Naomi E. Thrower, Sandra Bucci, Lydia Morris, Katherine Berry
Objective
Psychological formulation is a key competency for clinical psychologists. However, there is a lack of consensus regarding the key components and processes of formulation that are hypothesized to contribute to poor reliability of formulations. The aim of this study was to develop consensus on the essential components of a formulation to inform training for clinical psychologists and best practice guidelines.
Methods
A Delphi methodology was used. Items were generated from the literature and discussed and refined with a panel of experts (n = 10). In round one, 110 clinical psychologists in the United Kingdom rated the importance of components of formulation via an online questionnaire. Criteria for consensus were applied and statements were rerated in round two if consensus was not achieved.
Results
Consensus was achieved on 30 items, with 18 statements regarding components of a formulation and 12 statements regarding formulation process. Items that clinicians agreed upon emphasized the importance of integrating sociocultural, biological, strengths and personal meaning alongside well-established theoretical frameworks. Consensus was not reached on 20 items, including whether a formulation should be parsimonious or adhere to a model.
Conclusion
Our findings provide mixed evidence regarding consensus on the key components of formulation. There was an agreement that formulation should be client-led and incorporate strengths and sociocultural factors. Further research should explore client perspectives on the key components of formulation and how these compare to the clinicians' perspectives.
{"title":"The key components of a clinical psychology formulation: A consensus study","authors":"Naomi E. Thrower, Sandra Bucci, Lydia Morris, Katherine Berry","doi":"10.1111/bjc.12455","DOIUrl":"10.1111/bjc.12455","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>Psychological formulation is a key competency for clinical psychologists. However, there is a lack of consensus regarding the key components and processes of formulation that are hypothesized to contribute to poor reliability of formulations. The aim of this study was to develop consensus on the essential components of a formulation to inform training for clinical psychologists and best practice guidelines.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A Delphi methodology was used. Items were generated from the literature and discussed and refined with a panel of experts (<i>n</i> = 10). In round one, 110 clinical psychologists in the United Kingdom rated the importance of components of formulation via an online questionnaire. Criteria for consensus were applied and statements were rerated in round two if consensus was not achieved.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Consensus was achieved on 30 items, with 18 statements regarding components of a formulation and 12 statements regarding formulation process. Items that clinicians agreed upon emphasized the importance of integrating sociocultural, biological, strengths and personal meaning alongside well-established theoretical frameworks. Consensus was not reached on 20 items, including whether a formulation should be parsimonious or adhere to a model.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Our findings provide mixed evidence regarding consensus on the key components of formulation. There was an agreement that formulation should be client-led and incorporate strengths and sociocultural factors. Further research should explore client perspectives on the key components of formulation and how these compare to the clinicians' perspectives.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48211,"journal":{"name":"British Journal of Clinical Psychology","volume":"63 2","pages":"213-226"},"PeriodicalIF":3.1,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bjc.12455","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139484389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Assessment of autism-related behaviours (ARBs) in children has generally been limited to direct observations in clinical settings or informant-based reports. The widespread availability of video-streaming devices has made home observations of children's ARBs feasible. This approach could enable assessment of the generalization and durability of interventions and may be able to overcome methodological limitations of predominant current assessment approaches (response biases, limited sensitivity to treatment).
Design and Methods
Forty-four autistic children and their families participated in a repeated-measures study with a correlational design. Approximately 10 hr of unprompted behaviour at home were videorecorded over the course of a week (2 hr per day) for each participant. Gold standard measures of ARBs were also administered (ADOS-2 and ADI-R). Two home-based observational measures of ARBs utilizing streaming video were developed and evaluated: the ARCHER and the CHEERS. Trained independent evaluators made ratings on the ARCHER, CHEERS and an observational measure of parental responsiveness.
