Two-parameter Logistic Item Response Theory Research Articles

Validity and Reliability of a Questionnaire Developed to Assess the Knowledge of Pregnant Women about Cord Blood Banking

Introduction: Cord blood (CB) is rich in hematopoietic stem cells. There has been significant growth in cord blood banks (CBBs) throughout the world. In Malaysia, the CB units cryopreserved in public CBB is below its optimal level. Lack of knowledge about CB banking among mothers in other countries influenced their decision to donate CB, however, there is no local data to support this in Malaysia. Moreover, no validated and reliable tool is available for measuring local women’s knowledge about CB banking. In this study, a questionnaire to assess pregnant women’s knowledge about CB banking was developed and validated. Method: Several steps were taken to develop the knowledge items in the questionnaire which includes comprehensive literature review, content validity by a panel of experts, and face validity by a group of pregnant women. The questionnaire was developed in Malay language and contained 18 items. After modifications, the self-administered questionnaire was distributed to 121 pregnant women to assess its psychometric properties using two-parameter logistic item response theory analysis and internal consistency reliability analysis. Results: The majority of the knowledge items showed acceptable difficulty and discriminatory values. The Cronbach’s alpha and ICC values were 0.831 and 0.887, respectively, indicating good reliability. All 18 knowledge items were retained for the final version of the questionnaire. Conclusion: The newly developed questionnaire demonstrated acceptable psychometric properties and can be used as a reliable tool to assess knowledge about CB banking among pregnant women in the local population.

Development and Validation of Knowledge, Attitude, and Practice Questionnaire: Toward Safe Working in Confined Spaces.

Confined space workers do a wide range of tasks, many of which have a significant risk of hazardous exposure. Hence, a reliable and valid questionnaire is important in assessing the knowledge, attitude, and practice (KAP) of workers in this field. The present study was conducted to develop and validate a questionnaire that could assess the KAP for safe working in a confined space. The questionnaire went through a development and validation process. The development stage consisted of a literature review, expert’s opinion, and evaluation by experts in the field via cognitive debriefing. The validation stage encompassed exploratory and confirmatory parts to investigate the psychometric properties of the questionnaire. A total of 350 participants were recruited among confined space workers from two oil and gas companies in Malaysia. The two-parameter logistic item response theory (2-PL IRT) analysis was used for the knowledge section. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used in the attitude and practice sections of the validation stage. The development stage resulted in 30 items for knowledge, attitude, and practice sections. Items in the knowledge section showed an acceptable difficulty and discrimination, as noted during the 2-PL IRT analysis. The EFA resulted in a one-factor model for attitude and practice sections, and contained 18 items, with factor loading > 0.4. The Cronbach’s alpha was 0.804 and 0.917 for attitude and practice sections, respectively. The CFA for attitude and practice sections indicated a good model fitness (Raykov’s rho = 0.814 and 0.912, respectively). All items indicated good reliability and valid psychometrics for determining KAP on safe working in a confined space.

Design and analysis of a structured questionnaire to assess the probability of elimination of Rhipicephalus microplus from farms in a subtropical area

In areas in which R. microplus may be eliminated from farms, it is essential to evaluate the infestation situation and the biosecurity measures available when deciding whether or not to undertake an elimination effort. Multiple questionnaires have been developed to evaluate the cattle tick situation on farms, however, the validity of those questionnaires has not been evaluated. This study aimed to develop a standardized and validated questionnaire to estimate the likelihood of cattle tick elimination from farms. A list of items (topics) to be covered was sent to 25 experts for their evaluation, with 11 responding. Based on the selected items, thirty-five closed questions were developed and evaluated through a cognitive interview process with 8 veterinarians and 5 farmers. Subsequently, a focus group evaluation was carried out with 30 farmers and a pretest of the revised questionnaire was performed with 94 farmers. A test, re-test evaluation was carried out in a subset of the pretest respondents after two-weeks. The questionnaire took approximately 10 min to complete. The ability of the questionnaire to reliably produce a score reflecting the expected probability of a farm eliminating ticks was evaluated through the use of a two-parameter logistic item-response theory model. A subset of questions related to a unidimensional latent variable were identified. This set of items appeared to have good ability to predict which farms were more likely to achieve the elimination, although the evaluation of that predictive ability was beyond the scope of this work.

