Self-report Screening Tool Research Articles

The Prevalence of Autistic Traits in a Sample of Young Adults Referred to a Generalized Mental Health Outpatient Clinic.

The diagnosis of Autism Spectrum Disorders (ASD) is undergoing significant revisions, impacting prevalence estimates in the general population. Moreover, the rise of a dimensional perspective on psychopathology has broadened our understanding of autism, recognizing that subthreshold autistic features extend throughout the general population. However, there remains a limited understanding of the prevalence of ASD traits in individuals with psychiatric disorders, particularly in young adults, who are at an age where several mental health conditions emerge. The aim of this study was to evaluate the prevalence of ASD traits in a sample of young adults (18-24 years old) attending a generalized mental health outpatient clinic. A total of 259 young adult patients completed the self-report screening questionnaires Autism Quotient (AQ) and Ritvo Autism and Asperger Diagnostic Scale-Revised (RAADS-R). A total of 16.2% of our sample scored above the cut-off in both scales; this percentage decreased to 13.13% when restricting the RAADS-R cut-off to >119, as suggested for clinical samples. The association with sociodemographic features is discussed. We argue that screening for autistic traits should be integrated into the assessment of young adults presenting with nonspecific psychiatric symptoms or psychological distress. Although there is ongoing debate over the use of self-report screening tools, a positive result on both the AQ and RAADS-R should prompt clinicians to pursue a comprehensive diagnostic evaluation using structured or semi-structured interviews.

Prevalence and predictors of fibromyalgia among Egyptian physicians: a cross-sectional study

BackgroundFibromyalgia is a chronic, disabling disorder of widespread musculoskeletal pain. It is generally considered a stress-related syndrome. Healthcare workers are prone to mental and physical stress due to due to excessive work burdens, long working hours, and a lack of balance between work and social life.ObjectiveThe aim of this study was to examine the prevalence of fibromyalgia and its predictors among Egyptian physicians.MethodsSix hundred and ninety-one Egyptian physicians completed an online survey which included a self-reported fibromyalgia rapid screening tool (FiRST) as well as demographic (sex and age), health-related (chronic illnesses if any), and employment data (workday length, specialty, and employer). Logistic regression was performed to explore possible predictors of fibromyalgia.ResultsFibromyalgia was observed in 13.2% of participants, with a female to male ratio of 3.8:1. Predictors of FM in this cohort included the following: female sex (odds ratio (OR) 2.2, 95% confidence interval (CI) 1.2–3.9, p = 0.014), age 41–50 years (OR 3.8, 95% CI 1.5–9.6, p = 0.005), concomitant chronic illness: endocrinopathies (other than diabetes mellitus) (OR 2.69, 95% CI 1.09–6.64, p = 0.035), musculoskeletal disorders (OR 5.60, 95% CI 2.96–10.6, p < 0.001), autoimmune disorders (OR 3.61, 95% CI 1.69–7.73, p = 0.002), employment at a Ministry of Health Healthcare Facility (OR 1.8, 95% CI 1.1–3.1, p = 0.013), and a workday length of ≥ 13 h (OR 2.4, 95% CI 1.1–5.3, p = 0.038). Physicians in surgical specialties were less likely to suffer from FM (OR 0.47, 95% CI 0.24–0.94, p = 0.033).ConclusionEgyptian physicians have higher fibromyalgia prevalence than the general population. Demographic, health-related, and professional predictors of FM were identified in this cohort.

Diagnostic Accuracy of Mental Health Screening Tools After Mild Traumatic Brain Injury.

