Amplifying Their Voice: Inclusive Healthcare Provider Perspectives to Improve Advancement, Resilience, and Retention.

BACKGROUND AND OBJECTIVES:  Addressing the issues of workplace advancement, resilience, and retention within medicine is crucial for creating a culture of equity, respect, and inclusivity especially towards women and nonbinary (WNB) providers including advanced practice providers (APPs), most notably those from marginalized groups. This also directly impacts healthcare quality, patient outcomes, and overall patient and employee satisfaction. The purpose of this study was to amplify the voices on challenges faced by WNB providers within a pediatric academic healthcare organization, to rank workplace interventions addressing advancement, resilience, and retention highlighting urgency towards addressing these issues, and, lastly, to provide suggestions on how to improve inclusivity. METHODS:  Participants were self-identified WNB providers employed by a pediatric healthcare organization and its affiliated medical university. An eligibility screener was completed by 150 qualified respondents, and 40 WNBs actually participated in study interviews. Interviews were conducted using a semi-structured interview guide to rank interventions targeted at improving equity, with time allotted for interviewees to discuss their personal lives and how individual circumstances impacted their professional experiences. RESULTS:  WNB providers called for efficient workflows and reducing uncompensated job demands. Support for family responsibilities, flexible financial/compensation models, and improved job resources all were endorsed similarly. Participants ranked direct supervisor and leader support substantially lower than other interventions.  Conclusions: Career mentorship and academic support for WNB individuals are recognized interventions for advancement and retention but were not ranked as top priorities. Respondents focused on personal supports as they relate to family, job resources, and flexible compensation models. Future studies should focus on implementing realistic expectations and structures that support whole lives including professional ambitions, time with family, personal pursuits, and self-care.

Proceedings of the 1st biannual bridging the gaps in lung cancer conference.

Lung cancer is the leading cause of cancer death in the US and globally. The mortality from lung cancer has been declining, due to a reduction in incidence and advances in treatment. Although recent success in developing targeted and immunotherapies for lung cancer has benefitted patients, it has also expanded the complexity of potential treatment options for health care providers. To aid in reducing such complexity, experts in oncology convened a conference (Bridging the Gaps in Lung Cancer) to identify current knowledge gaps and controversies in the diagnosis, treatment, and outcomes of various lung cancer scenarios, as described here. Such scenarios relate to biomarkers and testing in lung cancer, small cell lung cancer, EGFR mutations and targeted therapy in non-small cell lung cancer (NSCLC), early-stage NSCLC, KRAS/BRAF/MET and other genomic alterations in NSCLC, and immunotherapy in advanced NSCLC.

Accuracy assessment of ChatGPT responses to frequently asked questions regarding anterior cruciate ligament surgery.

BACKGROUND: The emergence of artificial intelligence (AI) has allowed users to have access to large sources of information in a chat-like manner. Thereby, we sought to evaluate ChatGPT-4 response's accuracy to the 10 patient most frequently asked questions (FAQs) regarding anterior cruciate ligament (ACL) surgery. METHODS: A list of the top 10 FAQs pertaining to ACL surgery was created after conducting a search through all Sports Medicine Fellowship Institutions listed on the Arthroscopy Association of North America (AANA) and American Orthopaedic Society of Sports Medicine (AOSSM) websites. A Likert scale was used to grade response accuracy by two sports medicine fellowship-trained surgeons. Cohen's kappa was used to assess inter-rater agreement. Reproducibility of the responses over time was also assessed. RESULTS: Five of the 10 responses received a 'completely accurate' grade by two-fellowship trained surgeons with three additional replies receiving a 'completely accurate' status by at least one. Moreover, inter-rater reliability accuracy assessment revealed a moderate agreement between fellowship-trained attending physicians (weighted kappa = 0.57, 95% confidence interval 0.15-0.99). Additionally, 80% of the responses were reproducible over time. CONCLUSION: ChatGPT can be considered an accurate additional tool to answer general patient questions regarding ACL surgery. None the less, patient-surgeon interaction should not be deferred and must continue to be the driving force for information retrieval. Thus, the general recommendation is to address any questions in the presence of a qualified specialist.

Faculty Perception of Scenario-Based MCQs, SAQs, and MEQs in Medical Education at an Apex Institute.