Results
Correlations with the ADOS-2 and ADI-R were .47 and .34 for ARCHER scores and .51 and .48 for CHEERS scores, respectively. In linear mixed models, more responsive parenting was associated with fewer ARBs on a daily basis. Children spent their afternoons engaged in many typical activities including electronics, homework and games with family members, and ARBs were more prominent in some of these contexts (e.g., electronics) than others (e.g., family games).
Conclusions
Home-based observational assessment of ARBs may be useful for clinical and descriptive research.
{"title":"Home-based video assessment of children's autism-related behaviours: Psychometric analysis and linkages with parental responsiveness and context","authors":"Jeffrey J. Wood, John Danial, Samara Wolpe","doi":"10.1111/bjc.12449","DOIUrl":"10.1111/bjc.12449","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>Assessment of autism-related behaviours (ARBs) in children has generally been limited to direct observations in clinical settings or informant-based reports. The widespread availability of video-streaming devices has made home observations of children's ARBs feasible. This approach could enable assessment of the generalization and durability of interventions and may be able to overcome methodological limitations of predominant current assessment approaches (response biases, limited sensitivity to treatment).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Design and Methods</h3>\u0000 \u0000 <p>Forty-four autistic children and their families participated in a repeated-measures study with a correlational design. Approximately 10 hr of unprompted behaviour at home were videorecorded over the course of a week (2 hr per day) for each participant. Gold standard measures of ARBs were also administered (ADOS-2 and ADI-R). Two home-based observational measures of ARBs utilizing streaming video were developed and evaluated: the ARCHER and the CHEERS. Trained independent evaluators made ratings on the ARCHER, CHEERS and an observational measure of parental responsiveness.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Correlations with the ADOS-2 and ADI-R were .47 and .34 for ARCHER scores and .51 and .48 for CHEERS scores, respectively. In linear mixed models, more responsive parenting was associated with fewer ARBs on a daily basis. Children spent their afternoons engaged in many typical activities including electronics, homework and games with family members, and ARBs were more prominent in some of these contexts (e.g., electronics) than others (e.g., family games).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Home-based observational assessment of ARBs may be useful for clinical and descriptive research.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48211,"journal":{"name":"British Journal of Clinical Psychology","volume":"63 2","pages":"197-212"},"PeriodicalIF":3.1,"publicationDate":"2024-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139425770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rachel E. Menzies, Bethany Richmond, Louise Sharpe, Amira Skeggs, Janessa Liu, Daelin Coutts-Bain
Objectives
Therapists have long observed a phenomenon referred to as the ‘revolving door’ of mental health services, in which individuals often develop, seek treatment for, and recover from multiple mental illnesses across their life. However, this has not been systematically examined. If this phenomenon is widespread, one would expect that the number of lifetime disorders would exceed that of current disorders. The aim of this meta-analysis was to test this hypothesis.
Methods
A search was conducted of the following databases: MEDLINE, PsycINFO and Web of Science. In total, 38 studies were included in the current review; 27 of these contained sufficient quantitative data to be included in the meta-analysis, addressing the primary research aim. The remaining 11 studies were included in the systematic review only.
Results
Meta-analyses of the 27 studies indicated that the average number of lifetime disorders was 1.84 times that of current disorders. Previous treatment significantly moderated this relationship, while the clinical nature of the sample did not. Examination of the remaining studies revealed common temporal sequences, indicating disorders which typically develop first or consequently to other disorders.
Conclusions
These findings provide support for the revolving door of mental illness, suggesting a need for transdiagnostic treatments and broader conceptualisation of relapse prevention.
