We got this: Evaluating racial socialization competency among diverse ethnic-racial groups

Historically, research on racial socialization (RS) has centered on frequency, beliefs, and content of parent-child communications, with varied applications and implications across racial and ethnic subgroups. The Racial Socialization Competency Scale (RaSCS; Anderson et al., 2020) was developed to assess three dimensions of a novel construct, RS competency (confidence, skills, stress), among Black caregivers. In this article, we investigated the psychometric properties of the RaSCS across diverse ethnic-racial groups. Participants were 778 caregivers (Mage = 44.4 years) of youth between the ages of 10 and 18 recruited from across the United States. The sample was intentionally racially and ethnically diverse, with 26.1% identifying as Black, 24.2% identifying as Latinx, 24.9% identifying as Asian American, and 24.8% identifying as White. Confirmatory factor analyses replicated the previously identified structure of the RaSCS subscales, and scores were reliable. Multigroup measurement invariance analyses supported full scalar invariance across the four racial/ethnic subgroups for the Confidence, Skills, and General RS Stress subscales and partial scalar invariance for the Call to Action RS Stress subscale. These findings suggest that the RaSCS is an appropriate tool for assessing RS competency across racial and ethnic groups and that RS competency as a universal construct is relevant across groups. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The moral distress and resilience among emergency nurses in Arar city: Saudi Arabia

BACKGROUND

Understanding moral distress and resilience is crucial for supporting the well-being of emergency nursing staff and improving patient care. However, there is limited research specifically examining moral distress and resilience among emergency nursing staff in ARAR city hospitals.

AIMS

This study aims to examine moral distress and resilience levels among emergency nursing staff in ARAR city hospitals. Specifically, the study seeks to determine the correlation between moral distress and resilience among emergency nursing staff and examine differences in the levels of moral distress and resilience among different demographic and occupational characteristics.

METHODS

A cross-sectional study design was employed, involving a non-probability stratified sample of emergency nursing staff from two hospitals in ARAR city. The participants completed a Brazilian Moral Distress Scale in Nurses (MDSN-BR) and Rushton Moral Resilience Scale in Nurses (RMRS). Statistical analyses, including descriptive statistics and one-way- ANOVA, were conducted to analyze the data.

RESULTS

The study found that emergency nursing had a moderate level of moral distress, with a mean frequency of 2.70 (SD = 1.02) and a mean intensity of 2.79 (SD = 1.04). The overall self-reported moral resilience was also moderate, with a mean score of 2.48 (SD = 0.77). Significant positive correlations were observed between resilience and both moral distress frequency (r = 0.48, p = 0.001) and intensity (r = 0.48, p = 0.001). Educational levels and nursing positions were associated with variations in moral distress and resilience. Postgraduate diploma emergency nursing reported the highest levels of moral distress frequency (3.12, SD = 1.14) and intensity (3.21, SD = 1.16). A bachelor's degree in nursing exhibited higher levels of personal integrity (3.06, SD = 0.87), while a master's degree in nursing showed higher levels of moral efficacy (2.88, SD = 1.09). Head nurses experienced higher levels of moral distress compared to other positions (3.08, SD = 1.37 for frequency; 3.18, SD = 1.29 for intensity).

CONCLUSION

The study revealed that emergency nursing experienced relatively moderate levels of moral distress, which could be attributed to insufficient multidisciplinary teams and unprepared actions. The findings also highlighted moderate levels of moral resilience, particularly in relational integrity. Educational levels and nursing positions were found to influence moral distress and resilience. These results underscore the need for targeted interventions to support the well-being of emergency nurses and enhance ethical decision-making.

Reliability and validity of the training satisfaction questionnaire for family members (TSQ-FM) entering the ICU during an isolation disease outbreak

BACKGROUND

The presence of family members in an isolated ICU during an isolation disease outbreak is restricted by hospital policies because of the infectious risk. This can be overcome by conferring to family members the skill and the ability to safely don and doff the personal protective equipment (PPE) through a nurse-led training intervention and assess their satisfaction, to respond to the need to define a safe, effective and quality care pathway focused on Family-Centered Care (FCC) principles.

OBJECTIVE

the study aimed to build a valid and reliable instrument for clinical practice to assess family members' satisfaction to allow ICU nurses to restore family integrity in any case of infectious disease outbreak that requires isolation.

