Objective To examine adherence to smartphone- and wearable-based digital phenotyping in patients with first-episode psychosis (FEP) and explore stakeholder perspectives on its potential application for outcome prediction. Method We conducted a six-day mixed-methods digital phenotyping assessment involving ecological momentary assessment (EMA) via smartphone and passive monitoring using wearable devices. Patients with FEP (aged 12–35) were recruited from the Early Psychosis Intervention Nova Scotia program ( N = 40). The present analysis focuses on adherence, acceptability, and stakeholder perspectives. Active and passive adherence were defined as the proportion of completed EMA surveys and available wearable data, respectively. Exploratory mixed-effects regression analyses were conducted to examine temporal trends and factors associated with adherence. Semi-structured interviews were conducted with 19 patients, six caregivers, and six clinicians, and analyzed thematically. Results Mean active adherence was 71.32% (SD = 28.77). Mean passive adherence was 85.45% (SD = 25.80) for heart rate and accelerometry, and 82.90% (SD = 26.65) for sleep data, respectively. The odds of EMA survey completion declined beginning on Day 3, and passive adherence rate declined beginning on Day 2; however, neither trend remained significant after adjusting for prior adherence. In exploratory analyses, no consistent associations were observed between most demographic or clinical variables and adherence. Higher Social and Occupational Functioning Assessment Scale score was associated with lower odds of EMA survey completion (OR = 0.91, 95% CI: 0.84, 0.98), a finding that should be interpreted cautiously given the small sample. Barriers to adherence were identified by stakeholders, including EMA survey burden, psychological risks, usability and technical challenges, and inaccessibility to digital tools due to school or work restrictions. Conclusion Digital phenotyping appears generally feasible and acceptable in clinically stable FEP patients, but implementation should incorporate safeguards to minimize EMA burden, psychological distress, usability barriers, and ethical risks related to future predictive feedback.
Background Individuals with borderline personality disorder (BPD) frequently use cannabis, often for self-medication. However, cannabis use has also been linked to BPD symptom severity, suggesting heterogeneity in its effects. Individuals with BPD frequently experience psychotic-like symptoms and may demonstrate elevated psychosis vulnerability, which is associated with greater symptom severity and poorer clinical outcomes. Cannabis use may exacerbate psychotic symptoms. The relationship between psychosis vulnerability and BPD symptoms may therefore be influenced by cannabis use. This study examined whether cannabis use interacts with psychotic-like experiences (PLEs) in relation to BPD symptom severity in a clinical sample. Method Seventy-nine outpatients with BPD completed questionnaires assessing BPD symptom severity, cannabis use, and PLEs. Moderation analyses tested whether cannabis use influenced the association between PLEs and BPD symptoms. Results Cannabis use significantly moderated the relationship between PLEs and BPD symptom severity (ΔR 2 = 0.069, P = 0.006), such that the association between PLEs and BPD symptoms strengthened as cannabis use increased. A crossover interaction was observed: the lowest BPD symptom scores occurred in individuals with low PLEs and high cannabis use, whereas the highest BPD symptom scores occurred in those with high PLEs and high cannabis use. In addition, PLEs moderated the relationship between cannabis use and BPD symptoms, such that cannabis use was negatively associated with BPD symptoms among individuals with low PLEs ( β = −0.358, P = 0.018). Conclusions PLEs appear to be an important factor in understanding heterogeneous associations between cannabis use and BPD symptom severity. Individuals with BPD who endorse elevated PLEs may benefit from targeted psychoeducation regarding cannabis-related risks and consideration of treatment for cannabis use disorder when clinically indicated. Conversely, the observed negative association between cannabis use and BPD symptoms in individuals with lower PLEs warrants further study of clinically meaningful heterogeneity and individualized treatment approaches.
