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Background: The impact of traumatic experiences or adverse life experiences has been shown to potentially affect a wide range of mental health outcomes. However, there was no brief instrument to screen for a range of psychological problems in different domains after a potentially traumatic event, and for risk factors and protective factors. Objective: The aim of this study is to examine the internal consistency and concurrent validity of the Japanese version of the Global Psychotrauma Screen (GPS) in a traumatized sample in Japan. Method: A total sample (n = 58) with varying levels of potential posttrauma symptoms due to domestic violence or other events were recruited into this study. Self-rating measures of posttraumatic stress disorder (PTSD), depression, anxiety, and alcohol problems were conducted to investigate the concurrent validity. Results: The results show that a range of posttrauma symptoms assessed by the GPS were highly endorsed by this traumatized sample in all domains except for self-harm, derealization, and depersonalization. The GPS sum score was highly correlated (r > 0.79) with other measures of PTSD, depression, and anxiety symptoms. Also, the subdomain scores showed acceptable correlations with corresponding domain measures. Participants who had been sexually assaulted or had unwanted sexual experiences, and participants who had been physically assaulted during childhood, had higher scores on the total GPS and on subdomains of PTSD, as well as symptoms associated with Complex PTSD. Conclusions: This study provides an initial indication that the GPS may be a useful screening tool for trauma survivors and elucidates that the consequences of trauma are not limited to PTSD.

Based on recent psychometric developments, this paper presents a conceptual and practical guide for estimating internal consistency reliability of measures obtained as item sum or mean. The internal consistency reliability coefficient is presented as a by-product of the measurement model underlying the item responses. A three-step procedure is proposed for its estimation, including descriptive data analysis, test of relevant measurement models, and computation of internal consistency coefficient and its confidence interval. Provided formulas include: (a) Cronbach’s alpha and omega coefficients for unidimensional measures with quantitative item response scales, (b) coefficients ordinal omega, ordinal alpha and nonlinear reliability for unidimensional measures with dichotomic and ordinal items, (c) coefficients omega and omega hierarchical for essentially unidimensional scales presenting method effects. The procedure is generalized to weighted sum measures, multidimensional scales, complex designs with multilevel and/or missing data and to scale development. Four illustrative numerical examples are fully explained and the data and the R syntax are provided.

Objective and accurate assessment of the degree of ocular motor nerve palsy is helpful not only in the evaluation of prognosis, but also for the screening of treatment methods. However, there is currently no comprehensive measure of its severity. In this study, we designed the Ocular Motor Nerve Palsy Scale and investigated its validity and reliability. Six experts were invited to grade and evaluate the scale. The study recruited 106 patients with a definite diagnosis of unilateral isolated ocular motor nerve palsy. Three physicians evaluated the patients using the scale. One of the three physicians evaluated the patients again after 24 hours. The content validity index (CVI) and factor analysis were used to analyze the scale's construct validity. The intraclass correlation coefficient and Cronbach's alpha were used to evaluate the inter-rater and test-retest reliability and the internal consistency. The CVI results (I-CVI = 1.0, S-CVI = 0.9, P = 0.016, K* = 1) indicated good content validity. Factor analysis extracted two common factors that accounted for 85.2% of the variance. Furthermore, the load value of each component was above 0.8, indicating good construct validity. The Ocular Motor Nerve Palsy Scale was found to be highly reliable, with an inter-rater reliability intraclass correlation coefficient of 0.965 (P < 0.01), a test-retest reliability intraclass correlation coefficient of 0.976 (P < 0.01), and Cronbach's alpha values of 0.63-0.70. In conclusion, the Ocular Motor Nerve Palsy Scale with good validity and reliability can be used to quantify the severity of ocular motor nerve palsy. This study was registered at Chinese Clinical Trial Registry (registration number: ChiCTR-OOC-17010702).