Pre-statistical harmonization of behavioral instruments across eight surveys and trials

BackgroundData harmonization is a powerful method to equilibrate items in measures that evaluate the same underlying construct. There are multiple measures to evaluate dementia related behavioral symptoms. Pre-statistical harmonization of behavioral instruments in dementia research is the first step to develop a statistical crosswalk between measures. Studies that conduct pre-statistical harmonization of behavioral instruments rarely document their methods in a structured, reproducible manner. This is a crucial step which entails careful review, documentation and scrutiny of source data to ensure sufficient comparability between items prior to data pooling. Here, we document the pre-statistical harmonization of items measuring behavioral and psychological symptoms among people with dementia. We provide a box of recommended procedure for future studies.MethodsWe identified behavioral instruments that are used in clinical practice, a national survey, and randomized trials of dementia care interventions. We rigorously reviewed question content and scoring procedures to establish sufficient comparability across items as well as item quality prior to data pooling. Additionally, we standardized coding to Stata-readable format, which allowed us to automate approaches to identify potential cross-study differences in items and low-quality items. To ensure reasonable model fit for statistical co-calibration, we estimated two-parameter logistic Item Response Theory models within each of the eight studies.ResultsWe identified 59 items from 11 behavioral instruments across the eight datasets. We found considerable cross-study heterogeneity in administration and coding procedures for items that measure the same attribute. Discrepancies existed in terms of directionality and quantification of behavioral symptoms for even seemingly comparable items. We resolved item response heterogeneity, missingness and skewness, conditional dependency prior to estimation of item response theory models for statistical co-calibration. We used several rigorous data transformation procedures to address these issues, including re-coding and truncation.ConclusionsThis study highlights the importance of each aspect involved in the pre-statistical harmonization process of behavioral instruments. We provide guidelines and recommendations for how future research may detect and account for similar issues in pooling behavioral and related instruments.

Comparison of Testlet Effect on Parameter Estimates Using Different Item Response Theory Models

In this study, the testlet effect was calculated for each testlet in the PISA 2018 reading literacy test, and it was examined whether this effect caused a difference in item and ability parameters. The data set was analyzed with a two-parameter logistic item response theory model and a two-parameter logistic testlet model. The results show that variances of testlet effects range from .100 to .432. When the item and ability parameter estimation results of the models were compared, it was determined that the item and ability parameters estimated from the two approaches were highly correlated with each other. It can be said that the item slope and item intercept parameters estimated from different models remained unaffected. However, when the local dependency assumption is not met, it was observed that the standard error values of the two-parameter model for the ability parameter were underestimated. The implications for the analysis and evaluation of the tests based on testlet are discussed. In conclusion, in this study, it was concluded that the testlet effect caused a difference in parameter estimates, but the local dependence among the items was negligible because of the small testlet effects.

Development and validation of a structured survey questionnaire on knowledge, attitude, preventive practice, and treatment-seeking behaviour regarding dengue among the resident population of Sabah, Malaysia: an exploratory factor analysis

BackgroundSeveral studies have reported a significant association of knowledge, attitude and preventive practice (KAP) regarding dengue infection among community’s resident in endemic areas. In this study we aimed to assess and develop a reliable and valid KAP survey on the subject of dengue that is suitable for the resident population of Sabah, Malaysia.MethodsA community-based cross-sectional study was conducted from October 2019 to February 2020 involving 468 respondents. Information on the socio-demographic characteristics of the participants (six items), their KAP (44, 15 and 18 items on knowledge, attitude and practice, respectively) and treatment-seeking behaviour (five items) towards dengue was collected using a structured questionnaire. Data analysis was performed using SPSS and R software in the R Studio environment. The knowledge section was analysed by two-parameter logistic item response theory (2-PL IRT) using ltm package. The construct validity and reliability of items for sections on attitude, practice and treatment-seeking behaviour were analysed using psy package.ResultsFor the knowledge section, only 70.5% (31/44) of items were within or close to the parameter acceptable range of −3 to + 3 of difficulty. In terms of discrimination, 65.9% (29/44) of items were within or close to the acceptable range of 0.35 to 2.5, and 24 items (54.5%) failed to fit the 2-PL IRT model (P < 0.05) after assessing by goodness-of-fit analysis. Only eight items were reliable and retained in the attitude section with a Kaiser–Meyer–Olkin (KMO) test value of > 0.7, while based on the communalities, 11 items in the attitude section were excluded due to very low h2, factor loading values and low correlation with the total (< 0.5). The practice section was found suitable for factor analysis because the KMO value was > 0.7. The communalities of the practice section showed that seven items had low h2 values (< 0.3), which were therefore excluded from further analysis, and only 11 items were retained.ConclusionsThe KAP items retained in the final version of the survey were reliable and valid to be use as a questionnaire reference when conducting future similar studies among the population of Sabah.

