Optimising the use of electronic medical records for large scale research in psychiatry.

The explosion and abundance of digital data could facilitate large-scale research for psychiatry and mental health. Research using so-called "real world data"-such as electronic medical/health records-can be resource-efficient, facilitate rapid hypothesis generation and testing, complement existing evidence (e.g. from trials and evidence-synthesis) and may enable a route to translate evidence into clinically effective, outcomes-driven care for patient populations that may be under-represented. However, the interpretation and processing of real-world data sources is complex because the clinically important 'signal' is often contained in both structured and unstructured (narrative or "free-text") data. Techniques for extracting meaningful information (signal) from unstructured text exist and have advanced the re-use of routinely collected clinical data, but these techniques require cautious evaluation. In this paper, we survey the opportunities, risks and progress made in the use of electronic medical record (real-world) data for psychiatric research.

Clinical reappraisal of the composite international diagnostic interview version 3.3 in Qatar's National Mental Health Study.

OBJECTIVES: Lifetime DSM-5 diagnoses generated by the lay-administered Composite International Diagnostic Interview for DSM-5 (CIDI) in the World Mental Health Qatar (WMHQ) study were compared to diagnoses based on blinded clinician-administered reappraisal interviews. METHODS: Telephone follow-up interviews used the non-patient edition of the Structured Clinician Interview for DSM-5 (SCID) oversampling respondents who screened positive for five diagnoses in the CIDI: major depressive episode, mania/hypomania, panic disorder, generalized anxiety disorder, and obsessive-compulsive disorder. Concordance was also examined for a diagnoses of post-traumatic stress disorder based on a short-form versus full version of the PTSD Checklist for DSM-5 (PCL-5). RESULTS: Initial CIDI prevalence estimates differed significantly from the SCID for most diagnoses ( χ 1 2 ${\chi }_{1}^{2}$  = 6.6-31.4, p = 0.010 < 0.001), but recalibration reduced most of these differences and led to consistent increases in individual-level concordance (AU-ROC) from 0.53-0.76 to 0.67-0.81. Recalibration of the short-form PCL-5 removed an initially significant difference in PTSD prevalence with the full PCL-5 (from χ 1 2 ${\chi }_{1}^{2}$  = 610.5, p < 0.001 to χ 1 2 ${\chi }_{1}^{2}$  = 2.5, p = 0.110) while also increasing AU-ROC from 0.76 to 0.81. CONCLUSIONS: Recalibration resulted in valid diagnoses of common mental disorders in the Qatar National Mental Health Survey, but with inflated prevalence estimates for some disorders that need to be considered when interpreting results.

Traumatic Brain Injuries: Manifestations, Evaluation, Management, and Outcomes.

The Psychiatric Consultation Service at Massachusetts General Hospital sees medical and surgical inpatients with comorbid psychiatric symptoms and conditions. During their twice-weekly rounds, Dr Stern and other members of the Consultation Service discuss diagnosis and management of hospitalized patients with complex medical or surgical problems who also demonstrate psychiatric symptoms or conditions. These discussions have given rise to rounds reports that will prove useful for clinicians practicing at the interface of medicine and psychiatry.Prim Care Companion CNS Disord 2024;26(3):23f03667. Author affiliations are listed at the end of this article.

Dual-factor Models of Mental Health: A Systematic Review of Empirical Evidence.

