Item Bank Research Articles

Psychometric evaluation of the PROMIS parent proxy mobility item bank for use in Duchenne muscular dystrophy.

To evaluate the psychometric properties and measurement quality of the Patient-Reported Outcomes Measurement Information System Parent Proxy (PROMIS PP) Mobility item bank (v1.0, 23 items) for children with Duchenne muscular dystrophy (DMD), through Rasch statistical analysis. De-identified PROMIS PP Mobility items were completed by the caregivers of male patients with DMD, aged 4 to 12 years, as part of standard clinical care at the Nationwide Children's Hospital clinic; data were mined retrospectively from electronic health records. Rasch analysis was used to assess the internal functioning of the measure and items. Overall, 151 observations were available for the Rasch analysis, equally split between patients aged 4 to 7 years and 8 to 12 years. After removing clinically irrelevant items and regrouping response options for specific items, the resulting 19-item measure demonstrated overall good fit to Rasch model expectations and the ability to discriminate between respondents with different mobility levels (Person Separation Index = 0.95, excellent reliability). The customized PROMIS PP Mobility measure demonstrated good fit and may be a reliable option for mobility assessment in children with DMD. Rasch analysis can be used by other researchers to improve the sensitivity of patient-reported outcomes in their field of interest.

Implementing Computer Adaptive Testing for High-Stakes Assessment: A Shift for Examinations Council of Lesotho

We examine the feasibility of implementing Computer Adaptive Testing (CAT) for high-stakes assessments in Lesotho, specifically through the Examination Council of Lesotho (ECoL). CAT, a cutting-edge testing method, enhances precision and efficiency by adjusting test items in real-time based on an examinee's ability. While CAT has gained widespread global adoption, its implementation in developing countries presents significant challenges, particularly regarding infrastructure, expertise, and resource limitations. Our research addresses a critical gap in understanding how CAT can be effectively integrated into educational systems in developing contexts such as Lesotho. We conducted a literature review across five databases—Google Scholar, ERIC, PsycINFO, JSTOR, and PubMed—retrieving 48 studies published between 2013 and 2023. Of these, 18 studies met our inclusion criteria, focusing on CAT's advantages, challenges, and real-world applications in educational assessments. We applied thematic analysis to identify key benefits and barriers, focusing on precision, fairness, and infrastructure requirements. We outline the essential stages of CAT development, including feasibility studies, item bank creation, pretesting and calibration, specification determination, and live CAT publication. We highlight critical tasks such as using Monte Carlo simulations to validate CAT feasibility and developing a robust item bank calibrated with Item Response Theory (IRT). We also address challenges like building a robust technological infrastructure, providing comprehensive stakeholder training, and securing adequate funding. We emphasize the importance of continuous evaluation and stakeholder engagement to ensure CAT's successful implementation and sustainability. Global trends indicate growing adoption, driven by advancements in psychometrics and technology. CAT has the potential to offer more equitable and accurate assessments, making it a promising solution to improve educational outcomes in Lesotho.

Development and validation of electronic health record-based, machine learning algorithms to predict quality of life among family practice patients

Health-related quality of life (HRQol) is a crucial dimension of care outcomes. Many HRQoL measures exist, but methodological and implementation challenges impede primary care (PC) use. We aim to develop and evaluate a novel machine learning (ML) algorithm that predicts binary risk levels among PC patients by combining validated elements from existing measures with demographic data from patient electronic health records (eHR) to increase predictive accuracy while reducing prospectively-collected data required to generate valid risk estimates. Self-report questions from previously validated QoL surveys were collected from PC patients and combined with their demographic and social determinant (SD) data to form a 53-question item bank from which ML chose the most predictive elements. For algorithm development, 375 observations were allocated to training (n = 301, 80%) or test partitions (n = 74, 20%). Questions that asked participants to rate how happy or satisfied they have been with their lives and how easy or hard their emotional health makes work/school showed a good ability to classify participants’ mental QoL (98% max balanced accuracy). Questions that asked participants to rate how easy or hard it is to do activities such as walking or climbing stairs and how much pain limits their everyday activities showed ability to classify physical QoL (94% max balanced accuracy). No demographic or SD factors were significantly predictive. Supervised machine learning can inform QoL measurements to reduce data collection, simplify scoring, and allow for meaningful use by clinicians. Results from the current study show that a reduced 4-question model may predict QoL almost as well as a full-length 40-question measure.

