Associations between urine glyphosate levels and metabolic health risks: insights from a large cross-sectional population-based study.

BACKGROUND: The prevalence of metabolic syndrome (MetS) in American adults increased from 37.6% in the 2011-12 period to 41.8% in 2017-2018. Environmental exposure, particularly to common compounds such as glyphosate, has drawn increasing attention as a potential risk factor. METHODS: We employed three cycles of data (2013-2018) from the National Health and Nutrition Examination Survey (NHANES) in a cross-sectional study to examine potential associations between urine glyphosate measurements and MetS incidence. We first created a MetS score using exploratory factor analysis (EFA) of the International Diabetes Federation (IDF) criteria for MetS, with data drawn from the 2013-2018 NHANES cycles, and validated this score independently on an additional associated metric, the albumin-to-creatinine (ACR) ratio. The score was validated via a machine learning approach in predicting the ACR score via binary classification and then used in multivariable regression to test the association between quartile-categorized glyphosate exposure and the MetS score. RESULTS: In adjusted multivariable regressions, regressions between quartile-categorized glyphosate exposure and MetS score showed a significant inverted U-shaped or saturating dose‒response profile, often with the largest effect for exposures in quartile 3. Exploration of potential effect modification by sex, race, and age category revealed significant differences by race and age, with older people (aged > 65 years) and non-Hispanic African American participants showing larger effect sizes for all exposure quartiles. CONCLUSIONS: We found that urinary glyphosate concentration is significantly associated with a statistical score designed to predict MetS status and that dose-response coefficient is nonlinear, with advanced age and non-Hispanic African American, Mexican American and other Hispanic participants exhibiting greater effect sizes.

Psychometric evaluation of the Japanese neck disability index by exploratory factor analysis in preoperative patients with cervical spondylotic myelopathy: impact of pain and numbness.

BACKGROUND CONTEXT: The Neck Disability Index (NDI), a common Patient-Reported Outcome Measure (PROM) for neck pain, lacks sufficient study on its psychometric properties in preoperative patients with cervical spondylotic myelopathy (CSM). PURPOSE: This study aims to address these gaps by conducting an exploratory factor analysis of the Japanese NDI. The objectives are 2-fold: (1) to scrutinize the psychometric properties and internal consistency of the Japanese NDI, and (2) to explore the specific regions of pain and numbness influencing the NDI. STUDY DESIGN/SETTING: A single-center observational study. PATIENT SAMPLE: A total of 100 preoperative patients with CSM. OUTCOME MEASURES: The NDI and Numerical Rating Scale (NRS) were employed to assess preoperative neck disability and pain and numbness in various body regions. METHODS: Demographic and clinical characteristics were collected, encompassing age, sex, body mass index, American Society of Anesthesiologists classification, smoking status, comorbidities, pain and numbness at various sites using the NRS, and NDI. For evaluating the psychometric properties and internal consistency of the NDI, exploratory factor analysis (EFA) and Cronbach's α coefficient were utilized. Furthermore, the impact of pain and numbness on NDI factors was examined through multivariable regression analysis. RESULTS: EFA identified 2 factors-Physical and Mental-highlighting the dual nature of neck-related disability. Physical factors (std.ß=0.724, p<.001) exerted a stronger impact on NDI scores compared to Mental factors (std.ß=0.409, p<.001). Cronbach's α coefficient was 0.831 for physical factors and 0.723 for mental factors, indicating a high level of internal consistency. Numbness in the hand (std.ß=0.338, p<.001) and pain in the neck (std.ß=0.202, p=.035) were significant variables influencing Physical factor, while numbness in the hand (std.ß=0.485, p<.001) and pain in the head (std.ß=0.374, p<.001) impacted Mental factor. CONCLUSION: This study contributes valuable insights into the psychometric properties of the NDI in preoperative patients with CSM. The identified factors emphasize the importance of addressing both physical and sensory symptoms in preoperative care.

Stakeholders' perspectives on critical success factors for environmental social and governance (ESG) implementation.