Objective: Dual-factor models of mental health propose that mental health includes two interrelated yet distinct dimensions - psychopathology and well-being. However, there is no systematization of the evidence following these models. This review aims to address the following research question: what evidence exists using dual-factor models? Method: The current systematic review was conducted using PRISMA guidelines on the following databases: Web-of-science, Scopus, Academic Search Complete, APA PsycArticles, APA PsycInfo, Psychology and Behavioral Sciences Collection, ERIC, and MEDLINE. The screening process resulted in 85 manuscripts that tested the assumptions of dual-factor models. Results: Evidence revealed psychometric substantiation on the two-dimensionality of the dual-factor model, and 85% of the manuscripts provided evidence related to classifying participants into different mental health groups. Most studies showed that the Complete Mental Health or Positive Mental Health group is the most prevalent status group, and longitudinal evidence suggests that most participants (around 50%-64%) remain in the same group across time. Regarding the factors associated with mental health status groups, studies reviewed in this manuscript focus mainly on school-related outcomes, followed by supportive relationships, sociodemographic characteristics, psychological assets, individual attributes, physical health, and stressful events. Conclusions: This review highlights the importance of considering the two dimensions of mental health when conceptualizing, operationalizing, and measuring mental health. Fostering mental health must go beyond reducing symptoms, and practitioners would be able to include well-being-related interventions in their regular practice to improve individuals' mental health outcomes.

Association of type 2 diabetes with family history of diabetes, diabetes biomarkers, mental and physical disorders in a Kenyan setting.

This study aimed to determine the degree of family relations and associated socio-demographics characteristics, clinical/physical and mental disorders in type 2 diabetes mellitus in a Kenyan diabetes clinic. This study was part of a large multicentre study whose protocol and results had been published. It took place at the outpatient diabetes clinic at a County Teaching and Referral Hospital in South East Kenya involving 182 participants. We used a socio-demographic questionnaire, the Hamilton Depression (HAM-D) and PHQ-9 rating scales for depression, the MINI International Neuropsychiatric Interview (MINI; V5 or V6) for DSM-5 diagnoses, the WHO-5 Well-being scale and Problem Areas in Diabetes Scale (PAID). We extracted from the notes all physical conditions. We enquired about similar conditions in 1st and 2nd degree relatives. Descriptive, Chi-square test, Fisher's exact test, one way ANOVA, and Multinomial logistic regression analysis were conducted to test achievements of our specific aims. Of the 182 patients who participated in the study, 45.1% (82/182) reported a family history of diabetes. Conditions significantly (p < 0.05) associated with a degree of family history of diabetes were retinopathy, duration of diabetes (years), hypertension, and depressive disorder. On average 11.5% (21/182) scored severe depression (≥ 10) on PHQ-9 and 85.2% (115/182) scored good well-being (≥ 13 points). All DSM-5 psychiatric conditions were found in the 182 patients in varying prevalence regardless of relations. In addition, amongst the 182 patients, the highest prevalence was poor well-being on the WHO quality of life tool. This was followed by post-traumatic disorders (current), suicidality, and psychotic lifetime on DSM-5. The least prevalent on DSM-5 was eating disorders. Some type 2 diabetes mellitus physical disorders and depression have increased incidence in closely related patients. Overall, for all the patients, the prevalence of all DSM-5 diagnoses varied from 0.5 to 9.9%.

Building diagnostic neuroimaging biomarkers for psychiatric disorders using reverse inference approaches: A viable route?

The advent of structural magnetic resonance imaging (sMRI) at the end of the 20th century opened the way toward a deeper understanding of the neurophysiology of psychiatric disorders, substantiating regional structural abnormalities underlying this group of clinical conditions. However, despite abundant and flourishing scientific research, sMRI methodologies are not currently integrated into daily diagnostic practice. One reason behind this failed translation may be the prevailing approach to logical reasoning in neuroimaging: The forward inference via frequentist-based statistics. This reasoning prevents clinicians from obtaining information about the selectivity of results, which are therefore of limited use regarding the definition of biomarkers and refinement of diagnostic processes. Recently, another type of inferential approach has started to emerge in the neuroimaging field: The reverse inference via Bayesian statistics. Here, we introduce the key concepts of this approach, with a particular emphasis on the clinical sMRI environment. We survey recent findings showing significant potential for clinical translation. Clinical opportunities and challenges for developing reverse inference-based neural markers for psychiatry are also discussed. We propose that a systematic sharing of imaging data across the human brain mapping community is an essential first step toward a paradigmatic clinical shift. We conclude that a defined synergy between forward-based and reverse-based sMRI research can illuminate current discussions on diagnostic brain markers, offering clarity on key issues and fostering new tailored diagnostic avenues.