Sleep Value and Sleep Resilience are Important Dimensions of Sleep Health and We Measured Them: Methods for the Sleep Resilience and Variance in Sleep Valuation (SRVIV) Study

Abstract Sleep health is a multidimensional construct that is essential for general health and well-being. Sleep value, the amount of worth an individual places on their sleep, and sleep resilience, the ability to function emotionally, cognitively, and physically in the presence of sleep disturbances are overlooked dimensions of sleep health. To study these sleep health dimensions, we developed the Sleep Valuation Item Bank 2.0, Values Inventory, Monetary Sleep Value Questionnaire, and Sleep Resilience Questionnaire. This paper describes the methods for the Sleep Resilience and Variance in Sleep Valuation (SRVIV) Study. The SRVIV study was conducted to explore the factor structure of sleep value and sleep resilience and determine how they relate to demographic, sleep, and psychological variables. This study resulted in an analysis sample of 455 participants who were recruited by a Qualtrics team and completed a Qualtrics survey consisting of demographic, anxiety, depression, and sleep-related questionnaires, in addition to sleep value and sleep resilience questionnaires. Adult participants were recruited throughout the continental United States and were predominately female (53%), white (82%), married (50%), and had an average age of 45.4 years. The data resulting from this study can be used to address important questions in the field of sleep psychology.

Identifying Careless Responses in Computer-Adaptive Affective Surveys Using Person Fit Analysis

ABSTRACT Careless responding is a pervasive concern in research using affective surveys. Although researchers have considered various methods for identifying careless responses, studies are limited that consider the utility of these methods in the context of computer adaptive testing (CAT) for affective scales. Using a simulation study informed by recent research, we explored the impact of careless response patterns on three types of response quality indicators: model-based person fit statistics, CAT-specific statistical process control indicators, and standalone indices of carelessness. We focused on over-consistency and random responding as forms of carelessness. All three types of indicators were sensitive to carelessness, with some differences related to CAT termination rules and item bank size. Our findings suggest that person fit analysis techniques may also be useful in affective CAT contexts to evaluating response quality from a measurement model perspective, including identifying carelessness. We discuss the implications of our work for research and practice.

Initial development and validation of item banks to measure problematic hypersexuality

Background Problematic Hypersexuality (PH) is defined as a distress caused by hypersexuality, to the extent that seeking treatment is considered. PH was previously measured with instruments stemming from different perspectives on problems related to hypersexuality. These instruments might best be analyzed in unison to discover the most optimal set of characteristics to measure PH. Methods A total of 58 items were investigated with Item Response Theory (IRT). We included 1211 participants (592 women, 618 men, 1 other) from a representative Dutch general population sample of 18 years or older. In addition, 371 participants (116 women, 253 men, 2 other) in a web-based survey who sought information on their current level of PH were included. This latter group was divided into those that did or did not consider treatment and group differences in item averages were assessed. Results After item selection, 26 out of 58 items were retained and divided in two scales: Emotion Dysregulation-PH – 9 items representing the distressing emotional patterns coinciding with hypersexual preoccupation – and Negative Effects-PH – 17 items representing the negative consequences of patterns of hypersexual thoughts and behavior. Assumptions for IRT analyses were met (unidimensionality, local independence and monotonicity). After an IRT graded response model was fit, the scales showed sufficient reliability for the target population of hypersexual individuals. In the general population the scales showed large floor effects and were less reliable. Conclusions With this study a first step is taken in validating two complementary item banks to measure PH. Further development of the item banks should include the investigation of responsiveness. New items should be constructed to assess less-explored areas of PH and improve differentiating power of the scales. This study showed that diagnostic accuracy for PH is currently difficult to attain with a survey, even when using an extended item set representing the most unique characteristics of PH.