Purpose: This study explores the current knowledge and overall awareness of the faculty at an Apex institute about the use and difficulties of scenario-based multiple-choice questions (SB-MCQs), short-answer questions (SB-SAQs), and modified essay questions (SB-MEQs) in the assessment of the undergraduate and postgraduate students. Objectives: To assess faculty perception of awareness and use of SB-MCQs, SB-SAQs, and SB-MEQs and to understand the challenges encountered while designing scenario-based questions (SBQs) and the ways to overcome them. Study Procedure: The tool used for data collection was a Google form questionnaire designed with a total of 16 questions-12 Likert-scale format items and four open-ended questions. The quantitative data collected as a response to close-ended questions was analyzed by descriptive statistics and percentage values. For qualitative data, thematic analysis was done for open-ended questions. Conclusion: The study showed that the faculty has the motivation and agreeability to switch over from traditional questions to scenario-based questions but constant training in the form of regular faculty development programs and workshops is required for its effective implementation. On the administrative level, challenges like lack of sufficient faculty and proper inter-departmental integration for designing scenarios must be addressed. Supplementary Information: The online version contains supplementary material available at 10.1007/s40670-024-02052-6.

Assessing Health-Related Quality of Life in Children With Spina Bifida in Lithuania.

Introduction In recent years, more emphasis has been placed on improving the health-related quality of life (HRQOL) in children with spina bifida (SB). Chronic disability is understood to impact various aspects of the person's life, family, and social functioning, in addition to the specific needs of the disease. The HRQOL is done to assess the patient's quality of life (QOL) in various domains including physical and mental. Back in the 1900s, few children survived SB, whereas today, they almost have normal life expectancy. By understanding the contributing factors to the quality of life (QOL), more targeted interventions can be put in place in order to maximize the psychological and social well-being of these patients. Aim The aim of this study is to estimate the health-related quality of life (HRQOL) in Lithuanian children with spina bifida (SB) in relation to comorbidities, level of lesions, and mobility. Objectives The objectives of this study are to investigate the HRQOL of Lithuanian children with SB born between 1999 and 2012; to analyze the relation between the HRQOL and its comorbidities, including hydrocephalus, Chiari II malformation, incontinence, and epilepsy; and to determine the relationship of health variables, the level of lesions, and mobility to the HRQOL. Methods This was a quantitative cross-sectional study on children with spina bifida across Lithuania to assess the HRQOL. Subjects were chosen and interviewed from various cities including Kaunas, Vilnius, Marijampole, Gargzdai, Birzai, Panevezys, Palanga, and Alytus. A questionnaire was used as an instrument to measure the HRQOL. The level of lesions, comorbidities, and other health variables were obtained from the medical files and directly from the patient's history. Results Regarding the HRQOL, our study population showed the highest scores in the emotional, medical, intellectual, and social domains. The lowest sub-scores were in recreational, vocational, environmental, and then physical domains. We also found that certain comorbidities including hydrocephalus, epilepsy, and incontinence negatively affected the QOL. In our study group, we also found that the ambulatory group scored significantly higher in the overall QOL. However, when comparing the level of lesions to the HRQOL, we found no statistically significant difference. Conclusion Positive results were obtained regarding the medical, emotional, intellectual, and social aspects of patients with SB in Lithuania as they scored high in this domain. However, the environmental and vocational domains scored low, suggesting that further examination needs to be carried in these domains. We concluded that having various comorbidities including hydrocephalus and incontinence has negative impacts on the QOL. Patients who suffered from epilepsy had a statistically significant lower QOL. No significant difference was found in the association between the level of lesion and the QOL in our study.

International Headache Society global practice recommendations for the acute pharmacological treatment of migraine.

BACKGROUND: In an effort to improve migraine management around the world, the International Headache Society (IHS) has here developed a list of practical recommendations for the acute pharmacological treatment of migraine. The recommendations are categorized into optimal and essential, in order to provide treatment options for all possible settings, including those with limited access to migraine medications. METHODS: An IHS steering committee developed a list of clinical questions based on practical issues in the management of migraine. A selected group of international senior and junior headache experts developed the recommendations, following expert consensus and the review of available national and international headache guidelines and guidance documents. Following the initial search, a bibliography of twenty-one national and international guidelines was created and reviewed by the working group. RESULTS: A total of seventeen questions addressing different aspects of acute migraine treatment have been outlined. For each of them we provide an optimal recommendation, to be used whenever possible, and an essential recommendation to be used when the optimal level cannot be attained. CONCLUSION: Adoption of these international recommendations will improve the quality of acute migraine treatment around the world, even where pharmacological options remain limited.