ObjectiveLanguage and communication disturbances are enduring features of schizophrenia, often manifesting as impoverishment of speech. This exploratory study aims to examine how communicative deficits overlap with a cognitive profile of treatment-resistant chronic schizophrenia inpatients.MethodsWe employed Iterative Constrained Principal Component Analysis in a sample of inpatients (n = 138) to identify the optimized, multidimensional overlap between 17 neuropsychological measures and 26 symptom items from the Positive and Negative Syndrome Scale. Cognition was assessed via neuropsychological tests of verbal comprehension, semantic memory/verbal fluency, cognitive flexibility, verbal and visuospatial learning, processing speed, and working memory.ResultsThe analysis identified a distinct symptom-cognition cluster. Communication Impoverishment (specifically the Lack of Spontaneity and Flow of Conversation) was the primary predictor of a cognitive component characterized by Verbal Fluency and Executive Functioning. This component was defined by performance on tasks measuring category-based word generation, the ability to switch between semantic rules, and the depth of word knowledge and general factual information. This association was independent of antipsychotic dosage and correlated with real-world social and occupational functioning.ConclusionsThe results indicate that communication impoverishment in persistent psychosis reflects dysfunction within the verbal-semantic system, likely involving both the fluid executive ability to navigate categories and the integrity of the semantic store itself.
ObjectivePrior research in Canada had only assessed suicide mortality rates through 2018, meaning that suicide trends during and beyond the COVID-19 pandemic are unknown. Thus, this study aimed to extend previous literature by characterizing trends of age- and sex-specific suicide mortality from 2000 to 2024.MethodsYearly rates of suicide in Canada were generated from 2000 to 2024 in overall, age- (by five-year age categorizations) and sex-stratified groups. Joinpoint regression analysis was then employed to determine annual percent change (APC) of defined trendlines, and nodes at which the direction or slope of the trendline changed (joinpoints).ResultsOverall rates of suicide in Canada have significantly declined from 2018 to 2024 by an APC of -4.85 (95% CI: -6.26, -3.68; p = 0.002). Most male age groups under 40 years of age saw significantly declining trends from 2018 to 2024. For example, males aged 15-19 years had an annual percent decline of 8.37 percentage points from 2018 to 2024 (95% CI: -17.86, -3.52; p = 0.01). However, females aged 10 to 14 years saw a significant increase of 2.40 percentage points per year (95%CI: 0.72, 4.39; p = 0.007) from 2000 to 2024, while 25-29-year-old females had an annual increase of 1.85 percentage points (95%CI: 1.00, 2.85; p < 0.001) during this same time. No other age/sex groups had significantly increasing trends through 2024.ConclusionsOverall trends and many Canadian age and sex groups have seen declining rates of suicide mortality beginning in 2018, though some young female groups have continued to have increasing rates of suicide from 2000 to 2024. Future literature should look to determine whether these changing suicide trends relate to changing patterns of mental disorder, particularly in young females, or whether other characteristics may better explain the different trends in suicide observed across distinct age and sex groups.
BackgroundWe evaluated whether summaries and large language models (LLMs) preserve predictive performance for inpatient violence risk and assessed performance across demographics.MethodsWe conducted a retrospective study of inpatient encounters at Harborview Medical Center between March 2021 and September 2023. Cases were inpatient behavioural violence events, and each was matched to 10 control encounters. For each encounter, we used clinical notes from the 72 hours before the event for cases and a matched window for controls. We compared Clinical-Longformer trained on original notes with pipelines that first generated summaries and then classified risk. Summaries were either general or guided by clinician-defined risk entities. We also tested Llama-3.1-8B and MedGemma-27B in zero-shot (ZS) and fine-tuned settings. Primary endpoints were positive-class precision, recall, and F1. We also reported overall and subgroup area under the receiver operating characteristic curve (AUROC) with bootstrap confidence intervals for sex, race, ethnicity, age, and mental health flag.ResultsClinical-Longformer on original notes achieved the strongest performance (F1 = 0.776, AUROC = 0.959). Replacing original notes with general or entity-guided summaries reduced performance (F1 = 0.465 and 0.510). Llama-3.1-8B improved with sequence-classification fine-tuning on original notes but remained below Clinical-Longformer (F1 = 0.701; AUROC = 0.933), while ZS prompting performed poorly. MedGemma-27B also remained inferior, with its best performance from sequence-classification fine-tuning on original notes (F1 = 0.612, AUROC = 0.947). Subgroup AUROCs were high across sex, race, ethnicity, and age, with lower performance among patients with a documented mental health flag.ConclusionDirect classification of original notes remained the most reliable strategy. Summaries of clinical notes may compress or alter cues needed for discrimination, and off-the-shelf prompting was inadequate as a stand-alone predictor. A practical path is to anchor risk scoring in long-context discriminative models and use LLMs for auditable, clinician-facing summaries or rationales. Prospective and external validation are needed before clinical deployment.