Environmental Social and Governance (ESG) has emerged as a sensitive issue, attracting the attention of a large audience that could not be ignored. Government bodies continue to pass regulations mandating organizations to comply with ESG principles. However, many organizations have had unsatisfactory results while promoting sustainability ideals due to various challenges. To achieve ESG goals, the present study offers a thorough framework for ESG implementation across organizations based on the critical success factor (CSF) theory and the opinions of diverse stakeholders. Following a literature review and brainstorming with ESG experts and academicians, a survey questionnaire was sent to 400 respondents to evaluate the 20 factors identified as 'super-set' CSFs for ESG implementation. This paper represents a novel attempt in ESG research as it conducts a survey supported by exploratory factor analysis (EFA). The interactions between the significant CSFs were studied by employing total interpretative structural modeling (TISM) and fuzzy MICMAC approach. ESG implementation is found to be highly driven by firm characteristics, earnings quality, and environmental performance, which can be argued to be the fundamental determinants of ESG implementation. According to these findings, organizations' leadership should (1) focus on effectively structuring firms' attributes to swiftly operate the ESG implementation framework, (2) ensure consistent business earnings that signal improved future performance, and (3) continuously monitor and assess their environmental performance. These efforts should be supported by engaging with diverse stakeholder groups, each playing its respective role in ESG implementation. Consequently, ESG implementation across organizations is anticipated to accelerate with thoughtful organizational coordination, strategic planning, and compliance with authoritative policies. However, rather than solely focusing on creating ESG disclosure laws, policymakers should also focus on creating better ESG outcomes through effective ESG implementation. Therefore, this research offers valuable insights into improving ESG practices, which facilitates the adoption of mandatory ESG disclosure regulations.

Factor structure and reliability of the symptom measurement of post-stroke depression in the rehabilitation stage.

BACKGROUND: The incidence of Post Stroke Depression (PSD) in the Rehabilitation Stage is high, which can bring serious physical and psychological disorders to patients. However, there is still a lack of targeted tools for screening PSD in the rehabilitation stage. Therefore, the aim of this study was to evaluate the factor structure and reliability of a measurement instrument to screen for PSD in the rehabilitation stage. METHODS: A cross-sectional study was conducted on 780 hospitalized stroke patients who were within the rehabilitation stage from May to August 2020. Exploratory factor analysis (EFA) as well as first- and second-order confirmatory factor analysis (CFA) were performed to evaluate the factor structure of the newly developed Symptom Measurement of Post-Stroke Depression in the Rehabilitation Stage (SMPSD-RS). The reliability and validity of the SMPSD-RS were also verified using several statistical methods. RESULTS: EFA extracted a 24-item, five-factor (cognition, sleep, behavior, emotion, and obsession) model that can clinically explain the symptoms of PSD during the rehabilitation stage. A first-order CFA confirmed the EFA model with good model fit indices, and the second-order CFA further confirmed the five-factor structure model and showed acceptable model fit indices. Acceptable reliability and validity were also achieved by the corresponding indicators. CONCLUSION: The SMPSD-RS was proven to have a stable factor structure and was confirmed to be reliable and valid for assessing PSD symptoms in stroke patients during the rehabilitation stage.

Determining Sample Size Requirements in EFA Solutions: A Simple Empirical Proposal.

In unrestricted or exploratory factor analysis (EFA), there is a wide range of recommendations about the size samples should be to attain correct and stable solutions. In general, however, these recommendations are either rules of thumb or based on simulation results. As it is hard to establish the extent to which a particular data set suits the conditions used in a simulation study, the advice produced by simulation studies is not direct enough to be of practical use. Instead of trying to provide general and complex recommendations, in this article, we propose to estimate the sample size that is needed to analyze a data set at hand. The estimation takes into account the specified EFA model. The proposal is based on an intensive simulation process in which the sample correlation matrix is used as a basis for generating data sets from a pseudo-population in which the parent correlation holds exactly, and the criterion for determining the size required is a threshold that quantifies the closeness between the pseudo-population and the sample reproduced correlation matrices. The simulation results suggest that the proposal works well and that the determinants identified agree with those in the literature.

