OBJECTIVE:As mental health systems worldwide shift toward supporting personal recovery, valid tools are needed to evaluate and guide service transformation. The Recovery Self-Assessment Scale (RSA-R) is the leading patient-reported measure of recovery-oriented care. This study aimed to adapt the RSA-R to the French context and assess its psychometric properties. METHODS:The RSA-R was translated and administered online to 169 adults with serious mental illness. Exploratory factor analyses were conducted to assess the structural validity of the French RSA-R French Recovery Self-Assessment-Revised (RSAR-Fr), and internal consistency statistics were computed. Multiple linear regression analysis tested the RSAR-Fr association with a measure of personal recovery (the French Questionnaire about the Process of Recovery). Items were mapped onto an established framework of recovery-oriented care to assess content validity. RESULTS:Exploratory factor analyses supported a concise three-factor model: The person-centered, organizational engagement, and social inclusion dimensions accounted for 46.3% of the variance, with excellent internal consistencies (McDonald's ω values ranging from .92 to .94). Hypotheses for construct validity were not verified, as RSAR-Fr subscales did not significantly predict personal recovery. Expert review supported content validity, confirming the items' relevance and comprehensiveness. CONCLUSIONS AND IMPLICATIONS FOR PRACTICE:The RSAR-Fr demonstrated adequate psychometric properties, addressing known concerns regarding the scale's dimensionality. Despite sample limitations and the absence of test-retest data, these findings highlight the utility of the RSAR-Fr in measuring recovery-oriented care from the perspective of service users. Routine use of the RSAR-Fr may strengthen the recognition of lived experience within services and support improvements in recovery-oriented practices. (PsycInfo Database Record (c) 2026 APA, all rights reserved).
The Hypersomnia Severity Index (HSI) is a self-report instrument assessing hypersomnolence using a dimensional approach based on two factors: symptoms and distress/impairment. This study aimed to translate, adapt, and validate the French version of the HSI in a large quota-based sample of the French general population, and to propose an original dimensional visualization of hypersomnolence profiles. Following a forward–backward translation procedure, the French HSI was administered to 1000 adults aged 18–65 from the general French population. Internal consistency and structural validity were assessed using confirmatory factor analysis (CFA) and exploratory factor analysis (EFA) when necessary. External validity was examined through correlations with validated self-report measures of hypersomnolence and sleep-related parameters. An original polar chart visualization was developed to represent item-level HSI profiles. The French HSI demonstrated good internal consistency (Cronbach’s α = 0.82). CFA did not confirm an adequate fit for the original two-factor model. EFA confirmed the distress/impairment factor but split the symptoms factor into two subfactors, labeled “sleepiness symptoms” and “alertness symptoms.” HSI scores were significantly correlated with established hypersomnolence and sleep-related measures, supporting convergent validity. Polar chart visualizations revealed distinct symptom patterns across subgroups, supporting the identification of dimensional hypersomnolence symptom profiles. The French version of the HSI is a reliable and clinically meaningful instrument for the dimensional assessment of hypersomnolence. Its cross-cultural validation supports its use in research and clinical practice. The HSI provides a multidimensional and easily administered measure, with potential utility for symptom profiling and monitoring hypersomnolence. Future studies should examine its longitudinal sensitivity and prognostic value.
Purpose :Although Attention Deficit/Hyperactivity Disorder (ADHD) has historically been described in male children, its clinical presentation varies across age and gender. As a result, ADHD remains under-recognized in adulthood, particularly among women, often leading to delayed diagnosis. This study aimed to examine the association between gender and time to ADHD diagnosis in adulthood, while accounting for established influencing factors, including psychiatric comorbidities. Methods :Data were collected at a referral adult ADHD center in Bordeaux, France. Adults recently diagnosed with ADHD in adulthood completed a self-report questionnaire. The primary outcome was the duration between first psychiatric consultation and ADHD diagnosis. Associations with self-identified gender (woman, man, non-binary) were examined while adjusting for socio-demographic characteristics, ADHD presentation and treatment, comorbidities, age, and prior childhood mental health care. Results :The sample included 187 adults with a confirmed ADHD diagnosis. Most participants reported functionally impairing symptoms beginning in childhood. Diagnostic delay was significantly associated with gender and comorbid anxiety disorders. Women and non-binary individuals experienced substantially longer delays compared to men. After adjustment for age and anxiety, women were diagnosed on average four times later than men, while non-binary individuals experienced delays approximately three times longer. Women with comorbid anxiety exhibited the longest delays, with a mean duration exceeding seven years. Conclusion :These findings highlight a gender-related diagnostic delay in adult ADHD, strongly influenced by anxiety comorbidity. Improving diagnostic accuracy requires gender-sensitive clinical approaches, including systematic exploration of childhood symptoms and consideration of ADHD screening in women presenting with anxiety.