Health-related quality of life and symptom-specific functional impairment among patients treated with parenterally administered complement inhibitors for paroxysmal nocturnal hemoglobinuria

AbstractThis study describes the health-related quality of life (HRQoL) and symptom-specific functional impairment of patients with paroxysmal nocturnal hemoglobinuria (PNH) in a real-world setting. US-based adults with PNH treated with a parenterally administered complement inhibitor (PACI) for ≥ 6 months completed an online, cross-sectional, observational survey; a subset of patients also participated in semi-structured qualitative interviews. The survey included the PROMIS® 29 + 2 Profile v2.1 (PROMIS 29 + 2) to measure HRQoL. The FACIT-Fatigue, Neuro-QOL Item Bank v2.0 Cognitive Function Short Form, and PROMIS Item Bank v1.0 Dyspnea Functional Limitations 10a Short Form measured symptom-specific functional impairment. For each patient with PNH who completed the online survey, 3 age- and sex-matched adults from the general population (GP) also completed the survey. The HRQoL and functional impairment of the PNH sample were compared to that of the GP sample. The association between HRQoL/functional impairment and fatigue severity for the PNH sample was also investigated. Compared to the age- and sex-matched GP sample, patients treated with PACIs for PNH had significantly worse HRQoL and greater functional impairment for all measured domains (p < 0.05). Within the PNH sample, statistically significant associations (p < 0.05) were observed between fatigue severity and HRQoL/functional impairment for all outcomes except the PROMIS 29 + 2 Sleep Disturbance domain. Interview participants described fatigue-related impairments in their physical, social, and cognitive functioning. Despite receiving treatment for PNH, patients experienced deficits in HRQoL and functional impairment, suggesting that opportunities to improve patient-relevant outcomes through treatment should be identified.

Memetic ant colony optimization for multi-constrained cognitive diagnostic test construction.

Cognitive diagnostic tests (CDTs) assess cognitive skills at a more granular level, providing detailed insights into the mastery profile of test-takers. Traditional algorithms for constructing CDTs have partially addressed these challenges, focusing on a limited number of constraints. This paper intends to utilize a meta-heuristic algorithm to produce high-quality tests and handle more constraints simultaneously. This paper presents a memetic ant colony optimization (MACO) algorithm for constructing CDTs while considering multiple constraints. The MACO method utilizes pheromone trails to represent successful test constructions from the past. Additionally, it innovatively integrates item quality and constraint adherence into heuristic information to manage multiple constraints simultaneously. The method evaluates the assembled tests based on the diagnosis index and constraint satisfaction. Another innovation of MACO is the incorporation of a local search strategy to further enhance diagnostic accuracy by partially optimizing item selection. The optimal local search parameter settings are explored through a parameter investigation. A series of simulation experiments validate the effectiveness of MACO under various conditions. The results demonstrate the great ability of meta-heuristic algorithms to handle multiple constraints and achieve high statistical performance. MACO exhibited superior performance in generating high-quality CDTs while meeting multiple constraints, particularly for mixed and low discrimination item banks. It achieved faster convergence than the ant colony optimization in most scenarios. MACO provides an effective solution for multi-constrained CDT construction, especially for shorter tests and item banks with mixed or lower discrimination. The experimental results also suggest that the suitability of different optimization approaches may depend on specific test conditions, such as the characteristics of the item bank and the length of the test.

A practical guide to item bank calibration with multiple matrix sampling

When it is required to estimate item parameters of a large item bank, Multiple Matrix Sampling (MMS) design provides an efficient way while minimizing the test burden on students. The current study exemplifies how to calibrate a large item pool using MMS design for various purposes, such as developing a CAT administration. The purpose of the current study is to explain and provide an example of how to use MMS design for item bank calibration. Two functions of mirt package, mirt() and multipleGroup() were compared using real data. The results of the present study showed that the standard mirt() function is more practical and makes more precise estimations compared to the multipleGroup() function.