Salivary, lacrimal and nasal (SALANS) measure to assess side effects following radioactive iodine treatment: development, psychometric properties, and factor structure.

PURPOSE: This study aimed to develop and psychometrically evaluate a patient-reported outcome measure (PROM), SAlivary, LAcrimal, NaSal (SALANS), to document patients' symptoms after radioactive iodine (RAI) treatment for differentiated thyroid cancer (DTC). METHODS: We generated and iteratively revised SALANS items based on expert input, focus group discussions and feedback from cognitive testing (n = 17). We administered an initial SALANS measure with 39 items to patients diagnosed with DTC in the past two years (n = 105). Exploratory factor analysis (EFA) examined the factor structure of the SALANS items. We assessed the consistency reliability and related the total and subscale scores of the final SALANS to existing PROMs to assess validity. RESULTS: The final SALANS consisted of 33 items and six subscales (sialadenitis, taste, xerostomia, dry eyes, epiphora, and nasal) with six factors extracted by EFA. The six subscales demonstrated good internal reliability (α range = 0.87-0.92). The SALANS total score showed good convergent validity with the Xerostomia Inventory (r = 0.86) and good discriminant validity with a measure of spirituality (r = - 0.05). The mean SALANS total score was significantly higher (d = 0.5, p < 0.04) among patients who had RAI compared to those who did not have RAI. CONCLUSION: Preliminary evidence suggests that SALANS is a novel and reliable PROM to assess the type and frequency all symptoms experienced after RAI treatment for DTC. Future work is needed to further validate and develop the scale.

Professional autonomy among Registered Nurses-Validation of the translation of the Dempster Practice Behaviour Scale and survey results.

AIM: To test the psychometric properties of the Finnish version of the Dempster Practice Behaviour Scale and explore nurses' professional autonomy along with which characteristics are related to it. DESIGN: An instrument validation and a descriptive cross-sectional study. METHODS: The web-based survey was conducted in September 2021 at two university hospitals in Finland. Exploratory factor analysis (EFA) was used to explore the factor structure of the modified instrument, while Cronbach's α coefficients were calculated to determine the reliability of the scale. Descriptive univariate and multivariate analyses were conducted to examine Registered Nurses' professional autonomy. The study followed STROBE guidelines. RESULTS: During the validation process, the 30 items of the Dempster Practice Behaviour Scale were reduced to 25 items. The S-CVI/Ave for the translated scale was 0.94. When one additional item was omitted from the EFA, the results supported five factors, which explained 45.9% of the total variance. The mean overall autonomy score was 3.63 out of 5, with readiness and empowerment the subscales with the highest and lowest, respectively, mean values. The linear regression models showed that age, nursing experience, unit type, education, shift, and perceptions of the importance of professional autonomy were related to the subscales describing professional autonomy. CONCLUSION: The psychometric testing provided evidence that the translated instrument was reliable. Nurses assessed that they are skilled professionals who are accountable for their actions. However, they experienced rather low levels of professional autonomy in empowerment and valuation. Health care organizations should consider this through authentic leadership and, thus, possibly strengthen professional autonomy.

Factor retention in ordered categorical variables: Benefits and costs of polychoric correlations in eigenvalue-based testing.

An essential step in exploratory factor analysis is to determine the optimal number of factors. The Next Eigenvalue Sufficiency Test (NEST; Achim, 2017) is a recent proposal to determine the number of factors based on significance tests of the statistical contributions of candidate factors indicated by eigenvalues of sample correlation matrices. Previous simulation studies have shown NEST to recover the optimal number of factors in simulated datasets with high accuracy. However, these studies have focused on continuous variables. The present work addresses the performance of NEST for ordinal data. It has been debated whether factor models - and thus also the optimal number of factors - for ordinal variables should be computed for Pearson correlation matrices, which are known to underestimate correlations for ordinal datasets, or for polychoric correlation matrices, which are known to be instable. The central research question is to what extent the problems associated with Pearson correlations and polychoric correlations deteriorate NEST for ordinal datasets. Implementations of NEST tailored to ordinal datasets by utilizing polychoric correlations are proposed. In a simulation, the proposed implementations were compared to the original implementation of NEST which computes Pearson correlations even for ordinal datasets. The simulation shows that substituting polychoric correlations for Pearson correlations improves the accuracy of NEST for binary variables and large sample sizes (N = 500). However, the simulation also shows that the original implementation using Pearson correlations was the most accurate implementation for Likert-type variables with four response categories when item difficulties were homogeneous.