BackgroundThe COVID-19 pandemic and associated public health measures, including lockdowns, school closures, quarantine, and social restrictions, substantially disrupted social and economic life in Canada. These conditions intensified risk factors for depressive symptoms. However, reported prevalence estimates vary widely across studies, highlighting the need for comprehensive syntheses of evidence specific to the Canadian context. The present study aimed to estimate the pooled prevalence of depressive symptoms and examine key demographic, geographic, and methodological sources of variability.MethodsA systematic review and meta-analysis were conducted following a PROSPERO-registered protocol (CRD42024552536). Five databases were searched for studies published since 2020 assessing depressive symptoms in Canada during COVID-19. Methodological quality was evaluated using Joanna Briggs Institute (JBI) appraisal checklists. Random-effects meta-analyses estimated pooled prevalence, with subgroup analyses and meta-regressions.ResultsA total of 144 studies including 406,043 participants were analysed. The pooled prevalence of depressive symptoms in Canada during the COVID-19 pandemic was 31.1% (95% confidence interval [CI], 28.4%-33.9%), with substantial heterogeneity (I2 = 99.71). Prevalence was higher among women (29.2% [95% CI, 25.8%-32.7%]) than men (21.1% [95% CI, 18.5%-23.8%]) (p = .0003) and varied significantly across provinces (p = .0001), measurement tools (p < .0001), evaluation periods (p = .017), and study designs (p = .041). No significant publication bias was detected (Egger's test: z = 1.05, p = .295).ConclusionsThese findings underscore the critical need for a comprehensive and coordinated national mental health strategy in Canada. Such a strategy should expand the mental health workforce, implement large-scale promotion and early intervention program across schools, workplaces, and community settings, and provide gender-responsive support. Future research should focus on standardizing depressive assessment measurements and prioritizing studies and interventions targeting healthcare workers, as well as racialized and Indigenous populations, to promote equitable access, strengthen resilience, and enhance preparedness for future public health crises.
BackgroundPalliative psychiatry, which emphasizes improving quality of life and reducing suffering for individuals with severe and persistent mental illness (SPMI), has gained recognition internationally. Canadian psychiatrists' perspectives on palliative psychiatry remain under-explored. We adapted a survey created by Trachsel et al. on the acceptability of palliative psychiatry amongst German-speaking Swiss psychiatrists for the Canadian context to address this gap.MethodWe conducted a cross-sectional survey of Canadian psychiatrists (n = 69). We collected data on demographics, attitudes towards palliative care in psychiatry, and responses to 3 case vignettes describing a patient experiencing anorexia nervosa, schizophrenia, or major depressive disorder, respectively. Additional questions explored participants' views on coercion. Participants could elaborate on their responses to the case vignettes using optional free-text boxes. We analyzed the survey data using descriptive statistics and the qualitative data using structured tabular thematic analysis.ResultsParticipants broadly endorsed treatment goals focused on improving function, reducing suffering, preventing suicide, and maintaining patient autonomy, while placing less emphasis on curative approaches. Participants were divided on whether palliative care relates to end-of-life care. There was strong acceptance for a palliative approach in SPMI care. Attitudes towards prognosis and treatment futility varied by diagnosis amongst the case vignettes. Participants expressed nuanced views on coercion, highlighting ethical tensions when considering interventions contrary to patient preferences. Our qualitative analysis uncovered themes of ethical dimensions, clinical paradigms, characteristics of mental illness, considering comprehensive treatment options, psychosocial factors, and systemic factors in participants' consideration of their responses.ConclusionsThis cohort of Canadian psychiatrists largely endorses the applicability of palliative care approaches within SPMI care. Our findings underscore the need for further research with larger samples to understand potential gaps between theoretical acceptance and practical implementation. Future research should include the perspectives of patients, families, and other interest-holders to guide the potential integration of a palliative care model into psychiatric practice.
