This study aimed to quantify associations between chronic conditions and mental illness; investigate potential moderating effects of child age, sex, health functioning, mental health service contact and household income on these associations; and explore the potential mediating effect of family functioning. This study conducted secondary data analyses on a sample of 6242 children aged 4-17 years from the 2014 Ontario Child Health Study (OCHS). Chronic conditions were assessed using a standard list of conditions developed by the Statistics Canada. Mental illness was assessed with the Emotional Behavioural Scales (EBS). The Health Utility Index Mark III measured health functioning. Logistic regression models quantified associations between chronic conditions and mental illness. Moderating effects were tested with product-term interactions in logit models and interpreted using average marginal effects. Mediating effects were explored using the product of coefficients method. Having a chronic condition was associated with mood disorder (OR = 2.25 [95% CI: 1.36-3.74]). For children who have better health functioning, average marginal effects indicated that children with chronic conditions are 29% more likely to have any mental illness (p < 0.01), 21% more likely to have anxiety disorders (p < 0.05) and 21% more likely to have ADHD (p < 0.05) than children with no conditions. For children who have poorer health functioning, there was no association between chronic conditions and mental illnesses. Family functioning did not mediate any associations between chronic conditions and mental illness outcomes. The association between chronic conditions and mental illness in children is nuanced, with health functioning moderating this association for any mental illness, anxiety disorders and attention-deficit hyperactivity disorder specifically. Mental health screening programs should ensure children with chronic conditions who have better health functioning are routinely assessed and upstream interventions initiated early to reduce the incidence of physical-mental multimorbidity.

With the proliferation of social media, there is a growing opportunity to leverage user-generated content for early mental health screening. A significant portion of online discourse reflects users' mental states, but manual analysis is infeasible at scale. This study addresses the challenge of accurately identifying signs of depression from social media text using automated methods. To tackle this problem, we evaluated the effectiveness of a baseline TF-IDF with Logistic Regression model and a Convolutional Neural Network (CNN) on a large dataset of Reddit posts. Both models demonstrated high efficacy, achieving accuracy and F1-scores of approximately 93%. The models yielded excellent ROC AUC scores (0.9825 for Logistic Regression and 0.9782 for the CNN), indicating a strong ability to distinguish between depressed and non-depressed users. A detailed error analysis revealed that the CNN produced fewer false negatives, a critical consideration for clinical applications. This work establishes a strong baseline for using machine learning for depression detection and highlights the importance of model selection based on specific error-reduction goals

This study aims to investigate the association between the perceived functional impact of hearing loss, assessed using the evaluation of the impact of hearing loss in adults (Évaluation du Retentissement de la Surdité chez l'Adulte; ERSA), and depressive symptoms quantified by the Beck Depression Inventory (BDI) in adults with hearing impairment. This cross-sectional study comprised adult individuals exhibiting hearing loss of at least 25 dB in 1 ear for a minimum period of 6 months. The ERSA scale assessed hearing-related quality of life (QOL) in functional and psychosocial domains, whereas depression symptoms were measured using the BDI. Demographic and clinical attributes were documented. Correlations between ERSA scores and BDI scores were analyzed in various aspects. A total of 103 adults with hearing loss were included in this study. Higher BDI scores were significantly correlated with lower ERSA scores in the QOL, personal life, and social life domains. Strong negative correlations were observed between BDI scores and ERSA total scores (ERSA 150 and ERSA 200). Participants exhibiting more severe, bilateral, and mixed-type hearing loss showed higher depressive symptom scores and lower ERSA outcomes. Hearing aid users exhibited higher BDI scores and lower ERSA scores compared with non-users. A higher socioeconomic status correlated with reduced depression symptoms and improved hearing-related QOL. The perceived functional and psychosocial impact of hearing loss, as evaluated by ERSA, is strongly associated with the severity of depressive symptoms measured by the BDI. These findings highlight the necessity of incorporating patient-reported outcome measures and mental health screening into routine audiological assessment. A multidisciplinary, patient-centered approach addressing both auditory and psychological requirements may improve overall outcomes in adults with hearing loss.

