In psychological research, comparisons between two groups are frequently made to demonstrate that one group exhibits higher values. Although Welch’s unequal variances t-test has become the preferred parametric test for this purpose, surpassing Student’s equal variances t-test, the Wilcoxon–Mann–Whitney test remains the predominant nonparametric approach despite sharing similar limitations with Student’s t-test. Specifically, the Wilcoxon–Mann–Whitney test is associated with strong, unrealistic assumptions and lacks robustness when these assumptions are violated. The Brunner–Munzel test overcomes these limitations, featuring fewer assumptions, akin to Welch’s t-test in the parametric domain, and has thus been recommended over the Wilcoxon–Mann–Whitney test. However, the Brunner–Munzel test is currently unavailable in user-friendly statistical software, such as SPSS, making it inaccessible to many researchers. In this paper, I introduce the bmtest module for jamovi, a freely available user-friendly software. By making the Brunner–Munzel test accessible to a wide range of researchers, the bmtest module has the potential to improve nonparametric statistical analysis in psychology and other disciplines.
{"title":"bmtest: A Jamovi Module for Brunner–Munzel’s Test—A Robust Alternative to Wilcoxon–Mann–Whitney’s Test","authors":"J. Karch","doi":"10.3390/psych5020026","DOIUrl":"https://doi.org/10.3390/psych5020026","url":null,"abstract":"In psychological research, comparisons between two groups are frequently made to demonstrate that one group exhibits higher values. Although Welch’s unequal variances t-test has become the preferred parametric test for this purpose, surpassing Student’s equal variances t-test, the Wilcoxon–Mann–Whitney test remains the predominant nonparametric approach despite sharing similar limitations with Student’s t-test. Specifically, the Wilcoxon–Mann–Whitney test is associated with strong, unrealistic assumptions and lacks robustness when these assumptions are violated. The Brunner–Munzel test overcomes these limitations, featuring fewer assumptions, akin to Welch’s t-test in the parametric domain, and has thus been recommended over the Wilcoxon–Mann–Whitney test. However, the Brunner–Munzel test is currently unavailable in user-friendly statistical software, such as SPSS, making it inaccessible to many researchers. In this paper, I introduce the bmtest module for jamovi, a freely available user-friendly software. By making the Brunner–Munzel test accessible to a wide range of researchers, the bmtest module has the potential to improve nonparametric statistical analysis in psychology and other disciplines.","PeriodicalId":93139,"journal":{"name":"Psych","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42683046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Item response theory models and applications are affected by many sources of variability, including errors associated with item parameter estimation. Metric stability analysis (MSA) is one method to evaluate the effects of item parameter standard errors that quantifies how well a model determines the latent trait metric. This paper describes how to evaluate MSA in dichotomous and polytomous data and describes a Bayesian implementation of MSA that does not require a positive definite variance–covariance matrix among item parameters. MSA analyses are illustrated in the context of an oral-health-related quality of life measure administered before and after prosthodontic treatment. The R code to implement the methods described in this paper is provided.
{"title":"Applications and Extensions of Metric Stability Analysis","authors":"L. Feuerstahler","doi":"10.3390/psych5020025","DOIUrl":"https://doi.org/10.3390/psych5020025","url":null,"abstract":"Item response theory models and applications are affected by many sources of variability, including errors associated with item parameter estimation. Metric stability analysis (MSA) is one method to evaluate the effects of item parameter standard errors that quantifies how well a model determines the latent trait metric. This paper describes how to evaluate MSA in dichotomous and polytomous data and describes a Bayesian implementation of MSA that does not require a positive definite variance–covariance matrix among item parameters. MSA analyses are illustrated in the context of an oral-health-related quality of life measure administered before and after prosthodontic treatment. The R code to implement the methods described in this paper is provided.","PeriodicalId":93139,"journal":{"name":"Psych","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44348078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
I. Partchev, J. Koops, T. Bechger, R. Feskens, G. Maris
In this study, we present a package for R that is intended as a professional tool for the management and analysis of data from educational tests and useful both in high-stakes assessment programs and survey research. Focused on psychometric models based on the sum score as the scoring rule and having sufficient statistics for their parameters, dexter fully exploits the many theoretical and practical advantages of this choice: lack of unnecessary assumptions, stable and fast estimation, and powerful and sensible diagnostic techniques. It includes an easy to use data management system tailored to the structure of test data and compatible with the current paradigm of tidy data. Companion packages currently include a graphical user interface and support for multi-stage testing.
