Symptom-based Approaches Research Articles

Psychodynamic profiles of major depressive disorder and generalized anxiety disorder in China.

Traditional clinical diagnoses relying on symptoms may overlook latent factors that illuminate mechanisms and potentially guide treatment. The Operationalized Psychodynamic Diagnosis (OPD) system may compensate for symptom-based diagnosis by measuring psychodynamic profiles underlying mental disorders through conflicts and structure axes. However, OPD has not been widely adopted in China, and it remains unclear whether OPD can be used as an effective approach to distinguish between depression and anxiety. The current study aims to adopt the OPD system to investigate the psychodynamic profiles of major depressive disorder (MDD) and generalized anxiety disorder (GAD) in China, targeting patients with "pure" symptoms without comorbidity. We recruited 42 MDD patients, 32 GAD patients, and 31 healthy controls (HC), and assessed their self-report depression and anxiety symptoms, along with their underlying psychodynamic profiles through OPD interviews. Overall, both MDD and GAD patients showed more prominent conflict issues and lower levels of structure than HC. The MDD and GAD groups yielded different conflict profiles and conflict processing modes when processing their second conflicts. Importantly, the multi-dimensional psychodynamic profiles achieved machine learning classification of clinical groups with an accuracy of 0.84, supporting successful distinction of MDD and GAD patients. In conclusion, the OPD demonstrated sensitivity in revealing distinct psychodynamic profiles underlying "pure" depression and anxiety clinical populations in China. This work calls for future incorporation of OPD as a tool to investigate psychodynamic formulations underlying mental disorders, compensating for traditional symptom-based diagnostic approaches to guide precise individualized interventions.

Code Smell Detection using Machine Learning Classification Algorithm

Code smell indicates a poor implementation choice that affects software quality attributes (Pérez, 2013). Fowler (1999) also describes it as an internal code-level problem where the code becomes complex, the design broken, and eventually worsens software quality. Jose (2020) has reported that most applied existing approaches for code smells detection are search-based (30.1%), metric-based (24.1%), and symptom-based approaches (19.3%). However, these existing approaches can only apply to simpler detection; the greater the complexity of code smell, the lower the results for code smell detection (Mantyla M, 2004). Kessentini (2014) also has reported that detecting the problems of code smell is difficult and the performance is not effective using the existing approaches such as search-based, symptom-based, visualization-based, probabilistic, cooperative-based, manual, metrics-based, and rule-based. As a result, many of these approaches extend to the application of machine learning classifiers in software code smell detection. Fontana (2016) reported that a supervised machine learning strategy can be used to forecast the value of the dependent variable using machine learning classifiers to address the problem. In this project, we propose a machine learning supervised Gaussian processes algorithm for JAVA open-source code smell detection. The Gaussian process is a highly interpretable supervised machine learning algorithm used in regression testing to quantify prediction uncertainty. A code smell detection application prototype will be developed to implement the proposed work. The effectiveness of the proposed work in terms of detection accuracy will be evaluated further.

Transformation and Articulation of Clinical Data to Understand Students' and Health Professionals' Clinical Reasoning: Protocol for a Scoping Review.

There are still unanswered questions regarding effective educational strategies to promote the transformation and articulation of clinical data while teaching and learning clinical reasoning. Additionally, understanding how this process can be analyzed and assessed is crucial, particularly considering the rapid growth of natural language processing in artificial intelligence. The aim of this study is to map educational strategies to promote the transformation and articulation of clinical data among students and health care professionals and to explore the methods used to assess these individuals' transformation and articulation of clinical data. This scoping review follows the Joanna Briggs Institute framework for scoping reviews and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) checklist for the analysis. A literature search was performed in November 2022 using 5 databases: CINAHL (EBSCOhost), MEDLINE (Ovid), Embase (Ovid), PsycINFO (Ovid), and Web of Science (Clarivate). The protocol was registered on the Open Science Framework in November 2023. The scoping review will follow the 9-step framework proposed by Peters and colleagues of the Joanna Briggs Institute. A data extraction form has been developed using key themes from the research questions. After removing duplicates, the initial search yielded 6656 results, and study selection is underway. The extracted data will be qualitatively analyzed and presented in a diagrammatic or tabular form alongside a narrative summary. The review will be completed by February 2024. By synthesizing the evidence on semantic transformation and articulation of clinical data during clinical reasoning education, this review aims to contribute to the refinement of educational strategies and assessment methods used in academic and continuing education programs. The insights gained from this review will help educators develop more effective semantic approaches for teaching or learning clinical reasoning, as opposed to fragmented, purely symptom-based or probabilistic approaches. Besides, the results may suggest some ways to address challenges related to the assessment of clinical reasoning and ensure that the assessment tasks accurately reflect learners' developing competencies and educational progress. DERR1-10.2196/50797.

