The emphasis on formulation, as a lynchpin and driver of cognitive behavior therapy (CBT) has received increasing attention, consensus of value among practitioners and emerging studies of efficacy. The terms, “formulation” and “conceptualisation” are frequently used interchangeably in literature which is exclusively focussed on high intensity CBT. In contrast, little has been included on the value or recognising the existence of formulation, for Low Intensity CBT practitioners providing guided self-help. This may contribute to misconceptions that Low Intensity CBT is a mechanistic set of techniques. Links to CBT competencies, curricula, role of supervision and roots in UK Behavioral Nurse Therapist training, are made to highlight the implicit presence of Low Intensity formulation. We suggest a definition of formulation, as a key Low Intensity competency. This uses an individualised treatment rationale and problem statement, derived from a structured functional assessment. We propose, explicitly emphasising these, constitutes Low Intensity case formulation, which guides intervention. This is a refocus of existing practice, not introduction of completely new elements. A brief illustration of “how to” deliver formulation-driven Low Intensity CBT is made. This promotes a concise “within-session” and “between-session” thread. This adjustment, on what guides Low Intensity interventions, is relevant to practitioners, supervisors and trainers in promoting Low Intensity best practice. This argues that recognising the value of formulation assists in optimising skills development, client outcomes and satisfaction with Low Intensity CBT. Cautions with the approach and the need for further research are noted.
{"title":"What guides guided self-help? Recognising the role of formulation in Low Intensity CBT","authors":"Paul Cromarty, Dominic Gallagher","doi":"10.1002/mhs2.15","DOIUrl":"https://doi.org/10.1002/mhs2.15","url":null,"abstract":"<p>The emphasis on formulation, as a lynchpin and driver of cognitive behavior therapy (CBT) has received increasing attention, consensus of value among practitioners and emerging studies of efficacy. The terms, “formulation” and “conceptualisation” are frequently used interchangeably in literature which is exclusively focussed on high intensity CBT. In contrast, little has been included on the value or recognising the existence of formulation, for Low Intensity CBT practitioners providing guided self-help. This may contribute to misconceptions that Low Intensity CBT is a mechanistic set of techniques. Links to CBT competencies, curricula, role of supervision and roots in UK Behavioral Nurse Therapist training, are made to highlight the implicit presence of Low Intensity formulation. We suggest a definition of formulation, as a key Low Intensity competency. This uses an individualised treatment rationale and problem statement, derived from a structured functional assessment. We propose, explicitly emphasising these, constitutes Low Intensity case formulation, which guides intervention. This is a refocus of existing practice, not introduction of completely new elements. A brief illustration of “how to” deliver formulation-driven Low Intensity CBT is made. This promotes a concise “within-session” and “between-session” thread. This adjustment, on what guides Low Intensity interventions, is relevant to practitioners, supervisors and trainers in promoting Low Intensity best practice. This argues that recognising the value of formulation assists in optimising skills development, client outcomes and satisfaction with Low Intensity CBT. Cautions with the approach and the need for further research are noted.</p>","PeriodicalId":94140,"journal":{"name":"Mental health science","volume":"1 1","pages":"48-54"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mhs2.15","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50118095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Depression is measured in most studies by surveys that sum individual symptom scores into one common variable. Given the high heterogeneity of depressive disorders and the diversity of symptom profiles at the same levels of depression, a significant amount of information is, therefore, not evaluated. In this study, we aimed to investigate how distinct depression symptoms from the tripartite model of anxiety and depression relate to the dimensions of core affect. The study included N = 1102 individuals who completed depression, anxiety and stress, and core affect scales. Participants were recruited from the convenience sample and were aged between 18 and 59 years (M = 39.70; SD = 12.03) with 38.2% men and 61.8% women, whose average number of years spent in education was M = 14.17; SD = 3.63. Correlation and regression analysis with JASP and R software showed that all depressive symptoms were significantly related to the core affect dimensions (valence and activation), and network analysis indicated which symptoms formed undirected interrelationships and what their possible roles were in the model. We concluded that not all depression symptoms in the network model formed similar relationships with the dimensions of core affect, which may be explained through both validity and nonclinical sampling aspects.