Unveiling the underlying structure of awe in virtual reality and in autobiographical recall: an exploratory study.

Over the last two decades, awe has attracted the attention of an increasing number of researchers. The use of virtual reality has been identified as one of the most effective techniques for eliciting awe, in addition to more personalized methods for inducing emotion, such as autobiographical recall. However, previous measures of awe were unable to uncover the hidden structure of this experience. Awe experience scale (AWE-S) has been validated as a comprehensive measure of contingent awe in English, providing new opportunities for analysis. In this two-phases study, we investigated whether the latent structure of the experience of awe evoked by the autobiographical recall technique (Study 1) overlapped with that induced by exposing participants to a validated virtual reality awe-eliciting training (Study 2). The original English AWE-S structure held both in autobiographical recall induction and virtual reality-based elicitation. Despite evidence of overlap between English and Italian structures, low correlations were found between Italian trait measures used to test the concurrent validity of the AWE-S in the Italian sample and AWE-S state dimensions. This study highlights cultural differences in awe experience, trait, and state variations, and provides new insights into the standardized induction of this emotion through simulated environments.

Academic optimism, capital indicators as predictors of cognitive, affective, and psychomotor learning outcome among students in secondary school. Hierarchical regression approach (HRA).

Background: Studies that were carried out previously on learning outcomes focused mainly on the student's cognitive domain while identifying factors that predicted it. More so, most of the learner's assessments in school are largely dependent on the score obtained from specific subjects by the learner, and efforts to address other domains of instruction such as affective and psychomotor domains have been minimal or absent in regard to the variables selected for the study. This study therefore sought to address that gap by finding out the relative and composite contribution of academic optimism and capital indicators to the learning outcomes (of students. Methods: The study adopted a correlational design with a multistage sampling technique to select a total of 534 senior secondary class II students. Two research instruments, the Academic Optimism and Capital Indicators Scale (AOCIS) and the Learning Outcomes Scale (LOS), were used for data collection. Exploratory and confirmatory factors analysis were used to assess the dimensionality of the items and factor structure of the scales. The psychometric properties obtained for scale were adequate for the instrument to be adjudged valid and reliable.The collected data were analysed using the hierarchical regression approach (HRA). Results: The findings of the study revealed that academic emphasis, collective efficacy, faculty trust, social capital, economic capital, and cultural capital, relatively and jointly, predict overall learning outcomes (cognitive, affective, and psychomotor construct). The result showed that there was an increased proportion of variance with each addition of a predictor to the model. Social capital reduced the percentage change at the initial time, but with the addition of economic capital, the proportion of change increased among others in the subsequent model examination. Conclusion: /implication: The study provides knowledge and empirical evidence that academic optimism and capital indicators, with their dimensions, affect composite learning outcomes among students. This study will help school ministries, policymakers, and curriculum planners make sure that the educational objectives, philosophies, and programmes are planned to reflect the total learner in order to produce the total learner that will effect changes in the society. This study has provided evidence that academic inputs and capital indicators are crucial indices of their learning outcomes in the three area of learning. The ability of the school to emphasise academics, ensure that all school agents are committed to instructional delivery, and gain the trust of parents is crucial for adequate support to enhance students learning outcomes. The outcome has implication for policy development and providing a climate that can stimulate equity, trust and motivation.