METHODS

A cross-sectional study was conducted to test the psychometric properties. The questionnaire was constructed based on a literature review on the needs of family members in the ICU. 76 family members were admitted to a COVID-ICU. Cronbach's coefficient, Geomin rotated loading, and EFA were applied to assess the reliability and validity of the instrument.

RESULTS

The Kaiser-Mayer-Olkin (KMO) measure was 0.662, the Bartlett sphericity test showed a significant p-value (χ²=448.33; df=45; p < 0.01), Cronbach's alpha coefficient was.896. A further CFA analysis confirmed that all fit indices were acceptable. The results showed satisfactory validity and reliability, which could be generalized and extended to any outbreak of isolation disease.

CONCLUSIONS

This study provides a valid and reliable instrument for clinical practice to maintain family integrity in the dyadic relationship between the patient and the family member, even during an emergency infectious disease outbreak that requires isolation.

Validation of the Chinese version of the Fear of Birth Scale among pregnant women

AIM

Adapt Fear of Birth Scale (FOBS) for the Chinese context, evaluate psychometric properties and determine optimal cutoff point for pregnant women in 3rd trimester.

DESIGN

This is a descriptive cross-sectional study. Cultural guidelines informed the development of the Chinese version of FOBS (FOBS-C) incorporating validation on translation, equivalence index, content validity index, and cognitive debriefing. Thirty pregnant women took a test-retest survey and another 1019 took three cross-sectional surveys. Convergent validation of the FOBS-C involved comparison with Childbirth Attitudes Questionnaire (CAQ), Wijma Delivery Expectancy Questionnaire (WDEQ-A), Edinburgh Postnatal Depression Scale (EPDS), Generalized Anxiety Disorder Scale (GAD-7), and physiological indicators. Cutoff points for FOBS-C were identified using receiver operating characteristic analysis against medical indicators.

FINDINGS

FOBS-C demonstrated high translation equivalence (0.833-1), content validity (0.800-0.933), internal consistency (0.897), and test-retest reliability (0.860). Convergent validity was supported by statistically significant correlations between FOBS scores, heart rate, skin conductance changes, as well as scores from WDEQ-A, CAQ, EPDS, and GAD-7. Known-group validity was observed with different medical indicators. FOBS-C cutoff points indicating severe fear of childbirth were identified as 65, 68, 71, and 56, respectively, against WDEQ-A ≥ 85, CAQ ≥ 52, preference for C-section birth, and preference for analgesia, demonstrating known-group validity. A cutoff point of 65 showed the FOBS-C's strongest known-group validity.

CONCLUSION

The FOBS-C exhibits robust psychometric properties, making it a valid screening tool for identifying severe fear of birth. Establishing a cutoff point at 65 facilitates effective screening.

Efficient Corrections for Standardized Person-Fit Statistics

Many popular person-fit statistics belong to the class of standardized person-fit statistics, T, and are assumed to have a standard normal null distribution. However, in practice, this assumption is incorrect since T is computed using (a) an estimated ability parameter and (b) a finite number of items. Snijders (Psychometrika 66(3):331-342, 2001) developed mean and variance corrections for T to account for the use of an estimated ability parameter. Bedrick (Psychometrika 62(2):191-199, 1997) and Molenaar and Hoijtink (Psychometrika 55(1):75-106, 1990) developed skewness corrections for T to account for the use of a finite number of items. In this paper, we combine these two lines of research and propose three new corrections for T that simultaneously account for the use of an estimated ability parameter and the use of a finite number of items. The new corrections are efficient in that they only require the analysis of the original data set and do not require the simulation or analysis of any additional data sets. We conducted a detailed simulation study and found that the new corrections are able to control the Type I error rate while also maintaining reasonable levels of power. A real data example is also included.

Learning Bayesian Networks: A Copula Approach for Mixed-Type Data

Estimating dependence relationships between variables is a crucial issue in many applied domains and in particular psychology. When several variables are entertained, these can be organized into a network which encodes their set of conditional dependence relations. Typically however, the underlying network structure is completely unknown or can be partially drawn only; accordingly it should be learned from the available data, a process known as structure learning. In addition, data arising from social and psychological studies are often of different types, as they can include categorical, discrete and continuous measurements. In this paper, we develop a novel Bayesian methodology for structure learning of directed networks which applies to mixed data, i.e., possibly containing continuous, discrete, ordinal and binary variables simultaneously. Whenever available, our method can easily incorporate known dependence structures among variables represented by paths or edge directions that can be postulated in advance based on the specific problem under consideration. We evaluate the proposed method through extensive simulation studies, with appreciable performances in comparison with current state-of-the-art alternative methods. Finally, we apply our methodology to well-being data from a social survey promoted by the United Nations, and mental health data collected from a cohort of medical students. R code implementing the proposed methodology is available at https://github.com/FedeCastelletti/bayes_networks_mixed_data .