Designing a Measure of Body Image: Cognitive Interview Findings from an Adolescent and Young Adult Cancer Sample.

Purpose: A cancer diagnosis in adolescence and young adulthood significantly impacts a person's quality of life, particularly concerning identity, self-esteem, and subsequently, body image. This study aims to develop a psychometrically-sound patient-reported outcome measure of body image for adolescent and young adult (AYA) oncology patients that was guided by the National Institutes of Health's Patient-Reported Outcomes Measurement Information System® (PROMIS) Scientific Standards and our past concept elicitation interviews with AYAs. Methods: We conducted a multi-step approach involving item identification, refinement, generation; translatability and reading level review; and cognitive interviews. A purposive sample of 25 AYA patients participated, ensuring representation across educational levels, gender, treatment status, and cancer type. Results: Translatability and reading level reviews facilitated language adjustments. Cognitive interviews revealed that 76% of AYAs found the 50 candidate items assessing body image concerns to be easy to answer. AYAs reported that the body image items captured their lived experiences. Three items were excluded due to comprehension difficulties. Conclusion: This study addresses the critical gap in validated measures for assessing body image in AYA oncology patients. Interview findings provided evidence for the content validity and comprehensibility for 47 items assessing body image. The next steps involve large-scale psychometric testing to evaluate the reliability and validity of the body image items to form an item bank allowing the design of short forms or use of computerized-adaptive testing. Ultimately, this work lays the foundation for developing interventions to mitigate the impact of cancer on AYAs' body image during diagnosis, treatment, and recovery.

Design and psychometrics of a tool for measuring social cognitive factors related to the preventive behaviors toward Covid-19 in the society

With the emergence of new strains of Covid-19, the adoption of preventive behaviors is still considered a requirement to control this disease. Therefore, considering the importance of social cognitive factors in adopting various types of preventive behaviors, the present study was conducted to design and psychometrically measure the social cognitive factors related to Covid-19 preventive behaviors. A cross-sectional study was conducted on 526 people ages 18 and over with multi-stage stratified, cluster and random sampling in Isfahan, Iran in 2022. The questionnaire was validated and formulated in three stages: designing, creating and reducing items. After collecting information and creating a bank of items, qualitative and quantitative methods were used to calculate the tool’s validity. Data analysis was done in SPSS23 software at a significance level of less than 0.05. In the present study, the average age score of the participants was 39.16 ± 11.48. The results related to the construct validity in the exploratory part show that the five factors (Outcome expectations, self-efficacy, social support, self-regulation and barrier self-efficacy) obtained have a specific value higher than one and range from 1.376 to 9.343. Correlation between factors shows that all factors have a relatively high relationship with each other (P < 0.05). According to the exploratory factor analysis, the final questionnaire contains 29 items and 5 constructs from socio-cognitive theory. The results showed that the thematically and technically designed tool has been prepared in an appropriate way for each of the structures and can accurately measure the structures of outcome expectations, self-efficacy, social support, self-regulation and barrier self-efficacy to explain the preventive behaviors of Covid-19 to evaluate.

A comprehensive item bank of internal validity issues of relevance to in vitro toxicology studies

A comprehensive item bank of internal validity issues of relevance to in vitro toxicology studies

An item bank to measure health-related quality of life among young children (0-5-years-old) affected by respiratory illnesses – expert stakeholders and end-users from the Western Cape, South Africa