Comorbid depression and anxiety in patients with diabetes mellitus (DM) is associated with poor disease outcomes, yet its burden and associated factors are not well-characterized in low-resource settings like Uganda. This study aimed to determine the prevalence and factors associated with comorbid depression and anxiety among patients with DM in Uganda. A cross-sectional study was conducted at the diabetes clinic of Mulago National Specialised Hospital. The study consecutively enrolled 223 adult patients (≥18 years) with DM. The Mini-International Neuropsychiatric Interview (MINI) was used to diagnose depression and anxiety disorders. Data on socio-demographics, clinical characteristics, alcohol use (AUDIT-C), social support (MSPSS), and quality of life (WHOQOL-BREF) were collected. Logistic regression was used to identify factors associated with comorbid depression and anxiety. The mean age of participants was 54.6 years (SD = 13.1), and 72.2% were female. The prevalence of comorbid depression and anxiety was 14.3% (95% CI: 10.3-19.6). In the multivariable analysis, factors significantly associated with increased odds of comorbidity included having a higher number of children (Adjusted Odds Ratio, aOR=1.15, 95% CI: 1.02-1.32), longer duration since DM diagnosis (aOR=1.07, 95% CI: 1.01-1.12), high blood pressure (aOR=2.19, 95% CI: 1.94-5.08), and moderate/high alcohol use (aOR=1.46, 95% CI: 1.09-5.14). Conversely, diagnosis of Type II DM (aOR=0.40, 95% CI: 0.16 - 0.91), older age (aOR=0.97, 95% CI: 0.94-0.99) and higher scores across all WHOQOL-BREF domains (physical, psychological, social, environmental) were associated with significantly reduced odds of comorbidity. Nearly one in seven patients with DM in this Ugandan cohort had comorbid depression and anxiety. The findings underscore the need for integrated mental health screening and intervention within diabetic care services, particularly targeting younger patients, those with Type 1 DM, longer disease duration, hypertension, and hazardous alcohol use.

BACKGROUND The increasing prevalence of adolescent depression has led to widespread antidepressant use, with associated risks of intentional and accidental poisoning. Family dysfunction, parental mental health problems, and poor family psychological environment are known risk factors for adolescent self-harm behaviors, but their specific role in antidepressant poisoning has not been systematically investigated. AIM To analyze the incidence characteristics of adolescent antidepressant poisoning in emergency departments, explore the influence of family psychological environment on adolescent antidepressant poisoning, and provide scientific evidence for developing effective prevention strategies. METHODS A retrospective study design was employed, collecting data from 250 adolescent patients aged 12-18 years admitted to the emergency department of a hospital from January 2020 to January 2025, including 28 cases of antidepressant poisoning (poisoning group) and 222 cases of non-drug poisoning adolescent patients (normal group). Family psychological environment was assessed using Family Social Climate Questionnaire, Family Adaptability and Cohesion Evaluation Scales-II, Symptom Checklist-90, Egna Minnen Betraffande Uppfostran, Life Events Scale, and Social Support Rating Scale. Adolescent psychosocial factors were evaluated using Center for Epidemiologic Studies Depression Scale, Self-Rating Anxiety Scale, Adolescent Life Events Scale, Interpersonal Reactivity Index, and Coping Style Questionnaire. Statistical analyses included t -tests, χ 2 tests, and multivariate logistic regression analysis for influencing factors. RESULTS The incidence of adolescent antidepressant poisoning in emergency departments was 11.2% [95% confidence interval (CI): 7.8%-15.8%]. Multivariate logistic regression analysis showed that female gender [odds ratio (OR) = 2.847, 95%CI: 1.024-7.913], high Center for Epidemiologic Studies Depression Scale scores (OR = 1.124, 95%CI: 1.062-1.190), low Family Structure Characteristics Questionnaire total scores (OR = 0.934, 95%CI: 0.891-0.979), high parental Symptom Checklist-90 total scores (OR = 1.018, 95%CI: 1.005-1.031), and low Social Support Rating Scale total scores (OR = 0.895, 95%CI: 0.839-0.955) were independent influencing factors for adolescent antidepressant poisoning (all P &lt; 0.05). CONCLUSION The incidence of adolescent antidepressant poisoning is relatively high, with female gender, depression severity, family structure instability, parental mental health problems, and lack of social support being important influencing factors. A family-centered multi-level comprehensive prevention and treatment system should be established, strengthening adolescent mental health screening, improving family psychological environment, and enhancing social support levels.