目的：长期以来，治疗师们一直在观察一种被称为心理健康服务 "旋转门 "的现象，即一个人在一生中往往会患上、寻求治疗并从多种精神疾病中康复。然而，这种现象并没有得到系统的研究。如果这种现象普遍存在，人们就会认为终生患有精神疾病的人数会超过目前患有精神疾病的人数。本荟萃分析旨在验证这一假设：方法：对以下数据库进行了检索：方法：对以下数据库进行了检索：MEDLINE、PsycINFO 和 Web of Science。共有 38 项研究被纳入本次综述；其中 27 项研究包含足够的定量数据，可纳入荟萃分析，以实现主要研究目标。其余 11 项研究仅纳入系统综述：对 27 项研究进行的元分析表明，终生失调的平均次数是当前失调的 1.84 倍。曾经接受过的治疗在很大程度上调节了这种关系，而样本的临床性质则没有调节作用。对其余研究的审查显示了共同的时间顺序，表明失调症通常先出现或随后出现其他失调症：这些研究结果为精神疾病的 "旋转门 "提供了支持，表明需要跨诊断治疗和更广泛的预防复发概念。
{"title":"The ‘revolving door’ of mental illness: A meta-analysis and systematic review of current versus lifetime rates of psychological disorders","authors":"Rachel E. Menzies, Bethany Richmond, Louise Sharpe, Amira Skeggs, Janessa Liu, Daelin Coutts-Bain","doi":"10.1111/bjc.12453","DOIUrl":"10.1111/bjc.12453","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>Therapists have long observed a phenomenon referred to as the ‘revolving door’ of mental health services, in which individuals often develop, seek treatment for, and recover from multiple mental illnesses across their life. However, this has not been systematically examined. If this phenomenon is widespread, one would expect that the number of lifetime disorders would exceed that of current disorders. The aim of this meta-analysis was to test this hypothesis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A search was conducted of the following databases: MEDLINE, PsycINFO and Web of Science. In total, 38 studies were included in the current review; 27 of these contained sufficient quantitative data to be included in the meta-analysis, addressing the primary research aim. The remaining 11 studies were included in the systematic review only.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Meta-analyses of the 27 studies indicated that the average number of lifetime disorders was 1.84 times that of current disorders. Previous treatment significantly moderated this relationship, while the clinical nature of the sample did not. Examination of the remaining studies revealed common temporal sequences, indicating disorders which typically develop first or consequently to other disorders.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>These findings provide support for the revolving door of mental illness, suggesting a need for transdiagnostic treatments and broader conceptualisation of relapse prevention.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48211,"journal":{"name":"British Journal of Clinical Psychology","volume":"63 2","pages":"178-196"},"PeriodicalIF":3.1,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bjc.12453","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139404753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Laura Fusar-Poli, Fabio Panariello, Katherine Berry, Matteo Rocchetti, Letizia Casiraghi, Matteo Malvezzi, Fabrizio Starace, Manuel Zamparini, Cristina Zarbo, Giovanni de Girolamo, DiAPAson Consortium
Objectives
Working Alliance (WA) is important in the care of patients with Schizophrenia Spectrum Disorders (SSD). This study aims to determine which sociodemographic and clinical factors are associated with WA, as assessed by patients and staff members in Residential Facilities (RFs), and may predict WA dyads' discrepancies.
Methods
Three hundred and three SSD patients and 165 healthcare workers were recruited from 98 RFs and characterized for sociodemographic features. WA was rated by the Working Alliance Inventory (WAI) for patients (WAI-P) and staff members (WAI-T). SSD patients were assessed for the severity of psychopathology and psychosocial functioning.
Results
Pearson's correlation revealed a positive correlation (ρ = .314; p < .001) between WAI-P and WAI-T ratings. Linear regression showed that patients with higher education reported lower WAI-P ratings (β = −.50, p = .044), while not being engaged in work or study was associated with lower WAI-T scores (β = −4.17, p = .015). A shorter lifetime hospitalization was associated with higher WAI-P ratings (β = 5.90, p = .008), while higher psychopathology severity negatively predicted WAI-T (β = −.10, p = .002) and WAI-P ratings (β = −.19, p < .001). Better functioning level positively foresaw WAI-T (β = .14, p < .001) and WAI-P ratings (β = .12, p < .001). Regarding discrepancies, staff members' age was associated with higher dyads discrepancy in Total scale and Agreement subscale scores, which were also associated with more severe negative symptoms, while patients' age was negatively correlated to Relationship subscale discrepancy.