ObjectivesThis study examined the point prevalence of patients with intellectual and developmental disabilities (IDDs) in Ontario forensic inpatient units and compared the demographic, clinical, and system-level profiles of long-stay forensic patients with and without IDD.MethodThis cross-sectional study utilized Ontario administrative health data held at ICES. All patients over 18 years of age who occupied an Ontario forensic inpatient bed on 30th September 2023 were included in the analysis. Focus was given to patients with a length of stay (LOS) of at least 365 days (i.e., "long-stay" patients). Within this group, the prevalence of IDD was assessed, and patients with and without IDD were compared on their demographics, clinical characteristics, LOS, and support needs using standardized differences (StdDiff).ResultsAmong long-stay forensic patients (n = 549), 42.4% had IDD. Long-stay forensic patients with and without IDD had a mean age of 43 years, and the majority of patients in both groups were male (87.6% vs. 90.8%; StdDiff = 0.105). In the 2 years prior to admission, the majority of all long-stay patients were diagnosed with a psychotic disorder, though the proportion was higher among patients without IDD (80.3% vs. 92.1%; StdDiff = 0.348). Long-stay patients with IDD had a substantially longer LOS (mean LOS = 7.2 years vs. 4.9 years; StdDiff = 0.459) and were more likely to be restrained (5.2% vs. 2.2%; StdDiff = 0.156). A higher proportion of long-stay patients with IDD had difficulty with activities of daily living (23.2% vs. 11.7%; StdDiff = 0.306), and severe cognitive impairment (14.6% vs. 6.6%; StdDiff = 0.260).ConclusionsThis study found that almost half of long-stay forensic patients had IDD and this patient group had different demographic and clinical profiles from other patients, which may impact their support needs within the hospital and pose barriers to discharge.
IntroductionHomeless youth experience disproportionately high rates of mental disorders, suicidality, and overdose. Understanding their heterogeneous needs is essential for designing integrated care models. This study examined characteristics, help-seeking reasons, and service use among youth accessing ACCESS Open Minds (ACCESS-OM)-Réseau d'intervention de proximité auprès des jeunes de la rue (RIPAJ), a Montréal-based network serving homeless and at-risk youth.MethodsWe analyzed sociodemographic and clinical data, presenting concerns, and services received by youth referred to ACCESS-OM-RIPAJ (2016-2020). Latent class analysis (LCA) identified clusters based on (1) presenting concerns and (2) service use.ResultsA total of 681 referrals were made to ACCESS-OM-RIPAJ. LCA identified 4 distinct help-seeking clusters: (1) a group characterized by severe material deprivation, including homelessness and unmet basic needs, alongside notable social isolation and higher prevalence of psychotic symptoms, who were more often referred to specialized psychiatric services; (2) a group defined by substance misuse with homelessness and financial instability, with fewer co-occurring concerns, requiring coordination across services; (3) a cluster marked by trauma-related experiences, family difficulties, and suicidality, with less clearly defined service use patterns; and (4) a group characterized by emotional distress, occurring alongside financial precarity and risk of homelessness, who were primarily offered psychological interventions.ConclusionThese findings highlight the heterogeneity of needs among homeless and at-risk youth and the importance of integrated, multi-component mental health programs. Improving access to care across the continuum of needs and presentation severities is essential for preventing adverse outcomes and addressing the cyclical relationship between mental health and homelessness.