Menarche is a normative milestone of female puberty, yet its role in adolescent mental health and brain development remains poorly understood. Using longitudinal data from 5,016 females (7 annual visits, ages 10-16 years) in the Adolescent Brain Cognitive Development Study, we found that menarche onset functions as an inflection point for the development of internalizing symptoms and gross brain morphometry. The onset of menarche, largely independent of timing and socio-environmental factors, preceded a significant spike in internalizing symptoms, while altering the rate of ongoing structural brain development. Following menarche onset, individuals with faster declines in gray matter volume and surface area also had heightened internalizing symptoms. These findings suggest that menarche is not only a reproductive milestone but a neuroendocrine driver of adolescent brain and mental health trajectories. This normative and easily identifiable marker could define a critical window for mental health screenings with greater precision than current age-based guidelines.

Digital perinatal mental health screening and psychosocial assessment using iCOPE: experiences and insights from healthcare providers.

Mental health conditions can be considered one of the most serious social disasters of the twenty-first century. “World Health Organization” (WHO) states that a global population of over one billion is living with some mental health problem, that over half a billion suffer depression and other disorders of anxiety and that each year, suicide kills about 727,000 with more than 580 million people affected. Timely intervention and early detection is desperately wanting especially in low and middle-income countries where more than three quarters of victims go untreated. The growth of social networks such as Twitter/X, Reddit, and Facebook produces large amounts of user-generated data that can record current emotional states, behavioural tendencies, and linguistic indicators and can serve as an unprecedented source of non-invasive data to monitor mental health. The paper is a systematic review of the use of artificial intelligence (AI)-based tools in the early prediction of mental health issues, such as depression, anxiety, bipolar disorder, and suicidal thoughts, with the help of social media data. The review summarizes more recent “natural language processing” (NLP), deep learning systems, including BERT, RoBERTa, and Bidirectional LSTM networks, multimodal fusion models, and “Explainable AI” (XAI) models related to improving clinical interpretability. Empirical results suggest state of the art transformer designs can do so with a depression detection accuracy of over 91, a suicidal ideation detection rate of up to 94.29 and the AI systems are able to detect other crisis telltales on average 7.2 days before professional clinicians. Data privacy, cross-cultural generalizability, and the Ethical aspects of autonomous mental health screening are highlighted as key issues of autonomous systems in healthcare. This review offers a guide on how AI-driven social media analytics can be responsibly integrated into the proactive mental health care systems.

Mental health disorders like depression and anxiety pose global challenges, requiring accurate, non-invasive detection methods. Classical modes of diagnosis are typically based on self-reported symptoms or clinical evaluation, which could be subjective and protracted in time. To address these limitations, this study proposes NeuroHAGWO-Net, an advanced artificial intelligence-based framework for automated mental health status detection using multimodal data. The proposed model integrates electroencephalogram (EEG) signals and behavioral textual data to enable early and reliable mental health screening. EEG signals are pre-processed with Empirical Mode Decomposition (EMD) for noise removal, while behavioral text data is transformed into embeddings using Bidirectional Encoder Representations from Transformers (BERT) models. The hybrid BiLSTM-CNN architecture captures temporal dependencies and spatial patterns in EEG data, enhanced by integrating behavioral embeddings for multimodal analysis. Features are selected using a novel Hybrid Ant-Grey Wolf Optimization (HAGWO) approach, combining Ant Colony Optimization (ACO) and Modified Grey Wolf Optimization (mGWO), respectively. The AI-based mental health detection is performed using NeuroVisionNet, integrating EfficientNetV2 and Temporal CNNs (T-CNNs). The model's performance is validated on two datasets: behavioral data and EEG signals data. On behavioral data, it achieves an accuracy of 0.9945, precision of 0.9874, sensitivity of 0.9935, specificity of 0.9915, F1-Score of 0.9909, Matthews Correlation Coefficient (MCC) of 0.9925, Negative Predictive Value (NPV) of 0.9905, False Positive Rate (FPR) of 0.0151, and False Negative Rate (FNR) of 0.0092. With its strong accuracy and efficiency in detecting mental health situations under diverse data modalities, NeuroHAGWO-Net Model proves to be a robust tool for early mental health screening and clinical support using modern optimization techniques and deep learning architectures.