Reliability studies are commonly used in questionnaire development studies and questionnaire validation studies. This study reviews the sample size guideline for Cronbach's alpha test. Manual sample size calculation using Microsoft Excel software and sample size tables were tabulated based on a single coefficient alpha and the comparison of two coefficients alpha. For a single coefficient alpha test, the approach by assuming the Cronbach's alpha coefficient equals to zero in the null hypothesis will yield a smaller sample size of less than 30 to achieve a minimum desired effect size of 0.7. However, setting the coefficient of Cronbach's alpha larger than zero in the null hypothesis could be necessary and this will yield larger sample size. For comparison of two coefficients of Cronbach's alpha, a larger sample size is needed when testing for smaller effect sizes. In the assessment of the internal consistency of an instrument, the present study proposed the Cronbach's alpha's coefficient to be set at 0.5 in the null hypothesis and hence larger sample size is needed. For comparison of two coefficients' of Cronbach's alpha, justification is needed whether testing for extremely low and extremely large effect sizes are scientifically necessary.

Knowledge is an important predictor and outcome of learning and development. Its measurement is challenged by the fact that knowledge can be integrated and homogeneous, or fragmented and heterogeneous, which can change through learning. These characteristics of knowledge are at odds with current standards for test development, demanding a high internal consistency (e.g., Cronbach's Alphas greater .70). To provide an initial empirical base for this debate, we conducted a meta-analysis of the Cronbach's Alphas of knowledge tests derived from an available data set. Based on 285 effect sizes from 55 samples, the estimated typical Alpha of domain-specific knowledge tests in publications was α = .85, CI90 [.82; .87]. Alpha was so high despite a low mean item intercorrelation of .22 because the tests were relatively long on average and bias in the test construction or publication process led to an underrepresentation of low Alphas. Alpha was higher in tests with more items, with open answers and in younger age, it increased after interventions and throughout development, and it was higher for knowledge in languages and mathematics than in science and social sciences/humanities. Generally, Alphas varied strongly between different knowledge tests and populations with different characteristics, reflected in a 90% prediction interval of [.35, .96]. We suggest this range as a guideline for the Alphas that researchers can expect for knowledge tests with 20 items, providing guidelines for shorter and longer tests. We discuss implications for our understanding of domain-specific knowledge and how fixed cut-off values for the internal consistency of knowledge tests bias research findings.

Purpose The Patient-Reported Outcomes Measurement Information System® (PROMIS®) was designed to develop, validate, and standardize item banks to measure key domains of physical, mental, and social health in chronic conditions. This paper reports the calibration and validation testing of the PROMIS Self-Efficacy for Managing Chronic Conditions measures. Methods PROMIS Self-Efficacy for Managing Chronic Conditions item banks comprise five domains, Self-Efficacy for Managing: Daily Activities, Symptoms, Medications and Treatments, Emotions, and Social Interactions. Banks were calibrated in 1087 subjects from two data sources: 837 patients with chronic neurologic conditions (epilepsy, multiple sclerosis, neuropathy, Parkinson disease, and stroke) and 250 subjects from an online Internet sample of adults with general chronic conditions. Scores were compared with one legacy scale: Self-Efficacy for Managing Chronic Disease 6-Item scale (SEMCD6) and five PROMIS short forms: Global Health (Physical and Mental), Physical Function, Fatigue, Depression, and Anxiety. Results The sample was 57% female, mean age=53.8 (SD=14.7), 76% white, 21% African American, 6% Hispanic, and 76% with greater than high school education. Full-item banks were created for each domain. All measures had good internal consistency and correlated well with SEMCD6 (r=0.56-0.75). Significant correlations were seen between the Self-Efficacy measures and other PROMIS short forms (r >0.38). Conclusions The newly developed PROMIS Self-Efficacy for Managing Chronic Conditions measures include five domains of self-efficacy that were calibrated across diverse chronic conditions and show good internal consistency and cross-sectional validity.

•We detail EEG psychometric reliability profiles for testing individual differences.•We review internal consistency of power, ERP, nonlinear, connectivity measures.•We review test-retest reliability of power, ERP, nonlinear, connectivity measures.•We show how denoising, data quality measures improve individual difference studies.•We provide actionable recommendations to improve EEG individual difference analyses. Electroencephalographic (EEG) methods have great potential to serve both basic and clinical science approaches to understand individual differences in human neural function. Importantly, the psychometric properties of EEG data, such as internal consistency and test-retest reliability, constrain their ability to differentiate individuals successfully. Rapid and recent technological and computational advancements in EEG research make it timely to revisit the topic of psychometric reliability in the context of individual difference analyses. Moreover, pediatric and clinical samples provide some of the most salient and urgent opportunities to apply individual difference approaches, but the changes these populations experience over time also provide unique challenges from a psychometric perspective. Here we take a developmental neuroscience perspective to consider progress and new opportunities for parsing the reliability and stability of individual differences in EEG measurements across the lifespan. We first conceptually map the different profiles of measurement reliability expected for different types of individual difference analyses over the lifespan. Next, we summarize and evaluate the state of the field's empirical knowledge and need for testing measurement reliability, both internal consistency and test-retest reliability, across EEG measures of power, event-related potentials, nonlinearity, and functional connectivity across ages. Finally, we highlight how standardized pre-processing software for EEG denoising and empirical metrics of individual data quality may be used to further improve EEG-based individual differences research moving forward. We also include recommendations and resources throughout that individual researchers can implement to improve the utility and reproducibility of individual differences analyses with EEG across the lifespan.