Performance of ChatGPT in Solving Questions From the Progress Test (Brazilian National Medical Exam): A Potential Artificial Intelligence Tool in Medical Practice.

Background The use of artificial intelligence (AI) is not a recent phenomenon, but the latest advancements in this technology are making a significant impact across various fields of human knowledge. In medicine, this trend is no different, although it has developed at a slower pace. ChatGPT is an example of an AI-based algorithm capable of answering questions, interpreting phrases, and synthesizing complex information, potentially aiding and even replacing humans in various areas of social interest. Some studies have compared its performance in solving medical knowledge exams with medical students and professionals to verify AI accuracy. This study aimed to measure the performance of ChatGPT in answering questions from the Progress Test from 2021 to 2023. Methodology An observational study was conducted in which questions from the 2021 Progress Test and the regional tests (Southern Institutional Pedagogical Support Center II) of 2022 and 2023 were presented to ChatGPT 3.5. The results obtained were compared with the scores of first- to sixth-year medical students from over 120 Brazilian universities. All questions were presented sequentially, without any modification to their structure. After each question was presented, the platform's history was cleared, and the site was restarted. Results The platform achieved an average accuracy rate in 2021, 2022, and 2023 of 69.7%, 68.3%, and 67.2%, respectively, surpassing students from all medical years in the three tests evaluated, reinforcing findings in the current literature. The subject with the best score for the AI was Public Health, with a mean grade of 77.8%. Conclusions ChatGPT demonstrated the ability to answer medical questions with higher accuracy than humans, including students from the last year of medical school.

Antimicrobial Archetypes: Assessing the Knowledge, Attitude, and Practice (KAP) Trends in Antimicrobial Resistance (AMR) and Antimicrobial Stewardship Program (AMSP) Among Faculties, Residents, and Interns in a Tertiary Care Hospital.

Background Antimicrobial resistance (AMR) is caused by inappropriate use of antimicrobials. India's high antibiotic use contributes significantly to AMR. Antimicrobial Stewardship Programs (AMSPs) are crucial for optimizing antimicrobial use. Knowledge, Attitude, and Practice (KAP) studies are essential for evaluating healthcare professionals' beliefs and conduct regarding AMR and AMSPs. Materials and methods A cross-sectional study at Saveetha Medical College and Hospital evaluated doctors' knowledge, attitudes, and practices regarding AMR and stewardship programs. The study involved 202 participants, including faculty members, postgraduates, and interns. Results The study involved 202 participants, with residents being the majority at 51.4%, followed by faculty at 26.7% and interns at 21.7%. Faculty members showed the highest overall knowledge, followed by residents and interns. Despite possessing knowledge, practitioners did not consistently implement their knowledge in their daily practices, with a statistically significant difference of p < 0.01. There was a substantial disparity in attitude between the departments, as evidenced by a statistically significant p-value of less than 0.01. Conclusion Positive trends in knowledge and attitudes exist, but there are areas for improvement in translating attitudes into clinical practices. There is a significant disparity among faculty members, residents, and interns, highlighting the urgent need for interventions to bridge the gap. Implementing antibiotic prescribing guidelines at the institutional level and enhancing knowledge, attitudes, and practices among healthcare professionals are crucial to addressing AMR.

Surveillance of alcohol use through population surveys in the Americas from 2010 to 2019.