Recognising and responding to physical and mental health issues in neurodivergent girls and women.

People experience life and interact with others in many ways. The term 'neurodivergence' refers to variations from what is considered typical. Research and education into conditions that cooccur with neurodivergence are essential in shaping clinicians' approaches to people who may present with a wide range of symptoms. Neurodivergence may influence a person's style of communication, learning, attitudes, and behaviour, and they often experience inequity and rejection. This review highlights the huge burden of cooccurring conditions carried by neurodivergent women and girls whose medical issues have largely gone under the radar. We suggest how clinicians might increase their awareness of diagnosis and management of their problems with mutual benefit.

THE ROLE OF EMOTIONAL INTELLIGENCE IN THE DIAGNOSIS AND PSYCHOTHERAPY OF MENTAL DISORDERS: AN ANALYSIS OF PRACTICAL APPROACHES.

Emotional intelligence (EI) is an important psychological aspect that has a significant impact on the diagnosis and psychotherapy of mental disorders. It includes the ability to effectively recognise, understand, and regulate one's own emotions, as well as the ability to perceive and interact with the emotions of others. The purpose of the study was to assess and compare the role of emotional intelligence (EI) in different methods of diagnosing and treating mental disorders, as well as its impact on therapy outcomes. The study found that the development of EI improves therapy outcomes by increasing patients' emotional awareness and self-regulation. In addition, it is worth noting that minimising the likelihood of relapse in mental illness is associated with the ability of patients to cope with stress and overcome difficult circumstances. To sum up: In addition, developing emotional intelligence can improve patients' well-being by enhancing their interpersonal relationships, expanding their social network, and mitigating feelings of social isolation. The results of the study indicate that EI should be taken into account in clinical practice and that new psychotherapeutic techniques can be developed to improve the outcomes of the treatment of mental disorders.

Psychometric Assessment of an Item Bank for Adaptive Testing on Patient-Reported Experience of Care Environment for Severe Mental Illness: Validation Study.

BACKGROUND: The care environment significantly influences the experiences of patients with severe mental illness and the quality of their care. While a welcoming and stimulating environment enhances patient satisfaction and health outcomes, psychiatric facilities often prioritize staff workflow over patient needs. Addressing these challenges is crucial to improving patient experiences and outcomes in mental health care. OBJECTIVE: This study is part of the Patient-Reported Experience Measure for Improving Quality of Care in Mental Health (PREMIUM) project and aims to establish an item bank (PREMIUM-CE) and to develop computerized adaptive tests (CATs) to measure the experience of the care environment of adult patients with schizophrenia, bipolar disorder, or major depressive disorder. METHODS: We performed psychometric analyses including assessments of item response theory (IRT) model assumptions, IRT model fit, differential item functioning (DIF), item bank validity, and CAT simulations. RESULTS: In this multicenter cross-sectional study, 498 patients were recruited from outpatient and inpatient settings. The final PREMIUM-CE 13-item bank was sufficiently unidimensional (root mean square error of approximation=0.082, 95% CI 0.067-0.097; comparative fit index=0.974; Tucker-Lewis index=0.968) and showed an adequate fit to the IRT model (infit mean square statistic ranging between 0.7 and 1.0). DIF analysis revealed no item biases according to gender, health care settings, diagnosis, or mode of study participation. PREMIUM-CE scores correlated strongly with satisfaction measures (r=0.69-0.78; P<.001) and weakly with quality-of-life measures (r=0.11-0.21; P<.001). CAT simulations showed a strong correlation (r=0.98) between CAT scores and those of the full item bank, and around 79.5% (396/498) of the participants obtained a reliable score with the administration of an average of 7 items. CONCLUSIONS: The PREMIUM-CE item bank and its CAT version have shown excellent psychometric properties, making them reliable measures for evaluating the patient experience of the care environment among adults with severe mental illness in both outpatient and inpatient settings. These measures are a valuable addition to the existing landscape of patient experience assessment, capturing what truly matters to patients and enhancing the understanding of their care experiences. TRIAL REGISTRATION: ClinicalTrials.gov NCT02491866; https://clinicaltrials.gov/study/NCT02491866.