Mental health disorders are common after mild traumatic brain injury (mTBI) and likely exacerbate postconcussive symptoms and disability. Early detection could improve clinical outcomes, but the accuracy of mental health screening tools in this population has not been well established. To determine the diagnostic accuracy of the Patient Health Questionnaire-9 (PHQ-9), Generalizaed Anxiety Disorder-7 (GAD-7), and Primary Care PTSD (Posttramatic Stress Disorder) Screen for Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) (DSM-5) (PC-PTSD-5) in adults with mTBI. This diagnostic study was performed as a secondary analysis of a cluster randomized clinical trial. Self-report mental health screening tools (PHQ-9, GAD-7, and PC-PTSD-5) were administered online 12 weeks after mTBI and compared against a structured psychodiagnostic interview (Mini-International Neuropsychiatric Interview for DSM-5 (MINI) over videoconference at the same time. Adults with mTBI (N = 537) were recruited from February 1, 2021, to October 25, 2022. Presence of a major depressive episode, anxiety disorders, and PTSD were determined by a blinded assessor with the MINI. Diagnostic accuracy statistics were derived for the PHQ-9, GAD-7, and PC-PTSD-5. Findings were disaggregated for participants with and without persistent postconcussion symptoms (PPCS) by International and Statistical Classification of Diseases, Tenth Revision criteria. Data were available for 499 of 537 trial participants, 278 (55.7%) of whom were female; the mean (SD) age was 38.8 (13.9) years. Each screening questionnaire had strong diagnostic accuracy in the overall sample for optimal cut points (area under the curve [AUC], ≥0.80; sensitivity, 0.55-0.94; specificity, 0.64-0.94). The AUC (difference of 0.01-0.13) and specificity (difference, 5-65 percentage points) were lower in those with PPCS present compared with PPCS absent, but the prevalence of at least 1 mental health disorder was 3 to 5 times higher in patients with PPCS present. The GAD-7 had slightly better performance than the PC-PTSD-5 for detecting PTSD (AUC, 0.85 [95% CI, 0.80-0.89] vs 0.80 [95% CI, 0.72-0.87]). The optimal cutoff on the PHQ-9 was 5 or more symptoms experienced on more than half of days; on the GAD-7, a total score of at least 7. The findings of this diagnostic study suggest that the PHQ-9, GAD-7 and PC-PTSD-5 accurately screen for mental health disorders in patients with mTBI. Future research should corroborate optimal test cutoffs for this population.

Evaluation of a self-reported G8 screening tool on Epic MyChart for older patients with cancer.

e13766 Background: The Geriatric 8 (G8) is a screening tool validated for cancer patients to identify those in need of a comprehensive geriatric assessment (CGA). It evaluates eight domains encompassing mobility, polypharmacy, age, and self-rated health. The existing original-G8 requires administration by a healthcare professional, limiting its accessibility and practicality. An electronic, patient-reported version could broaden its reach, enhancing care coordination. This study focuses on the implementation and evaluation of a self-reported G8 tool on Epic MyChart and its alignment with the original-G8. Methods: The MyChart-G8 underwent adaptation from the original-G8, retaining all domains while optimizing questions for patient self-completion and adhering to health communication design principles. We introduced MyChart-G8 across our Jefferson health system for all patients aged ≥ 65 with a new cancer diagnosis. For a subset of patients, an oncology nurse or medical assistant also administered the original G8 during the new patient visit rooming process. Agreement between MyChart-G8 and original-G8 for individual items was measured using Kappa statistics. Diagnostic accuracy of MyChart-G8 compared to the original-G8 was also assessed. Results: Our cohort comprised 203 older cancer patients who completed both MyChart-G8 and the original-G8. The frequency of abnormal scores (≤14) for the original-G8 and MyChart-G8 was 40.0% and 67.7%, respectively. Discrepancies between the two tools were partly attributed to less than moderate agreement for three individual items: neuropsychological problems (Kappa 0.15), BMI (Kappa 0.27), and self-rated health (Kappa 0.31). A MyChart-G8 cutoff of 14.5 demonstrated the best balance of sensitivity (0.86 ± 0.13) and specificity (0.57 ± 0.06) when compared to the original G8. Conclusions: The incorporation of self-reported G8 assessments into Epic MyChart is feasible and implementable. Persistent challenges arise in accurately assessing self-reported problems among older adult cancer patients in the electronic format, potentially resulting in MyChart over-flagging abnormalities. The introduction of the Practical Geriatric Assessment (PGA) presents an opportunity to streamline the CGA. By subsequently conducting a PGA for individuals identified as vulnerable through the MyChart G8, we can confirm frailty domains, inform treatment decisions, and address impairments through targeted interventions. This integrated, stepped-up assessment approach holds significant potential to optimize resource utilization, enhance patient engagement, and tailor individualized treatments, ultimately with the goal of maximizing treatment outcomes. The Sidney Kimmel Cancer Center is in the process of developing a decentralized model of PGA using MyChart G8 as a step-up approach across the Jefferson Health enterprise.