Establishing Patient-Centered Outcomes for MCT8 Deficiency: Stakeholder Engagement and Systematic Literature Review.

The SCL16A2 gene encodes the thyroid hormone (TH) transporter MCT8. Pathogenic variants result in a reduced TH uptake into the CNS despite high serum T3 concentrations. Patients suffer from severe neurodevelopmental delay and require multidisciplinary care. Since a first compassionate use study in 2008, the development of therapies has recently gained momentum. Treatment strategies range from symptom-based approaches, supplementation with TH or TH-analogs, to gene therapy. All these studies have mainly used surrogate endpoints and clinical outcomes. However, the EMA and FDA strongly encourage researchers to involve patients and their advocacy groups in the design of clinical trials. This should strengthen the patients' perspective and identify clinical endpoints that are clinically relevant to their daily life. We involved patient families to define patient-relevant outcomes for MCT8 deficiency. In close collaboration with patient families, we designed a questionnaire asking for their five most preferred therapeutic goals, which, if achieved at least, make a difference in their lives. In addition, we performed a systematic review according to Cochrane recommendations of the published treatment trials. We obtained results from 15 families with completed questionnaires from 14 mothers and 8 fathers. Improvement in development, especially in gross motor skills, was most important to the parents. 59% wished for head control and 50% for sitting ability. Another 36% wished for weight gain, 32% for improvement of expressive language skills, and 18% for a reduction of dystonia/spasticity, less dysphagia, and reflux. Paraclinical aspects were least important (5-9%). In a treatment trial (n=46) and compassionate use cases (n=83), the results were mainly inconclusive, partly due to a lack of predefined patient-centered clinical endpoints. We recommend that future trials should define a relevant improvement in "development" and/or other patient-relevant outcomes compared to natural history as treatment goals.

Understanding Attentional Functioning in Adult Attention Deficit Hyperactivity Disorder—Could This Improve Diagnostic Specificity?

The diagnostic criteria for attention deficit hyperactivity disorder (ADHD) reflect the behavioural and functional outcomes of cognitive processes. Historically they have been based on external observations and lack specificity: clinical cohorts of children meeting diagnostic criteria show that around 40% may also meet diagnostic criteria for oppositional defiant disorder (ODD). We have proposed a clinical model to explain this: the Mental Effort Reward Imbalances model of ADHD (MERIM). This model views the lower levels of task completion that underlie several of the diagnostic criteria for ADHD as being due to a summation of deficits in executive functioning and reward processing. The subjective experience of inadequate reward from task completion may explain the reduced motivation, negativity, and oppositional attitude associated with ODD. The hypothesis for this study is that descriptions of affected individuals' attentional characteristics could be more specific for the executive functioning deficits associated with ADHD than the current symptom-based approaches. To test whether this might be usable in practice, we conducted a workshop that aimed to characterise in depth the patterns of attention experienced by adults with ADHD and how they impact functioning. Three main patterns were described: (1) complete lapses in attention; (2) partial attention to a task; (3) attending to multiple tasks and distractions, either simultaneously or in rapid sequence. All of these resulted in reduced productivity. They also described strategies for managing their attention deficits. Some people used distractions positively, to stimulate the mind to remain active and engaged rather than losing focus. Multi-tasking could also achieve this by providing higher levels of stimulation, however, the stimulation could itself become a distraction. Interest or stress might maintain engagement; extremes could sometimes lead to hyperfocusing, which was typically infrequent but could be highly productive. Focusing on executive functions may improve diagnostic sensitivity, as the current criteria fail to identify people who function adequately due to their use of strategies that mitigate the effects of their attentional deficits. Such people may present with secondary depression or anxiety rather than clear, behavioural symptoms of ADHD. With further development, the approach described in this paper may provide a more simple and fundamental way of recognising ADHD within the community. In the longer term, focusing more specifically on executive functions may provide cohorts with a 'purer' form of ADHD for scientific study.

