Criterion Validation of the Scales of Autonomy, Collaboration, Empathy, Problem-solving and Self-confidence of the 3SQ. Soft Skills Self-evaluation Questionnaire Adapted for Lower Secondary School

The Soft Skills Self-evaluation Questionnaire (3SQ, 41 items) was validated using the responses of 1216 Italian students attending the fourth and the fifth grade of upper secondary school (Lucisano & du Mérac, 2019a), demonstrating good psychometric properties (du Mérac & De Santis, 2020; du Mérac, Livi, & Lucisano, 2020). The adaptation of the 3SQ (40 items) for 8th-grade students was validated in Rome using the responses of 507 students, confirming the factorial structure, sufficient independence, and a good internal consistency (Cronbach alpha between .75 and .92 and 52.23% of the total variance explained). Here, we present the criterion-related validity of the five scales of the adapted 3SQ: Self-confidence, Autonomy, Problem-solving, Cooperation, Empathy. During a PhD research project (Scippo, 2021), these dimensions were also measured in Rome with other instruments, using a sample of 403 8th grade students. The analysis of the data confirms good reliability of the five scales (between .79 and .92), shows good indices of the confirmatory factor analysis of all the scales (RMSEA = .05, SRMR = .08), and reveals significant correlations (between .38 and .68) between the scales of the adapted 3SQ and the other scales measuring the same dimensions. In conclusion, this concurrent validity check reinforces the validity of the adapted 3SQ construct and, consequently, its usefulness for both research and guidance.

Development and Validation of the Aesthetic Competence Scale

<div>This study aimed to develop and validate the Aesthetic Competence Scale to measure students’ Aesthetic Quotient. A total of 654 undergraduate students participated in the survey. In phase 1, participants completed a 40-item Aesthetic Competence Scale intended to measure the four factors of Aesthetic Quotient, namely, music, drawing, literature, and film. Exploratory factor analysis was conducted to eliminate items with low factor coefficients and generate a concise instrument. In phase 2, confirmatory factor analysis was used to validate the revised questionnaire. The findings of the exploratory and confirmatory factor analyses supported the hypothetical factor structure of the Aesthetic Competence Scale. All subscales of the Aesthetic Competence Scale showed good internal consistency reliabilities. Concurrent validity was evaluated by structural equation modeling, which examined the relationships between the Aesthetic Competence Scale, emotions, and creativity. The result provided the criterion validation and revealed the value of the Aesthetic Competence Scale.<br></div><div><br></div>The data concerning this manu is stored in scienceDB, see https://www.scidb.cn/en. <br>

Development and Validation of the Aesthetic Competence Scale

<div>This study aimed to develop and validate the Aesthetic Competence Scale to measure students’ Aesthetic Quotient. A total of 654 undergraduate students participated in the survey. In phase 1, participants completed a 40-item Aesthetic Competence Scale intended to measure the four factors of Aesthetic Quotient, namely, music, drawing, literature, and film. Exploratory factor analysis was conducted to eliminate items with low factor coefficients and generate a concise instrument. In phase 2, confirmatory factor analysis was used to validate the revised questionnaire. The findings of the exploratory and confirmatory factor analyses supported the hypothetical factor structure of the Aesthetic Competence Scale. All subscales of the Aesthetic Competence Scale showed good internal consistency reliabilities. Concurrent validity was evaluated by structural equation modeling, which examined the relationships between the Aesthetic Competence Scale, emotions, and creativity. The result provided the criterion validation and revealed the value of the Aesthetic Competence Scale.<br></div><div><br></div>The data concerning this manu is stored in scienceDB, see https://www.scidb.cn/en. <br>

Development of measures for assessing mistreatment of women during facility-based childbirth based on labour observations

IntroductionMistreatment of women during childbirth is increasingly recognised as a significant issue globally. Research and programmatic efforts targeting this phenomenon have been limited by a lack of validated measurement tools. This study aimed to develop a set of concise, valid and reliable multidimensional measures for mistreatment using labour observations applicable across multiple settings.MethodsData from continuous labour observations of 1974 women in Nigeria (n=407), Ghana (n=912) and Guinea (n=655) were used from the cross-sectional WHO’s multicountry study ‘How women are treated during facility-based childbirth’ (2016–2018). Exploratory factor analysis was conducted to develop a scale measuring interpersonal abuse. Two indexes were developed through a modified Organisation for Economic Co-operation and Development approach for generating composite indexes. Measures were evaluated for performance, validity and internal reliability.ResultsThree mistreatment measures were developed: a 7-item Interpersonal Abuse Scale, a 3-item Exams & Procedures Index and a 12-item Unsupportive Birth Environment Index. Factor analysis results showed a consistent unidimensional factor structure for the Interpersonal Abuse Scale in all three countries based on factor loadings and interitem correlations, indicating good structural construct validity. The scale had a reliability coefficient of 0.71 in Nigeria and approached 0.60 in Ghana and Guinea. Low correlations (Spearman correlation range: −0.06–0.19; p≥0.05) between mistreatment measures supported our decision to develop three separate measures. Predictive criterion validation yielded mixed results across countries. Both items within measures and measure scores were internally consistent across countries; each item co-occurred with other items in a measure, and scores consistently distinguished between ‘high’ and ‘low’ mistreatment levels.ConclusionThe set of concise, comprehensive multidimensional measures of mistreatment can be used in future research and quality improvement initiatives targeting mistreatment to quantify burden, identify risk factors and determine its impact on health and well-being outcomes. Further validation and reliability testing of the measures in other contexts is needed.