Conclusions
This study provides insight into the factors that influence WA in SSD patients and health workers in RFs. The findings address interventions to improve WA and ultimately patient outcomes.
{"title":"Working alliance in treating staff and patients with Schizophrenia Spectrum Disorder living in Residential Facilities","authors":"Laura Fusar-Poli, Fabio Panariello, Katherine Berry, Matteo Rocchetti, Letizia Casiraghi, Matteo Malvezzi, Fabrizio Starace, Manuel Zamparini, Cristina Zarbo, Giovanni de Girolamo, DiAPAson Consortium","doi":"10.1111/bjc.12450","DOIUrl":"10.1111/bjc.12450","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>Working Alliance (WA) is important in the care of patients with Schizophrenia Spectrum Disorders (SSD). This study aims to determine which sociodemographic and clinical factors are associated with WA, as assessed by patients and staff members in Residential Facilities (RFs), and may predict WA dyads' discrepancies.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Three hundred and three SSD patients and 165 healthcare workers were recruited from 98 RFs and characterized for sociodemographic features. WA was rated by the Working Alliance Inventory (WAI) for patients (WAI-P) and staff members (WAI-T). SSD patients were assessed for the severity of psychopathology and psychosocial functioning.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Pearson's correlation revealed a positive correlation (<i>ρ</i> = .314; <i>p</i> < .001) between WAI-P and WAI-T ratings. Linear regression showed that patients with higher education reported lower WAI-P ratings (<i>β</i> = −.50, <i>p</i> = .044), while not being engaged in work or study was associated with lower WAI-T scores (<i>β</i> = −4.17, <i>p</i> = .015). A shorter lifetime hospitalization was associated with higher WAI-P ratings (<i>β</i> = 5.90, <i>p</i> = .008), while higher psychopathology severity negatively predicted WAI-T (<i>β</i> = −.10, <i>p</i> = .002) and WAI-P ratings (<i>β</i> = −.19, <i>p</i> < .001). Better functioning level positively foresaw WAI-T (<i>β</i> = .14, <i>p</i> < .001) and WAI-P ratings (<i>β</i> = .12, <i>p</i> < .001). Regarding discrepancies, staff members' age was associated with higher dyads discrepancy in Total scale and Agreement subscale scores, which were also associated with more severe negative symptoms, while patients' age was negatively correlated to Relationship subscale discrepancy.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>This study provides insight into the factors that influence WA in SSD patients and health workers in RFs. The findings address interventions to improve WA and ultimately patient outcomes.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48211,"journal":{"name":"British Journal of Clinical Psychology","volume":"63 2","pages":"156-177"},"PeriodicalIF":3.1,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bjc.12450","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138812420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Previous research on psychotherapy treatment response has mainly focused on outpatients or clinical trial data which may have low ecological validity regarding naturalistic inpatient samples. To reduce treatment failures by proactively screening for patients at risk of low treatment response, gain more knowledge about risk factors and to evaluate treatments, accurate insights about predictors of treatment response in naturalistic inpatient samples are needed.
Methods
We compared the performance of different machine learning algorithms in predicting treatment response, operationalized as a substantial reduction in symptom severity as expressed in the Patient Health Questionnaire Anxiety and Depression Scale. To achieve this goal, we used different sets of variables—(a) demographics, (b) physical indicators, (c) psychological indicators and (d) treatment-related variables—in a naturalistic inpatient sample (N = 723) to specify their joint and unique contribution to treatment success.
Results
There was a strong link between symptom severity at baseline and post-treatment (R2 = .32). When using all available variables, both machine learning algorithms outperformed the linear regressions and led to an increment in predictive performance of R2 = .12. Treatment-related variables were the most predictive, followed psychological indicators. Physical indicators and demographics were negligible.