Identifying Symptoms of ADHD and Disruptive Behavior Disorders Most Strongly Associated with Functional Impairment in Children: A Symptom-Level Approach

To enhance the understanding of how symptoms of attention-deficit/hyperactivity disorder (ADHD) and disruptive behavior disorders such as oppositional defiant disorder (ODD), conduct disorder (CD), including callous-unemotional (CU) traits, differentially relate to functional impairment (FI). Participants were 474 German school-age children (age: M = 8.90, SD = 1.49, 81% male) registered for participation in the ESCAschool trial (ESCAschool: Evidence-based, Stepped Care of ADHD in school-aged children). Clinicians assessed the severity of individual symptoms and five FI domains specifically associated with ADHD symptoms or ODD/CD/CU symptoms using a semi-structured clinical interview. We conducted two multiple linear regression analyses, combined with relative importance analyses, to determine the impact of individual symptoms on global FI associated with ADHD and ODD/CD/CU symptoms. Next, we estimated two networks and identified the strongest associations of ADHD symptoms or ODD/CD/CU symptoms with the five FI domains. Symptoms varied substantially in their associations with global FI. The ADHD symptom Easily Distracted (15%) and ODD symptom Argues with Adults (10%) contributed most strongly to the total explained variance. FI related to academic performance, home life and family members, and psychological strain were most strongly associated with ADHD inattention symptoms, whereas FI related to relationships with adults and relationships with children and recreational activities were most strongly associated with hyperactivity-impulsivity symptoms. By comparison, the ODD/CD/CU symptoms most closely linked to FI domains originated from the ODD and CD dimensions. Our findings contribute to a growing body of literature on the importance of analyzing individual symptoms and highlight that symptom-based approaches can be clinically useful.

P028 Sensory Sensitivity, Anxiety and Hyperactivity are Related to Different Parent-Reported Sleep Problems in Children with Autism Spectrum Disorder

Abstract INTRODUCTION This study aimed to understand how ASD symptoms may relate to different sleep problems. METHODS 128 parents of children with ASD aged 4-14 participated in an anonymous survey. Parents completed the Short Sensory Profile (SSP), Children Sleep Habits Questionnaire (CSHQ), Strengths and Weaknesses of Attention-Deficit/Hyperactivity-symptoms and Normal-behaviours (SWAN) and Revised Child Anxiety and Depression Scale (RCADS). It was hypothesised that: 1) hyper-sensitivity indicated by the SSP, would be positively correlated with night waking from the CSHQ; 2) children at risk of Delayed Sleep Phase Syndrome (DSPS), indicated by the CSHQ, would be more light sensitive as indicated by the SSP; 3) anxiety measured by the RCADS would be positively correlated with longer Sleep Onset Latency (SOL) from the CSHQ; and 4) hyperactivity and inattentiveness from the SWAN would be positively correlated with SOL and parasomnias from the CSHQ. RESULTS Results revealed: 1) under-responsivity and low energy from the SSP were correlated with night waking (r = -.31 and r = .36, p < .05). 2) children at risk of DSPS demonstrated greater light sensitivity than those not at risk (t (55) = 2.83, p < .01); 3) Anxiety was not correlated with SOL; 4) Hyperactivity and inattention were related to longer SOL (r = .25 and r = .61, p < .05) and hyperactivity was correlated with parasomnias (r = .29, p < .05). DISCUSSION These findings suggest that different sleep problems may relate to different ASD symptomology, and that symptom-based approaches should be considered for future research.

Symptom-Based Cluster Analysis Categorizes Sjögren's Disease Subtypes: An International Cohort Study Highlighting Disease Severity and Treatment Discordance.