Breast cancer (BC) is a leading cause of mortality among women. Comorbidity with mood disorders is a condition either disregarded or underdiagnosed in BC patients, but that might ultimately jeopardize health trajectories. This is supported by evidence indicating that the same biological pathways relevant for mood disorders may also underlie tumorigenesis. In this study, we aimed at deriving a reliable biosignature of mental health vulnerability in BC patients. We conducted a cross-sectional study in a population of 44 women diagnosed with BC who underwent surgery before receiving adjuvant chemotherapy. All subjects were scored for symptoms of depression, anxiety and stress; blood samples were used to measure relevant biomarkers of inflammation, energy homeostasis and brain plasticity, while circadian cortisol rhythm was assessed in the saliva. Based on a rigorous statistical approach, we identified a specific immune- metabolic biosignature of depression relying upon each subject's BMI, IL-5 and leptin. Following the validation of the model, we defined a cut-off value to identify those subjects who are at elevated risk of poor prognosis based on our biosignature. This signature holds potential for the timely identification of those individuals for whom depressive symptoms are sustained by a deranged immune-metabolic milieu and might therefore be at higher risk of poorer health outcomes. Our results strengthen the importance of accounting for brain-body communication in cancer and suggest that routine screening for mental health in BC patients should be prioritized in order to put in place tailored intervention strategies to improve health outcomes.

Nicotine metabolite ratio (NMR) is a biomarker for the rate of nicotine metabolism and may be linked to depression, but evidence from large, representative populations is scarce. The role of smoking status as a potential effect modifier of this association is poorly understood. Identifying smoker-specific vulnerability may inform risk stratification and integration of mental-health screening within smoking-cessation settings. We aimed to investigate the association between NMR and clinically significant depressive symptoms in U.S. adults and among active smokers. We conducted a cross-sectional, observational analysis of 9287 adults (≥20 years) from the National Health and Nutrition Examination Survey 2013 to 2018. The exposure was the natural ln(NMR). The outcome was clinically significant depressive symptoms (Patient Health Questionnaire-9 [PHQ-9] score ≥10). We used survey-weighted modified Poisson regression to estimate relative risks with 95% confidence intervals; missing covariates were addressed using multiple imputation. Analyses were stratified by smoking status using a union definition (self-report or serum cotinine ≥3 ng/mL); robustness was evaluated using a stricter threshold of ≥10 ng/mL. In the overall population, ln(NMR) was not associated with depressive symptoms (per 1- standard deviation [SD] increase, RR 1.03; 95% CI 0.93-1.14). However, among smokers (union definition; cotinine ≥3 ng/mL), a higher ln(NMR) was associated with a higher prevalence of clinically significant depressive symptoms (RR per 1-SD, 1.15; 95% CI, 1.02-1.29). This finding was robust using a stricter cotinine cutoff of ≥10 ng/mL (RR per 1-SD, 1.16; 95% CI, 1.02-1.32). Restricted cubic splines revealed a near-linear dose-response relationship in smokers only. Significant interactions were observed across multiple covariates - including body mass index, poverty-income ratio, race/ethnicity, sex, smoking status, hypertension, diabetes, cotinine level, and stroke - after false discovery rate control. In this study, higher ln(NMR) was associated with a higher prevalence of clinically significant depressive symptoms among active smokers, but not in the overall U.S. adult. These findings highlight a smoker-specific vulnerability and suggest that NMR may be useful for risk stratification to support integrated smoking-cessation and mental-health screening; longitudinal and interventional studies are needed to clarify directionality and clinical utility.

In Vietnam, in 2024, the HIV prevalence was estimated at 0.4% accounting for approximatively 270,000 adult people living with HIV (PLHIV). PLHIV may also face hepatitis C virus (HCV) co-infection, although co-infection disproportionally affects people who inject drugs (PWID). It has been shown that usually, PLHIV have lower health-related quality of life (HRQoL) than HIV-negative individuals. This study, focusing on HIV-HCV co-infected individuals on antiretroviral therapy (ART), offers the opportunity to investigate their HRQoL and compare PWID to non-PWID.The MOVIDA Hep 2 project, a prospective cohort study, enrolled HIV-HCV co-infected patients on ART in Vietnam. At enrolment, the HRQoL in the cohort was assessed using the EQ-5D-5L standardized scale. Low self-rated HRQoL was defined as providing a score below the 25th percentile. Factors associated with this outcome were identified using mixed-effects logistic regression models.A total of 343 HIV-HCV co-infected participants were enrolled in the study, of whom 249 (72.6%) were PWID. Participants were on ART for 116 months in median. Overall, 62 (18.1%) participants reported pain/discomfort and 42 (12.2%) reported anxiety/depression, the proportions did not differ by PWID status (p=0.85 and p=0.07, respectively; Fisher exact test). However, when self-rating their HRQoL, PWID gave a significantly lower score (p<0.001). Factors associated with low self-rated HRQoL were PWID status, ethnicity and alcohol consumption as well as reporting pain/discomfort and anxiety/depression. Interestingly, PWID self-rated their HRQoL at a lower level than non-PWID despite similar long the duration of ART (around 10 years in median) in both groups. Our results suggest that PWID face more physical and psychological distress. The extent of such problems is difficult to ascertain, but screening patients to identify those who need more specific support or attention would be beneficial. Offering integrated mental health screening and care could also benefit these patients, but then the question of integrating mental health care in the national health insurance must also be questioned or addressed.