AIMS: The aims of this study were to identify alcohol-related population surveys administered in the Americas, determine which alcohol-related measures are examined and identify coverage gaps regarding alcohol-related measures. METHODS: As part of the Global Information System on Alcohol and Health study, a systematic search was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses criteria to identify regionally or nationally representative survey reports of the general population from 1 January 2010 to 6 August 2019. Alcohol-related measures extracted from surveys were categorized into 10 domains: alcohol consumption status; alcohol consumption; unrecorded alcohol consumption; drinking patterns; symptoms of dependence and/or harmful use; drinking during pregnancy; treatment coverage; second-hand harms; economic; and other. RESULTS: The systematic search identified 7417 survey reports, 94 of which were new and included in this study, with an additional 11 studies included from a previous systematic study of alcohol surveys. In total, 94 unique surveys and 161 unique survey waves were located, representing 105 unique survey questionnaires covering 30 countries. No population surveys were found for five member states; namely, Antigua and Barbuda, Dominica, Haiti, Saint Vincent and the Grenadines and Saint Kitts and Nevis. All countries with population-based alcohol surveys had had a population survey probing alcohol use in the past year/month. Questions regarding heavy episodic drinking, alcohol use disorders, treatment-seeking for alcohol use, drinking during pregnancy, harms to others and the amounts spent on alcohol were asked in 26, 25, 10, 6, 22 and 11 countries, respectively. CONCLUSIONS: The heterogeneity in alcohol-related population surveys in the Americas from 2010 to 2019 limits their comparability throughout countries and over time. Future surveys should implement a standardized set of core questions to provide consistency in the monitoring of alcohol consumption and alcohol-related harms.

ChatGPT-3.5 Versus Google Bard: Which Large Language Model Responds Best to Commonly Asked Pregnancy Questions?

Large language models (LLM) have been widely used to provide information in many fields, including obstetrics and gynecology. Which model performs best in providing answers to commonly asked pregnancy questions is unknown. A qualitative analysis of Chat Generative Pre-Training Transformer Version 3.5 (ChatGPT-3.5) (OpenAI, Inc., San Francisco, California, United States) and Bard, recently renamed Google Gemini (Google LLC, Mountain View, California, United States), was performed in August of 2023. Each LLM was queried on 12 commonly asked pregnancy questions and asked for their references. Review and grading of the responses and references for both LLMs were performed by the co-authors individually and then as a group to formulate a consensus. Query responses were graded as "acceptable" or "not acceptable" based on correctness and completeness in comparison to American College of Obstetricians and Gynecologists (ACOG) publications, PubMed-indexed evidence, and clinical experience. References were classified as "verified," "broken," "irrelevant," "non-existent," and "no references." Grades of "acceptable" were given to 58% of ChatGPT-3.5 responses (seven out of 12) and 83% of Bard responses (10 out of 12). In regard to references, ChatGPT-3.5 had reference issues in 100% of its references, and Bard had discrepancies in 8% of its references (one out of 12). When comparing ChatGPT-3.5 responses between May 2023 and August 2023, a change in "acceptable" responses was noted: 50% versus 58%, respectively. Bard answered more questions correctly than ChatGPT-3.5 when queried on a small sample of commonly asked pregnancy questions. ChatGPT-3.5 performed poorly in terms of reference verification. The overall performance of ChatGPT-3.5 remained stable over time, with approximately one-half of responses being "acceptable" in both May and August of 2023. Both LLMs need further evaluation and vetting before being accepted as accurate and reliable sources of information for pregnant women.

The Accuracy of Artificial Intelligence ChatGPT in Oncology Examination Questions.

The aim of this study is to assess the accuracy of Chat Generative Pretrained Transformer (ChatGPT) in response to oncology examination questions in the setting of one-shot learning. Consecutive national radiation oncology in-service multiple-choice examinations were collected and inputted into ChatGPT 4o and ChatGPT 3.5 to determine ChatGPT's answers. ChatGPT's answers were then compared with the answer keys to determine whether ChatGPT correctly or incorrectly answered each question and to determine if improvements in responses were seen with the newer ChatGPT version. A total of 600 consecutive questions were inputted into ChatGPT. ChatGPT 4o answered 72.2% questions correctly, whereas 3.5 answered 53.8% questions correctly. There was a significant difference in performance by question category (P < .01). ChatGPT performed poorer with respect to knowledge of landmark studies and treatment recommendations and planning. ChatGPT is a promising technology, with the latest version showing marked improvement. Although it still has limitations, with further evolution, it may be considered a reliable resource for medical training and decision making in the oncology space.

A framework for player movement analysis in team sports.