Although symptom relief is a critical aspect for successful drug development in Sjögren's disease, patient experiences with Sjögren's-related symptoms are understudied. Our objective was to determine how pain, dryness, and fatigue, the cardinal symptoms of Sjögren's disease, drive cluster phenotypes. We used data from the Sjögren's International Collaborative Clinical Alliance (SICCA) Registry and a Sjögren's Foundation survey. We performed hierarchical clustering of symptoms by levels of dryness, fatigue, and pain. Using international and US cohorts, we performed multiple logistic regression analysis to compare the clusters, which included comparisons of differences in symptoms, quality of life (QoL), medication use, and systemic manifestations. Four similar clusters were identified among 1,454 SICCA registrants and 2,920 Sjögren's Foundation survey participants: 1) low symptom burden in all categories (LSB); 2) dry with low pain and low fatigue (DLP); 3) dry with high pain and low to moderate fatigue (DHP); and 4) high symptom burden in all categories (HSB). Distribution of SICCA registrants matching the symptom profile for each cluster was 10% in the LSB cluster, 30% in the DLP cluster, 23% in the DHP cluster, and 37% in the HSB cluster. Distribution of survey participants matching the symptom profile for each cluster was 23% in the LSB cluster, 14% in the DLP cluster, 21% in the DHP cluster, and 42% in the HSB cluster. Individuals in the HSB cluster had more total symptoms and lower QoL but lower disease severity than those in the other clusters. Despite having milder disease as measured by laboratory tests and organ involvement, individuals in the HSB cluster received immunomodulatory treatment most often. We identified 4 symptom-based Sjögren's clusters and showed that symptom burden and immunomodulatory medication use do not correlate with Sjögren's end-organ or laboratory abnormalities. Findings highlight a discordance between objective measures and treatments and offer updates to proposed symptom-based clustering approaches.

Associations of presenting symptoms and subsequent adverse clinical outcomes in people with unipolar depression: a prospective natural language processing (NLP), transdiagnostic, network analysis of electronic health record (EHR) data

ObjectiveTo investigate the associations of symptoms of mania and depression with clinical outcomes in people with unipolar depression.DesignA natural language processing electronic health record study. We used network analysis to...

DNA Methylation and Non-Coding RNAs during Tissue-Injury Associated Pain.

While about half of the population experience persistent pain associated with tissue damages during their lifetime, current symptom-based approaches often fail to reduce such pain to a satisfactory level. To provide better patient care, mechanism-based analgesic approaches must be developed, which necessitates a comprehensive understanding of the nociceptive mechanism leading to tissue injury-associated persistent pain. Epigenetic events leading the altered transcription in the nervous system are pivotal in the maintenance of pain in tissue injury. However, the mechanisms through which those events contribute to the persistence of pain are not fully understood. This review provides a summary and critical evaluation of two epigenetic mechanisms, DNA methylation and non-coding RNA expression, on transcriptional modulation in nociceptive pathways during the development of tissue injury-associated pain. We assess the pre-clinical data and their translational implication and evaluate the potential of controlling DNA methylation and non-coding RNA expression as novel analgesic approaches and/or biomarkers of persistent pain.

From measurement to classificatory practice: improving psychiatric classification independently of the opposition between symptom-based and causal approaches

The article advances a new way of thinking about classifications in general and the classification of mental disorders in particular. By applying insights from measurement practice to the context of classification, I defend a notion of epistemic accuracy that allows one to evaluate and improve classifications by comparing different classifying methods to each other. Progress in classification arises from the mutual development of classification systems and classifying methods. Based on this notion of accuracy, the article illustrates with an example how psychiatric classifications can be improved via circumscribed comparisons of different perspectives on mental disorders, without relying on complete models of their complex aetiology. When applying this strategy, the traditional opposition between symptom-based and causal approaches is of little consequence for making progress in the epistemic accuracy of psychiatric classification.

Proactive and blended approach for COVID-19 control in Taiwan

Coronavirus disease 2019 (COVID-19) has become the greatest threat to human society in a century. To better devise control strategies, policymakers should adjust policies based on scientific evidence in hand. Several countries have limited the epidemics of COVID-19 by prioritizing containment strategies to mitigate the impacts on public health and healthcare systems. However, asymptomatic/pre-symptomatic transmission of COVID-19 complicated traditional symptom-based approaches for disease control. In addition, drastic population-based interventions usually have significant societal and economic impacts. Therefore, in Taiwan, the containment strategies consisted of the more extended case-based interventions (e.g., case detection with enhanced surveillance and contact tracing with active monitoring and quarantine of close contacts) and more targeted population-based interventions (e.g., face mask use in recommended settings and risk-oriented border control with corresponding quarantine requirement). The success of the blended approach emphasizes not only the importance of evidence-supported policymaking but also the coordinated efforts between the government and the people.