Mental Health Diagnoses on the Mini International Psychiatric Interview Are Associated With Higher Scores on the Edinburgh Postnatal Depression Scale

OBJECTIVE

To understand if Mini International Psychiatric Interview (MINI) scores in pregnancy are associated with higher scores on the Edinburgh Postnatal Depression Scale (EPDS).

DESIGN

Cross-sectional pilot study of participants who completed the EPDS during pregnancy and were then invited to complete the MINI.

SETTING/LOCAL PROBLEM

An urban outpatient clinic at an academic medical setting from November 2020 to June 2021.

PARTICIPANTS

Convenience sample of 20 pregnant people.

INTERVENTION/MEASUREMENTS

Analysis of variance was used to examine differences based on EPDS scores and MINI symptom burden. Nonparametric tests (Mann-Whitney U or Kruskal-Wallis test) were used if assumptions were violated. Descriptive statistics were used to describe sample characteristics.

RESULTS

Nine participants screened 9 or higher on the EPDS and completed the MINI. There were no significant differences in demographic variables by EPDS score. There were significant differences between demographic variables, including employment status (p = .003) and type of health insurance (p = .019), between participants who met criteria for at least one diagnosis on the MINI and those who did not. Participants with public health insurance met the criteria for four more diagnoses compared to people with private insurance. Participants not employed full-time had nearly five more diagnoses compared to those employed full-time. Higher EPDS scores were correlated with all measured MINI symptoms or diagnoses. Higher EPDS scores were significantly correlated with and showed a moderate to strong positive correlation to suicidality and antisocial personality disorder.

CONCLUSION

Pregnant individuals who score 9 or higher on the EPDS may also have other severe mental health diagnoses. Recognizing perinatal mood and anxiety disorders in this population can inform the development of screening protocols and interventions during pregnancy to improve maternal access to mental health treatment and symptom reduction.

Measures of Agreement with Multiple Raters: Fréchet Variances and Inference

Most measures of agreement are chance-corrected. They differ in three dimensions: their definition of chance agreement, their choice of disagreement function, and how they handle multiple raters. Chance agreement is usually defined in a pairwise manner, following either Cohen's kappa or Fleiss's kappa. The disagreement function is usually a nominal, quadratic, or absolute value function. But how to handle multiple raters is contentious, with the main contenders being Fleiss's kappa, Conger's kappa, and Hubert's kappa, the variant of Fleiss's kappa where agreement is said to occur only if every rater agrees. More generally, multi-rater agreement coefficients can be defined in a g-wise way, where the disagreement weighting function uses g raters instead of two. This paper contains two main contributions. (a) We propose using Fréchet variances to handle the case of multiple raters. The Fréchet variances are intuitive disagreement measures and turn out to generalize the nominal, quadratic, and absolute value functions to the case of more than two raters. (b) We derive the limit theory of g-wise weighted agreement coefficients, with chance agreement of the Cohen-type or Fleiss-type, for the case where every item is rated by the same number of raters. Trying out three confidence interval constructions, we end up recommending calculating confidence intervals using the arcsine transform or the Fisher transform.

Post-selection Inference in Multiverse Analysis (PIMA): An Inferential Framework Based on the Sign Flipping Score Test