Introduction: This study aimed to examine COVID-19 pandemicrelated differences in the prevalence of anxiety and depression among adolescents aged 12–17 years in the United States. Methods: A cross-sectional study was conducted using NSCH data from the United States between 2016 and 2022, including adolescents aged 12–17 years. The pre-pandemic period was defined as 2016–2019, and the pandemic period as 2020–2022. Weighted prevalence and prevalence ratios (PR) were calculated. Results: The prevalence of anxiety was 13.14% (12.6, 13.7) during the prepandemic period and 17.59% (16.95, 18.26) during the pandemic. The PR of anxiety during the pandemic versus the pre-pandemic period was 1.339 (1.266, 1.416), p &lt; 0.001. The prevalence of depression was 8.45% (7.95, 8.97) during the pre-pandemic period and 10.68% (10.16, 11.22) during the pandemic. The PR of depression during the pandemic versus the pre-pandemic period was 1.264 (1.17, 1.367), p &lt; 0.001. Anxiety trends consistently increased across all subgroup analyses, whereas the increase in depression was more pronounced in specific subgroups, including White, female, and Hispanic adolescents. Discussion: Our study identified an increase in the prevalence of anxiety and depression among adolescents aged 12–17 years during the COVID-19 pandemic compared to the pre-pandemic period. The rise in anxiety prevalence was observed consistently across all subgroups analyzed, including both males and females, as well as across diverse racial and socioeconomic groups. Conclusion: The prevalence of anxiety and depression among US adolescents was higher during the COVID-19 pandemic. These findings underscore the need for targeted mental health screening, school-based prevention programs, and expanded access to telehealth.

Prenatal Mental Health Screening and Support in a Multidisciplinary Fetal Imaging Program: a Brief Report on Protocol and Early Findings.

Assessing the YAM-5 and PeSSKi questionnaires as tools for mental health screening in migrant children ages 7-12 years living on the Thailand-Myanmar border.

Anxiety, Mental Well-Being, and Life Satisfaction Among Postpartum Women After the Kahramanmaraş Earthquake: Interrelations and Predictors.

Objective: To compare the perceived social support and psychosocial burden of patients with psoriatic arthritis, osteoarthritis, and rheumatoid arthritis. Study Design: Comparative Cross-Sectional StudyPlace and Duration of Study: This study was conducted at the Department of Medicine, Madinah Teaching Hospital / University Medical and Dental College, Faisalabad from January to June 2025. Methods: Based on estimations from the World Health Organization calculator and corrected for non-response, 500 persons with psoriatic arthritis, osteoarthritis, or rheumatoid arthritis were included in the sample. Stratified random sampling was used to choose the eligible participants. A standardized questionnaire that included sociodemographic information, the Multidimensional Scale of Perceived Social Support, and the Depression Anxiety Stress Scale-21 was used to gather data in person. Tukey post-hoc tests, one-way analysis of variance, and descriptive statistics were used in the Statistical Package for the Social Sciences version 26 analysis; p &lt; 0.05 was deemed significant. Results: PsA patients showed significantly higher levels of depression, anxiety, and stress (p&lt;0.05) than RA and OA patients, as well as the lowest scores of MSPSS. Conclusion: The findings highlight the significant psychological burden experienced by PsA patients as well as the significance of patient education, mental health screening, and a multidisciplinary approach in rheumatology therapy.