Tenapanor: new approach to counter irritable bowel syndrome with constipation

Irritable bowel syndrome (IBS) is a functional gastrointestinal disorder chronic in nature and characterized predominantly by abdominal pain or discomfort associated with altered bowel habits, diagnosis requires characteristic symptoms during the last 3 months and onset ≥6 months ago. Symptom-based approaches for functional bloating, constipation and diarrhea are best utilised to identify IBS. IBS with constipation exerts significant impairment on work productivity by hampering quality of life. Inadequate relief by existing modalities, persistent hard stools and visceral abdominal pain demanded further clinical research. Tenanapor a novel molecule acts locally on gastrointestinal sodium/hydrogen exchanger isoform 3 (NHE3), an antiporter a counter transporter and exert antinociceptive effects on visceral sensation thereby decreases the frequency of abdominal pain. Action on NHE3 receptors located on small intestine and colon’s apical surface reduces the absorption of sodium and phosphate, with minimal systemic exposure. NHE3 Inhibition induced sodium absorption results in increase in water secretion into intestinal lumen resultant an accelerated intestinal transit time and softer stool consistency. Most common adverse reactions (≥2%) are diarrhea, abdominal distension, flatulence and dizziness. The drug is metabolised mainly by CYP3A4/5 and excreted in feaces (70%) and urine (7%). Tenapanor’s minimal systemic absorption is likely to be associated with a relatively inert safety and tolerability profile. Based on positive results from the phase III T3MPO trial program, tenapanor demonstrated promising results for IBS-C management and received US Food and Drug Administration approval as IBSRELA @ Ardelyx Pharma in September 2019 and augment existing modalities for management of IBS-C.

S115. EVALUATION OF THE CLINICAL UTILITY OF SYMPTOM DIMENSIONS ON LONG-TERM CLINICAL AND FUNCTIONAL OUTCOMES IN FIRST EPISODE PSYCHOSIS

BackgroundCurrent clinical utility of diagnostic categories in patients with psychosis is in debate. Alternatively, symptom-based dimensional approaches are suggested, but research on their utility and longitudinal stability is at its early phases, showing lack of consistencies. The aims of this prospective study are: 1) to test the stability of structure of symptom dimensions in first episode psychosis patients; 2) to explore the utility of symptom dimensions in predicting clinical and functional outcomes.MethodsThis study included a total of 208 with first episode of psychosis-spectrum disorders aged 18–65 years who presented to psychiatric services in South London, recruited as part of the Genetics and Psychosis Outcome (GAP) case-control study and EU-GEI multicentre case-control study. A subsample of 114 patients were traced after a mean of 6.5 years. Psychopathology was assessed at baseline and at follow-up using OPCRIT and tested with bifactor model, encompassing one general psychosis dimension and five specific symptom dimensions (positive, negative, disorganisation, mania, and depression). Follow up measures on functional outcome (assessed with GAF scale) and clinical outcomes (number and total length of hospitalisations) were derived from clinical records. Predictor role of baseline symptom dimensions was tested by multiple linear regression to predict global functioning; and by negative binomial regression for length of hospitalisation and number of hospital admissions.ResultsFactor loadings of disorganisation dimension were most likely to change longitudinally while loadings of positive dimension were most stable. Regarding dimension stability over time, all positive, disorganised and depressive symptoms significantly improved over time while manic and negative symptoms did not significantly differ. In terms of prediction of outcome, baseline manic symptoms were associated with reduced risk of hospitalisation (adj OR 1.56; 95% CI 1.01–2.38), reduced length of hospitalisation (adj IRR= 0.73; 95% CI 0.56–0.95) and better global functioning (β=5.21; 95% CI 2.46–7.95) at follow up. Similarly, depressive symptoms were associated with reduced length of hospitalisation (adj IRR= 0.77; CI 0.61–0.97). On the other hand, baseline positive symptoms were associated with increased risk of hospitalisation (adj OR 1.93; 95% CI 1.25–2.96). No other significant associations were found between the rest of symptom dimensions and outcomes.DiscussionThis study provides new evidence on the longitudinal stability of bifactor model of psychosis and, shows that all except manic and negative symptoms significantly improved over time. Whereas affective symptoms (including mania and depression) were associated with good prognosis, positive symptoms seem to predict poor clinical outcomes. The particular and different influence of affective and psychotic symptoms on long-term functional and clinical outcomes may have therapeutic implications and support the potential clinical utility of incorporating symptom-based approach in further outcome research.