Player movement is a fundamental component of evaluating performance in most team sports. Movement can be evaluated across multiple scales, referring to the function of anatomical structures through various planes of motion or an individual regulating their field position based on the movement of opposition players. Developments in commercially available tracking systems have afforded end users the ability to investigate the spatiotemporal features of movement in fine detail. These advancements, in conjunction with overlaid contextual information, have provided insights into the strategies adopted by players in relation to their movement. Understanding movement beyond its semantic value allows practitioners to make informed decisions surrounding performance evaluation and training design. This investigation proposes a framework to guide the analysis of player movement within team sports environments. The framework describes how operational standards for assessing movement can be designed in reference to theory and a set training philosophy. Such practice allows for the spatial and temporal complexities within team sports to be described and could potentially lead to better-applied outcomes through greater interdisciplinary collaboration and an improved holistic understanding of movement. To inform its development, this study evaluates the current research and identifies several open questions to guide future investigations.

Item Response Modeling of Clinical Instruments With Filter Questions: Disentangling Symptom Presence and Severity.

Clinical instruments that use a filter/follow-up response format often produce data with excess zeros, especially when administered to nonclinical samples. When the unidimensional graded response model (GRM) is then fit to these data, parameter estimates and scale scores tend to suggest that the instrument measures individual differences only among individuals with severe levels of the psychopathology. In such scenarios, alternative item response models that explicitly account for excess zeros may be more appropriate. The multivariate hurdle graded response model (MH-GRM), which has been previously proposed for handling zero-inflated questionnaire data, includes two latent variables: susceptibility, which underlies responses to the filter question, and severity, which underlies responses to the follow-up question. Using both simulated and empirical data, the current research shows that compared to unidimensional GRMs, the MH-GRM is better able to capture individual differences across a wider range of psychopathology, and that when unidimensional GRMs are fit to data from questionnaires that include filter questions, individual differences at the lower end of the severity continuum largely go unmeasured. Practical implications are discussed.

Introducing the high-context communication style interview protocol to detect deception in pairs.

In four experiments, we examined whether pairs of truth tellers could be distinguished from pairs of lie tellers by taking advantage of the fact that only pairs of truth tellers can refer to shared events by using brief expressions (high-context communication style). In Experiments 1 and 2, pairs of friends and pairs of strangers pretending to be friends answered (i) questions they likely had expected to be asked (e.g., 'How did you first meet'?) and (ii) unexpected questions (e.g., 'First, describe a shared event in a few words. Then elaborate on it'). Pairs were interviewed individually (Experiment 1, N = 134 individuals) or collectively (Experiment 2, N = 130 individuals). Transcripts were coded for the verbal cues details, complications, plausibility, predictability, and overlap (Experiment 1 only) or repetitions (Experiment 2 only). In two lie detection experiments observers read the individual transcripts in Experiment 3 (N = 146) or the collective transcripts in Experiment 4 (N = 138). The verbal cues were more diagnostic of veracity and observers were better at distinguishing between truths and lies in the unexpected than in the expected questions condition, but only when the pair members were interviewed individually.

To Talk or not to Talk About Existential Questions - An Interview Study With Elderly Persons and Patients With Fatal Disease.

Background: Existential experiences often come to the fore in the case of a severe and/or life-threatening disease and in old age. This can evoke a variety of thoughts and emotions. The existential dimension is a concept that encompasses spiritual, religious and secular perspectives. Objective: The aim of this study was to gain a deeper understanding of how patients describe the existential dimension of life and whether and in what way the existential questions are raised in conversations and other forms of support within care. Methods: A qualitative design, with in-depth semi-structured interviews with patients admitted to an out-clinic oncology department at one hospital and participants living in a nursing home. The interviews were analysed using qualitative content analysis. Results: A total of 15 persons were interviewed. The respondents varied in age from 44 to 96. Two main themes emerged: What are existential questions? and Talk about existential questions. The existential questions refer to life as a whole and death as an end of life. It was summarized into three subcategories: The experience of the life, Existing within context and Spirituality and religion. About half of the participants thought it was important to talk about existential questions. They wanted to choose who to talk to, when and about what. Support was received from loved ones, professionals and experiences beyond conversations. Conclusions: The study provide new knowledge of how patients and elderly experience the existential dimension. The respondents emphasized a desire to be selective with whom they shared these questions and thoughts.

Comparing ChatGPT and a Single Anesthesiologist's Responses to Common Patient Questions: An Exploratory Cross-Sectional Survey of a Panel of Anesthesiologists.