The Patient Activation Measure-13 (PAM-13) in an oncology patient population: psychometric properties and dimensionality evaluation.

BACKGROUND: Accurate assessment and enhancement of health-related skills among oncology patients are pivotal for optimizing cancer care. The Patient Activation Measure (PAM-13), a questionnaire designed to reflect an individual's knowledge, skills, and confidence in self-healthcare management, has been validated across diverse countries and settings. Concerns have been raised regarding the cross-situational applicability, as patients with specific diseases and cultural backgrounds interpret questionnaire items differently. This study aimed to examine the structural validity and psychometric properties of the PAM-13 in an oncological patient cohort. METHODS: Baseline data from a longitudinal non-randomized controlled study involving cancer out-patients (n = 1,125) from Comprehensive Cancer Centres in Southern Germany were analysed. The German version of the PAM-13 was employed. With classical test and item response theory methods data quality, reliability, convergent and structural validity, as well as psychometric properties were assessed. Exploratory (EFA) and confirmatory factor analyses (CFA) were employed to investigate the postulated unidimensionality of the underlying construct. With a partial credit model (PCM) we examined item fit, targeting, local independence and differential item functioning. RESULTS: Participants were predominantly female (73.0%) with a breast cancer diagnosis (41.3%). While items were generally well-accepted, ceiling effects were observed and a high mean PAM-13 score (69.7, SD = 14.2) was noted, potentially compromising responsiveness to interventions. Reliability was adequate (Cronbach's α = 0.81), person and item separation reliability were good to excellent (0.81 and 0.99, respectively). Explorations of the unidimensionality of the construct (EFA, CFA, PCM) yielded inconclusive results, hinting towards a two-factor solution. Item difficulty rankings deviated from the original. No differential item functioning was identified, and local independence was confirmed. CONCLUSIONS: While the PAM-13 serves as a valuable instrument for comprehending and promoting health-related skills in cancer patients, the identification of ceiling effects, disordered item-difficulty rankings, and inconclusive findings regarding unidimensionality contribute to the expanding body of evidence, emphasizing the dependency of PAM-13's validity and reliability on distinctive characteristics within the population under investigation. Future research should prioritize refining or adding PAM-13 items to better capture the specific health-related challenges within diverse populations, paving the way for more effective patient engagement strategies in oncology. TRIAL REGISTRATION NUMBER: DRKS00021779.

From everyday life to measurable problematic smartphone use: The development and validation of the Smartphone Use Problems Identification Questionnaire (SUPIQ).

Background and aims: Problematic smartphone use (PSU) has gained attention, but its definition remains debated. This study aimed to develop and validate a new scale measuring PSU-the Smartphone Use Problems Identification Questionnaire (SUPIQ). Methods: Using two separate samples, a university community sample (N = 292) and a general population sample (N = 397), we investigated: (1) the construct validity of the SUPIQ through exploratory and confirmatory factor analyses; (2) the convergent validity of the SUPIQ with correlation analyses and the visualized partial correlation network analyses; (3) the psychometric equivalence of the SUPIQ across two samples through multigroup confirmatory factor analyses; (4) the explanatory power of the SUPIQ over the Short Version of Smartphone Addiction Scale (SAS-SV) with hierarchical multiple regressions. Results: The results showed that the SUPIQ included 26 items and 7 factors (i.e., Craving, Coping, Habitual Use, Social Conflicts, Risky Use, Withdrawal, and Tolerance), with good construct and convergent validity. The configural measurement invariance across samples was established. The SUPIQ also explained more variances in mental health problems than the SAS-SV. Discussion and conclusions: The findings suggest that the SUPIQ shows promise as a tool for assessing PSU. Further research is needed to enhance and refine the SUPIQ as well as to investigate its clinical utility.

Evaluating the psychometric properties of the Swedish version of the Impostor Profile scale (IPP30).