Social Anxiety Disorder (SAD) is especially prevalent among young individuals aged 18–25 and significantly affects daily social activities and interpersonal relationships. Public Speaking Anxiety (PSA), a subtype of SAD, is a widespread concern that affects one in five individuals. The study focuses on the Public Speaking Anxiety Scale (PSAS), with the aim of assessing the factor structure and reliability of the Lithuanian version (PSAS-LT). The PSAS-LT, administered to 227 participants aged 18–25, comprises 17 Likert-scaled items, evaluating cognitive, behavioral, and physiological aspects of PSA. Three models were tested: a single-factor model, a three-factor model and a single factor model with positive and negative item wording factors model. Results indicate less than desirable fit for the single, and three-factor models, suggesting the need for alternative structures. The model that included a single factor as well as positive and negative item wording factors demonstrated a reasonably good fit. The diagnostic validity confirmed that the PSAS-LT effectively differentiated between participants with and without history of anxiety disorders. The total score of the PSAS-LT had excellent internal consistency. Despite limitations, including convenience sampling and nonrepresentative sample, the study contributes valuable insights into refining the understanding of PSA assessment features, emphasizing the importance of considering response patterns. Future research should validate these findings with larger and more diverse samples of the Lithuanian population.

During the 20th century the alpha coefficient (α) was widely used in the estimation of the internal consistency reliability of test scores. After misuses were identified in the early 21st century alternatives became widespread, especially the omega coefficient (ω). Nowadays, α is re-emerging as an acceptable option for reliability estimation. A review of the recent academic contributions, journal publication habits and recommendations from normative texts was carried out to identify good practices in estimation of internal consistency reliability. To guide the analysis, we propose a three-phase decision diagram, which includes item description, fit of the measurement model for the test, and choice of the reliability coefficient for test score(s). We also provide recommendations on the use of R, Jamovi, JASP, Mplus, SPSS and Stata software to perform the analysis. Both α and ω are suitable for items with approximately normal distributions and approximately unidimensional and congeneric measures without extreme factor loadings. When items show non-normal distributions, strong specific components, or correlated errors, variants of ω are more appropriate. Some require specific data gathering designs. On a practical level we recommend a critical approach when using the software.

En este trabajo se presenta una guía conceptual y práctica para estimar la fiabilidad de consistencia interna de medidas obtenidas mediante suma o promedio de ítems con base en las aportaciones más recientes de la psicometría. El coeficiente de fiabilidad de consistencia interna se presenta como un subproducto del modelo de medida subyacente en las respuestas a los ítems y se propone su estimación mediante un procedimiento de análisis de los ítems en tres fases, a saber, análisis descriptivo, comprobación de los modelos de medida pertinentes y cálculo del coeficiente de consistencia interna y su intervalo de confianza. Se proporcionan las siguientes fórmulas: (a) los coeficientes alfa de Cronbach y omega para medidas unidimensionales con ítems cuantitativos (b) los coeficientes omega ordinal, alfa ordinal y de fiabilidad no lineal para ítems dicotómicos y ordinales, y (c) los coeficientes omega y omega jerárquico para medidas esencialmente unidimensionales con efectos de método. El procedimiento se generaliza al análisis de medidas obtenidas por suma ponderada, de escalas multidimensionales, de diseños complejos con datos multinivel y/o faltantes y también al desarrollo de escalas. Con fines ilustrativos se expone el análisis de cuatro ejemplos numéricos y se proporcionan los datos y la sintaxis en R.