Increased patient access to electronic medical records and resources has resulted in higher volumes of health-related questions posed to clinical staff, while physicians' rising clinical workloads have resulted in less time for comprehensive, thoughtful responses to patient questions. Artificial intelligence chatbots powered by large language models (LLMs) such as ChatGPT could help anesthesiologists efficiently respond to electronic patient inquiries, but their ability to do so is unclear. A cross-sectional exploratory survey-based study comprised of 100 anesthesia-related patient question/response sets based on two fictitious simple clinical scenarios was performed. Each question was answered by an independent board-certified anesthesiologist and ChatGPT (GPT-3.5 model, August 3, 2023 version). The responses were randomized and evaluated via survey by three blinded board-certified anesthesiologists for various quality and empathy measures. On a 5-point Likert scale, ChatGPT received similar overall quality ratings (4.2 vs. 4.1, p = .81) and significantly higher overall empathy ratings (3.7 vs. 3.4, p < .01) compared to the anesthesiologist. ChatGPT underperformed the anesthesiologist regarding rate of responses in agreement with scientific consensus (96.6% vs. 99.3%, p = .02) and possibility of harm (4.7% vs. 1.7%, p = .04), but performed similarly in other measures (percentage of responses with inappropriate/incorrect information (5.7% vs. 2.7%, p = .07) and missing information (10.0% vs. 7.0%, p = .19)). In conclusion, LLMs show great potential in healthcare, but additional improvement is needed to decrease the risk of patient harm and reduce the need for close physician oversight. Further research with more complex clinical scenarios, clinicians, and live patients is necessary to validate their role in healthcare.

Urdu-Language Translation and Validation of the Ask Suicide-Screening Questions (ASQ) Tool: A Focus on Connotation and Context.

Background Suicide is a significant cause of death in the world, and Pakistan, a low- and middle-income country, is no exception. Despite the increasing number of suicides, Pakistan does not have a validated suicide risk screening tool to identify suicide risk in the national language, Urdu, accurately. This study aims to translate and validate the Ask Suicide-Screening Questions (ASQ) tool into Urdu for suicide risk screening in Pakistan. Methodology We conducted this study at the Services Institute of Medical Sciences (SIMS), a large teaching hospital in Lahore, Pakistan, after receiving the approval of the SIMS Institutional Review Board. The study used a cross-sectional instrument validation study design. The inclusion criteria were youth and adults of both sexes aged 15-45 years, with an ability to understand, speak, read, and write in the Urdu language, who had no cognitive or intellectual limitation to consenting, and who were medically stable to participate. Exclusion criteria included any medical, physical, or cognitive unstable condition to consent or participate. We enrolled 300 participants in our convenience sample from the emergency department (ED), inpatient, and outpatient settings. The ASQ and the ASQ Brief Suicide Safety Assessment (BSSA) were translated and back-translated by Urdu language experts and modified to accommodate cultural and linguistic nuances. The clinician-administered BSSA Urdu version was used as a standard criterion to validate the ASQ by comparing the ASQ-Urdu responses vs. BSSA-Urdu responses. RStudio (version 2023.09.1+494) was used for statistical analyses Results The sample had an enrollment rate of 99.7% (300/301). The sample was 52% female (158/300); the mean age was 27.1 years (SD = 9.4), the overall screen-positive rate was 41.7% (125/300), and 9.3% (28/300) of the participants endorsed a past suicide attempt. In our sample, 35.9% (33/92) of outpatients, 32.2% (19/59) of inpatients, and 49.0% (73/149) of ED patients screened positive on the Urdu ASQ. The screen-positive rate was 16.9% (10/59) for participants aged 17 years and younger, 40.7% (35/86) for participants aged 18 to 25 years, and 51.6% (80/155) for participants aged 26 years and older. Compared to the criterion standard clinician-administered assessment, the Urdu ASQ had a sensitivity of 94.2% (95% confidence interval (CI) = 85.8%-98.4%), a specificity of 73.9% (95% CI = 67.7%-79.5%), a negative predictive value of 97.7% (95% CI = 94.2%-99.1%), and a positive predictive value of 52.0% (95% CI = 46.4%-57.6%). Conclusions The Urdu ASQ has strong psychometric properties, allowing healthcare professionals in Pakistan and worldwide with Urdu-speaking diaspora to identify individuals at risk for suicide efficiently. Utilizing cultural contexts in adapted screening tools improves the accuracy of suicide detection by ensuring that the tools are relevant, sensitive, and respectful to the cultural context of the individuals being assessed. High screen-positive rates in our pilot study underscore the need for early detection and intervention of suicide as a major global public health problem.