Purpose: To evaluate the risk of developing depression, anxiety, and suicidal behavior in older adults newly diagnosed with blindness. Methods: A retrospective cohort study was conducted using the TriNetX Analytics Network, analyzing de-identified electronic health records from 2006 to 2024. Patients ages ≥60 years with a diagnosis of blindness based on International Classification of Diseases, Tenth Revision, Clinical Modification codes were identified. Patients were matched 1:1 to control subjects with normal vision using propensity score matching (PSM), based on demographics and psychiatric comorbidities. Primary outcomes included incident major depressive episodes, persistent depression, anxiety disorders, and suicide attempts at 1-, 3-, and 5-year follow-up intervals. Results: After PSM, 143 668 subjects were included in each cohort. Compared with matched controls, blindness was associated with increased risk of major depression at 1 year (relative risk [RR] 1.69; 95% confidence interval, 1.64-1.72), 3 years (RR 1.47), and 5 years (RR 1.39). Similar trends at 1, 3, and 5 years were observed for risk of persistent depression (RRs of 1.88, 1.43, and 1.29, respectively), anxiety (RRs of 1.92, 1.45, and 1.30, respectively), and suicide attempts (RRs of 8.50, 5.26, and 3.42, respectively). Risks remained elevated in validation and subgroup analyses. Suicide attempts were particularly high among those with preexisting depression (suicide attempt rate at 1 year, 0.24%). Mental health risks were highest within the first year after diagnosis and declined over time but remained significantly elevated. Conclusions: Blindness in older adults is associated with significantly increased risks of depression, anxiety, and suicide, especially within the first year of diagnosis. These findings suggest the need for mental health screening and early psychosocial intervention in newly blind patients to mitigate long-term psychiatric morbidity.

ABSTRACT Background People who inject drugs (PWID) experience a high burden of common mental disorders, often compounded by social marginalization, housing instability, and stigma in healthcare settings. This study assessed depressive symptomatology and anxiety among PWID engaged in methadone maintenance services in Albania during 2021. Methods A cross-sectional survey was conducted over six months (2021) in collaboration with the Albanian Institute of Public Health, Aksion+,and the Stop AIDS organization. Convenience sampling was conducted at service sites and through outreach staff who facilitated access to eligible clients. Measures included a structured sociodemographic/socioeconomic questionnaire and two screening measures: the Patient Health Questionnaire-9 and the Beck Anxiety Inventory. Results The analytic sample comprised N = 180. Participants were predominantly male (86%) with a mean age of 31 years. Moderate-to-severe depressive symptoms were observed in 50% of participants; 30% had moderate symptoms, and 20% had mild symptoms. Anxiety levels were high overall (70% moderate anxiety; 20% high anxiety). Conclusions PWID engaged in methadone maintenance services in Albania exhibited high levels of depressive symptomatology and anxiety, alongside substantial social vulnerability. Integrated mental health screening and referral pathways within harm-reduction services may help address the mental health burden and related barriers to care.

Comorbid psychological distress (anxiety and depression) in inflammatory bowel disease (IBD) is common and associated with poorer outcomes and increased healthcare burden. Scalable and accessible integrated care is needed. This study examined the feasibility of implementing routine digital mental health screening and digital cognitive-behavioral therapy (COMPASS-IBD) for psychological distress in a large IBD service. During implementation, distress was identified by screening or IBD clinician referral. Further triage determined eligibility to receive COMPASS-IBD with trainee therapist support (12 weeks). Pre- and post-intervention outcomes examined reach, acceptability, implementation, and potential effectiveness of the new pathway. Screening was completed by 827 patients (from November 2022 to September 2023), with 196 patients meeting clinical cutoffs and referred for IBD psychology triage. An additional 82 patients were directly referred via IBD clinicians. Of 91 eligible patients, 65 (71.4%) were enrolled into COMPASS-IBD. Distress significantly reduced post-intervention (Patient Health Questionnaire Anxiety and Depression Scale = -6.203; 95% confidence interval, -8.76 to -3.64; P < .001; Cohen's d = -0.553). Symptoms of anxiety, depression, and IBD-related quality of life significantly improved, but IBD symptomatology did not. Full adherence (≥5 online and ≥3 therapist sessions) to COMPASS-IBD was completed by 32.3% of patients. After initially increasing, the IBD psychology waitlist decreased in wait time (30.8%) and number (63.4%) by the end of study implementation. Patients were accepting of the new treatment pathway. Routine mental health screening and COMPASS-IBD were successfully implemented in an outpatient IBD service, but support from trainee psychologists and the research team was required. This new integrated pathway can identify and treat psychological distress in IBD with minimal service resource.