When analyzing data, researchers make some choices that are either arbitrary, based on subjective beliefs about the data-generating process, or for which equally justifiable alternative choices could have been made. This wide range of data-analytic choices can be abused and has been one of the underlying causes of the replication crisis in several fields. Recently, the introduction of multiverse analysis provides researchers with a method to evaluate the stability of the results across reasonable choices that could be made when analyzing data. Multiverse analysis is confined to a descriptive role, lacking a proper and comprehensive inferential procedure. Recently, specification curve analysis adds an inferential procedure to multiverse analysis, but this approach is limited to simple cases related to the linear model, and only allows researchers to infer whether at least one specification rejects the null hypothesis, but not which specifications should be selected. In this paper, we present a Post-selection Inference approach to Multiverse Analysis (PIMA) which is a flexible and general inferential approach that considers for all possible models, i.e., the multiverse of reasonable analyses. The approach allows for a wide range of data specifications (i.e., preprocessing) and any generalized linear model; it allows testing the null hypothesis that a given predictor is not associated with the outcome, by combining information from all reasonable models of multiverse analysis, and provides strong control of the family-wise error rate allowing researchers to claim that the null hypothesis can be rejected for any specification that shows a significant effect. The inferential proposal is based on a conditional resampling procedure. We formally prove that the Type I error rate is controlled, and compute the statistical power of the test through a simulation study. Finally, we apply the PIMA procedure to the analysis of a real dataset on the self-reported hesitancy for the COronaVIrus Disease 2019 (COVID-19) vaccine before and after the 2020 lockdown in Italy. We conclude with practical recommendations to be considered when implementing the proposed procedure.

Gamified Assessment of the Emotion Regulation Abilities in Youth: Validation of the REThink Online System

Objective: Emotional problems in the youth population are a major issue that can have a significant negative impact for their future development as adults. Their emotion regulation (ER) abilities represent a preventive measure for those emotional problems. REThink is an online therapeutic game that was proved to be effective in rigorous studies, and is based on the rational emotive behavioral therapy, with seven levels built to train various emotional regulation skills. Each level has a section that can be used for the assessment of the targeted skills within the level. The present study aimed at investigating the reliability and validity of the evaluation modules from the REThink game regarding the assessment of ER abilities in children/adolescents. Methods: In accordance with established guidelines, 110 children and adolescents aged 8-14 years old were recruited. Following parental informed consent, the participants filled out the standard questionnaires and, subsequently, they played the evaluation module of the REThink game. The reliability aspect was investigated by evaluating internal consistency, while validity was evaluated by using concurrent and predictive validity analyses. Results: The results revealed statistically significant positive associations between the game scores obtained by the participants and the emotion regulation scale. In terms of predictive validity, there were significant negative associations between game scores and the presence of emotional and behavioral problems. Moreover, in terms of the reliability of the REThink game, an acceptable value for the internal consistency was observed. Conclusion: In conclusion, the REThink therapeutic game was proved to be a valid measure for assessing emotion regulation abilities in children and adolescents. Clinical Trial Registration No. NCT04788901.

Psychometric Properties of the Healthy Lifestyle Behaviors Scale in Portuguese Pregnant Women

BACKGROUND

Pregnancy provides a privileged and opportune moment to implement interventions promoting healthy lifestyle behaviors and significantly improving perinatal outcomes. The Healthy Lifestyle Behaviors Scale (HLBES) can be used to assess health promoting behaviors, such as diet, physical activity, and mental health.

PURPOSE

This study aimed to examine the psychometric properties of the HLBES in Portuguese pregnant women.

METHODS

A methodological study was conducted on a convenience sample of 192 pregnant women receiving prenatal care. After cross-cultural adaptation, an exploratory factor analysis and internal consistency assessment were carried out to evaluate the psychometric properties of the scale. Data collected included the Healthy Lifestyle Beliefs Scale to assess the HLBES' criterion validity.

RESULTS

Exploratory factor analysis with Varimax rotation yielded 2 subscales that explained 45.23% of the total variance. The scale revealed an overall internal consistency of 0.78 and a good criterion validity with the Healthy Lifestyle Beliefs Scale (r = 0.65, P < .01).

CONCLUSION

Our results suggest that the HLBES is an instrument for reporting healthy lifestyle behaviors in Portuguese pregnant women; however, further studies are recommended. This scale can be used to not only describe healthy lifestyle behaviors in pregnant women but also to determine the effects of health promoting interventions.

Restricted Latent Class Models for Nominal Response Data: Identifiability and Estimation

Restricted latent class models (RLCMs) provide an important framework for diagnosing and classifying respondents on a collection of multivariate binary responses. Recent research made significant advances in theory for establishing identifiability conditions for RLCMs with binary and polytomous response data. Multiclass data, which are unordered nominal response data, are also widely collected in the social sciences and psychometrics via forced-choice inventories and multiple choice tests. We establish new identifiability conditions for parameters of RLCMs for multiclass data and discuss the implications for substantive applications. The new identifiability conditions are applicable to a wealth of RLCMs for polytomous and nominal response data. We propose a Bayesian framework for inferring model parameters, assess parameter recovery in a Monte Carlo simulation study, and present an application of the model to a real dataset.