Plain Language SummaryResponding to concerns regarding the methods and findings of a study on autism and gender diversity in CanadaDinu and colleagues wrote a letter to the editor about a recently published study that looked at differences in characteristics between autistic and non-autistic adults who were seen by clinicians at a Canadian gender identity clinic. Dinu and colleagues encouraged interpreting the findings of the original article with caution, because they were concerned about the type of data, the method of analyzing the data, and the interpretations that the authors made. In this response, we address their concerns and clarify the goals and findings of our original study. Like all retrospective chart review studies, our original study has important limitations. We agree that these limitations should be considered when interpreting our findings, but they do not change the main conclusions of the study. Dinu and colleagues interpreted our study as recommending specific approaches to care for autistic adults. Our response clarifies that our study described autistic transgender and gender diverse adults attending an adult gender identity clinic as having substantial mental health needs and did not recommend specific approaches to care. We conclude that further research and service planning are needed to improve access to individualized mental health and gender-related care for autistic transgender and gender-diverse adults.
BackgroundPosttraumatic stress disorder (PTSD) is common yet frequently underdiagnosed, in part due to barriers to systematic screening and the reliance on self-report instruments. Large language models (LLMs) have shown promise in extracting clinically relevant information from unstructured language, but their ability to infer item-level PTSD symptom severity from clinical interviews remains unclear.MethodsUsing the Distress Analysis Interview Corpus-Wizard of Oz (DAIC-WoZ), we analyzed 100 semi-structured clinical interview transcripts paired with item-level PTSD Checklist-Civilian Version (PCL-C) scores. Six LLMs (DeepSeek 3.1, Claude Sonnet 4, LLaMA 4 Scout, GPT-4o, GPT-5, and Gemini 2.5 Flash) used zero-shot prompting to predict all 17 PCL-C items. Performance was assessed for binary symptom endorsement (≥3 vs. < 3), 5-point Likert prediction, and DSM-IV symptom-cluster analyses using accuracy, F1 score, and Matthews correlation coefficient (MCC).ResultsFor binary prediction, Claude 4 achieved the highest mean accuracy (0.705; 95% CI, 0.681-0.728), followed by DeepSeek 3.1(0.699; 95% CI, 0.675-0.724) and Gemini 2.5 (0.698; 95% CI, 0.677-0.718). For Likert prediction, DeepSeek 3.1 performed best (accuracy = 0.438; 95% CI, 0.401-0.475), only modestly above the majority-class baseline (0.399; 95% CI, 0.355-0.443). Performance varied by symptom domain, with re-experiencing and hyperarousal symptoms generally predicted more accurately than avoidance/numbing symptoms. Across models, predicted item-level symptom patterns showed a meaningful alignment with observed PCL-C responses despite reduced accuracy in fine-grained severity estimation.ConclusionZero-shot LLMs' performance was insufficient for clinical application in predicting PTSD symptoms from semi-structured interview transcripts. While models showed some ability to capture overall symptom patterns, performance varied across domains and remained limited for fine-grained severity estimation. Given these constraints and the non-trauma-specific nature of the dataset, findings should be interpreted as preliminary, with only modest differences observed between models.Plain Language Summary TitleCan Artificial Intelligence Identify PTSD Symptoms from Conversations? A Study Using Clinical Interview TranscriptsPlain Language SummaryPost-traumatic stress disorder (PTSD) is a common mental health condition, but it is often missed in clinical settings. Screening usually relies on questionnaires that patients must complete themselves, which may not always happen due to time, stigma, or discomfort discussing trauma. Researchers are exploring whether artificial intelligence (AI) could help identify PTSD symptoms from conversations instead.In this study, we tested several advanced AI systems, known as large language models, to see if they could estimate PTSD symptoms based on written transcripts of clinical interviews. These interviews were not specifically designed to assess trauma, which makes the task more challenging but closer to real-world situations. We compared the AI predictions to participants' own questionnaire responses about their symptoms.We found that the AI models were somewhat able to recognize general patterns of PTSD symptoms, especially more visible ones like sleep problems or distressing dreams. However, they struggled with more internal or less obvious symptoms, such as avoidance or emotional numbness. Overall, their accuracy was moderate and not reliable enough for clinical use, particularly when trying to estimate how severe symptoms were.Importantly, differences between the AI models were small, and none performed well enough to replace existing screening methods. These findings suggest that while AI may have future potential as a supportive tool, it is not yet ready to be used for diagnosing or screening PTSD on its own.Further research using better data, improved methods, and real clinical settings is needed before this approach could be considered for practical use.