Trouble with the curve: the 90-9-1 rule to measure volitional participation inequalities among Royal Canadian Mounted Police cadets during training.

The Royal Canadian Mounted Police (RCMP) Study includes longitudinal multimodal assessments of RCMP cadets from pre-training (i.e., starting the Cadet Training Program [CTP]) to post-deployment and for five years thereafter. The data allow for investigating the multidimensionality of volitional participation in digital health data collection frameworks within serial data collection platforms and the impact of participation inequalities by classifying cadets using the 90-9-1 rule. By classifying cadets as Lurkers, Contributors, and Superusers formally described by the 90-9-1 rule, where 90% of actors do not participate, 9% seldom contribute, and 1% contribute substantially allows for the assessing of relationships between participation inequalities in self-monitoring behaviors as well as whether mental health disorder symptoms at pre-training (i.e., starting the CTP) were associated with subsequent participation. Participants were asked to complete a Full Assessment prior to their training at CTP, as well as short daily surveys throughout their training. Participation frequency was described using a process where participants were rank ordered by the number of daily surveys completed and classified into one of three categories. Full assessment surveys completed prior to their training at CTP included screening tools for generalized anxiety disorder (GAD), major depressive disorder (MDD), posttraumatic stress disorder (PTSD), alcohol use disorder (AUD), and panic disorder (PD). The Kruskal-Wallis H test was used to assess differences in participation rates between mental health disorder symptom screening groups for each measure at pre-training, and Spearman's Rho was used to test for associations amongst self-reported Full Assessment screening tool responses and the number of daily surveys completed during CTP. There were 18557 daily survey records collected from 772 participants. The rank-ordering of cadets by the number of daily surveys completed produced three categories in line with the 90-9-1 rule: Superusers who were the top 1% of cadets (n=8) and produced 6.4% of all recordings; Contributors who were the next 9% of cadets (n=68) and produced 49.2% of the recordings; and Lurkers who were the next 90% of cadets (n=695) and produced 44.4% of daily survey recordings. Lurkers had the largest proportion of positive screens for self-reported mental health disorders at pre-training. The creation of highly individualized, population-based mental health injury programs has been limited by an incomplete understanding of the causal relationships between protective factors and mental health. Disproportionate rates of disengagement from persons who screen positive for mental health disorders further compounds the difficulty in understanding the relationships between training programs and mental health. The current results suggest persons with mental health challenges may be less likely to engage in some forms of proactive mental health training. The current results also provide useful information about participation, adherence, and engagement that can be used to inform evidence-based paradigm shifts in health-related data collection in occupational populations.

Development of a self-report screening instrument for emotional dysregulation: the Reactivity, Intensity, Polarity and Stability questionnaire, screening version (RIPoSt-SV)

BackgroundEmotional dysregulation (ED) refers to the inability to manage emotional experiences or expressions hindering goal-oriented behavior. Moderate impairment on at least two domains among temper control, affective lability, and emotional over-reactivity has been proposed to identify ED in adults with attention-deficit/hyperactivity disorder (ADHD). No screening measure designed for use in diverse psychiatric samples exists. We aimed to develop a self-report screening tool for ED based on the 40-item version of the Reactivity, Intensity, Polarity, and Stability questionnaire (RIPoSt-40). Methods150 adult outpatients with non-psychotic conditions were enrolled between February and July 2023 at the Second Psychiatry Unit of Pisa University Hospital. Clinically significant ED (CSED) was defined based on the previously suggested approach for ADHD. Differences between patients with and without CSED were tested. To develop our screening instrument, a decision tree algorithm was trained by hyperparameter tuning through 5-fold cross-validation in 120 subjects and tested on the remaining 30. Results75 subjects met criteria for CSED (50 %). CSED was associated with lower age and higher prevalence of psychiatric conditions, including minor mood disorders, ADHD, cannabis use disorders, and eating disorders. We identified a decision tree consisting of six items from RIPoSt-40 that effectively detected CSED, with accuracy, sensitivity, specificity, positive and negative predictive values of 80 % or higher in both the training and testing sets. LimitationsTertiary-level; no consensus on criteria; sample size. ConclusionThe screening version of the Reactivity, Intensity, Polarity, and Stability questionnaire (RIPoSt-SV) demonstrates promise as a valuable tool for ED screening in clinical settings.