BackgroundHealth-related quality of life (HRQoL) is a crucial patient-centred outcome for developing policy. However, there is a lack of appropriate HRQoL measures for young children (0-5-years), who are particularly vulnerable to respiratory illnesses like pulmonary tuberculosis (PTB) and other respiratory infections, especially in low- and middle-income countries (LMICs). We aimed to develop a disease-specific HRQoL item bank for young children with acute and chronic respiratory illnesses.MethodsAn exploratory sequential design with three phases was used to develop a HRQoL item bank. The content validity of the item bank was evaluated by local and international experts specialising in HRQoL and child health. The group included paediatric pulmonologists, researchers with expertise in respiratory illnesses, and experts in scale development. Cognitive interviews with 37 caregivers of children with TB, pneumonia, adenovirus respiratory infection, other lower respiratory tract infections, reactive airway disease, and protracted bronchitis in Cape Town, South Africa, and consultations with 22 stakeholders were conducted for final revisions. The item bank was progressively refined at each phase of the study.FindingsThe Delphi experts recommended dividing the item bank into two age groups (0-2-years and 3-5-years) and using a 5-point Likert scale. Overall, 41 items (42%) met the predetermined > 70% threshold for inclusion in the item bank. Cognitive interviews confirmed that the domains were relevant. Minor modifications were made to five items in cohort 1 (0-2-years) and seven in cohort 2 (3-5-years), with 8 items (13%) and 14 items (22%) excluded. Phase 3 consultations emphasised the importance of including all seven domains and expanding the items to cover early childhood development, play, social interactions, and care routines. The final item bank includes versions for both age groups and incorporates these refinements.ConclusionAn item bank was developed as a first step to develop a comprehensive disease-specific HRQoL tool for young children with respiratory illnesses in an LMIC. Input from caregivers and content experts was crucial in creating two HRQoL item banks tailored to the developmental differences between 0 and 2 and 3-5-year age groups. Their contributions ensured the tool effectively captures age-appropriate aspects of HRQoL. Future studies should focus on assessing the validity and reliability of these item banks.

Adolescents’ mental health is associated with food parenting practices among British Columbian families

BackgroundAdolescence is a developmental period marked by significant changes related to the body and food parenting practices. However, few studies have explored child-level psychological correlates of these practices during adolescence. Our study examined whether adolescents’ weight status, weight concerns, self-esteem, and anxiety were associated with food parenting practices, and whether these associations significantly differed by adolescents’ gender among 297 families in British Columbia, Canada. MethodsParents (47 years, 76% mothers) completed a food parenting practice item bank. Adolescents (14 years, 52% girls) self-reported their height and weight, weight concerns, self-esteem, and anxiety. Covariate-adjusted regression models evaluated the association of adolescents’ weight and mental health with nine practices (main effects). Interactions were used to evaluate the moderating role of gender, and further decomposed in all models to examine simple effects within each gender group. ResultsMain-effect models showed positive associations between: (1) weight concerns and child involvement, (2) weight concerns and accommodating practices, (3) self-esteem and healthy eating opportunities, and (4) self-esteem with meal routines, as well as negative associations between: (5) self-esteem and accommodating practices, (6) self-esteem and coercive control, and (7) anxiety and rules and limits. In these 7 models interactions with gender were not significant; however, in all cases (except in model 5) the decomposed effects showed only significant associations among girls. A significant gender interaction emerged in (8) the association between anxiety and coercive control, but the decomposed effects were not significant for either gender. Adolescents’ weight status was not associated with food parenting practices in any model. ConclusionsFood parenting practices are associated with mental health indicators among British Columbian families; however, future studies should examine multidirectional relationships between these practices, adolescents’ mental health, and eating habits.

The legality and appropriateness of keeping Korean Medical Licensing Examination items confidential: a comparative analysis and review of court rulings

This study examines the legality and appropriateness of keeping the multiple-choice question items of the Korean Medical Licensing Examination (KMLE) confidential. Through an analysis of cases from the United States, Canada, and Australia, where medical licensing exams are conducted using item banks and computer-based testing, we found that exam items are kept confidential to ensure fairness and prevent cheating. In Korea, the Korea Health Personnel Licensing Examination Institute (KHPLEI) has been disclosing KMLE questions despite concerns over exam integrity. Korean courts have consistently ruled that multiple-choice question items prepared by public institutions are non-public information under Article 9(1)(v) of the Korea Official Information Disclosure Act (KOIDA), which exempts disclosure if it significantly hinders the fairness of exams or research and development. The Constitutional Court of Korea has upheld this provision. Given the time and cost involved in developing high-quality items and the need to accurately assess examinees’ abilities, there are compelling reasons to keep KMLE items confidential. As a public institution responsible for selecting qualified medical practitioners, KHPLEI should establish its disclosure policy based on a balanced assessment of public interest, without influence from specific groups. We conclude that KMLE questions qualify as non-public information under KOIDA, and KHPLEI may choose to maintain their confidentiality to ensure exam fairness and efficiency.

