Suicidal Ideation and Attempts Among Youth With Physical-Mental Comorbidity in Canada: Proposal for an Epidemiological Study.

BACKGROUND: Evidence suggests that having a chronic physical illness (CPI; eg, asthma, diabetes, and epilepsy) is an independent risk factor for suicidality (ie, suicidal ideation or attempts) among youth. Less is known about the mechanisms linking CPI and suicidality. Some evidence suggests that mental illness (eg, depression and anxiety) or neurodevelopmental disorder (eg, attention-deficit/hyperactivity disorder) mediates or moderates the CPI-suicidality association. Missing from the knowledge base is information on the association between having co-occurring CPI and mental illness or neurodevelopmental disorder (MIND) on youth suicidality. OBJECTIVE: This study uses epidemiological data from the 2019 Canadian Health Survey of Children and Youth (CHSCY) to study the intersection of CPI, MIND, and suicidality in youth. We will estimate prevalence, identify predictors, and investigate psychosocial and service use outcomes for youth with CPI-MIND comorbidity versus other morbidity groups (ie, healthy, CPI only, and MIND only). METHODS: Conducted by Statistics Canada, the CHSCY collected data from 47,850 children (aged 1-17 years) and their primary caregiving parent. Measures of youth CPI, MIND, family environment, and sociodemographics are available using youth and parent informants. Information on psychiatric services use is available via parent report and linkage to national administrative health data found in the National Ambulatory Care Reporting System and the Discharge Abstract Database, which allow the investigation of hospital-based mental health services (eg, emergency department visits, hospitalizations, and length of stay in hospital). Questions about suicidality were restricted to youths aged 15-17 years (n=6950), which form our analytic sample. Weighted regression-based analyses will account for the complex survey design. RESULTS: Our study began in November 2023, funded by the American Foundation for Suicide Prevention (SRG-0-008-22). Access to the linked CHSCY microdata file was granted in May 2024. Initial examination of CHSCY data shows that approximately 20% (1390/6950) of youth have CPI, 7% (490/6950) have MIND, 7% (490/6950) seriously considered suicide in the past year, and 3% (210/6950) had attempted suicide anytime during their life. CONCLUSIONS: Findings will provide estimates of suicidality among youth with CPI-MIND comorbidity, which will inform intervention planning to prevent loss of life in this vulnerable population. Modeling correlates of suicidality will advance understanding of the relative and joint effects of factors at multiple levels-information needed to target prevention efforts and services. Understanding patterns of psychiatric service use is vital to understanding access and barriers to services. This will inform whether use matches need, identifying opportunities to advise policy makers about upstream resources to prevent suicidality. Importantly, findings will provide robust baseline of information on the link between CPI-MIND comorbidity and suicidality in youth, which can be used by future studies to address questions related to the impact of the COVID-19 pandemic and associated countermeasures in this vulnerable population of youth. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/57103.

P factor in children with chronic physical illness.

BACKGROUND: The p factor represents the overall liability for the development of mental illness. While evidence supporting the p factor in adults has been reported, studies in children are fewer, and none have examined the p factor in children with chronic physical illness (CPI). OBJECTIVE: We aimed to model the p factor in a longitudinal sample of children with CPI using a parent-reported checklist and examine its construct validity against a structured diagnostic interview. METHODS: We used data from 263 children aged 2-16 years diagnosed with a CPI who were enrolled in the Multimorbidity in Children and Youth across the Life-course (MY LIFE) study. The p factor was modelled using the Emotional Behavioural Scales over 24 months using confirmatory factor analysis. Validation of the p factor was set against the Mini International Neuropsychiatric Interview for Children and Adolescents. RESULTS: Factorial evidence supported the p factor, modelled using a bi-factor structure, compared to a standard correlated-factors (i.e., two-factor) structure [Δχ2 = 9.66(4), p = 0.047]. p factor scores were correlated with the number of different mental illness diagnoses (r = 0.71) and total number of diagnoses (r = 0.72). Dose-response relationships were shown for the number of different diagnoses (p < 0.001) and total number of diagnoses (p < 0.001). CONCLUSION: In this first study of the p factor in children with CPI, we showed evidence of its bi-factor structure and associations with mental illness diagnoses. Mental comorbidity in children with CPI is pervasive and warrants transdiagnostic approaches to integrated pediatric care.

Continuity of mental disorders in children with chronic physical illness.