Conclusions
Treatment response in naturalistic inpatient settings can be predicted to a considerable degree by using baseline indicators. Regularization via machine learning algorithms leads to higher predictive performances as opposed to including nonlinear and interaction effects. Heterogenous aspects of mental health have incremental predictive value and should be considered as prognostic markers when modelling treatment processes.
{"title":"Predicting treatment response using machine learning: A registered report","authors":"Kristin Jankowsky, Lina Krakau, Ulrich Schroeders, Rüdiger Zwerenz, Manfred E. Beutel","doi":"10.1111/bjc.12452","DOIUrl":"10.1111/bjc.12452","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>Previous research on psychotherapy treatment response has mainly focused on outpatients or clinical trial data which may have low ecological validity regarding naturalistic inpatient samples. To reduce treatment failures by proactively screening for patients at risk of low treatment response, gain more knowledge about risk factors and to evaluate treatments, accurate insights about predictors of treatment response in naturalistic inpatient samples are needed.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We compared the performance of different machine learning algorithms in predicting treatment response, operationalized as a substantial reduction in symptom severity as expressed in the Patient Health Questionnaire Anxiety and Depression Scale. To achieve this goal, we used different sets of variables—(a) demographics, (b) physical indicators, (c) psychological indicators and (d) treatment-related variables—in a naturalistic inpatient sample (<i>N</i> = 723) to specify their joint and unique contribution to treatment success.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>There was a strong link between symptom severity at baseline and post-treatment (<i>R</i><sup>2</sup> = .32). When using all available variables, both machine learning algorithms outperformed the linear regressions and led to an increment in predictive performance of <i>R</i><sup>2</sup> = .12. Treatment-related variables were the most predictive, followed psychological indicators. Physical indicators and demographics were negligible.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Treatment response in naturalistic inpatient settings can be predicted to a considerable degree by using baseline indicators. Regularization via machine learning algorithms leads to higher predictive performances as opposed to including nonlinear and interaction effects. Heterogenous aspects of mental health have incremental predictive value and should be considered as prognostic markers when modelling treatment processes.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48211,"journal":{"name":"British Journal of Clinical Psychology","volume":"63 2","pages":"137-155"},"PeriodicalIF":3.1,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bjc.12452","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138819293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Objective: Previous research on psychotherapy treatment response has mainly focused on outpatients or clinical trial data which may have low ecological validity regarding naturalistic inpatient samples. To reduce treatment failures by proactively screening for patients at risk of low treatment response, gain more knowledge about risk factors and to evaluate treatments, accurate insights about predictors of treatment response in naturalistic inpatient samples are needed.
Methods: We compared the performance of different machine learning algorithms in predicting treatment response, operationalized as a substantial reduction in symptom severity as expressed in the Patient Health Questionnaire Anxiety and Depression Scale. To achieve this goal, we used different sets of variables-(a) demographics, (b) physical indicators, (c) psychological indicators and (d) treatment-related variables-in a naturalistic inpatient sample (N = 723) to specify their joint and unique contribution to treatment success.
Results: There was a strong link between symptom severity at baseline and post-treatment (R2 = .32). When using all available variables, both machine learning algorithms outperformed the linear regressions and led to an increment in predictive performance of R2 = .12. Treatment-related variables were the most predictive, followed psychological indicators. Physical indicators and demographics were negligible.
Conclusions: Treatment response in naturalistic inpatient settings can be predicted to a considerable degree by using baseline indicators. Regularization via machine learning algorithms leads to higher predictive performances as opposed to including nonlinear and interaction effects. Heterogenous aspects of mental health have incremental predictive value and should be considered as prognostic markers when modelling treatment processes.