Widespread Morphometric Abnormalities in Major Depression: Neuroplasticity and Potential for Biomarker Development.

Major depression is common and debilitating. Identifying neurobiological subtypes that comprise the disorder and predict clinical outcome are key challenges. Genetic and environmental factors leading to major depression are expressed in neural structure and function. Volumetric decreases in gray matter have been demonstrated in corticolimbic circuits involved in emotion regulation. MR imaging observable abnormalities reflect cytoarchitectonic alterations within a local neuroendocrine milieu with systemic effects. Multivariate pattern analysis offers the potential to identify the neurobiological subtypes and predictors of clinical outcome. It is essential to characterize disease heterogeneity by incorporating data-driven inductive and symptom-based deductive approaches in an iterative process.

The pathway to diagnosis and treatment for surgically managed lung cancer patients.

Most lung cancer is diagnosed at an advanced stage, resulting in poor survival. This study examined diagnostic pathways for patients with operable lung cancer to identify factors contributing to early diagnosis. Surgically treated lung cancer patients (aged ≥40, within 6 months of diagnosis), approached via the population-based Cancer Registry, with their primary care physicians (PCPs) and specialists completed cross-sectional surveys assessing symptoms, diagnostic route (symptomatic or 'investigation' of other problem), tests, key event dates and treatment. Time intervals to diagnosis and treatment were determined, and quantile regression examined differences between the two diagnostic routes. Cox proportional hazard regression analyses examined associations between survival and diagnostic route adjusting for stage, sex and age. One hundred and ninety-two patients (36% response rate), 107 PCPs and 55 specialists participated. Fifty-eight per cent of patients had a symptomatic diagnostic route reporting an average of 1.6 symptoms, most commonly cough, fatigue or haemoptysis. Symptomatic patients had longer median primary care interval than 'investigation' patients (12 versus 9 days, P < 0.05) and were more likely to report their PCP first-ordered imaging tests. Secondary care interval was shorter for symptomatic (median = 43 days) than investigation (median = 62 days, P < 0.05) patients. However, 56% of all patients waited longer than national recommendations (6 weeks). While survival estimates were better for investigation than symptomatic patients, these differences were not significant. Many operable lung cancer patients are diagnosed incidentally, highlighting the difficulty of symptom-based approaches to diagnosing early stage disease. Longer than recommended secondary care interval suggests the need for improvements in care pathways.

Neurostructural Heterogeneity in Youths With Internalizing Symptoms

BackgroundInternalizing disorders such as anxiety and depression are common psychiatric disorders that frequently begin in youth and exhibit marked heterogeneity in treatment response and clinical course. Given that symptom-based classification approaches do not align with underlying neurobiology, an alternative approach is to identify neurobiologically informed subtypes based on brain imaging data. MethodsWe used a recently developed semisupervised machine learning method (HYDRA [heterogeneity through discriminative analysis]) to delineate patterns of neurobiological heterogeneity within youths with internalizing symptoms using structural data collected at 3T from a sample of 1141 youths. ResultsUsing volume and cortical thickness, cross-validation methods indicated 2 highly stable subtypes of internalizing youths (adjusted Rand index = 0.66; permutation-based false discovery rate p < .001). Subtype 1, defined by smaller brain volumes and reduced cortical thickness, was marked by impaired cognitive performance and higher levels of psychopathology than both subtype 2 and typically developing youths. Using resting-state functional magnetic resonance imaging and diffusion images not considered during clustering, we found that subtype 1 also showed reduced amplitudes of low-frequency fluctuations in frontolimbic regions at rest and reduced fractional anisotropy in several white matter tracts. In contrast, subtype 2 showed intact cognitive performance and greater volume, cortical thickness, and amplitudes during rest compared with subtype 1 and typically developing youths, despite still showing clinically significant levels of psychopathology. ConclusionsWe identified 2 subtypes of internalizing youths differentiated by abnormalities in brain structure, function, and white matter integrity, with one of the subtypes showing poorer functioning across multiple domains. Identification of biologically grounded internalizing subtypes may assist in targeting early interventions and assessing longitudinal prognosis.