Data on the chronicity of mental disorder in children with chronic physical illness (CPI) are limited. We examined the prevalence and predictors of homotypic and heterotypic continuity of mental disorder in children with CPI. A sample of 263 children aged 2-16 years with physician-diagnosed CPI were recruited from outpatient clinics (e.g., dermatology, respiratory) at a Canadian pediatric academic hospital and followed for 24 months. Parent and child-reported mental disorders (mood, anxiety, behavioral, attention-deficit hyperactivity disorder [ADHD]) were assessed using the Mini International Neuropsychiatric Interview for Children and Adolescents at baseline, 6, 12, and 24 months. Marginal regression models were computed to identify clinical, parent, and demographic factors associated with mental comorbidity over time. Mental disorder was observed in 24-27% of children with CPI based on child reports and 35-39% based on parent reports. Parent-reported models revealed significant homotypic continuity for all mental disorders (ORs = 4.2-9.5), and heterotypic continuity between mood and anxiety disorders (OR = 2.2), ADHD and behavioral disorders (OR = 5.1), and behavioral and each mental disorder (ORs = 6.7-8.4). Child-reported models revealed significant homotypic continuity for mood (OR = 8.8) and anxiety disorder (OR = 6.0), and heterotypic continuity between anxiety and mood disorders (OR = 12.4). Child disability (ORs = 1.3-1.5) and parent psychopathology (ORs = 1.2-1.8) were the most consistent predictors of both child- and parent-reported mental disorder over time. Mental comorbidity was prevalent and persistent in children with CPI with homotypic and heterotypic continuity common across informants. Child disability and parent psychopathology may be priority targets within integrated family-centered models of care to prevent mental comorbidity in children with CPI.

Mental and psychosocial health among youth after their first psychiatric hospitalization: a feasibility study.

OBJECTIVE: This pilot study investigated the feasibility of studying 12-month readmission of youth aged 10-16 years following their first psychiatric hospitalization and changes in youth mental and psychosocial health prospectively. RESULTS: Inpatient youth with a first psychiatric hospitalization and their parents were recruited from a regional hospital in Canada. Data were collected at recruitment, and at 3-, 6-, and 12-months post-discharge. Repeated measures ANOVA was performed to assess changes in health outcomes. Nineteen eligible youth were approached and 15 (78.9%) consented to participate (13.9 ± 2.0 years, 73.3% female). Eleven youth (73.3%) gave permission to contact their parents, all of whom participated (39.2 ± 7.6 years). Four youth dropped out of the study (26.7%) and six youth-parent dyads completed all four follow-ups. The readmission rate was 20.0% (n = 3) over 12 months. Significant changes in youth-reported symptoms of conduct disorder (F = 3.0, p = 0.06) and adverse childhood experiences (F = 3.4, p = 0.05) were found. Changes in parent-reported youth mental health symptoms (F = 3.1, p = 0.06), particularly among internalizing disorders, youth health-related quality of life (F = 11.3, p < 0.01), and youth disability (F = 2.7, p = 0.08) were significant. This preliminary work demonstrates the feasibility of, and need to, engage youth and their families to understand their mental and psychosocial health during this vulnerable period of time.

Contact-Free Screening of Atrial Fibrillation by a Smartphone Using Facial Pulsatile Photoplethysmographic Signals.

BACKGROUND: We aimed to evaluate a novel method of atrial fibrillation (AF) screening using an iPhone camera to detect and analyze photoplethysmographic signals from the face without physical contact by extracting subtle beat-to-beat variations of skin color that reflect the cardiac pulsatile signal. METHODS AND RESULTS: Patients admitted to the cardiology ward of the hospital for clinical reasons were recruited. Simultaneous facial and fingertip photoplethysmographic measurements were obtained from 217 hospital inpatients (mean age, 70.3±13.9 years; 71.4% men) facing the front camera and with an index finger covering the back camera of 2 independent iPhones before a 12-lead ECG was recorded. Backdrop and background light intensity was monitored during signal acquisition. Three successive 20-second (total, 60 seconds) recordings were acquired per patient and analyzed for heart rate regularity by Cardiio Rhythm (Cardiio Inc, Cambridge, MA) smartphone application. Pulse irregularity in ≥1 photoplethysmographic readings or 3 uninterpretable photoplethysmographic readings were considered a positive AF screening result. AF was present on 12-lead ECG in 34.6% (n=75/217) patients. The Cardiio Rhythm facial photoplethysmographic application demonstrated high sensitivity (95%; 95% confidence interval, 87%-98%) and specificity (96%; 95% confidence interval, 91%-98%) in discriminating AF from sinus rhythm compared with 12-lead ECG. The positive and negative predictive values were 92% (95% confidence interval, 84%-96%) and 97% (95% confidence interval, 93%-99%), respectively. CONCLUSIONS: Detection of a facial photoplethysmographic signal to determine pulse irregularity attributable to AF is feasible. The Cardiio Rhythm smartphone application showed high sensitivity and specificity, with low negative likelihood ratio for AF from facial photoplethysmographic signals. The convenience of a contact-free approach is attractive for community screening and has the potential to be useful for distant AF screening.