The Impostor Profile scale (IPP30) is a recently developed tool designed to delve into the nuanced aspects of the Impostor Phenomenon (IP), a psychological phenomenon where individuals wrongly attribute their successes to external factors, discounting their own abilities and often feeling like frauds. This study aimed to assess the psychometric properties, including factor structure, internal consistency, and nomological validity, of the Swedish version of IPP30 (S-IPP30). In a sample of Swedish students (N = 1,010; 76.7% women; Mage = 25.65, SDage = 6.43), Exploratory and Confirmatory Factor Analyses were conducted to scrutinize S-IPP30's structure. The analyses supported a bifactor model with six specific factors and one overarching factor. However, two items in the scale displayed poor alignment with their intended subscales, adversely affecting the internal consistency of the two subscales. Consequently, a rephrasing of these items was suggested. The remaining four S-IPP30 subscales exhibited good internal consistency (Cronbach's α = 0.76-0.90, McDonald's ω = 0.77-0.91). Convergent validity was confirmed by largely replicating correlations among various S-IPP30 facets, the unidimensional IP measure, personality variables, and self-esteem, thereby accomplishing the goal of validating S-IPP30. This proposed modification of the two items requires further validation using a new sample to ensure its appropriateness and effectiveness in measuring the intended constructs.

Development and Validation of the Interprofessional Collaboration Practice Competency Scale (IPCPCS) for Clinical Nurses.

Interprofessional collaborative practice is a core competency and is the key to strengthening health practice systems in order to deliver safe and high-quality nursing practice. However, there is no Interprofessional Collaboration Practice Competency Scale (IPCPCS) for clinical nurses in Taiwan. Therefore, the purposes of this study were to develop an IPCPCS and to verify its reliability and validity. This was a psychometric study with a cross-sectional survey using convenience sampling to recruit nurses from the seven hospitals of a medical foundation. A self-designed structured IPCPCS was rolled out via a Google survey. The data were analyzed using descriptive statistics, principal-axis factoring (PAF) with Promax rotation, Pearson correlation, reliability analysis, and one-way ANOVA. PAF analysis found that three factors could explain 77.76% of cumulative variance. These were collaborative leadership and interprofessional conflict resolution, interprofessional communication and team functioning, and role clarification and client-centered care. The internal consistency of the three factors (Cronbach's α) was between 0.970 to 0.978, and the Pearson correlation coefficients were between 0.814 to 0.883. Significant differences were presented in the IPCPCS score by age, education level, total years of work experience, position on the nursing clinical ladder, and participation in interprofessional education. In conclusion, the three factors used in the IPCPCS have good reliability and construct validity. This scale can be used as an evaluation tool of in-service interprofessional education courses for clinical nurses.

Omega-3 Fatty Acids and Risk of Ischemic Stroke in REGARDS.

We examined associations between lipidomic profiles and incident ischemic stroke in the REasons for Geographic and Racial Differences in Stroke (REGARDS) cohort. Plasma lipids (n = 195) were measured from baseline blood samples, and lipids were consolidated into underlying factors using exploratory factor analysis. Cox proportional hazards models were used to test associations between lipid factors and incident stroke, linear regressions to determine associations between dietary intake and lipid factors, and the inverse odds ratio weighting (IORW) approach to test mediation. The study followed participants over a median (IQR) of 7 (3.4-11) years, and the case-cohort substudy included 1075 incident ischemic stroke and 968 non-stroke participants. One lipid factor, enriched for docosahexaenoic acid (DHA, an omega-3 fatty acid), was inversely associated with stroke risk in a base model (HR = 0.84; 95%CI 0.79-0.90; P = 8.33 × 10-8) and fully adjusted model (HR = 0.88; 95%CI 0.83-0.94; P = 2.79 × 10-4). This factor was associated with a healthy diet pattern (ß = 0.21; 95%CI 0.12-0.30; P = 2.06 × 10-6), specifically with fish intake (ß = 1.96; 95%CI 0.95-2.96; P = 1.36 × 10-4). DHA was a mediator between fish intake and incident ischemic stroke (30% P = 5.78 × 10-3). Taken together, DHA-containing plasma lipids were inversely associated with incident ischemic stroke and mediated the relationship between fish intake and stroke risk.