Are visual analogue scales valid instruments to measure psychological pain in psychiatric patients?

OBJECTIVE: The Psychological-Physical-Pain Visual Analogue Scale (PPP-VAS) was thought to probably help in identifying patients at risk of suicide. However, no data on its validity to measure psychological pain was available. Our main aim was to investigate the convergent validity of the PPP-VAS using two well-validated scales of psychological pain, the Orbach and Mikulincer Mental Pain scale (OMMP) and the Holden et al. Psychache Scale. METHODS: This multicentre study recruited a total of 1618 adult psychiatric inpatients and outpatients in Italy. Psychological pain was evaluated using the OMMP, Holden et al., and PPP-VAS scales. Psychiatric status, suicidal status, physical pain, depression, and hopelessness were also assessed. RESULTS: A structural equation model (SEM) using the items of psychological pain from the PPP-VAS showed that items loaded significantly on the psychological pain factor and showed good fit. Similarly, a second SEM model using the three scales of psychological pain showed acceptable fit and converged into a psychological pain construct. Correlations between the PPP-VAS and depression, hopelessness, and physical pain showed moderate correlations (r = 0.43 to r = 0.67). Finally, psychological pain evaluated with the PPP-VAS was significantly related with recent suicidal ideation in all patients (OR [95 % CI] = 1.07 [1.05, 1.09]) and recent suicide attempts in moderately to severely depressed patients, OR [95 % CI] = 1.01 [1.02, 1.03]. CONCLUSION: The PPP-VAS showed good psychometric properties in evaluating psychological pain. The characteristics of the PPP-VAS makes this scale a great option for its use in clinical practice to detect patients at risk of suicide.

Exploring perinatal mental health in Indonesia: A mixed-method study in Mataram, West Nusa Tenggara.

A significant number of postpartum mothers are at risk of experiencing perinatal mental health (PMH) due to various factors. The aim of this study was to investigate risk factors for PMH issues and explore the current implementation of early screening for PMH in Mataram, West Nusa Tenggara, Indonesia. A mixed-method study, cross-sectional and ethnographic approach, was conducted at Babakan Public Health Center, Mataram, West Nusa Tenggara, Indonesia, from July to August 2023. A cross-sectional study involved 33 postpartum mothers and analyzed seven potential risk factors: age, parity, age at marriage, type of childbirth, type of family, history of adolescent mental disorder, and history of mental disorder during pregnancy. An ethnographic approach, using in-depth interviews, was utilized to gain insights regarding the implementation of PMH screening, included seven healthcare workers: six midwives and one nurse. Among the seven risk factors analyzed, only a history of adolescent mental disorder acted as risk for high PMH with an odds ratio (OR) 1.17 and p=0.03. In-depth interviews revealed a consistent lack of understanding among all healthcare workers regarding PMH screening implementation: absence of early screening, lack of knowledge regarding PMH and how to identify them, reliance solely on subjective assessments for early screening, and a lack of standardized adequate PMH management. In conclusion, the history of adolescent mental disorder could lead to the development of PMH in postpartum mothers. Current screening implementation is still lacking among healthcare workers and public health centers. Therefore, integrating various stakeholders in early PMH screening is crucial to prevent future PMH in mothers and babies.

Coding of Childhood Psychiatric and Neurodevelopmental Disorders in Electronic Health Records of a Large Integrated Health Care System: Validation Study.