Knowledge, attitude, and practices to zoonotic disease risks from livestock birth products among smallholder communities in Ethiopia

Many causes of abortion in livestock are due to zoonotic pathogens that pose serious infection risks for humans. Carefully designed, empirical One Health research allows to untangle the complexity around these risks and guides the development of practical health education guidelines and best prevention practices for veterinary public health interventions. To support this, the study presented here aimed at understanding knowledge, attitudes, and practices (KAP) on zoonotic risks from livestock birth products among rural communities in Ethiopia. From July 2018 to February 2019, a cross-sectional study design was conducted with 327 randomly selected farmers and pastoralists in five districts in three regions in Ethiopia. The structured questionnaire consisted of 48 items to evaluate knowledge (24), attitude (9), and prevention practices (15) related to zoonotic diseases risks from livestock birth products. A unidimensional two-parameter logistic (2-PL) Item Response Theory (IRT) model was used for zoonotic disease risk KAP scale construction and evaluation. The 2-PL IRT model was fitted to determine the probability of a person to appropriately respond to an item with a provided zoonotic disease KAP level. We then examined differential item functioning (DIF) concerning to five important covariates. The attitude subscale had the highest total mean score (37.3, ± 28.92%) and the knowledge subscale had the lowest mean score (22.4, ± 33.6%) among the three subscales. The mixed model regression analysis indicated that region was the only apparent factor explaining differences in zoonotic diseases knowledge, attitude, and practice total mean scores. The knowledge and attitude subscales had good internal consistency with a Cronbach's α at 0.83 and 0.81, respectively, whereas the practice subscale had lower internal consistency with 0.51. There was a positive association between responding to knowledge questions correctly and a positive attitude (r2 = 0.44, p < 0.0001) and self-reported good practice (r2 = 0.307, p < 0.0001). The differential item functioning test showed that 19 of 37 (51.35%) and 12 of 37 (32.43%) items of the retained KAPs survey items had non-uniform and uniform DIF linked to at least one covariate respectively and all the covariates were related with DIF in at least one item. This study found substantial knowledge gaps, a low level of the desired attitude, and high-risk behavioural practices regarding zoonotic disease from livestock birth products. Consequently, livestock keepers are likely exposed to pathogens and thus these practices are an important contributing factor for zoonotic disease infection in people.

Improving the assessment of measurement invariance: Using regularization to select anchor items and identify differential item functioning.

A common challenge in the behavioral sciences is evaluating measurement invariance, or whether the measurement properties of a scale are consistent for individuals from different groups. Measurement invariance fails when differential item functioning (DIF) exists, that is, when item responses relate to the latent variable differently across groups. To identify DIF in a scale, many data-driven procedures iteratively test for DIF one item at a time while assuming other items have no DIF. The DIF-free items are used to anchor the scale of the latent variable across groups, identifying the model. A major drawback to these iterative testing procedures is that they can fail to select the correct anchor items and identify true DIF, particularly when DIF is present in many items. We propose an alternative method for selecting anchors and identifying DIF. Namely, we use regularization, a machine learning technique that imposes a penalty function during estimation to remove parameters that have little impact on the fit of the model. We focus specifically here on a lasso penalty for group differences in the item parameters within the two-parameter logistic item response theory model. We compare lasso regularization with the more commonly used likelihood ratio test method in a 2-group DIF analysis. Simulation and empirical results show that when large amounts of DIF are present and sample sizes are large, lasso regularization has far better control of Type I error than the likelihood ratio test method with little decrement in power. This provides strong evidence that lasso regularization is a promising alternative for testing DIF and selecting anchors. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Comparison of Recent Acceleration Techniques for the EM Algorithm in One- and Two-Parameter Logistic IRT Models