Bayesian Semiparametric Longitudinal Inverse-Probit Mixed Models for Category Learning

Understanding how the adult human brain learns novel categories is an important problem in neuroscience. Drift-diffusion models are popular in such contexts for their ability to mimic the underlying neural mechanisms. One such model for gradual longitudinal learning was recently developed in Paulon et al. (J Am Stat Assoc 116:1114-1127, 2021). In practice, category response accuracies are often the only reliable measure recorded by behavioral scientists to describe human learning. Category response accuracies are, however, often the only reliable measure recorded by behavioral scientists to describe human learning. To our knowledge, however, drift-diffusion models for such scenarios have never been considered in the literature before. To address this gap, in this article, we build carefully on Paulon et al. (J Am Stat Assoc 116:1114-1127, 2021), but now with latent response times integrated out, to derive a novel biologically interpretable class of 'inverse-probit' categorical probability models for observed categories alone. However, this new marginal model presents significant identifiability and inferential challenges not encountered originally for the joint model in Paulon et al. (J Am Stat Assoc 116:1114-1127, 2021). We address these new challenges using a novel projection-based approach with a symmetry-preserving identifiability constraint that allows us to work with conjugate priors in an unconstrained space. We adapt the model for group and individual-level inference in longitudinal settings. Building again on the model's latent variable representation, we design an efficient Markov chain Monte Carlo algorithm for posterior computation. We evaluate the empirical performance of the method through simulation experiments. The practical efficacy of the method is illustrated in applications to longitudinal tone learning studies.

What Can We Learn from a Semiparametric Factor Analysis of Item Responses and Response Time? An Illustration with the PISA 2015 Data

It is widely believed that a joint factor analysis of item responses and response time (RT) may yield more precise ability scores that are conventionally predicted from responses only. For this purpose, a simple-structure factor model is often preferred as it only requires specifying an additional measurement model for item-level RT while leaving the original item response theory (IRT) model for responses intact. The added speed factor indicated by item-level RT correlates with the ability factor in the IRT model, allowing RT data to carry additional information about respondents' ability. However, parametric simple-structure factor models are often restrictive and fit poorly to empirical data, which prompts under-confidence in the suitablity of a simple factor structure. In the present paper, we analyze the 2015 Programme for International Student Assessment mathematics data using a semiparametric simple-structure model. We conclude that a simple factor structure attains a decent fit after further parametric assumptions in the measurement model are sufficiently relaxed. Furthermore, our semiparametric model implies that the association between latent ability and speed/slowness is strong in the population, but the form of association is nonlinear. It follows that scoring based on the fitted model can substantially improve the precision of ability scores.

Psychometric validation of the PERMA-profiler for well-being in Chinese adults

Well-being is one of the central topics in psychology, and research on this topic has shifted from emotional experiences to flourishing life in recent years. Seligman's PERMA model is a prominent theory in this shift. However, this model is proposed in Western culture and has yet to be empirically validated in the Chinese context. The present research aims to examine the applicability of the five-dimension PERMA-Profiler in Chinese culture, which has been developed based on the PERMA model. A sample of 1468 Chinese adults participated in the research. After translation and validation, a series of psychometric analyses were conducted to examine the internal consistency reliability, construct validity, convergent and discriminant validity, and factorial invariance across genders. The PERMA-Profiler Chinese showed high Cronbach's alpha coefficients (α = 0.79-0.88), good divergent (r = -0.19 to -0.38) and convergent validity (r = 0.53-0.85), as well as satisfactory structural validity. Results of the structural validity demonstrated a better fit to the first-order model with five correlated factors after modification (χ2/df = 4.65, RMSEA = 0.058, SRMR = 0.030, CFI = 0.943, TLI = 0.924) than the second-order model with a higher-order factor of well-being. However, the engagement dimension of the PERMA-Profiler Chinese could be improved further. In conclusion, the PERMA model is applicable to the Chinese culture, and the PERMA-Profiler provides a valid measure of well-being for Chinese adults.

