Asymptotically Normally Distributed Person Fit Indices for Detecting Spuriously High Scores on Difficult Items.
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ABSTRACT:
SUBMITTER: Xia Y
PROVIDER: S-EPMC6023093 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BACKGROUND:Person-environment fit, which examines the individual's perceptions of if, and in what way, he or she is compatible with aspects of the work context, offers a promising conceptual model for understanding employees and their interactions in health care environments. There are numerous potential ways an individual feels they "fit" with their environment. The construct was first noted almost thirty years ago, yet still remains elusive. Feelings of fit with one's environment are typically measured by surveys, but current surveys encompass only a subset of the different components of fit, which may limit the conclusions drawn. Further, these surveys have rarely been conducted in a focused way in health care settings. METHOD:This article describes the development of a multidimensional survey tool to measure fit in relation to the person's work group (termed person-group (P-G) fit) and their organisation (person-organisation (P-O) fit). The participants were mental health care employees, volunteers, and university interns (n =?213 for P-O fit; n =?194 for P-G fit). Confirmatory Factor Analyses (CFAs) were conducted using LISREL. RESULTS:Valid and reliable sub-scales were found. CONCLUSION:This advanced multidimensional survey tool can be used to measure P-O and P-G fit, and illuminates new information about the theoretical structure of the fit construct.
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Project description:Job burnout and work pressure are pivotal concerns in human resource management and workplace mental health, profoundly impacting organizational sustainability and individual well-being. Grounded in the person-environment fit theory, this empirical study quantitatively investigates the psychological mechanisms of person-job fit and person-organization fit in job burnout, highlighting the mediating role of work pressure. To test our hypotheses, we investigated 477 employees from 63 IT enterprises around China's Pearl River Delta region. The findings reveal that person-job fit is negatively associated with job burnout and work pressure, while work pressure positively influences job burnout, partially mediating the relationship between person-job fit and job burnout. Similarly, person-organization fit negatively affects job burnout and work pressure. However, its direct influence on job burnout is insignificant, indicating that work pressure fully mediates the relationship between person-organization fit and job burnout. These findings are consistent with the person-environment fit theory, enhancing our understanding of how individuals fit with their jobs and how organizations affect job burnout through work pressure. This study offers valuable insights for organizations seeking to mitigate burnout and promote employee well-being.
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Project description:BackgroundDigital networks, mobile devices, and the possibility of mining the ever-increasing amount of digital traces that we leave behind in our daily activities are changing the way we can approach the study of human and social interactions. Large-scale datasets, however, are mostly available for collective and statistical behaviors, at coarse granularities, while high-resolution data on person-to-person interactions are generally limited to relatively small groups of individuals. Here we present a scalable experimental framework for gathering real-time data resolving face-to-face social interactions with tunable spatial and temporal granularities.Methods and findingsWe use active Radio Frequency Identification (RFID) devices that assess mutual proximity in a distributed fashion by exchanging low-power radio packets. We analyze the dynamics of person-to-person interaction networks obtained in three high-resolution experiments carried out at different orders of magnitude in community size. The data sets exhibit common statistical properties and lack of a characteristic time scale from 20 seconds to several hours. The association between the number of connections and their duration shows an interesting super-linear behavior, which indicates the possibility of defining super-connectors both in the number and intensity of connections.ConclusionsTaking advantage of scalability and resolution, this experimental framework allows the monitoring of social interactions, uncovering similarities in the way individuals interact in different contexts, and identifying patterns of super-connector behavior in the community. These results could impact our understanding of all phenomena driven by face-to-face interactions, such as the spreading of transmissible infectious diseases and information.
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Project description:Based on the "complementary-congruence model" of person-environment fit, this study focuses on housing in old age as an interaction between housing needs and housing conditions in urban settings. The research aims are (1) to establish a set of housing-related person-environment (p-e) fit indices based on the relationship between environmental needs and existing conditions in different physical and social domains, and to describe housing among elders aged 51-80 years and in different urban districts with these indices; the study distinguishes between basic, higher-order and social needs relating to housing; (2) to explain outdoor place attachment as an indicator for quality of life in different urban districts with a set of predictors including these person-environment fit indices. Data were drawn from telephone-based interviews with 365 older adults (51-80 years) who were questioned about individual housing needs and housing conditions. Results revealed higher p-e fit scores in the domains of higher-order and social housing needs and conditions in the districts which were considered to be more pleasant but had poor access to the city and to public transportation. By contrast, age was more important in explaining differences in the domain of basic housing needs and conditions with higher p-e fit scores among older participants. In explaining outdoor place attachment, the fit between basic and social housing needs and conditions was important, but the higher-order fit did not play a role.