Autism Spectrum Disorders traits in a sample of young adults referring to a generalized mental health outpatient clinic

IntroductionThe diagnosis of Autism Spectrum Disorders is currently witnessing several changes, with direct consequences on the prevalence rates in the general population. However, little is known about ASD traits prevalence in clinical samples, and how much these traits interact with other mental health conditions, especially in young adults, a critical age for the outbreak of many psychiatric diseases.ObjectivesThe aim of this study was to assess the prevalence of ASD traits in a sample of young adults (aged between 18 and 24 years old) referring to a specialized mental health outpatient clinic.MethodsWe administered to 259 patients the Autism Quotient (AQ) and the Ritvo Autism and Asperger Diagnostic Scale-Revised (RAADS‐R), along with a detailed sociodemographic and anamnestic interview.ResultsWe found that 16.2% of our sample scored above the cut-off at both scales (a percentage that went down to 13.13% when restricting the RAADS-R cut-off at &gt;119, as suggested for clinical samples).Conclusions This prevalence seems considerably higher than the one reported in the general population, and not negligible. The association with sociodemographic features such as sex assigned at birth, gender identity and employment status, and the validity of the screening tools we implemented, are discussed. In conclusion, we suggest that an assessment for autistic traits should be implemented in young adults seeking help for unspecified psychiatric symptoms and psychological suffering and that, despite the not unanimous consensus over self-report screening tools, a positivity to both the AQ and the RAADS-R should lead the clinician to conduct a full diagnostic evaluation with structured or semi-structured interviews.Disclosure of InterestNone Declared

The relationship between the Hopkins symptom checklist-10 and diagnoses of anxiety and depression among inpatients with substance use disorders

Introduction The Hopkins Symptom Checklist-10 (HSCL-10) is a self-report inventory of anxiety and depression symptoms that may assist clinicians in screening for clinical conditions among patients with substance use disorder (SUD). We examined the HSCL-10 as a screening tool for anxiety and depressive disorders within a general population of SUD inpatients. Methods We used data from a cohort study of 611 SUD inpatients. Receiver operating characteristic (ROC) analyses were conducted, with and without covariates, to evaluate the potential of the HSCL-10 as a screening tool. This was explored using any anxiety disorder, especially posttraumatic stress disorder (PTSD), and any mood disorder, especially major depressive disorders, as the outcome criteria. Candidate covariates included gender, age, education, polydrug use and treatment center. Results: The HSCL-10 had a moderate ability to identify caseness (i.e. having or not having a clinical diagnosis) according to each outcome criterion, with the area under the ROC curve (AUC) varying from 0.64 to 0.66. Adding relevant covariates markedly enhanced the instrument’s ability to identify those who met the criteria for any anxiety disorder (AUC = 0.77), especially PTSD (AUC = 0.82). Conclusion In a real-world clinical setting, the HSCL-10 has fair-to-good clinical utility for identifying SUD inpatients who have comorbid clinical symptoms of anxiety disorders or PTSD, when combined with common background variables. The HSCL-10, a brief self-report screening tool, may serve as an efficient proxy for comprehensive interviews used in research and for clinical anxiety symptom screening among patients with SUD.

Sleep disorders and associated factors among medical students in the Middle East and North Africa: a systematic review and meta-analysis

Sleep disturbances like poor and insufficient sleep are common among medical students in the Middle East and North Africa (MENA) countries; however, the extent of medically defined sleep disorders (SDs) remains unclear. This meta-analysis determines SD prevalence and identifies associated factors among medical students in the MENA. PubMed, Web of Science, Google Scholar, and reference lists of included studies were searched (latest search: June 2022). Meta-analyses included 22 studies and were performed using random-effect models. Included studies used self-reported screening tools for assessing SDs and then estimated the proportion of participants at high risk of developing a SD. Central disorders of hypersomnolence were the most prevalent SD [prevalencepooled range: 30.9% (Jordan) to 62.5% (Saudi Arabia)], followed by insomnia disorders [prevalencepooled range: 30.4% (Jordan) to 59.1% (Morocco)], circadian rhythm sleep–wake disorders [prevalencepooled range: 13.5% (Jordan) to 22.4% (Saudi Arabia)], sleep-related breathing disorders [prevalencepooled range: 12.2% (Jordan) to 22.5% (Pakistan)], sleep-related movement disorders [prevalencepooled range: 5.9% (Egypt) to 30.6% (Saudi Arabia)], and parasomnias [prevalencepooled range: 5.6% (Jordan) to 17.4% (Saudi Arabia)]. Female sex, studying in the latter academic years, having anxiety, excessive internet use, and poor academic performance were significantly associated with SDs. SDs are prevalent among MENA medical students. Implementing student-centered interventions targeting high risk groups in medical schools should be considered to improve students’ health and wellbeing.