Background: Mental, emotional, and behavioral disorders are chronic pediatric conditions, and their prevalence has been on the rise over recent decades. Affected children have long-term health sequelae and a decline in health-related quality of life. Due to the lack of a validated database for pharmacoepidemiological research on selected mental, emotional, and behavioral disorders, there is uncertainty in their reported prevalence in the literature. objectives: We aimed to evaluate the accuracy of coding related to pediatric mental, emotional, and behavioral disorders in a large integrated health care system's electronic health records (EHRs) and compare the coding quality before and after the implementation of the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) coding as well as before and after the COVID-19 pandemic. Methods: Medical records of 1200 member children aged 2-17 years with at least 1 clinical visit before the COVID-19 pandemic (January 1, 2012, to December 31, 2014, the ICD-9-CM coding period; and January 1, 2017, to December 31, 2019, the ICD-10-CM coding period) and after the COVID-19 pandemic (January 1, 2021, to December 31, 2022) were selected with stratified random sampling from EHRs for chart review. Two trained research associates reviewed the EHRs for all potential cases of autism spectrum disorder (ASD), attention-deficit hyperactivity disorder (ADHD), major depression disorder (MDD), anxiety disorder (AD), and disruptive behavior disorders (DBD) in children during the study period. Children were considered cases only if there was a mention of any one of the conditions (yes for diagnosis) in the electronic chart during the corresponding time period. The validity of diagnosis codes was evaluated by directly comparing them with the gold standard of chart abstraction using sensitivity, specificity, positive predictive value, negative predictive value, the summary statistics of the F-score, and Youden J statistic. κ statistic for interrater reliability among the 2 abstractors was calculated. Results: The overall agreement between the identification of mental, behavioral, and emotional conditions using diagnosis codes compared to medical record abstraction was strong and similar across the ICD-9-CM and ICD-10-CM coding periods as well as during the prepandemic and pandemic time periods. The performance of AD coding, while strong, was relatively lower compared to the other conditions. The weighted sensitivity, specificity, positive predictive value, and negative predictive value for each of the 5 conditions were as follows: 100%, 100%, 99.2%, and 100%, respectively, for ASD; 100%, 99.9%, 99.2%, and 100%, respectively, for ADHD; 100%, 100%, 100%, and 100%, respectively for DBD; 87.7%, 100%, 100%, and 99.2%, respectively, for AD; and 100%, 100%, 99.2%, and 100%, respectively, for MDD. The F-score and Youden J statistic ranged between 87.7% and 100%. The overall agreement between abstractors was almost perfect (κ=95%). Conclusions: Diagnostic codes are quite reliable for identifying selected childhood mental, behavioral, and emotional conditions. The findings remained similar during the pandemic and after the implementation of the ICD-10-CM coding in the EHR system.

Using Wearable Digital Devices to Screen Children for Mental Health Conditions: Ethical Promises and Challenges.

In response to a burgeoning pediatric mental health epidemic, recent guidelines have instructed pediatricians to regularly screen their patients for mental health disorders with consistency and standardization. Yet, gold-standard screening surveys to evaluate mental health problems in children typically rely solely on reports given by caregivers, who tend to unintentionally under-report, and in some cases over-report, child symptomology. Digital phenotype screening tools (DPSTs), currently being developed in research settings, may help overcome reporting bias by providing objective measures of physiology and behavior to supplement child mental health screening. Prior to their implementation in pediatric practice, however, the ethical dimensions of DPSTs should be explored. Herein, we consider some promises and challenges of DPSTs under three broad categories: accuracy and bias, privacy, and accessibility and implementation. We find that DPSTs have demonstrated accuracy, may eliminate concerns regarding under- and over-reporting, and may be more accessible than gold-standard surveys. However, we also find that if DPSTs are not responsibly developed and deployed, they may be biased, raise privacy concerns, and be cost-prohibitive. To counteract these potential shortcomings, we identify ways to support the responsible and ethical development of DPSTs for clinical practice to improve mental health screening in children.

Emotion regulation across psychiatric disorders.