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Project description:ObjectivesPeople interact with their work environment through being, to a greater or lesser extent, compatible with aspects of their setting. This interaction between person and environment is particularly relevant in healthcare settings where compatibility affects not only the healthcare professionals, but also potentially the patient. One way to examine this association is to investigate person-organisation (P-O) fit and person-group (P-G) fit. This systematic review aimed to identify and synthesise knowledge on both P-O fit and P-G fit in healthcare to determine their association with staff outcomes. It was hypothesised that there would be a positive relationship between fit and staff outcomes, such that the experience of compatibility and 'fitting in' would be associated with better staff outcomes.DesignA systematic review was conducted based on an extensive search strategy guided by Preferred Reporting Items for Systematic review and Meta-Analyses to identify relevant literature.Data sourcesCINAHL Complete, EMBASE, Ovid MEDLINE, PsycINFO and Scopus.Eligibility criteriaArticles were included if they were empirical studies, published in peer-reviewed journals in English language, set in a healthcare context and addressed the association that staff outcomes have with P-O and/or P-G fit.Data extraction and synthesisIncluded texts were examined for study characteristics, fit constructs examined and types of staff outcomes assessed. The Quality Assessment Tool was used to assess risk of bias.ResultsTwenty-eight articles were included in the review. Of these, 96.4% (27/28) reported a significant, positive association between perception of fit and staff outcomes in healthcare contexts, such that a sense of compatibility had various positive implications for staff, including job satisfaction and retention.ConclusionAlthough the results, as with all systematic reviews, are prone to bias and definitional ambiguity, they are still informative. Generally, the evidence suggests an association between employees' perceived compatibility with the workplace or organisation and a variety of staff outcomes in healthcare settings.
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Project description:We propose a novel response-adaptive randomization procedure for multi-armed trials with continuous outcomes that are assumed to be normally distributed. Our proposed rule is non-myopic, and oriented toward a patient benefit objective, yet maintains computational feasibility. We derive our response-adaptive algorithm based on the Gittins index for the multi-armed bandit problem, as a modification of the method first introduced in Villar et al. (Biometrics, 71, pp. 969-978). The resulting procedure can be implemented under the assumption of both known or unknown variance. We illustrate the proposed procedure by simulations in the context of phase II cancer trials. Our results show that, in a multi-armed setting, there are efficiency and patient benefit gains of using a response-adaptive allocation procedure with a continuous endpoint instead of a binary one. These gains persist even if an anticipated low rate of missing data due to deaths, dropouts, or complete responses is imputed online through a procedure first introduced in this paper. Additionally, we discuss how there are response-adaptive designs that outperform the traditional equal randomized design both in terms of efficiency and patient benefit measures in the multi-armed trial context.
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Project description:The purpose of this study was to thoroughly examine the performance of three information-based fit indices-Akaike's Information Criterion (AIC), Bayesian Information Criterion (BIC), and sample-size-adjusted BIC (SABIC)-using the log-linear cognitive diagnosis model and a set of well-known item response theory (IRT) models. Two simulation studies were conducted to examine the extent to which relative fit indices can identify the generating model under a variety of data conditions and model misspecifications. Generally, indices performed better when item quality was stronger. When the IRT was the generating model, all three indices correctly selected the IRT model for all replications. When the true model was a diagnostic classification model, for all three fit indices, the multidimensional IRT model was incorrectly selected as frequently as 70% of the replications. The results of this study identify situations for researchers where commonly used-and typically well-performing-fit indices may not be appropriate to compare models for selection.
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Project description:This article introduces three new variants of entropy to detect person misfit (Ei, EMi , and EMRi ), and provides preliminary evidence that these measures are worthy of further investigation. Previously, entropy has been used as a measure of approximate data-model fit to quantify how well individuals are classified into latent classes, and to quantify the quality of classification and separation between groups in logistic regression models. In the current study, entropy is explored through conceptual examples and Monte Carlo simulation comparing entropy with established measures of person fit in item response theory (IRT) such as lz, lz*, U, and W. Simulation results indicated that EMi and EMRi were successfully able to detect aberrant response patterns when comparing contaminated and uncontaminated subgroups of persons. In addition, EMi and EMRi performed similarly in showing separation between the contaminated and uncontaminated subgroups. However, EMRi may be advantageous over other measures when subtests include a small number of items. EMi and EMRi are recommended for use as approximate person-fit measures for IRT models. These measures of approximate person fit may be useful in making relative judgments about potential persons whose response patterns do not fit the theoretical model.
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