... The value of Kaiser-Meyer-Olkin (KMO = 0.863) and Bartlett's test (Bartlett's statistic (435) = 5597.2; p < 0.001) obtained indicated that the correlation matrix was adequate for the factor analysis . The exploratory factor analysis classified the items in two subscales: 1) compassion satisfaction (CS), and 2) compassion fatigue (CF). ...
Many workers contribute to the success of animal welfare and study outcomes in biomedical research. However, the professional quality of life (ProQoL) of those who work with laboratory animals has not been explored in Spain. To this end, we adapted the ProQoL scale to the Spanish population working with laboratory animals. Participants were contacted by email and asked to complete an anonymous on-line questionnaire. The study comprised a total of 498 participants, 12.4% welfare officers/veterinarians, 19.5% caretaker/technicians, 13.9% principal investigators, 20.7% investigators, 13.6% research technicians, and 19.9% PhD students. The adapted scale revealed very good reliability and internal validity, providing information about two different sub-scales, compassion satisfaction and compassion fatigue. Animal facility personnel showed higher total ProQoL and compassion satisfaction scores than researchers; PhD students showed the lowest scores. Thus, our results indicate that job category is a contributing factor in perceived professional quality of life. We observed that compassion satisfaction is negatively associated with the perceived animal stress/pain. Participants reporting poorer compassion satisfaction also reported lower social-support scores. Overall, our ProQoL scale is a useful tool for analyzing the professional quality of life in the Spanish population, and may help to design future interventions to improve workplace wellbeing in Spain and other Spanish-speaking populations.
The presence of people with disabilities in a family can modify family functioning and relationships. This study aimed to verify the initial evidence of internal structure validity and convergence of the Brazilian version of the Family APGAR Scale, in order to evaluate the perception of family functionality in family members of people with disabilities, users of Social Assistance services. Participated in this study 185 family members of people with disabilities, users of a service of a non-governmental entity providing assistance to people with disabilities in a capital of southeastern Brazil. The results from exploratory factorial procedures demonstrated the internal one-dimensional structure of the adapted measure, composed of five items, with good precision indicators of the Alpha (α = 0,96) and Omega (ω = 0.96). Evidence of convergent validity between the adapted measure in this study and the Total Social Support Scale of the Medical Outcomes Study (MOS) was also observed. Thus, the results indicate that the adapted Brazilian version of the measure had adequate psychometric properties and can be used in this context and population.
Ten steps for test development.
Tests are the measurement instruments most used by psychologists to obtain data about people, both in professional and research contexts. The main goal of this paper is to synthesize in ten steps the fundamental aspects that must be taken into account when building a test in a rigorous way.
For the elaboration of the ten proposed phases, the specialized psychometric literature was revised, and previous works by the authors on the subject were updated.
Ten steps are proposed for the objective development of a test: delimitation of the general framework, definition of the variable to be measured, specifications, items development, edition of the test, pilot studies, selection of other measurement instruments, test administration, psychometric properties, and development of the final version.
Following the ten proposed steps, objective tests can be developed with adequate psychometric properties based on empirical evidence.
The use of positively worded items and reversed forms aims to reduce response bias and is a commonly used practice nowadays. The main goal of this research is to analyze the psychometric implications of the use of positive and reversed items in measurement instruments.
A sample of 374 participants was tested aged between 18 and 73 (M=33.98; SD=14.12), 62.60% were women. A repeated measures design was used, evaluating the participants with positive, reversed, and combined forms of a self-efficacy test.
When combinations of positive and reversed items are used in the same test the reliability of the test is flawed and the unidimensionality of the test is jeopardized by secondary sources of variance. In addition, the variance of the scores is reduced, and the means differ significantly from those in tests in which all items are either positive or reversed, but not combined.
The results of this study present a trade-off between a potential acquiescence bias when items are positively worded and a potential different understanding when combining regular and reversed items in the same test. The specialized literature recommends combining regular and reversed items for controlling for response style bias, but these results caution researchers in using them as well after accounting for the potential effect of linguistic skills and the findings presented in this study.
Conventional methods for producing test norms are often plagued with “jumps” or “gaps” (i.e., discontinuities) in norm tables and low confidence for assessing extreme scores. We propose a new approach for producing continuous test norms to address these problems that also has the added advantage of not requiring assumptions about the distribution of the raw data: Norm values are established from raw data by modeling the latter ones as a function of both percentile scores and an explanatory variable (e.g., age). The proposed method appears to minimize bias arising from sampling and measurement error, while handling marked deviations from normality – such as are commonplace in clinical samples. In addition to step-by-step instructions in how to apply this method, we demonstrate its advantages over conventional discrete norming procedures using norming data from two different psychometric tests, employing either age norms (N = 3.555) or grade norms (N = 1.400).
An R package for applying the procedure is available via https://www.psychometrica.de/cNorm_en.html
The Cronbach's alpha is the most widely used method for estimating internal consistency reliability. This procedure has proved very resistant to the passage of time, even if its limitations are well documented and although there are better options as omega coefficient or the different versions of glb, with obvious advantages especially for applied research in which the ítems differ in quality or have skewed distributions. In this paper, using Monte Carlo simulation, the performance of these reliability coefficients under a one-dimensional model is evaluated in terms of skewness and no tau-equivalence. The results show that omega coefficient is always better choice than alpha and in the presence of skew items is preferable to use omega glb coefficients even in small samples.
A must-have resource for researchers, practitioners, and advanced students interested or involved in psychometric testing. Over the past hundred years, psychometric testing has proved to be a valuable tool for measuring personality, mental ability, attitudes, and much more. The word 'psychometrics' can be translated as 'mental measurement'; however, the implication that psychometrics as a field is confined to psychology is highly misleading. Scientists and practitioners from virtually every conceivable discipline now use and analyze data collected from questionnaires, scales, and tests developed from psychometric principles, and the field is vibrant with new and useful methods and approaches. This handbook brings together contributions from leading psychometricians in a diverse array of fields around the globe. Each provides accessible and practical information about their specialist area in a three-step format covering historical and standard approaches, innovative issues and techniques, and practical guidance on how to apply the methods discussed. Throughout, real-world examples help to illustrate and clarify key aspects of the topics covered. The aim is to fill a gap for information about psychometric testing that is neither too basic nor too technical and specialized, and will enable researchers, practitioners, and graduate students to expand their knowledge and skills in the area. Provides comprehensive coverage of the field of psychometric testing, from designing a test through writing items to constructing and evaluating scales. Takes a practical approach, addressing real issues faced by practitioners and researchers. Provides basic and accessible mathematical and statistical foundations of all psychometric techniques discussed. Provides example software code to help readers implement the analyses discussed.