The expectation–maximization (EM) algorithm is an important numerical method for maximum likelihood estimation in incomplete data problems. However, convergence of the EM algorithm can be slow, and for this reason, many EM acceleration techniques have been proposed. After a review of acceleration techniques in a unified notation with illustrations, three recently proposed EM acceleration techniques are compared in detail: quasi-Newton methods (QN), “squared” iterative methods (SQUAREM), and parabolic EM (PEM). These acceleration techniques are applied to marginal maximum likelihood estimation with the EM algorithm in one- and two-parameter logistic item response theory (IRT) models for binary data, and their performance is compared. QN and SQUAREM methods accelerate convergence of the EM algorithm for the two-parameter logistic model significantly in high-dimensional data problems. Compared to the standard EM, all three methods reduce the number of iterations, but increase the number of total marginal log-likelihood evaluations per iteration. Efficient approximations of the marginal log-likelihood are hence an important part of implementation.

Construct validity of the Physiotherapy Evidence Database (PEDro) quality scale for randomized trials: Item response theory and factor analyses.

BackgroundThere is an agreement that the methodological quality of randomized trials should be assessed in systematic reviews, but there is a debate on how this should be done. We conducted a construct validation study of the Physiotherapy Evidence Database (PEDro) scale, which is widely used to assess the quality of trials in physical therapy and rehabilitation.MethodsWe analyzed 345 trials that were included in Cochrane reviews and for which a PEDro summary score was available. We used one‐ and two‐parameter logistic item response theory (IRT) models to study the psychometric properties of the PEDro scale and assessed the items' difficulty and discrimination parameters. We ran goodness of fit post estimations and examined the IRT unidimensionality assumption with a multidimensional IRT (MIRT) model.ResultsOut of a maximum of 10, the mean PEDro summary score was 5.46 (SD = 1.51). The allocation concealment and intention‐to‐treat scale items contributed most of the information on the underlying construct (with discriminations of 1.79 and 2.05, respectively) at similar difficulties (0.63 and 0.65, respectively). The other items provided little additional information and did not distinguish trials of different quality. There was substantial evidence of departure from the unidimensionality assumption, suggesting that the PEDro items relate to more than one latent trait.ConclusionsOur findings question the construct validity of the PEDro scale to assess the methodological quality of clinical trials. PEDro summary scores should not be used; rather, the physiotherapy community should consider working with the individual items of the scale.

An Item Response Theory Analysis of DSM-5 Heroin Use Disorder in a Clinical Sample of Chinese Adolescents.

The study examined the dimensionality and psychometric properties of Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5) criteria for heroin use disorder in a clinical sample of Chinese adolescents using item response theory approach. We examined 168 adolescents aged 14.8–17.9 years, who were in treatment for heroin use disorder. A two-parameter logistic item response theory model was conducted to examine the severity and discrimination of DSM-5 criteria for heroin use disorder. Differential item functioning across age and ethnicity was assessed. Results supported the hypothesis that the DSM-5 criteria for heroin use disorder were arrayed an underlying unitary dimension of severity in clinical adolescents. All the items exhibited good discriminatory power in distinguishing between clinical adolescent heroin users. Although three criteria exhibited measurement non-invariance at the item level, the overall DSM-5 heroin use disorder diagnostic criteria set appears to achieve measurement invariance at the scale level.

Development and validation of a Chinese character acquisition assessment for second-language kindergarteners

Demand for second-language (L2) Chinese education for kindergarteners has grown rapidly, but little is known about these kindergarteners’ L2 skills, with existing studies focusing on school-age populations and alphabetic languages. Accordingly, we developed a six-subtest Chinese character acquisition assessment to measure L2 kindergarteners’ abilities to make associations among the forms, sounds, and meanings of 40 Chinese characters, and administered it to 173 five- and six-year-old L2 kindergarteners in Hong Kong. We found a high model-to-data fit using the two-parameter logistic item response theory model ( MSinfit= .87 to 1.07, ps &gt; .41). Of the 40 items, 36 exhibited a range of difficulty and good discrimination. Internal consistency reliability and inter-rater reliability were also high. The children scored highest in the category of meaning-sound associations, followed by mapping from meaning to form. The results demonstrate that the instrument is adequately valid and reliable for assessing L2 kindergarteners’ character acquisition and imply that child L2 learners may develop abilities to map meanings and sounds prior to their development of form-related mapping. With minor modifications, the developed instrument can be used in various child Chinese L2 programs around the world.

The Development and Validation of an Online Spatial Network Measure.