A comprehensive multivariate analysis of the center of pressure during quiet standing in patients with Parkinson's disease.

BACKGROUND: We hypothesized that postural instability observed in individuals with Parkinson's disease (PD) can be classified as distinct subtypes based on comprehensive analyses of various evaluated parameters obtained from time-series of center of pressure (CoP) data during quiet standing. The aim of this study was to characterize the postural control patterns in PD patients by performing an exploratory factor analysis and subsequent cluster analysis using CoP time-series data during quiet standing. METHODS: 127 PD patients, 47 aged 65 years or older healthy older adults, and 71 healthy young adults participated in this study. Subjects maintain quiet standing for 30 s on a force platform and 23 variables were calculated from the measured CoP time-series data. Exploratory factor analysis and cluster analysis with a Gaussian mixture model using factors were performed on each variable to classify subgroups based on differences in characteristics of postural instability in PD. RESULTS: The factor analysis identified five factors (magnitude of sway, medio-lateral frequency, anterio-posterior frequency, component of high frequency, and closed-loop control). Based on the five extracted factors, six distinct subtypes were identified, which can be considered as subtypes of distinct manifestations of postural disorders in PD patients. Factor loading scores for the clinical classifications (younger, older, and PD severity) overlapped, but the cluster classification scores were clearly separated. CONCLUSIONS: The cluster categorization clearly identifies symptom-dependent differences in the characteristics of the CoP, suggesting that the detected clusters can be regarded as subtypes of distinct manifestations of postural disorders in patients with PD.

Data-driven shortened Insomnia Severity Index (ISI): a machine learning approach.

BACKGROUND: The Insomnia Severity Index (ISI) is a widely used questionnaire with seven items for identifying the risk of insomnia disorder. Although the ISI is still short, more shortened versions are emerging for repeated monitoring in routine clinical settings. In this study, we aimed to develop a data-driven shortened version of the ISI that accurately predicts the severity level of insomnia disorder. METHODS: We collected a sample of 800 responses from the EMBRAIN survey system. Based on the responses, seven items were grouped based on the similarity of their response using exploratory factor analysis (EFA). The most representative item within each group was selected by using eXtreme Gradient Boosting (XGBoost). RESULTS: Based on the selected three key items, maintenance of sleep, interference with daily function, and concerns about sleep problems, we developed a data-driven shortened questionnaire of ISI, ISI-3 m (machine learning). ISI-3 m achieved the highest coefficient of determination ( R 2 = 0.910 ) for the ISI score prediction task and the accuracy of 0.965, precision of 0.841, and recall of 0.838 for the multiclass-classification task, outperforming four previous versions of the shortened ISI. CONCLUSION: As ISI-3 m is a highly accurate shortened version of the ISI, it allows clinicians to efficiently screen for insomnia and observe variations in the condition throughout the treatment process. Furthermore, the framework based on the combination of EFA and XGBoost developed in this study can be utilized to develop data-driven shortened versions of the other questionnaires.

Inflammatory bowel disease patients' perspectives of non-medical needs.