What can Somali community talk about mental health tell us about our own? Contextualizing the symptoms of mental health

Purpose The purpose of this paper is to review all the research on Somali refugee communities’ “explanatory models” of “mental health” or psychological suffering, and also report original research in order to allow for more contexts on their “mental health” terms to emerge. Design/methodology/approach The authors talked in a conversational manner with a small number (11) of Somali people (10 females and 1 male), but this was done intensively over time and on multiple occasions. They discussed their community terms for “mental health” issues but in their own contexts and with their own examples. Findings The results showed that Somali as a community had three main groupings of symptoms: Jinn or spirit possession; waali or “craziness”; and a group of terms for serious anxieties, rumination, worrying and thinking too much. What was new from their broader descriptions of context was that the community discourses were based on particular contexts of the person and their behavior within their life history, rather than aiming to universal categories like the DSM. Practical implications Both research and practice on mental health should focus less on universal diagnoses and more on describing the contexts in which the symptoms emerge and how to change those contexts, especially with refugee and other less well-understood groups. Originality/value The review and original results support symptom-based or contextual approaches to mental health; we should treat the “mental health” symptoms in their life contexts rather than as a disease or disorder. We can learn from how Somali describe their “mental health” symptoms rather than treat their descriptions as crude forms of the “correct” western diagnostics.

Addressing heterogeneity (and homogeneity) in treatment mechanisms in depression and the potential to develop diagnostic and predictive biomarkers.

It has been 10 years since machine learning was first applied to neuroimaging data in psychiatric disorders to identify diagnostic and prognostic markers at the level of the individual. Proof of concept findings in major depression have since been extended in international samples and are beginning to include hundreds of samples from multisite data. Neuroimaging provides the unique capability to detect an acute depressive state in major depression, while we would not expect perfect classification with current diagnostic criteria which are based solely on clinical features. We review developments and the potential impact of heterogeneity, as well as homogeneity, on classification for diagnosis and prediction of clinical outcome. It is likely that there are distinct biotypes which comprise the disorder and which predict clinical outcome. Neuroimaging-based biotypes could aid in identifying the illness in individuals who are unable to recognise their illness and perhaps to identify the treatment resistant form early in the course of the illness. We propose that heterogeneous symptom profiles can arise from a limited number of neural biotypes and that apparently heterogeneous clinical outcomes include a common baseline predictor and common mechanism of treatment. Baseline predictors of clinical outcome reflect factors which indicate the general likelihood of response as well as those which are selective for a particular form of treatment. Irrespective of the mechanism, the capacity for response will moderate the outcome, which includes inherent models of interpersonal relationships that could be associated with genetic risk load and represented by patterns of functional and structural neural correlates as a predictive biomarker. We propose that methods which directly address heterogeneity are essential and that a synergistic combination could bring together data-driven inductive and symptom-based deductive approaches. Through this iterative process, major depression can develop from being syndrome characterized by a collection of symptoms to a disease with an identifiable pathophysiology.

Genetic rodent models of brain disorders: Perspectives on experimental approaches and therapeutic strategies.

Neurobehavioral disorders comprised of neurodegenerative, neurodevelopmental, and psychiatric disorders together represent leading causes of morbidity and mortality. Despite significant academic research and industry efforts to elucidate the disease mechanisms operative in these disorders and to develop mechanism‐based therapies, our understanding remains incomplete and our access to tractable therapeutic interventions severely limited. The magnitude of these short‐comings can be measured by the growing list of disappointing clinical trials based on initially promising compounds identified in genetic animal models. This review and commentary will explore why this may be so, focusing on the central role that genetic models of neurobehavioral disorders have come to occupy in current efforts to identify disease mechanisms and therapies. In particular, we will highlight the unique pitfalls and challenges that have hampered success in these models as compared to genetic models of non‐neurological diseases as well as to symptom‐based models of the early 20th century that led to the discovery of all major classes of psychoactive pharmaceutical compounds still used today. Using examples from specific genetic rodent models of human neurobehavioral disorders, we will highlight issues of reproducibility, construct validity, and translational relevance in the hopes that these examples will be instructive toward greater success in future endeavors. Lastly, we will champion a two‐pronged approach toward identifying novel therapies for neurobehavioral disorders that makes greater use of the historically more successful symptom‐based approaches in addition to more mechanism‐based approaches.