Planning is an essential cognitive process of executive functions and is considered as one of the most important brain functions. Planning has been extensively studied in the field of neuropsychology, but there is a lack of computerized assessment tools of planning ability that are easily accessible to researchers and clinicians. The present study aims to validate a newly developed online spatial network test that is designed for both clinical and nonclinical populations. Exploratory factor analysis revealed a unidimensional factorial structure with moderate to high internal consistency in the test. Two-parameter logistic item response theory analysis showed acceptable item and model fit and no violation of the local independence assumption. The overall success rate exhibited a positive correlation with the performance of planning before attempting to solve the items. After correcting for attenuation, moderate to high correlations were found between the spatial network test and the International Cognitive Ability Resource 16 short form cognitive ability test and the automated perceptual maze test, respectively, demonstrating convergent, discriminant, and criterion validity. Future directions and potential applications of the spatial network test as an assessment tool to measure planning for researchers and clinicians are discussed in the end.

A Note on the Conversion of Item Parameters Standard Errors

The relations among alternative parameterizations of the binary factor analysis (FA) model and two-parameter logistic (2PL) item response theory (IRT) model have been thoroughly discussed in literature. However, the conversion formulas widely available are mainly for transforming parameter estimates from one parameterization to another. There is a lack of discussion about the standard error (SE) conversion among different parameterizations, when SEs of IRT model parameters are often of immediate interest to practitioners. This article provides general formulas for computing the SEs of transformed parameter values, when these parameters are transformed from FA to IRT models. These formulas are suitable for unidimensional 2PL, multidimensional 2PL, and bi-factor 2PL models. A simulation study is conducted to verify the formula by providing empirical evidence. A real data example is given in the end for an illustration.

Careful with Those Priors: A Note on Bayesian Estimation in Two-Parameter Logistic Item Response Theory Models

ABSTRACTThis study examined the use of Bayesian analysis methods for the estimation of item parameters in a two-parameter logistic item response theory model. Using simulated data under various design conditions with both informative and non-informative priors, the parameter recovery of Bayesian analysis methods were examined. Overall results showed that the Bayesian estimates obtained with both informative and non-informative priors exhibited varying levels of bias ranging in most cases from moderate to severe bias. Results are discussed in light of these findings and recommendations concerning the use of priors in empirical research are provided.

Development of the Healthcare Triggering Questionnaire in adult sexual abuse survivors.

One in 4 women and 1 in 10 men in the United States are survivors of sexual abuse (SA). For these survivors, healthcare experiences may trigger memories, thoughts, feelings or sensations related to this past abuse. Such triggering can be associated with negative responses to healthcare (e.g., anxiety, avoidance). However, to date, no healthcare triggering assessment tool exists. Therefore, the study goal was to describe the prevalence of healthcare triggering, to develop a brief Healthcare Triggering Questionnaire (HTQ), and to examine its initial validity. An initial pool of 117 items was developed based on previous research. Two-parameter logistic item response theory models were used to develop the scales. SA survivors [male (n = 233), female (n = 222)] and a comparison group of non-SA individuals [male (n = 114), female (n = 106)] were recruited through Amazon Mechanical Turk and completed the study anonymously online. Three 10-item scales were developed: (a) the HTQ-M for males; (b) the HTQ-F for females; and (c) the HTQ-U (unisex) for all respondents. The results supported the utility and initial validity of the gender-specific and unisex scales. The HTQ scales are a psychometrically sound approach to evaluating healthcare triggering experienced by adult sexual abuse survivors. The HTQ may be considered for use by researchers interested in studying healthcare triggering, healthcare retraumatization, and healthcare adherence. The HTQ may also be of use to clinicians interested in identifying trauma survivors who are more likely to experience triggering in healthcare settings. (PsycINFO Database Record

Item Response Theory for Medical Educationists

Item analysis (IA) is commonly used to describe difficulty and discrimination indices of multiple true-false (MTF) questions. However, item analysis is basically a plain descriptive analysis with limited statistical value. Item response theory (IRT) can provide a better insight into the difficulty and discriminating ability of questions in a test. IRT consists of a collection of statistical models that allows evaluation of test items (questions) and test takers (examinees) at the same time. Specifically, this article focuses on two-parameter logistic IRT (2-PL IRT) model that is concerned with estimation of difficulty and discrimination parameters. This article shows how 2-PL IRT analysis is performed in R software environment, guides the interpretation of the IRT results and compares the results to IA on a sample of MTF questions.