{"title":"Depression symptoms and core affect: Results from network and regression analyses","authors":"Edmunds Vanags, Malgožata Raščevska","doi":"10.1002/mhs2.13","DOIUrl":"https://doi.org/10.1002/mhs2.13","url":null,"abstract":"<p>Depression is measured in most studies by surveys that sum individual symptom scores into one common variable. Given the high heterogeneity of depressive disorders and the diversity of symptom profiles at the same levels of depression, a significant amount of information is, therefore, not evaluated. In this study, we aimed to investigate how distinct depression symptoms from the tripartite model of anxiety and depression relate to the dimensions of core affect. The study included <i>N</i> = 1102 individuals who completed depression, anxiety and stress, and core affect scales. Participants were recruited from the convenience sample and were aged between 18 and 59 years (<i>M</i> = 39.70; SD = 12.03) with 38.2% men and 61.8% women, whose average number of years spent in education was <i>M</i> = 14.17; SD = 3.63. Correlation and regression analysis with JASP and R software showed that all depressive symptoms were significantly related to the core affect dimensions (valence and activation), and network analysis indicated which symptoms formed undirected interrelationships and what their possible roles were in the model. We concluded that not all depression symptoms in the network model formed similar relationships with the dimensions of core affect, which may be explained through both validity and nonclinical sampling aspects.</p>","PeriodicalId":94140,"journal":{"name":"Mental health science","volume":"1 1","pages":"37-47"},"PeriodicalIF":0.0,"publicationDate":"2023-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mhs2.13","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50153031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bilal Ahmad Khan, Humaira Khalid, Najma Siddiqi, Faiza Aslam, Rubab Ayesha, Medhia Afzal, Sukanya Rajan, Kavindu Appuhamy, Kamrun Nahar Koly, Maria Bryant, Richard I. G. Holt, Gerardo A. Zavala
People with severe mental illness (SMI) have a higher prevalence of obesity as compared with the general population, however, there is mixed evidence about the prevalence of underweight. Thus, the aim of this study is to determine the pooled prevalence of underweight in people with SMI and its association with socio-demographic factors; and to compare the prevalence of underweight between SMI and the general population. MEDLINE, PsycINFO, and EMBASE databases were searched to identify observational studies assessing the prevalence of underweight in adults with SMI (schizophrenia, major depressive disorder with psychotic features, and bipolar disorders). Screening, data extraction, and risk of bias assessments were performed independently by two co-authors, with disagreements resolved by consensus. Random effect estimates for the pooled prevalence of underweight and the pooled odds of underweight in people with SMI compared with the general population were calculated. Subgroup analyses were conducted for the type of SMI, setting, antipsychotic medication, region of the world, World Bank country income classification, data collection, and sex. Forty estimates from 22 countries were included. The pooled prevalence of underweight in people with SMI was 3.8% (95% confidence interval [CI] = 2.9–5.0). People with SMI were less likely to be underweight than the general population (odds ratio [OR] 0.65; 95% CI = 0.4–1.0). The pooled prevalence of underweight in SMI in South Asia was 7.5% (95% CI = 5.8–14.1) followed by Europe and Central Asia at 5.2% (95% CI = 3.2–8.1) and North America at 1.8% (95% CI = 1.2–2.6). People with SMI have lower odds of being underweight compared to the general population. People with schizophrenia had the highest prevalence of underweight compared to other types of SMI. Japan and South Asia have the highest prevalence of underweight in people with SMI.
{"title":"Prevalence of underweight in people with severe mental illness: Systematic review and meta-analysis","authors":"Bilal Ahmad Khan, Humaira Khalid, Najma Siddiqi, Faiza Aslam, Rubab Ayesha, Medhia Afzal, Sukanya Rajan, Kavindu Appuhamy, Kamrun Nahar Koly, Maria Bryant, Richard I. G. Holt, Gerardo A. Zavala","doi":"10.1002/mhs2.7","DOIUrl":"https://doi.org/10.1002/mhs2.7","url":null,"abstract":"<p>People with severe mental illness (SMI) have a higher prevalence of obesity as compared with the general population, however, there is mixed evidence about the prevalence of underweight. Thus, the aim of this study is to determine the pooled prevalence of underweight in people with SMI and its association with socio-demographic factors; and to compare the prevalence of underweight between SMI and the general population. MEDLINE, PsycINFO, and EMBASE databases were searched to identify observational studies assessing the prevalence of underweight in adults with SMI (schizophrenia, major depressive disorder with psychotic features, and bipolar disorders). Screening, data extraction, and risk of bias assessments were performed independently by two co-authors, with disagreements resolved by consensus. Random effect estimates for the pooled prevalence of underweight and the pooled odds of underweight in people with SMI compared with the general population were calculated. Subgroup analyses were conducted for the type of SMI, setting, antipsychotic medication, region of the world, World Bank country income classification, data collection, and sex. Forty estimates from 22 countries were included. The pooled prevalence of underweight in people with SMI was 3.8% (95% confidence interval [CI] = 2.9–5.0). People with SMI were less likely to be underweight than the general population (odds ratio [OR] 0.65; 95% CI = 0.4–1.0). The pooled prevalence of underweight in SMI in South Asia was 7.5% (95% CI = 5.8–14.1) followed by Europe and Central Asia at 5.2% (95% CI = 3.2–8.1) and North America at 1.8% (95% CI = 1.2–2.6). People with SMI have lower odds of being underweight compared to the general population. People with schizophrenia had the highest prevalence of underweight compared to other types of SMI. Japan and South Asia have the highest prevalence of underweight in people with SMI.</p>","PeriodicalId":94140,"journal":{"name":"Mental health science","volume":"1 1","pages":"10-22"},"PeriodicalIF":0.0,"publicationDate":"2022-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mhs2.7","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50148779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}