{"title":"Predicting treatment response using machine learning: A registered report.","authors":"Kristin Jankowsky, Lina Krakau, Ulrich Schroeders, Rüdiger Zwerenz, Manfred E Beutel","doi":"10.1111/bjc.12452","DOIUrl":"https://doi.org/10.1111/bjc.12452","url":null,"abstract":"<p><strong>Objective: </strong>Previous research on psychotherapy treatment response has mainly focused on outpatients or clinical trial data which may have low ecological validity regarding naturalistic inpatient samples. To reduce treatment failures by proactively screening for patients at risk of low treatment response, gain more knowledge about risk factors and to evaluate treatments, accurate insights about predictors of treatment response in naturalistic inpatient samples are needed.</p><p><strong>Methods: </strong>We compared the performance of different machine learning algorithms in predicting treatment response, operationalized as a substantial reduction in symptom severity as expressed in the Patient Health Questionnaire Anxiety and Depression Scale. To achieve this goal, we used different sets of variables-(a) demographics, (b) physical indicators, (c) psychological indicators and (d) treatment-related variables-in a naturalistic inpatient sample (N = 723) to specify their joint and unique contribution to treatment success.</p><p><strong>Results: </strong>There was a strong link between symptom severity at baseline and post-treatment (R<sup>2</sup> = .32). When using all available variables, both machine learning algorithms outperformed the linear regressions and led to an increment in predictive performance of R<sup>2</sup> = .12. Treatment-related variables were the most predictive, followed psychological indicators. Physical indicators and demographics were negligible.</p><p><strong>Conclusions: </strong>Treatment response in naturalistic inpatient settings can be predicted to a considerable degree by using baseline indicators. Regularization via machine learning algorithms leads to higher predictive performances as opposed to including nonlinear and interaction effects. Heterogenous aspects of mental health have incremental predictive value and should be considered as prognostic markers when modelling treatment processes.</p>","PeriodicalId":48211,"journal":{"name":"British Journal of Clinical Psychology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138812408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sarah Giles, Elizabeth K. Hughes, David Castle, Zoe Jenkins, Andrea Phillipou, Susan Rossell, Gemma Urbini, Matthew Fuller-Tyszkiewicz, Isabel Krug
Objectives
Cognitive flexibility and psychological distress, such as depression and anxiety, have been implicated in the aetiology of Anorexia Nervosa (AN). Despite the known associations between eating disorder (ED) symptoms, depression, anxiety, and cognitive flexibility, the specific pathways that connect these constructs are unclear. We therefore used network analysis to examine the relationship between these symptoms in an AN sample.
Methods
One hundred and ninety-three treatment-seeking individuals diagnosed with AN (95.6% female, M = 26.89 [SD = 9.45] years old) completed self-report measures assessing depression, anxiety, cognitive flexibility, and ED symptoms. To determine each symptom's influence in the network, we calculated the expected influence.
Results
The two relationships with the greatest edges were those between (1) weight/shape concerns and eating/dietary restraint and (2) weight/shape concerns and psychological distress (a measure that combined depression and anxiety). Cognitive flexibility was not connected to weight/shape concerns but had negative partial associations with eating concerns/dietary restraint and psychological distress. There was also a slight, non-zero connection between eating concerns/dietary restraint and psychological distress.
Conclusions
The findings underscore the importance of weight/shape, eating/dietary concerns, and psychological distress in the AN network and suggest that addressing cognitive flexibility may be a useful target for eating concerns/dietary restraint and psychological distress. Future studies assessing the longitudinal course of psychopathology within the AN network structure may help in identifying whether specific symptoms function as risk factors or maintaining factors for this co-occurrence.