Arabic Translation and Rasch Validation of PROMIS Anxiety Short Form among General Population in Saudi Arabia.

This study aimed to translate, culturally adapt, and psychometrically validate the PROMIS Anxiety Short Form 8a item bank into Arabic for the general population of Saudi Arabia. The PROMIS Anxiety Short Form was translated according to the FACIT group method. Second, psychometric validation was conducted on a convenience sample of 322 participants (mean age, 26 ± 10.4 years; predominantly female) from the general population in Saudi Arabia. Rasch analysis (Winsteps® version 5.6.1) was used to examine category functioning, item fit, the person separation index, item difficulty, unidimensionality, and local dependency. Translation and cultural adaptation demonstrated that most of the items were culturally suitable and conveyed the same underlying concepts as the original scale. The five response categories of the scale satisfied the category functioning criteria, and all items fit the underlying construct, with the exception of one item that demonstrated a misfit. The item difficulty demonstrated poor targeting for the sample population; however, the person separation index and reliability were good (2.67 and 0.88, respectively) and no local dependency was noted. The Arabic translation of PROMIS-A SF8a demonstrated good structural validity and psychometrics, making it a valuable tool for screening anxiety in Arabic-speaking populations. The application of this outcome measure shows promise for healthcare professionals and patients alike, as it contributes to the provision of high-quality care and formulation of appropriate treatment plans.

Perceived Cognitive Function in Neurosurgical Patients.

This study explores perceived cognitive function in preoperative cranial neurosurgical patients and its association with neuropsychological testing (NPT). A total of 96 patients were referred for NPT by neurosurgical service. Patients completed the Neuro-QoL Item Bank v2.0-Cognitive Function-Short Form (Neuro-QoL) to measure perceived cognitive function, as well as NPT. Linear regression (LR) models were analyzed for demographic variables (ie, age, sex, handedness, educational attainment, employment/academic status, candidacy vs baseline testing, and history of neurological, mental health, and developmental conditions) and NPT outcomes (ie, intellectual estimation, attention/working memory, processing speed, executive functioning, learning/memory, language, visual-spatial, anxiety symptoms, and depression symptoms). Significant predictors from the LR models were then combined into a single model to identify the most robust predictors of perceived cognitive function. Patients were aged 17 to 79 years (M = 49.64, SD = 18.56) and comprised 45 men and 51 women. The most common referrals for NPT were related to intracranial mass (39%), Chiari malformation type 1 (33%), and deep brain stimulation (20%). Results of the final LR model indicated mental health and developmental history, as well as elevated anxiety symptoms, significantly predicted 50.7% of the variance in perceived cognitive function (F = 30.91, P < .001). Patients referred to determine surgical candidacy reported significantly fewer cognitive complaints (P < .001) vs those referred for baseline testing by approximately 0.5 SDs. Perceived cognitive function in neurosurgical patients appears to be strongly predicted by demographic factors, with mental health variables being robust predictors. Perceived cognition is not a proxy for measured cognitive function.

Field-Testing Multiple-Choice Questions With AI Examinees: English Grammar Items.