Preliminary identification of clinical cut-off of the vegetarian vegan eating disorder screener (V-EDS) in a community and self-reported clinical sample of vegetarians and vegans

BackgroundThe vegetarian vegan eating disorder screener (V-EDS) is an 18-item self-report screening tool designed to assess the unique elements of eating disorder symptomology in vegetarians and vegans. Previous results have suggested strong initial psychometric properties in non-clinical community samples of vegetarians and vegans. The present study sought to identify a preliminary threshold cut-off score to discriminate eating disorder pathology in a self-reported clinical and community sample.MethodsThis study involved secondary analysis using data collected in McLean et al. (Development and preliminary validation of a novel eating disorder screening tool for vegetarians and vegans: the V-EDS, 2023), comprising 599 non-clinical participants and 51 self-reported clinical participants. Receiver operating characteristic (ROC) curve analysis was used to compute possible cut-off values for the V-EDS. Results: ROC analysis indicated good performance of the V-EDS (area under the curve = 0.87), with integration of the Youden index demonstrating a global score of ≥ 18 to be optimal in predicting clinical caseness with good sensitivity (0.804) and specificity (0.843).ConclusionsThe present study fills an important gap as the first to investigate an optimal V-EDS score to discriminate level of impairment from eating disorder pathology in a sample of vegetarian and vegan community and self-reported clinical participants. We extend the utility of the V-EDS in discovering good discrimination power in classifying clinical caseness with a cut-off score of 18 shown to optimise the trade-off between sensitivity and specificity. Future research should focus on expanding the psychometric properties of the V-EDS in larger and more diverse participant groups, including gender, age, cultural identity, and eating disorder history.

Addressing the elephant in the screening room: an item response theory analysis of the Prodromal Questionnaire (PQ-16) for at-risk symptoms of psychosis.

Within the context of patients at-risk of psychosis, where a variety of symptoms are present, identifying the most discriminative symptoms is essential for efficient detection and management. This cross-sectional online study analyzed individuals from the general population in order to better assess their risk of presenting symptoms belonging to the clinical high risk (CHR) for psychosis, called "CHR-related symptoms". The Prodromal Questionnaire-16 (PQ-16) served as a self-report screening tool. Item response theory (IRT) with a graded response model was used to assess the discrimination and difficulty of its criteria. The analysis included 936 participants (mean age: 21.5 years; 28.1% male, 71.9% female). "Déjà vu" stood out for its high discriminative power, while "Voices or whispers" and "Seen things" demonstrated strong precision relatively to the other CHR-related symptoms. Conversely, "Smell or taste" and "Changing face" were associated with the most severe cases relatively to the other CHR-related symptoms. This study identified the most indicative CHR-related symptoms to emphasize their significance in accurately assessing severity and guiding targeted preventative interventions.

A digital self-reported G8 screening tool: A comparison study

Background Geriatric assessment (GA) has been shown to be pivotal to the prognosis of elderly cancer patients. A G8 screening tool could act as a potential surrogate to identify patients who would benefit from further GA in a busy oncology clinic and a digital version would allow for a wider application. Objectives To develop a digital self-reported version of G8, and to compare its outcomes with in-person G8 administered by a healthcare professional. Methods A total of 483 cancer patients aged 70 years and older who received an in-person G8 assessment at the National Cancer Centre Singapore (NCCS) clinic, and another 544 who completed the digital self-reported G8 were analysed. Total G8 score ≤14 was defined as positive screen. Results Response rate of the digital self-reported G8 was 50%. Median G8 total score was lower among online screeners than in-person screeners (11 vs 12.5, p &lt; 0.001). The odds of a G8 positive screen among online screeners was higher than that of in-person screeners on multivariable logistic regression analysis (odds ratio = 1.56, 95% CI 1.08-2.26). Some 20 in-person screeners had also completed the digital self-reported G8, and the agreement between their in-person and online G8 total scores was high (concordance correlation coefficient = 0.798, 95% CI 0.635-0.962). Conclusions A digital self-reported G8 is feasible. However, given the higher positive screen rate among the online screeners, replacement of the in-person G8 with the digital self-reported G8 should be implemented only after more conclusive evidence on the agreement between in-person and online G8 score is available.