BACKGROUND: Inflammatory bowel disease (IBD) imposes a huge burden on the healthcare systems and greatly declines the patient's quality of life. However, there is a paucity of detailed data regarding information and supportive needs as well as sources and methods of obtaining information to control different aspects of the disease from the perspectives of the patients themselves. This study aimed to establish the IBD patients' preferences of informational and supportive needs through Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). METHODS: IBD patients were recruited from different centers. Considering inclusion and exclusion criteria, 521 participants were filled a predefined questionnaire. This questionnaire was prepared through literature review of the recent well-known guidelines on the needs of IBD patients, which was further approved by the experts of IBD area in three rounds of Delphi consensus. It includes 56 items in four sections of informational needs (25), supportive needs (15), sources of information (7), and methods of obtaining information (9). RESULTS: In particular, EFA was used to apply data reduction and structure detection. Given that this study tries to identify patterns, structures as well as inter-relationships and classification of the variables, EFA was utilized to simplify presentation of the variables in a way that large amounts of observations transform into fewer ones. Accordingly, the EFA identified five factors out of 25 items in the information needs section, three factors out of 15 items in the supportive needs section, two factors out of 7 items in the information sources section, and two factors out of 9 items in the information presentation methods. Through the CFA, all 4 models were supported by Root Mean Squared Error of Approximation (RMSEA); Incremental Fit Index (IFI); Comparative Fit Index (CFI); Tucker-Lewis Index (TLI); and SRMR. These values were within acceptable ranges, indicating that the twelve factors achieved from EFA were validated. CONCLUSIONS: This study introduced a reliable 12-factor model as an efficient tool to comprehensively identify preferences of IBD patients in informational and supportive needs along with sources and methods of obtaining information. An in-depth understanding of the needs of IBD patients facilitates informing and supporting health service provision. It also assists patients in a fundamental way to improve adaptation and increase the quality of life. We suggest that health care providers consider the use of this tool in clinical settings in order to precisely assess its efficacy.

Development of an infection control competency scale for clinical nurses: an instrument design study.

BACKGROUND: Nurses work in close proximity to patients, and as such, they can have a direct impact on the control of infections; thus, it is important for nurses to be competent in infection control. However, the scales used to measure infection control performance in nurses are not suitable for measuring infection control competencies that reflect nurses' expertise, clinical environment, and work. Thus, this study aimed to develop a valid and reliable measure to assess infection control competency of clinical nurses. METHODS: A concept analysis, using a hybrid model, was performed on the infection control competency of clinical nurses to confirm the components and develop 67 initial items. Ten experts evaluated the content validity of these items, and a Korean language expert and a Doctor of Nursing reviewed the questions to consolidate them into 59 items. Subsequently, 267 nurses working at a certified tertiary hospital in D City were surveyed to confirm the validity and reliability of the scale. RESULTS: As a result of the study, the final scale comprising seven factors and 33 questions was derived, and the cumulative explanatory power of these factors was 60.8%. To verify convergent and discriminant validity, confirmatory factor analysis was conducted, and the average variance extraction index, composite reliability values, and confidence interval of the correlation coefficient between factors were confirmed. Convergent and discriminant validities were verified by comparison with standard values. The Cronbach's α for the entire scale in this study was 0.93. Consequently, the validity and reliability of the clinical nurses' infection control competency measurement scale were verified. CONCLUSIONS: The validity and reliability of the infection control competency measurement scale for clinical nurses (ICCS-CN) developed in this study was verified, and the scale can be effectively used to measure the infection control competency of clinical nurses. Measuring the infection control competency of clinical nurses will help reduce the harm caused by infection and ensure patient safety by decreasing infection rates in medical institutions.

A Model Implied Instrumental Variable Approach to Exploratory Factor Analysis (MIIV-EFA).

Spearman (Am J Psychol 15(1):201-293, 1904. https://doi.org/10.2307/1412107 ) marks the birth of factor analysis. Many articles and books have extended his landmark paper in permitting multiple factors and determining the number of factors, developing ideas about simple structure and factor rotation, and distinguishing between confirmatory and exploratory factor analysis (CFA and EFA). We propose a new model implied instrumental variable (MIIV) approach to EFA that allows intercepts for the measurement equations, correlated common factors, correlated errors, standard errors of factor loadings and measurement intercepts, overidentification tests of equations, and a procedure for determining the number of factors. We also permit simpler structures by removing nonsignificant loadings. Simulations of factor analysis models with and without cross-loadings demonstrate the impressive performance of the MIIV-EFA procedure in recovering the correct number of factors and in recovering the primary and secondary loadings. For example, in nearly all replications MIIV-EFA finds the correct number of factors when N is 100 or more. Even the primary and secondary loadings of the most complex models were recovered when the sample sizes were at least 500. We discuss limitations and future research areas. Two appendices describe alternative MIIV-EFA algorithms and the sensitivity of the algorithm to cross-loadings.