Field-testing is an essential yet often resource-intensive step in the development of high-quality educational assessments. I introduce an innovative method for field-testing newly written exam items by substituting human examinees with artificially intelligent (AI) examinees. The proposed approach is demonstrated using 466 four-option multiple-choice English grammar questions. Pre-trained transformer language models are fine-tuned based on the 2-parameter logistic (2PL) item response model to respond like human test-takers. Each AI examinee is associated with a latent ability θ, and the item text is used to predict response selection probabilities for each of the four response options. For the best modeling approach identified, the overall correlation between the true and predicted 2PL correct response probabilities was .82 (bias = 0.00, root mean squared error = 0.18). The study results were promising, showing that item response data generated from AI can be used to calculate item proportion correct, item discrimination, conduct item calibration with anchors, distractor analysis, dimensionality analysis, and latent trait scoring. However, the proposed approach did not achieve the level of accuracy obtainable with human examinee response data. If further refined, potential resource savings in transitioning from human to AI field-testing could be enormous. AI could shorten the field-testing timeline, prevent examinees from seeing low-quality field-test items in real exams, shorten test lengths, eliminate test security, item exposure, and sample size concerns, reduce overall cost, and help expand the item bank. Example Python code from this study is available on Github: https://github.com/hotakamaeda/ai_field_testing1.

Item Bank Development and Content Validation of a Youth Sport Specialization Assessment

OBJECTIVE: To refine and evaluate the content validity of a bank of items representing the physical, social, and motivation behaviors associated with youth sport specialization. DESIGN: Qualitative analysis METHODS: The conceptual framework for item generation involved an existing consensus-based definition of youth sport specialization. Purposive sampling recruited English literate youth athletes who participated in at least one organized sport in the past 12 months to participate in individual cognitive interviews. Three rounds of interviews used a ‘read aloud; think aloud’ strategy to evaluate the comprehension, relevance, and comprehensiveness of the items and their response structure. One reviewer conducted thematic analysis of verbatim transcripts following rounds 1-2; after round 3, two independent reviewers evaluated the content validity of all items. The full research team reviewed results and established consensus regarding item acceptance, revision or removal. RESULTS: Twenty-two participants (64% male, 13.8±3.0 years) were interviewed. Participants were classified as low (59%), moderate (23%), and high (18%) specialization. Thirty-one items organized into participation volume, physical, motivation, and social domains were tested. Comprehension of 24 items in the physical (n=6), motivation (n=12), and social (n=6) domains was acceptable. No participation volume items achieved content validity. Acceptable items were considered relevant to youth sport specialization, and the item bank was deemed comprehensive. Participants affirmed the response structure was easy to understand and use. CONCLUSION: Content validity was established for a bank of patient-reported items assessing youth sport specialization. An appropriate next step is to conduct psychometric evaluation and develop a youth sport specialization assessment.

Methods for online calibration of Q-matrix and item parameters for polytomous responses in cognitive diagnostic computerized adaptive testing.

The ability to rapidly provide examinees with detailed and effective diagnostic information is a critical topic in psychology. Knowing what diagnostic criteria the examinees have met enables the practitioner to seek the solution to help them in a timely manner, and this can be achieved by cognitive diagnostic computerized adaptive testing (CD-CAT). However, the pervasive challenge of replenishing items in the CD-CAT item bank limits its practical application. Online calibration is a means to address item replenishment, but in CD-CAT, most existing online calibration methods that jointly calibrate the Q-matrix and item parameters of the new items are developed only for dichotomous responses and are time-consuming. Notably, previous studies pay no attention to polytomously scored items that are frequently observed in testing, even though they can offer additional evidence for the examinees' diagnosis. To fill this gap, we propose a SCAD-based method (SCAD-EM) to calibrate the Q-matrix and item parameters of the new items with polytomous response data in order to promote the application of CD-CAT in practice. The performance of the SCAD-EM was investigated in two comprehensive simulation studies and compared against the revised single-item estimation method (SIE-BIC). Results indicated that the SCAD-EM produces a higher calibration accuracy for the category-level Q-matrix and is computationally more efficient across all conditions, but it produces a lower calibration accuracy for the item-level Q-matrix. An empirical study further demonstrated the utility of the SCAD-EM and the SIE-BIC methods in calibrating new items with a real dataset. The advantages of the proposed method, its limitations, and possible future research directions are offered at the end.