BACKGROUND:Late-life depression refers to a depression occurring in older adults, defined as individuals aged 65 years and older. It is common and often mismanaged due to complex clinical profiles, polypharmacy, and limited evidence-based guidance. Existing tools poorly address psychiatric nuances in older adults. This work aims to develop French recommendations based on experts' consensus on the use of antidepressants in unipolar late-life depression, to guide safer prescribing practices. METHODS:This tool was developed using a Delphi survey, based on a review of literature published between 2014 and 2024 and focused on "antidepressants" and "late-life depression" Experts from various fields: geriatric psychiatry, clinical pharmacy and general practice, rated items using a 9-point Likert scale. Items with a median score ≥ 7 and at least 80% agreement were validated and included in the final version of the tool. RESULTS:Twenty to 23 experts per round, different from the authors of the proposed items, participated in a four-round Delphi process. The resulting tool includes 57 validated items across 10 sections and a stepped-care algorithm for treating major depression in older adults. It addresses drug choice, dosing, monitoring, comorbidities, and treatment resistance, prioritizing safe first-line options like sertraline, citalopram, and escitalopram. CONCLUSION:A Delphi survey involving multidisciplinary experts led to a French consensus tool for prescribing antidepressants in unipolar late-life depression. It integrates clinical evidence and expert judgment to address treatment complexity, drug safety, and resistance. The tool offers practical, stepwise recommendations tailored to primary care, aiming to optimize antidepressant use, reduce iatrogenesis, and improve patient outcomes.
Background The Global Bipolar Cohort (GBC) was established to identify existing bipolar disorder (BD) cohorts worldwide and foster collaborations focused on descriptive and analytic outcomes relevant to BD. A distributed analytic framework has been implemented to engage multiple sites without the need for central data pooling. This report describes the GBC endeavor and global functional impairment patterns. Cross-cohort comparisons of functional correlates are limited by heterogeneous measures and data-sharing constraints. Large, culturally diverse comparisons are needed to distinguish broadly reproducible correlates from cohort-specific effects. Participating sites completed a 28-item descriptive survey covering diagnostic methods, cognition, genetics, treatment, functioning, and follow-up strategies. We implemented a harmonized local logistic regression model of dichotomized functional outcome and shared summary statistics only. Results We identified 69 cohorts across five continents. Thirty-seven cohorts contributed functional outcome analyses from 17,130 participants. Outcome measures included clinician-rated disability scales and social indicators such as employment and marital status. The proportion classified with poor functioning ranged from 16% to 77% (mean 50%). In 32 of 37 cohorts, the overall regression model significantly explained variance in functioning. Current depressive symptoms were the most robust and reproducible correlate of poor functional outcome: they were assessed in 29 cohorts, significant in 22 (75.8%), ranked among the top three correlates in 22, and were the top-ranked correlates in 19. Associations between depressive burden and poor functioning were observed across clinician-rated disability scales and work or social indicators, and across geographically diverse cohorts. Comorbid substance use disorder and medication-related variables were associated with poorer functioning in subsets of cohorts, whereas sex, ancestry, bipolar subtype, psychosis history, and premorbid IQ showed weak or inconsistent associations. Cognitive measures, available in a minority of regression models, showed modest and non-uniform effects. Conclusions Across heterogeneous international cohorts, current depressive symptom burden emerged as the most consistent correlate of poor functioning in bipolar disorder. These findings replicate earlier multisite work at a larger scale, show that protocol-based distributed analyses can identify reproducible clinical signals without sharing individual-level data, and support prioritizing detection and treatment of depressive symptoms when aiming to improve real-world functioning. Future work should expand longitudinal harmonization and representation of under-studied populations.