Background Public safety communicators (PSCs, 911 call-takers, dispatchers, and others) play a critical role in Canada's emergency response system, yet they remain largely understudied compared with other public safety professionals (PSP). Although PSCs do not intervene directly at emergency scenes, they are routinely exposed to potentially psychologically traumatic events and high operational stress during calls, placing them at elevated risk for post-traumatic stress injuries (PTSIs). This study aimed to (1) estimate the prevalence of various PTSIs and suicidal behaviors among Canadian PSCs, (2) compare the prevalence with those reported for other Canadian PSP, and (3) identify associated sociodemographic factors. Methods The final analytic sample included 508 PSCs. Participants completed validated screening measures assessing symptoms of post-traumatic stress disorder, major depressive disorder, generalized anxiety disorder, panic disorder, and alcohol use disorder, along with questions regarding suicidal behaviors. Results Nearly half of PSCs (48.6%) screened positive for at least 1 PTSI, exceeding the prevalence observed among other Canadian PSP. Symptoms of PTSD, depression, anxiety, and panic disorder were significantly higher, while alcohol abuse disorder symptoms were comparable to levels observed among other PSP. Suicide attempts were also significantly more frequent in our sample. Being female emerged as the strongest predictor of screening positive for a PTSI, whereas higher educational attainment was associated with reduced odds of both PTSI symptoms and suicidal ideation. Conclusions These findings highlight PSCs as a high-risk and overlooked subgroup within public safety. Trauma-informed training, targeted organizational adjustments, and profession-specific support resources are essential to mitigate the significant psychological burden on this workforce and foster long-term occupational well-being.
ObjectiveAddiction and mental health (AMH) disorders present significant psychosocial challenges among affected individuals. Previous research indicates a higher prevalence of AMH conditions among people experiencing homelessness (PEH). This study aims to determine the risk of mortality, suicide attempts, emergency department (ED) visits and hospitalizations among PEH with AMH conditions compared to individuals with AMH conditions who had not experienced homelessness in Alberta.MethodsThis retrospective cohort study used linked administrative data from Alberta Health Services from April 1, 2013 to March 31, 2023. We included adults residing in Alberta and diagnosed with any AMH condition within 5 years before the index date of April 1, 2018. Homelessness in the year prior to the index date was identified using relevant codes in records representing hospitalizations and ED visits. We used Cox Proportional Hazards models to evaluate the risk of ED visits, hospitalizations, suicide attempts, and all-cause mortality for up to 5 years, adjusted for age and sex. We also conducted matched propensity score analyses.ResultsAmong the 622,614 individuals with AMH conditions, 3,390 (0.54%) had an indicator of homelessness. In age and sex-adjusted analyses, PEH were at greater risk for ED visits for both AMH (HR = 8·75, 95% CI [8.37-9.16]) and non-AMH (HR = 2.56, HR = 2.47-2.63) reasons, and at greater risk of hospitalizations for AMH (HR = 8.34, 95% CI [7.73-9.00]) and non-AMH (HR = 6.03, 95% CI [5.73-6.35]) reasons. PEH were at greater risk of suicide attempts (HR = 9.18, 95% CI [8.43-10.01]) and all-cause mortality (HR = 8.15, 95% CI [7.56-8.79]). Findings were attenuated but still significant in the propensity-matched analyses.ConclusionsPEH are at much greater risk of ED visits, hospitalizations, suicide attempts and all-cause mortality. Given this population's high risk of adverse outcomes, PEH will likely need more intensive mental and physical healthcare, coordinated with housing and social support services. Further research is needed on the implementation of interventions tailored to the needs of PEH.