Psychometric properties of disease-specific health-related quality of life instruments for food allergy: A COnsensus-based Standards for the selection of health Measurement INstruments-based systematic review

Food allergies severely impact the health-related quality of life (HRQoL) of patients and their caregivers (family or informal caregivers). Currently there is no comprehensive review to provide an overview and critical assessment of the instruments in the field. Six databases were searched from inception until 10 August 2023, and a combination of subject terms and free words was used to search the literature. We used the COnsensus-based Standards for the selection of health Measurement INstruments methodology (COSMIN) to evaluate the measurement properties of the instruments. Forty-one studies reported on ten eligible instruments. Based on COSMIN guidelines, one instrument was recommended for Grade A, and the remaining nine instruments were recommended for Grade B. The Grade A instrument identified, the Food Allergy Quality of Life Questionnaire-Parent Form (FAQLQ-PF), can help researchers assess the effectiveness of treatment for patients with food allergy and to understand the psychosocial impact of the disease on patients.

A Spectral Method for Identifiable Grade of Membership Analysis with Binary Responses

Grade of membership (GoM) models are popular individual-level mixture models for multivariate categorical data. GoM allows each subject to have mixed memberships in multiple extreme latent profiles. Therefore, GoM models have a richer modeling capacity than latent class models that restrict each subject to belong to a single profile. The flexibility of GoM comes at the cost of more challenging identifiability and estimation problems. In this work, we propose a singular value decomposition (SVD)-based spectral approach to GoM analysis with multivariate binary responses. Our approach hinges on the observation that the expectation of the data matrix has a low-rank decomposition under a GoM model. For identifiability, we develop sufficient and almost necessary conditions for a notion of expectation identifiability. For estimation, we extract only a few leading singular vectors of the observed data matrix and exploit the simplex geometry of these vectors to estimate the mixed membership scores and other parameters. We also establish the consistency of our estimator in the double-asymptotic regime where both the number of subjects and the number of items grow to infinity. Our spectral method has a huge computational advantage over Bayesian or likelihood-based methods and is scalable to large-scale and high-dimensional data. Extensive simulation studies demonstrate the superior efficiency and accuracy of our method. We also illustrate our method by applying it to a personality test dataset.

Measurement invariance across countries of the Test of Memory Strategies (TMS): A contribution to the cross-national validity study

Previous literature showed a complex interpretation of recall tasks due to the complex relationship between Executive Functions (EF) and Long Term Memory (M). The Test of Memory Strategies (TMS) could be useful for assessing this issue, because it evaluates EF and M simultaneously. This study aims to explore the validity of the TMS structure, comparing the models proposed by Vaccaro et al. (2022) and evaluating the measurement invariance according to three countries (Italy, Spain, and Portugal) through Confirmatory Factor Analysis (CFA). Four hundred thirty-one healthy subjects (Age mean = 54.84, sd = 20.43; Education mean = 8.85, sd =4.05; M = 177, F = 259) were recruited in three countries (Italy, Spain, and Portugal). Measurement invariance across three country groups was evaluated through Structural Equation modeling. Also, convergent and divergent validity were examined through the correlation between TMS and classical neuropsychological tests. CFA outcomes suggested that the best model was the three-dimensional model, in which list 1 and list2 reflect EF, list 3 reflects a mixed factor of EF and M (EFM) and list4 and list5 reflect M. This result is in line with the theory that TMS decreases EF components progressively. TMS was metric invariant to the country, but scalar invariance was not tenable. Finally, the factor scores of TMS showed convergent validity with the classical neuropsychological tests. The overall results support cross-validation of TMS in the three countries considered.

Psychosocial Competencies Among Clinic-Referred and Community-Based Children: Known-Groups Validity of the Psychosocial Strengths Inventory for Children and Adolescents (PSICA)

Child psychosocial competencies protect against the development of psychopathology, ameliorate existing psychosocial problems, and predict positive long-term developmental cascades. Assessment of these competencies can improve identification of children in need of psychosocial services, enrich treatment planning, and improve treatment progress and outcome monitoring. Yet, appropriate measures are limited. One promising option is the Psychosocial Strengths Inventory for Children and Adolescents (PSICA), although its discriminative properties were formerly unknown. The present study evaluated the PSICA's sensitivity, specificity, and optimal cutoff scores with 228 youth (38 clinic-referred and 190 community-based youth with case-control matching) ages 2-10 years (Mage = 5.8, 71% boys, 77% White). Results indicated large, significant discrepancies, with clinic-referred youth rated as having less overall psychosocial competence overall and across domains of compliance, prosociality, and attention. Caregivers also reported significantly less satisfaction with the psychosocial competence of clinic-referred versus community youth. Discriminative accuracy of the PSICA's Frequency and Satisfaction scales, and its subscales, were good-to-excellent. Such discriminative accuracy and empirically derived, if preliminary, cutoff scores further support the PSICA as a pragmatic, psychometrically strong tool to screen children for referral into services, and potentiate future investigations into the PSICA's use in treatment planning and evaluation.