Enhancing Provider Mental Health Screening in Primary Care: A Quality Improvement Project.

Background: Depression and anxiety occur in 7.8% and 19.1% of the US population, respectively. About half of those patients are diagnosed in primary care. Objective: The purpose of this quality improvement project was to improve the screening and diagnosing of anxiety and/or depression among adult patients at a primary care clinic by implementing an evidence-based mental health screening interview technique. Methods: The team implemented a mental health screening interview technique that incorporates background, affect, trouble, handling, and empathy and motivational interviewing techniques in addition to self-report surveys. Pre- and post-intervention surveys were conducted to assess providers' perceptions of the new interview technique. ICD-10 code data were gathered to assess the effectiveness of the new mental health screening interview technique. Results: The number of documented diagnoses of single-episode major depressive disorder decreased by 18%, recurrent major depressive disorder increased by 34%, and anxiety disorders increased by 3%. There were more favorable provider perceptions of the new screening interview technique versus the traditional screening method. Conclusions: The results show an improvement in provider comfort and providers preferred the new mental health screening when using an evidence-based mental health screening interview technique. Implications for nursing: The results show the potential benefits of using a structured mental health interview with self-report screening tools when diagnosing anxiety and depression in primary care.

Enhancing Provider Mental Health Screening in Primary Care: A Quality Improvement Project.

Background: Depression and anxiety occur in 7.8% and 19.1% of the US population, respectively. About half of those patients are diagnosed in primary care. Objective: The purpose of this quality improvement project was to improve the screening and diagnosing of anxiety and/or depression among adult patients at a primary care clinic by implementing an evidence-based mental health screening interview technique. Methods: The team implemented a mental health screening interview technique that incorporates background, affect, trouble, handling, and empathy and motivational interviewing techniques in addition to self-report surveys. Pre- and post-intervention surveys were conducted to assess providers' perceptions of the new interview technique. ICD-10 code data were gathered to assess the effectiveness of the new mental health screening interview technique. Results: The number of documented diagnoses of single-episode major depressive disorder decreased by 18%, recurrent major depressive disorder increased by 34%, and anxiety disorders increased by 3%. There were more favorable provider perceptions of the new screening interview technique versus the traditional screening method. Conclusions: The results show an improvement in provider comfort and providers preferred the new mental health screening when using an evidence-based mental health screening interview technique. Implications for nursing: The results show the potential benefits of using a structured mental health interview with self-report screening tools when diagnosing anxiety and depression in primary care.

Validation and Clinical Utility of the Patient Health Questionnaire-9 and Center for Epidemiologic Studies Depression Scale as Depression Screening Tools in Collegiate Student-Athletes.

The National Athletic Trainers' Association recommends including mental health screening measures as part of the preparticipation examination for all student-athletes (SAs). Despite this recommendation, most mental health screening tools have not been validated in the SA population. To validate and examine the clinical utility of 2 depression screening tools in the collegiate SA population. Cross-sectional mixed-methods study. Two Northeastern United States university athletics programs. A total of 881 (men = 426, 48.4%; women = 455, 51.6%; mean age = 19.7 ± 1.4 years) National Collegiate Athletic Association Division II collegiate SAs completed the Patient Health Questionnaire-9 (PHQ-9) and Center for Epidemiologic Studies Depression Scale (CES-D); 290 SAs participated in a Mini-International Neuropsychiatric Interview. Depression symptoms were measured using 2 self-report depression screening tools, the PHQ-9 and CES-D, during the fall preparticipation examination. The SAs were selected using a random stratified sampling technique to participate in a Mini-International Neuropsychiatric Interview as the reference standard comparison for the receiver operating characteristic analysis. A cutoff score of 6 on the PHQ-9 corresponded to 78% sensitivity, 75% specificity, 17.3% positive predictive value, 98.1% negative predictive value (NPV), 3.2 positive likelihood ratio (+LR), and 0.3 negative likelihood ratio (-LR). A cutoff score of 15 on the CES-D corresponded to 83% sensitivity, 78% specificity, 19.7% positive predictive value, 98.6% NPV, 3.7 +LR, and 0.22 -LR. This was the first study to validate depression screening tools in the collegiate SA population. The results suggest cutoff scores on the PHQ-9 and CES-D in SA may need to be lower than those recommended for the general population and provide strong evidence for use as screeners to rule out depression. Referral and confirmatory testing should be implemented to confirm the presence of depression for SAs scoring at or above the cutoff thresholds. Given its brevity, inclusion of a suicidality or self-harm question and evidence of -LR and NPV strength, the PHQ-9 is a practical and effective screener for the SA population.