BackgroundPersons involved in compulsory mental health treatment-including clinicians, lawyers, service users, and family members-frequently express dissatisfaction with how the system is regulated and administered. Policy discussions on improving the system often fail to consider the voices of service users and family members. Policy development must also grapple with the contested values of autonomy and wellbeing, and the associated disjuncture in professional views. Community treatment orders (CTOs) are a key mechanism of compulsory mental health treatment in Ontario, and many other jurisdictions. We studied views on CTOs in Ontario to identify agreement across groups about where and how the system ought to be improved.MethodWe conducted semi-structured individual interviews followed by mixed focus groups including 72 participants: healthcare professionals, lawyers, tribunal members, service users ("clients"), family members, and advocates. Interview data were analyzed to identify recurring concerns and inform focus group discussion topics. Focus groups explored potential areas of alignment across participant groups, with particular attention to points of consensus. A lived-experience advisory panel informed study design.ResultsAcross participant groups, 6 main areas of agreement were visible. Participants identified the need for: (1) increased client involvement in treatment decisions, even within compulsory frameworks; (2) improved police involvement during CTO enforcement; (3) improved availability and quality of CTO-related data, enabling evaluation, accountability and attention to equity; (4) enhanced guidance and support for substitute decision-makers; (5) stronger oversight of medical decision-making, though preferred mechanisms varied; and (6) expanded community services-particularly housing, addiction treatment and case management-viewed as essential for CTOs to be able to have their intended benefit.ConclusionsThis study shows there is meaningful agreement on several areas requiring improvement in Ontario's CTO system. These points of convergence represent promising foundations for policy development, although translation into actionable reform will require further policy work.
ObjectiveTo estimate the prevalence of comorbid postpartum depression (PPD) and postpartum anxiety (PPA) in birthing parents seeking treatment for PPD in Ontario, Canada and who were enrolled in 1 of 9 randomized controlled trials (RCTs) of cognitive behavioural therapies (CBT) for PPD.MethodsSecondary analysis of 9 pooled RCTs containing baseline data from 1920 birthing parents and conducted between 2017 and 2025. All participants were living in Ontario, Canada with Edinburgh Postnatal Depression Scale (EPDS) Scores ≥10 and infants <12 months old. Comorbid anxiety was assessed using the Generalized Anxiety Disorder-7 (GAD-7) scale, the Penn State Worry Questionnaire (PSWQ) and/or the Mini International Neuropsychiatric Interview (MINI).ResultsSixty-six percent of participants with PPD (EPDS scores ≥10) had moderate to severe anxiety (GAD-7 scale score ≥10; 95% confidence interval (CI) 63-68%, 7 studies, n = 1654), and 69% with PPD met the cutoff for probable GAD (PSWQ scale score ≥61; 95% CI [63-74%], 2 studies, n = 254). Seventy percent of participants with MINI-defined current major depressive disorder (MDD) met Diagnostic and Statistical Manual of Mental Disorders-4th Edition-based criteria for any anxiety disorder (95% CI [64-76%], 6 studies, n = 448). Nearly 60% of participants with current MDD met criteria for GAD on the MINI (95% CI [52-61%], n = 448).ConclusionsMore than two-thirds of treatment-seeking individuals with PPD have clinically significant anxiety. Those with PPD, their families, and healthcare professionals should be aware of the high prevalence of anxiety in these individuals so that treatment plans can be optimized to best meet their needs.Trial RegistrationClinicalTrials.gov (https://clinicaltrials.gov/): NCT03039530, NCT03654261, NCT03285139, NCT04485000, NCT04928742, NCT04934488, NCT04913584, NCT05314361 and NCT05044455.