{"title":"A new network analysis model in anorexia nervosa patients based on self-reported eating disorder symptoms, psychological distress, and cognitive flexibility","authors":"Sarah Giles, Elizabeth K. Hughes, David Castle, Zoe Jenkins, Andrea Phillipou, Susan Rossell, Gemma Urbini, Matthew Fuller-Tyszkiewicz, Isabel Krug","doi":"10.1111/bjc.12451","DOIUrl":"10.1111/bjc.12451","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>Cognitive flexibility and psychological distress, such as depression and anxiety, have been implicated in the aetiology of Anorexia Nervosa (AN). Despite the known associations between eating disorder (ED) symptoms, depression, anxiety, and cognitive flexibility, the specific pathways that connect these constructs are unclear. We therefore used network analysis to examine the relationship between these symptoms in an AN sample.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>One hundred and ninety-three treatment-seeking individuals diagnosed with AN (95.6% female, <i>M</i> = 26.89 [SD = 9.45] years old) completed self-report measures assessing depression, anxiety, cognitive flexibility, and ED symptoms. To determine each symptom's influence in the network, we calculated the expected influence.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The two relationships with the greatest edges were those between (1) weight/shape concerns and eating/dietary restraint and (2) weight/shape concerns and psychological distress (a measure that combined depression and anxiety). Cognitive flexibility was not connected to weight/shape concerns but had negative partial associations with eating concerns/dietary restraint and psychological distress. There was also a slight, non-zero connection between eating concerns/dietary restraint and psychological distress.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The findings underscore the importance of weight/shape, eating/dietary concerns, and psychological distress in the AN network and suggest that addressing cognitive flexibility may be a useful target for eating concerns/dietary restraint and psychological distress. Future studies assessing the longitudinal course of psychopathology within the AN network structure may help in identifying whether specific symptoms function as risk factors or maintaining factors for this co-occurrence.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48211,"journal":{"name":"British Journal of Clinical Psychology","volume":"63 1","pages":"118-134"},"PeriodicalIF":3.1,"publicationDate":"2023-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bjc.12451","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138578895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Roanne V. F. J. Glas, Roy E. de Kleijn, Eline J. Regeer, Ralph W. Kupka, Manja A. Koenders
Objectives
In order to understand the working mechanisms of mania, it is necessary to perform studies during the onset of manic (-like) mood states. However, clinical mania is difficult to examine experimentally. A viable method to study manic mood like states is mood induction, but mood induction tasks thus far show variable effectiveness.
Methods
In this pilot study, a new paradigm to induce mood through virtual reality (VR) is examined. Both state characteristics, namely changes in emotion, and trait characteristics, such as high and low scores on the hypomanic personality scale (HPS), were measured in 65 students. These students participated in either a neutral VR mood induction or an activating VR mood induction in which excitement, goal directedness, and tension (being aspects of mania) were induced. All participants performed a risk-taking behavioural task, Balloon Analogue Risk Task (BART).
Results
The experimental VR task induced excitement and tension. In participants with higher sensitivity to hypomanic personality (HPS), irritation increased in response to activation whereas it decreased in the low HPS group, and excitement increased more steeply in the low HPS group. There were no effects on the behavioural task.
Conclusions
The VR task is effective in inducing relevant state aspects of hypomania and is suitable as a paradigm for future experimental studies. Activation of dual affective states (excitement and tension) is an essential aspect in manic-like mood induction paradigms.