Assessment of the psychometric properties of the italian version of the midwifery student evaluation of practice (MIDSTEP-IT): A validity and reliability study

BACKGROUND

Clinical learning is a crucial component of the midwifery education program, necessary to support the acquisition of professional abilities through the integration of theoretical and practical learning experiences. Evaluating Bachelor of Midwifery students' perception of their clinical learning experiences is important to improve midwifery educational programs.

AIM

the objective of this study was the translation, cultural adaptation, and validation of the Midwifery Student Evaluation of Practice (MidSTEP) in a group of Italian midwives' students.

METHODS

"Translation and Cultural Adaptation of Patient Reported Outcomes Measures - Principles of Good Practice" guidelines were adopted to achieve the MidSTEP Italian version. Exploratory Factor Analysis was performed. Internal consistency for reliability was assessed using Cronbach's alpha reliability coefficient (α) and Omega coefficient (ω), while Intraclass Correlation Coefficients (ICC) were used to determine if the tool was stable over time.

FINDINGS

The Italian version of MidSTEP (MidSTEP-IT) has good internal consistency: considering the Clinical Learning Environment Scale, Cronbach's α was 0.839 (for the "Skill Development" subscale α was equal to 0.739 and for the "Philosophy of Midwifery Practice" subscale α was equal to 0.825) while considering the Midwifery Preceptor Scale, Cronbach's α was 0.920. Factor analysis does not fully reflect the factorial analysis of the original version.

CONCLUSION

The MidSTEP-IT had been proven to be a valid and reliable tool, easy and fast to administer, that could be effectively helpful for investigating and measuring the Italian midwifery students' perception of their clinical learning experiences, according to the setting and impact of mentors on their professional growth. It is an innovative tool, valuable in both clinical practice and research to highlight the importance of encouraging a supportive clinical learning environment and an efficient preceptorship.

Health-Related Quality of Life in Patients with Spinocerebellar Ataxia: a Validation Study of the EQ-5D-3L

Although health-related quality of life (HRQoL) has developed into a crucial outcome parameter in clinical research, evidence of the EQ-5D-3L validation performance is lacking in patients with spinocerebellar ataxia (SCA) types 1, 2, 3, and 6. The objective of this study is to assess the acceptability, validity, reliability, and responsiveness of the EQ-5D-3L. For n = 842 predominantly European SCA patients of two longitudinal cohort studies, the EQ-5D-3L, PHQ-9 (Patient Health Questionnaire), and ataxia-specific clinical assessments (SARA: Scale for Assessment and Rating of Ataxia; ADL: activities of daily living as part of Friedreich's Ataxia Rating Scale; INAS: Inventory of Non-Ataxia Signs) were assessed at baseline and multiple annual follow-ups. The EQ-5D-3L was evaluated regarding acceptability, distribution properties, convergent and known-groups validity, test-retest reliability, and effect size measures to analyze health changes. The non-item response was low (EQ-5D-3L index: 0.8%; EQ-VAS: 3.4%). Ceiling effects occurred in 9.9% (EQ-5D-3L) and 3.0% (EQ-VAS) with a mean EQ-5D-3L index of 0.65 ± 0.21. In total, convergent validity showed moderate to strong Spearman's rho (rs > 0.3) coefficients comparing EQ-5D-3L and EQ-VAS with PHQ-9, SARA, ADL, and INAS. EQ-5D-3L could discriminate between groups of age, SARA, ADL, and INAS. Intra-class correlation coefficients (EQ-5D-3LICC: 0.95/EQ-VASICC: 0.88) and Kappa statistics (range 0.44 to 0.93 for EQ-5D-3L items) indicated tolerable reliability. EQ-5D-3L shows small (effect size < 0.3) to moderate (effect size 0.3-0.59) health changes regarding ataxia severity. The analysis confirms an acceptable, reliable, valid, and responsive recommended EQ-5D-3L in SCA patients, measuring the HRQoL adequately, besides well-established clinical instruments.