Prediction of depression onset risk among middle-aged and elderly adults using machine learning and Canadian Longitudinal Study on Aging cohort

BackgroundEarly identification of the middle-aged and elderly people with high risk of developing depression disorder in the future and the full characterization of the associated risk factors are crucial for early interventions to prevent depression among the aging population. MethodsCanadian Longitudinal Study on Aging (CLSA) has collected comprehensive information, including psychological scales and other non-psychological measures, i.e., socioeconomic, environmental, health, lifestyle, cognitive function, personality, about its participants (30,097 subjects aged from 45 to 85) at baseline phase in 2012–2015. We applied machine learning models for the prediction of these participants' risk of depression onset approximately three years later using information collected at baseline phase. ResultsIndividual-level risk for future depression onset among CLSA participants can be accurately predicted, with an area under receiver operating characteristic curve (AUC) 0.791 ± 0.016, using all baseline information. We also found the 10-item Center for Epidemiological Studies Depression Scale coupled with age and sex information could achieve similar performance (AUC 0.764 ± 0.016). Furthermore, we identified existing subthreshold depression symptoms, emotional instability, low levels of life satisfaction, perceived health, and social support, and nutrition risk as the most important predictors for depression onset independent from psychological scales. LimitationsDepression was based on self-reported doctor diagnosis and depression screening tool. ConclusionsThe identified risk factors will further improve our understanding of the depression onset among middle-aged and elderly population and the early identification of high-risk subjects is the first step for successful early interventions.

Exploring the relationship between food disgust and avoidant/restrictive food intake disorder (ARFID) presentations in a non-clinical collegiate sample.

Disgust is an established mechanism driving restrictive eating behavior. Avoidant/restrictive food intake disorder (ARFID) is a restrictive eating disorder diagnosis characterized by extremely selective eating with three hypothesized presentations. It has been suggested that disgust is significantly associated with ARFID; however, there is limited empirical research to support this hypothesis. This study explores relationships between food-specific disgust, ARFID symptoms, and ARFID presentations. Undergraduate students (n = 443, Mage = 19.14 years [SD = 1.25], 50.1% female, 52.7% White) completed a validated measure of food-specific disgust and an established self-report screening tool for the likely presence of ARFID and hypothesized ARFID presentations. Sixty-nine (14.5%) participants screened positively for the likely presence of ARFID. Food disgust did not differ between those who did and did not screen positively for ARFID (p > .05). Within the subsample of those screening positive for ARFID, disgust was not related to any of the three hypothesized presentations of ARFID (all p > .05). Our results did not show a significant association between disgust and positive ARFID screen or any of the hypothesized ARFID presentations. Importantly, these negative findings were obtained using validated screening tools for ARFID. Future research should seek to replicate these findings in clinical samples to further inform treatment. Avoidant/restrictive food intake disorder (ARFID) is associated with significant medical and psychosocial complications, but the mechanism involved in its development and maintenance remain poorly understood. Findings from this study of college students screening positively for ARFID suggests that food disgust in not a key driver of ARFID symptoms. Exposure-based approaches, which are generally not thought to be effective in targeting disgust, may thus be appropriate in the treatment of ARFID.