Modeling Evasive Response Bias in Randomized Response: Cheater Detection Versus Self-protective No-Saying.

Randomized response is an interview technique for sensitive questions designed to eliminate evasive response bias. Since this elimination is only partially successful, two models have been proposed for modeling evasive response bias: the cheater detection model for a design with two sub-samples with different randomization probabilities and the self-protective no sayers model for a design with multiple sensitive questions. This paper shows the correspondence between these models, and introduces models for the new, hybrid "ever/last year" design that account for self-protective no saying and cheating. The model for one set of ever/last year questions has a degree of freedom that can be used for the inclusion of a response bias parameter. Models with multiple degrees of freedom are introduced for extensions of the design with a third randomized response question and a second set of ever/last year questions. The models are illustrated with two surveys on doping use. We conclude with a discussion of the pros and cons of the ever/last year design and its potential for future research.

Predicting neuroticism with open-ended response using natural language processing.

Introduction: With rapid advancements in natural language processing (NLP), predicting personality using this technology has become a significant research interest. In personality prediction, exploring appropriate questions that elicit natural language is particularly important because questions determine the context of responses. This study aimed to predict levels of neuroticism-a core psychological trait known to predict various psychological outcomes-using responses to a series of open-ended questions developed based on the five-factor model of personality. This study examined the model's accuracy and explored the influence of item content in predicting neuroticism. Methods: A total of 425 Korean adults were recruited and responded to 18 open-ended questions about their personalities, along with the measurement of the Five-Factor Model traits. In total, 30,576 Korean sentences were collected. To develop the prediction models, the pre-trained language model KoBERT was used. Accuracy, F1 Score, Precision, and Recall were calculated as evaluation metrics. Results: The results showed that items inquiring about social comparison, unintended harm, and negative feelings performed better in predicting neuroticism than other items. For predicting depressivity, items related to negative feelings, social comparison, and emotions showed superior performance. For dependency, items related to unintended harm, social dominance, and negative feelings were the most predictive. Discussion: We identified items that performed better at neuroticism prediction than others. Prediction models developed based on open-ended questions that theoretically aligned with neuroticism exhibited superior predictive performance.

Assessing ChatGPT's Capability for Multiple Choice Questions Using RaschOnline: Observational Study.

BACKGROUND: ChatGPT (OpenAI), a state-of-the-art large language model, has exhibited remarkable performance in various specialized applications. Despite the growing popularity and efficacy of artificial intelligence, there is a scarcity of studies that assess ChatGPT's competence in addressing multiple-choice questions (MCQs) using KIDMAP of Rasch analysis-a website tool used to evaluate ChatGPT's performance in MCQ answering. OBJECTIVE: This study aims to (1) showcase the utility of the website (Rasch analysis, specifically RaschOnline), and (2) determine the grade achieved by ChatGPT when compared to a normal sample. METHODS: The capability of ChatGPT was evaluated using 10 items from the English tests conducted for Taiwan college entrance examinations in 2023. Under a Rasch model, 300 simulated students with normal distributions were simulated to compete with ChatGPT's responses. RaschOnline was used to generate 5 visual presentations, including item difficulties, differential item functioning, item characteristic curve, Wright map, and KIDMAP, to address the research objectives. RESULTS: The findings revealed the following: (1) the difficulty of the 10 items increased in a monotonous pattern from easier to harder, represented by logits (-2.43, -1.78, -1.48, -0.64, -0.1, 0.33, 0.59, 1.34, 1.7, and 2.47); (2) evidence of differential item functioning was observed between gender groups for item 5 (P=.04); (3) item 5 displayed a good fit to the Rasch model (P=.61); (4) all items demonstrated a satisfactory fit to the Rasch model, indicated by Infit mean square errors below the threshold of 1.5; (5) no significant difference was found in the measures obtained between gender groups (P=.83); (6) a significant difference was observed among ability grades (P<.001); and (7) ChatGPT's capability was graded as A, surpassing grades B to E. CONCLUSIONS: By using RaschOnline, this study provides evidence that ChatGPT possesses the ability to achieve a grade A when compared to a normal sample. It exhibits excellent proficiency in answering MCQs from the English tests conducted in 2023 for the Taiwan college entrance examinations.