Exploratory Procedure for Component-Based Structural Equation Modeling for Simple Structure by Simultaneous Rotation

Generalized structured component analysis (GSCA) is a structural equation modeling (SEM) procedure that constructs components by weighted sums of observed variables and confirmatorily examines their regressional relationship. The research proposes an exploratory version of GSCA, called exploratory GSCA (EGSCA). EGSCA is analogous to exploratory SEM (ESEM) developed as an exploratory factor-based SEM procedure, which seeks the relationships between the observed variables and the components by orthogonal rotation of the parameter matrices. The indeterminacy of orthogonal rotation in GSCA is first shown as a theoretical support of the proposed method. The whole EGSCA procedure is then presented, together with a new rotational algorithm specialized to EGSCA, which aims at simultaneous simplification of all parameter matrices. Two numerical simulation studies revealed that EGSCA with the following rotation successfully recovered the true values of the parameter matrices and was superior to the existing GSCA procedure. EGSCA was applied to two real datasets, and the model suggested by the EGSCA's result was shown to be better than the model proposed by previous research, which demonstrates the effectiveness of EGSCA in model exploration.

Using External Information for More Precise Inferences in General Regression Models

Empirical research usually takes place in a space of available external information, like results from single studies, meta-analyses, official statistics or subjective (expert) knowledge. The available information ranges from simple means and proportions to known relations between a multitude of variables or estimated distributions. In psychological research, external information derived from the named sources may be used to build a theory and derive hypotheses. In addition, techniques do exist that use external information in the estimation process, for example prior distributions in Bayesian statistics. In this paper, we discuss the benefits of adopting generalized method of moments with external moments, as another example for such a technique. Analytical formulas for estimators and their variances in the multiple linear regression case are derived. An R function that implements these formulas is provided in the supplementary material for general applied use. The effects of various practically relevant moments are analyzed and tested in a simulation study. A new approach to robustify the estimators against misspecification of the external moments based on the concept of imprecise probabilities is introduced. Finally, the resulting externally informed model is applied to a dataset to investigate the predictability of the premorbid intelligence quotient based on lexical tasks, leading to a reduction of variances and thus to narrower confidence intervals.

On the Identifiability of 3- and 4-Parameter Item Response Theory Models From the Perspective of Knowledge Space Theory

The present work aims at showing that the identification problems (here meant as both issues of empirical indistinguishability and unidentifiability) of some item response theory models are related to the notion of identifiability in knowledge space theory. Specifically, that the identification problems of the 3- and 4-parameter models are related to the more general issues of forward- and backward-gradedness in all items of the power set, which is the knowledge structure associated with IRT models under the assumption of local independence. As a consequence, the identifiability problem of a 4-parameter model is split into two parts: a first one, which is the result of a trade-off between the left-side added parameters and the remainder of the Item Response Function, e.g., a 2-parameter model, and a second one, which is the already well-known identifiability issue of the 2-parameter model itself. Application of the results to the logistic case appears to provide both a confirmation and a generalization of the current findings in the literature for both fixed- and random-effects IRT logistic models.

Examining the Burden of Self-Blame Attribution Among Women With Cervical Cancer

Background:Self-blame for past sexual behaviors or for the personal character may be associated with the development of cervical cancer. Purpose: Aims were to understand the burden of self-blame attribution (SBA) among women with cervical cancer by (1) examining relationships between SBA, psychological distress (PD), and spiritual well-being (SWB); (2) determining differences between behavioral (BSB) and characterological self-blame (CSB) attribution; and (3) describing associations between SBA and unwanted past sexual experiences. Methods: Women attending a cancer center in the southeastern United Stats (N = 106) completed an online survey including a demographic questionnaire and three instruments: (1) SBA for Cancer Scale; (2) Psychological Distress Subscale of the Psychological Adjustment to Cancer Scale-Self Report; and (3) Functional Assessment of Cancer Therapy-Spiritual Well-being. Results: Women with cervical cancer, 26-64 years of age, identified moderate levels of SBA, PD, and SWB. Relationships were found between PD, BSB and CSB, and unwanted sexual experiences. Significant inverse correlations between religious faith, BSB, unwanted sexual experiences, and SWB were noted. Unwanted sexual experiences were a significant predictor of SBA. Conclusion: SBA places women at risk for increased burden. Recognizing SBA in vulnerable cancer survivors is important to providing holistic nursing care.