Abstract P242: Accuracy of a Self-Report Screening Tool for Identifying Pregnant People With High Sedentary Behavior

Introduction: High levels of sedentary behavior (SB) are emerging as a distinct risk factor in pregnancy for poor maternal-fetal health outcomes. Thigh-worn accelerometry is ideal for quantifying SB but has high cost and participant burden; simple screening questions that could quickly identify those with high SB in clinical or research settings are desirable. We aimed to evaluate the accuracy of self-report screening questions for identifying pregnant participants with high SB. Methods: This secondary analysis used baseline data from the S edentary Behavior Reduction in Pr egnancy In tervention (SPRING) feasibility trial. During eligibility screening, participants in their first trimester met at least one of four study-developed, self-reported criteria that put them at risk for high SB: 1) mostly sitting job ≥ 30 h/week; 2) mostly sitting job &lt;30 h/week and reporting sitting ≥ ½ of non-work time; 3) did not work but reported sitting ≥ ¾ of time; and 4) &lt;6,000 steps/d from a wearable device. Eligible participants then underwent baseline SB assessment using a thigh-worn accelerometer (activPAL3, 7 d x 24 h). The proportion of participants meeting evidence-based definitions for high SB were calculated for each criterion. Definitions of high SB included: SB &gt; 10 h/d (+10h), SB &gt; 66.7% of waking time (+66.7%), and &lt; 6,000 steps per day (low steps). Results: Participants (n=51) enrolled in the study with mean (SD) age=32 (4) years, 82% White, and 84% with a college degree or greater. Of these, n=50 had valid objective SB data at baseline. On average, participants met high SB definitions with mean (SD) SB of 10.5 (1.5) hours per day, 77% (11%) of waking time in SB, and with 5,646 (2,954) steps per day. Among those with a mostly sitting job ≥ 30 h/week (n=33), 66% were above the +10h definition, 71% met the +66.7% definition, and 57% met the low steps definition. For participants with a mostly sitting but &lt;30 h/week job (n=7) and high sitting otherwise, 57% met the +10h definition, 100% met the +66.7% definition, and 71% met the low steps definition. Participants who did not work and reported ¾ time in SB (n=5) met each definition 80% of the time. Participants who reported &lt;6000 steps per day from a wearable (n=3) met all definitions 66.7% of the time. Those below the +10h SB threshold had mean (range) SB of 8.7 (7.5 to 9.4) h/d, those below the +67% SB threshold were sedentary 57.9% (51.1% to 61.3%) of the time, and those above the low steps threshold had 9,478 (6023 to 14,751) steps per day. Conclusions: Screening questions mostly identified participants who were highly sedentary, though approximately one in three did not meet thresholds for objectively-measured high SB. Future research refining screening questions is needed to improve the accuracy of identifying pregnant people with high SB by self-report, who may be at higher risk of adverse pregnancy outcomes.

Prevalence estimates of major depressive disorder in 27 European countries from the European Health Interview Survey: accounting for imperfect diagnostic accuracy of the PHQ-8

BackgroundCut-offs on self-report depression screening tools are designed to identify many more people than those who meet criteria for major depressive disorder. In a recent analysis of the European Health...

Approaches to the identification and management of depression in people living with chronic kidney disease: A scoping review of 860 papers.

Depression is prevalent across the spectrum of Chronic Kidney Disease and associated with poorer outcomes. There is limited evidence regarding the most effective interventions and care pathways for depression in Chronic Kidney Disease. To investigate how depression is identified and managed in adults with Chronic Kidney Disease. Scoping review. Systematic search of eight databases with pre-defined inclusion criteria. Data relevant to the identification and/or management of depression in adults with Chronic Kidney Disease were extracted. Of 2147 articles identified, 860 were included. Depression was most identified using self-report screening tools (n = 716 studies, 85.3%), with versions of the Beck Depression Inventory (n = 283, 33.7%) being the most common. A total of 123 studies included data on the management of depression, with nonpharmacological interventions being more frequently studied (n = 55, 45%). Cognitive Behavioural Therapy (n = 15) was the most common nonpharmacological intervention, which was found to have a significant effect on depressive symptoms compared to controls (n = 10). However, how such approaches could be implemented as part of routine care was not clear. There was limited evidence for antidepressants use in people with Chronic Kidney Disease albeit in a limited number of studies. Depression is commonly identified using validated screening tools albeit differences exist in reporting practices. Evidence regarding the management of depression is mixed and requires better-quality trials of both pharmacological and nonpharmacological approaches. Understanding which clinical care pathways are used and their evidence, may help facilitate the development of kidney care specific guidelines for the identification and management of depression.