{"title":"Do you feel up when you go up? A pilot study of a virtual reality manic-like mood induction paradigm","authors":"Roanne V. F. J. Glas, Roy E. de Kleijn, Eline J. Regeer, Ralph W. Kupka, Manja A. Koenders","doi":"10.1111/bjc.12445","DOIUrl":"10.1111/bjc.12445","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>In order to understand the working mechanisms of mania, it is necessary to perform studies during the onset of manic (-like) mood states. However, clinical mania is difficult to examine experimentally. A viable method to study manic mood like states is mood induction, but mood induction tasks thus far show variable effectiveness.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>In this pilot study, a new paradigm to induce mood through virtual reality (VR) is examined. Both state characteristics, namely changes in emotion, and trait characteristics, such as high and low scores on the hypomanic personality scale (HPS), were measured in 65 students. These students participated in either a neutral VR mood induction or an activating VR mood induction in which excitement, goal directedness, and tension (being aspects of mania) were induced. All participants performed a risk-taking behavioural task, Balloon Analogue Risk Task (BART).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The experimental VR task induced excitement and tension. In participants with higher sensitivity to hypomanic personality (HPS), irritation increased in response to activation whereas it decreased in the low HPS group, and excitement increased more steeply in the low HPS group. There were no effects on the behavioural task.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The VR task is effective in inducing relevant state aspects of hypomania and is suitable as a paradigm for future experimental studies. Activation of dual affective states (excitement and tension) is an essential aspect in manic-like mood induction paradigms.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48211,"journal":{"name":"British Journal of Clinical Psychology","volume":"63 1","pages":"105-117"},"PeriodicalIF":3.1,"publicationDate":"2023-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bjc.12445","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136399746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mental health problems and persistent COVID-19 symptoms were prevalent in the context of COVID-19. However, despite the long-observed association between physical symptoms and mental health problems, such association has not been adequately examined in the context of COVID-19. Our understanding of wider patterns of risk and vulnerability factors for mental health also remains limited. This study investigated the associations between general mental health, and persistent physical symptoms, and additional risk and vulnerability factors in the context of COVID-19.
Methods
Two hundred fourteen adults, living in the UK, recruited via social media, completed the online survey and were included in the analyses. Correlation and regression analyses were conducted to examine the associations of persistent physical symptoms and risk and vulnerability factors with measures of general mental health including depressive symptoms, anxiety and insomnia.
Results
78.5% of the participants reported between 1 and 26 persistent symptoms, and about 28%–92% of them associated these symptoms with COVID-19 infection. Persistent physical symptoms were uniquely associated with all measures of mental health, β = .19–.32. Mental health history and worries were the most prominent risk factors, |β| = .12–.43.
Conclusions
People who experience more persistent physical symptoms post-COVID-19 have poorer mental health. It may be important to consider and discuss the recovery from COVID-19 beyond a negative COVID-19 test. Multidisciplinary interventions that address the complex impact of COVID-19 for people with long COVID are needed.
{"title":"COVID-19 and mental health in the UK: Depression, anxiety and insomnia and their associations with persistent physical symptoms and risk and vulnerability factors","authors":"Lin Yu, Lance M. McCracken","doi":"10.1111/bjc.12446","DOIUrl":"10.1111/bjc.12446","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>Mental health problems and persistent COVID-19 symptoms were prevalent in the context of COVID-19. However, despite the long-observed association between physical symptoms and mental health problems, such association has not been adequately examined in the context of COVID-19. Our understanding of wider patterns of risk and vulnerability factors for mental health also remains limited. This study investigated the associations between general mental health, and persistent physical symptoms, and additional risk and vulnerability factors in the context of COVID-19.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Two hundred fourteen adults, living in the UK, recruited via social media, completed the online survey and were included in the analyses. Correlation and regression analyses were conducted to examine the associations of persistent physical symptoms and risk and vulnerability factors with measures of general mental health including depressive symptoms, anxiety and insomnia.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>78.5% of the participants reported between 1 and 26 persistent symptoms, and about 28%–92% of them associated these symptoms with COVID-19 infection. Persistent physical symptoms were uniquely associated with all measures of mental health, <i>β</i> = .19–.32. Mental health history and worries were the most prominent risk factors, |<i>β</i>| = .12–.43.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>People who experience more persistent physical symptoms post-COVID-19 have poorer mental health. It may be important to consider and discuss the recovery from COVID-19 beyond a negative COVID-19 test. Multidisciplinary interventions that address the complex impact of COVID-19 for people with long COVID are needed.</p>\u0000 </section>\u0000 </div>","PeriodicalId":48211,"journal":{"name":"British Journal of Clinical Psychology","volume":"63 1","pages":"92-104"},"PeriodicalIF":3.1,"publicationDate":"2023-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bjc.12446","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71487565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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