Commitment to Islam in Kazakhstan and Kyrgyzstan: An Item Response Theory Analysis

ABSTRACTWorthington conceptualized a model of religiosity assessment. The dimensions of the model include Religious Norms, Religious Doctrine, and Authority of Leaders. A 10-item scale for Islamic religious assessment was constructed and administered in Kazakhstan and Kyrgyzstan. First-order factor analysis conducted on the 10 items of the religiosity scale revealed factorial structure corresponding to Worthington’s model. A second-order factor analysis assured 1 underlying latent trait. Two-parameter logistic item response theory models were fit to responses collected in Kazakhstan and Kyrgyzstan. Results supported psychometric soundness of the instrument. The items on the scale revealed excellent discrimination properties between the populations of high and low religious commitment. The study offers a short, practical scale for assessment of commitment to Islam in Central Asian countries.

A Hierarchical Multi-Unidimensional IRT Approach for Analyzing Sparse, Multi-Group Data for Integrative Data Analysis.

The present paper proposes a hierarchical, multi-unidimensional two-parameter logistic item response theory (2PL-MUIRT) model extended for a large number of groups. The proposed model was motivated by a large-scale integrative data analysis (IDA) study which combined data (N = 24,336) from 24 independent alcohol intervention studies. IDA projects face unique challenges that are different from those encountered in individual studies, such as the need to establish a common scoring metric across studies and to handle missingness in the pooled data. To address these challenges, we developed a Markov chain Monte Carlo (MCMC) algorithm for a hierarchical 2PL-MUIRT model for multiple groups in which not only were the item parameters and latent traits estimated, but the means and covariance structures for multiple dimensions were also estimated across different groups. Compared to a few existing MCMC algorithms for multidimensional IRT models that constrain the item parameters to facilitate estimation of the covariance matrix, we adapted an MCMC algorithm so that we could directly estimate the correlation matrix for the anchor group without any constraints on the item parameters. The feasibility of the MCMC algorithm and the validity of the basic calibration procedure were examined using a simulation study. Results showed that model parameters could be adequately recovered, and estimated latent trait scores closely approximated true latent trait scores. The algorithm was then applied to analyze real data (69 items across 20 studies for 22,608 participants). The posterior predictive model check showed that the model fit all items well, and the correlations between the MCMC scores and original scores were overall quite high. An additional simulation study demonstrated robustness of the MCMC procedures in the context of the high proportion of missingness in data. The Bayesian hierarchical IRT model using the MCMC algorithms developed in the current study has the potential to be widely implemented for IDA studies or multi-site studies, and can be further refined to meet more complicated needs in applied research.

New English and Spanish social health measures will facilitate evaluating health determinants.

To develop psychometrically sound, culturally relevant, and linguistically equivalent English and Spanish self-report measures of social health guided by a comprehensive conceptual model and applicable across chronic illnesses. The Patient-Reported Outcomes Measurement Information System (PROMIS) Social Health Workgroup implemented a mixed methods approach to evaluate earlier results (v1.0); expand and refine domain definitions and items; translate items into Spanish; and obtain qualitative feedback. Computer-based and paper/pencil questionnaire administration was conducted with a variety of U.S. respondent samples during 2009-2012. Analyses included exploratory factor analysis (EFA), confirmatory factor analysis (CFA), two-parameter logistic item response theory (IRT) modeling, evaluation of differential item functioning (DIF), and evaluation of criterion and construct validity. Qualitative feedback supported the conceptualization of the Social Health domain framework (Social Function and Social Relationships subcomponents). Validation testing participants (n = 2,208 English; n = 644 Spanish) were diverse in terms of gender, age, education, and ethnicity/race. EFA, CFA, and IRT identified 7 unidimensional factors with good model fit. There was no DIF by language, and good evidence of criterion and construct validity. PROMIS English and Spanish language instruments (v2.0), including computer-adaptive tests and fixed-length short forms, are publicly available for assessment of Social Function (Ability to Participate in Social Roles and Activities, and Satisfaction with Social Roles and Activities) and Social Relationships (Companionship; Emotional, Informational and Instrumental Support; and Social Isolation). Measures of social health will play a key role in applications that use ecologic (or determinants of health) models that emphasize how patients' social environments influence their health.