Enhancement and Standardization of a Universal Social-Emotional Health Measure for Students’ Psychological Strengths

Robust evidence links students’ positive mental health with academic achievement and provides a compelling rationale for developing and refining strength-based assessments. The Social Emotional Health Survey–Secondary (SEHS-S) assesses adolescents’ social and emotional skills and positive psychological dispositions. Previous studies provide reliability and validity evidence; nonetheless, there is a need for continued refinement and validation across diverse groups. The current study revised and standardized the updated SEHS-S-2020 to validate further its use in secondary schools (Grades 9–12) with a large, diverse adolescent sample. Study participants included 72,740 from 113 California schools (structural validation sample), 10,757 students from 15 randomly selected California schools (criterion validation sample), and 707 students from four additional California schools (test-retest sample). Data analyses examined structural validity, measurement invariance, criterion validity, internal consistency, and response stability. Results supported the SEHS-S-2020 validity across diverse groups of youth in various contexts. The discussion focuses on implications for assessing students’ psychosocial assets and universal school-based screening.

Cognitive Practice Effects Delay Diagnosis; Implications for Clinical Trials

ObjectivePractice effects on cognitive tests obscure decline, thereby delaying detection of mild cognitive impairment (MCI). This reduces opportunities for slowing Alzheimer’s disease progression and can hinder clinical trials. Using a novel method, we assessed the ability of practice-effect-adjusted diagnoses to detect MCI earlier, and tested the validity of these diagnoses based on AD biomarkers.MethodsOf 889 Alzheimer’s Disease Neuroimaging Initiative participants who were cognitively normal (CN) at baseline, 722 returned at 1-year-follow-up (mean age=74.9±6.8). Practice effects were calculated by comparing returnee scores at follow-up to demographically-matched individuals who had only taken the tests once, with an additional adjustment for attrition effects. Practice effects for each test were subtracted from follow-up scores. The lower scores put additional individuals below the impairment threshold for MCI. CSF amyloid-beta, phosphorylated tau, and total tau were measured at baseline and used for criterion validation.ResultsPractice-effect-adjusted scores increased MCI incidence by 26% (p<.001). Adjustment increased proportions of amyloid-positive MCI cases (+20%) and reduced proportions of amyloid-positive CNs (−6%) (ps<.007). With the increased MCI base rate, adjustment for practice effects would reduce the sample size needed for detecting significant drug treatment effects by an average of 21%, which we demonstrate would result in multi-million-dollar savings in a clinical trial.InterpretationAdjusting for practice effects on cognitive testing leads to earlier detection of MCI. When MCI is an outcome, this reduces recruitment needed for clinical trials, study duration, staff and participant burden, and can dramatically lower costs. Importantly, biomarker evidence also indicates improved diagnostic accuracy.

Development and Validation of the Short Healthy Eating Index Survey with a College Population to Assess Dietary Quality and Intake

Because diet quality (DQ) is associated with risk of chronic disease and is a common construct assessed in health-related research, validated tools to assess DQ are needed that have low respondent and researcher burden. Thus, content experts develop the Short Healthy Eating Index (sHEI) tool and an associated scoring system. The sHEI scoring system was then refined using a classification and regression tree (CRT) algorithm methodology with an iterative feedback process with expert review and input. The sHEI scoring system was then validated using a concurrent criterion validation process that included the sHEI DQ scores (calculated from responses from 50 participants) being compared to the participants’ Healthy Eating Index scores derived from 24 h recalls. The total HEI score from the CRT algorithm highly correlated with the 24 h recall HEI score (0.79). For individual food group items, the correlation between the CRT algorithm scoring and the 24 h recall data scoring ranged from 0.44 for refined grains to 0.64 for whole fruits. The sHEI appears to be a valid tool for estimating overall dietary quality and individual items (with correlations > 0.49) for fruits, vegetables, dairy, added sugar, sugar from sugar-sweetened beverages, and calcium.