effects meta-analyses were conducted.

RESULTS

Twelve (n = 6024) of thirteen eligible studies (n = 6175) provided individual patient data. There was a 31% (95%CI: 25 to 37) difference in depressive symptoms at 3-4 months per standard deviation increase in baseline depressive symptoms. Four additional factors: the duration of anxiety; duration of depression; comorbid panic disorder; and a history of antidepressant treatment were also independently associated with poorer prognosis. There was evidence that the difference in prognosis when these factors were combined could be of clinical importance. Adding these variables improved the amount of variance explained in 3-4 month depressive symptoms from 16% using depressive symptom severity alone to 27%. Risk of bias (assessed with QUIPS) was low in all studies and quality (assessed with GRADE) was high. Sensitivity analyses did not alter our conclusions.

CONCLUSIONS

When adults seek treatment for depression clinicians should routinely assess for the duration of anxiety, duration of depression, comorbid panic disorder, and a history of antidepressant treatment alongside depressive symptom severity. This could provide clinicians and patients with useful and desired information to elucidate prognosis and aid the clinical management of depression.

Improvement in IAPT outcomes over time: are they driven by changes in clinical practice?

Treatment outcomes across Improving Access to Psychological Therapies (IAPT) services in England have improved year-on-year, with the national average proportion of patients in recovery at the end of treatment now exceeding the 50% target. This is despite the number of referrals and numbers of treated patients also increasing year-on-year, suggesting that services have evolved local practices and treatment delivery to meet needs whilst improving performance. This study explores whether there have been changes in clinical practice with regard to: (1) the number of sessions and length of treatments; (2) the number of cancellations and non-attendance; and (3) the recording of problem descriptor information, and the association with treatment outcomes in IAPT. Routinely collected data from seven IAPT services involved in the North and Central East London (NCEL) IAPT Service Improvement and Research Network (SIRN) were brought together to form a dataset of nearly 88,000 patients who completed a course of IAPT treatment. Results showed that there was a slight increase in the average number of sessions, and decreases in the length of time in treatment, as well as decreases in both the number of non-attended appointments and the use of inappropriate problem descriptors. These findings highlight a number of areas where potentially small changes to clinical practice may have had positive effects on patient outcomes. The value of using IAPT data to inform service improvement evaluations is discussed.

Predicting Response to Brain Stimulation in Depression: a Roadmap for Biomarker Discovery

PURPOSE OF REVIEW

Clinical response to brain stimulation treatments for depression is highly variable. A major challenge for the field is predicting an individual patient's likelihood of response. This review synthesises recent developments in neural predictors of response to targeted brain stimulation in depression. It then proposes a framework to evaluate the clinical potential of putative 'biomarkers'.

RECENT FINDINGS

Largely, developments in identifying putative predictors emerge from two approaches: data-driven, including machine learning algorithms applied to resting state or structural neuroimaging data, and theory-driven, including task-based neuroimaging. Theory-driven approaches can also yield mechanistic insight into the cognitive processes altered by the intervention.

SUMMARY

A pragmatic framework for discovery and testing of biomarkers of brain stimulation response in depression is proposed, involving (1) identification of a cognitive-neural phenotype; (2) confirming its validity as putative biomarker, including out-of-sample replicability and within-subject reliability; (3) establishing the association between this phenotype and treatment response and/or its modifiability with particular brain stimulation interventions via an early-phase randomised controlled trial RCT; and (4) multi-site RCTs of one or more treatment types measuring the generalisability of the biomarker and confirming the superiority of biomarker-selected patients over randomly allocated groups.

Time in treatment: Examining mental illness trajectories across inpatient psychiatric treatment

Early discharge or reduced length of stay for inpatient psychiatric patients is related to increased readmission rates and worse clinical outcomes including increased risk for suicide. Trajectories of mental illness outcomes have been identified as an important method for predicting the optimal length of stay but the distinguishing factors that separate trajectories remain unclear. We sought to identify the distinct classes of patients who demonstrated similar trajectories of mental illness over the course of inpatient treatment, and we explore the patient characteristics associated with these mental illness trajectories. We used data (N = 3406) from an inpatient psychiatric hospital with intermediate lengths of stay. Using growth mixture modeling, latent mental illness scores were derived from six mental illness indicators: psychological flexibility, emotion regulation problems, anxiety, depression, suicidal ideation, and disability. The patients were grouped into three distinct trajectory classes: (1) High-Risk, Rapid Improvement (HR-RI); (2) Low-Risk, Gradual Improvement (LR-GI); and (3) High-Risk, Gradual Improvement (HR-GI). The HR-GI was significantly younger than the other two classes. The HR-GI had significantly more female patients than males, while the LR-GI had more male patients than females. Our findings indicated that younger females had more severe mental illness at admission and only gradual improvement during the inpatient treatment period, and they remained in treatment for longer lengths of stay, than older males.