OBJECTIVE: Difficulties with emotion regulation have been associated with multiple psychiatric conditions. In this study, we aimed to investigate emotional regulation difficulties in young adults who gamble at least occasionally (ie, an enriched sample), and diagnosed with a range of psychiatric disorders using the validated Difficulties in Emotion Regulation Scale (DERS). METHODS: A total of 543 non-treatment-seeking individuals who had engaged in gambling activities on at least 5 occasions within the previous year, aged 18-29 were recruited from general community settings. Diagnostic assessments included the Mini International Neuropsychiatric Inventory, Minnesota Impulsive Disorders Interview, attention-deficit/hyperactivity disorder World Health Organization Screening Tool Part A, and the Structured Clinical Interview for Gambling Disorder. Emotional dysregulation was evaluated using DERS. The profile of emotional dysregulation across disorders was characterized using Z-scores (those with the index disorder vs. those without the index disorder). RESULTS: Individuals with probable ADHD displayed the highest level of difficulties in emotional regulation, followed by intermittent explosive disorder, social phobia, and generalized anxiety disorder. In contrast, participants diagnosed with obsessive-compulsive disorder showed relatively lower levels of difficulties with emotional regulation. CONCLUSIONS: This study highlights the importance of recognizing emotional dysregulation as a trans-diagnostic phenomenon across psychiatric disorders. The results also reveal differing levels of emotional dysregulation across diagnoses, with potential implications for tailored treatment approaches. Despite limitations such as small sample sizes for certain disorders and limited age range, this study contributes to a broader understanding of emotional regulation's role in psychiatric conditions.

Risks for re-hospitalization of persons with severe mental illness living in rehabilitation care settings.

BACKGROUND: The high rates of psychiatric re-hospitalizations (also termed "revolving door") presents a "wicked problem" which requires a systematic and holistic approach to its resolution. Israel's mental-health rehabilitation law provides a comprehensive set of services intended to support the ability of persons with severe mental illness to rely on community rather than in-patient facilities for their ongoing care needs. Guided by the Health Behavior Model, we examined the relationship between psychiatric re-hospitalizations and the three Health Behavior Model factors (predisposing factor: socio-demographic characteristics and health beliefs; enabling factor: personal and social/vocational relationships facilitated by rehabilitation interventions and services; and need factor: outcomes including symptoms, and mental health and functional status) among persons with severe mental illness receiving rehabilitation services. METHODS: Logistic regression models were used to measure the association between re-hospitalization within a year and variables comprising the three Health Behavior Model factors on the sample of consumers utilizing psychiatric services (n = 7,165). The area under the curve for the model was calculated for each factor separately and for all three factors combined. RESULTS: A total of 846 (11.8%) consumers were hospitalized within a year after the study began. Although multivariable analyses showed significant associations between re-hospitalization and all three Health Behavior Model factors, the magnitude of the model's area under the curve differed: 0.61 (CI = 0.59-0.64), 0.56 (CI = 0.54-0.58), 0.78 (CI = 0.77-0.80) and 0.78 (CI = 0.76-0.80) for predisposing, enabling, need and the full three-factor Health Behavior Model, respectively. CONCLUSION: Findings revealed that among the three Health Behavior Model factors, the need factor best predicted re-hospitalization. The enabling factor, comprised of personal relationships and social/vocational activities facilitated by interventions and services representing many of psychiatric rehabilitation's key goals, had the weakest association with reduced rates of re-hospitalization. Possible explanations may be inaccurate assessments of consumers' personal relationships and social/vocational activities by the mental healthcare professionals, problematic provider-consumer communication on the consumers' involvement in social/vocational activities, or ineffective methods of facilitating consumer participation in these activities. Clearly to reduce the wicked "revolving-door" phenomenon, there is a need for targeted interventions and a review of current psychiatric rehabilitation policies to promote the comprehensive integration of community rehabilitation services by decreasing the fragmentation of care, facilitating continuity of care with other healthcare services, and utilizing effective personal reported outcomes and experiences of consumers with severe mental illness.

In-Person Visits Before Initiation of Telemedicine for Mental Illness.

This cross-sectional study examines how often patients had an in-person visit before initiating telemedicine for mental illness between 2019 and 2022.