{"title":"dexter: An R Package to Manage and Analyze Test Data","authors":"I. Partchev, J. Koops, T. Bechger, R. Feskens, G. Maris","doi":"10.3390/psych5020024","DOIUrl":"https://doi.org/10.3390/psych5020024","url":null,"abstract":"In this study, we present a package for R that is intended as a professional tool for the management and analysis of data from educational tests and useful both in high-stakes assessment programs and survey research. Focused on psychometric models based on the sum score as the scoring rule and having sufficient statistics for their parameters, dexter fully exploits the many theoretical and practical advantages of this choice: lack of unnecessary assumptions, stable and fast estimation, and powerful and sensible diagnostic techniques. It includes an easy to use data management system tailored to the structure of test data and compatible with the current paradigm of tidy data. Companion packages currently include a graphical user interface and support for multi-stage testing.","PeriodicalId":93139,"journal":{"name":"Psych","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41446720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Sorrel, Scarlett Escudero, P. Nájera, R. S. Kreitchmann, Ramsés Vázquez-Lira
Cognitive diagnostic models (CDMs) are increasingly being used in various assessment contexts to identify cognitive processes and provide tailored feedback. However, the most commonly used estimation method for CDMs, marginal maximum likelihood estimation with Expectation–Maximization (MMLE-EM), can present difficulties when sample sizes are small. This study compares the results of different estimation methods for CDMs under varying sample sizes using simulated and empirical data. The methods compared include MMLE-EM, Bayes modal, Markov chain Monte Carlo, a non-parametric method, and a parsimonious parametric model such as Restricted DINA. We varied the sample size, and assessed the bias in the estimation of item parameters, the precision in attribute classification, the bias in the reliability estimate, and computational cost. The findings suggest that alternative estimation methods are preferred over MMLE-EM under low sample-size conditions, whereas comparable results are obtained under large sample-size conditions. Practitioners should consider using alternative estimation methods when working with small samples to obtain more accurate estimates of CDM parameters. This study aims to maximize the potential of CDMs by providing guidance on the estimation of the parameters.
{"title":"Exploring Approaches for Estimating Parameters in Cognitive Diagnosis Models with Small Sample Sizes","authors":"M. Sorrel, Scarlett Escudero, P. Nájera, R. S. Kreitchmann, Ramsés Vázquez-Lira","doi":"10.3390/psych5020023","DOIUrl":"https://doi.org/10.3390/psych5020023","url":null,"abstract":"Cognitive diagnostic models (CDMs) are increasingly being used in various assessment contexts to identify cognitive processes and provide tailored feedback. However, the most commonly used estimation method for CDMs, marginal maximum likelihood estimation with Expectation–Maximization (MMLE-EM), can present difficulties when sample sizes are small. This study compares the results of different estimation methods for CDMs under varying sample sizes using simulated and empirical data. The methods compared include MMLE-EM, Bayes modal, Markov chain Monte Carlo, a non-parametric method, and a parsimonious parametric model such as Restricted DINA. We varied the sample size, and assessed the bias in the estimation of item parameters, the precision in attribute classification, the bias in the reliability estimate, and computational cost. The findings suggest that alternative estimation methods are preferred over MMLE-EM under low sample-size conditions, whereas comparable results are obtained under large sample-size conditions. Practitioners should consider using alternative estimation methods when working with small samples to obtain more accurate estimates of CDM parameters. This study aims to maximize the potential of CDMs by providing guidance on the estimation of the parameters.","PeriodicalId":93139,"journal":{"name":"Psych","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46230629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background: Currently, educational attainment has risen significantly among young people, causing changes in the labor market where skills have become more important. Thus, tertiary education has become an “essential vehicle” to develop high-level skills that would boost students’ professional, social, and personal lives. Methods: The aim of the survey is to study the effects of an intervention program based on two methodologies, service-learning and peer mentoring, to enhance the learn-to-learn and social skills of undergraduate students. The sample was composed of 69 undergraduate students of four different degrees. The methodological design adopted was quasi-experimental pretest–posttest. The intervention consisted of 955 mentoring sessions (878 one-to-one and 77 in groups) among the undergraduate students and students in compulsory education. The undergraduate students participated as mentors. Before, they had three sessions of training. Weekly mentoring sessions were spread out during out-of-school time for 90 min each. Results: The results show a few statistically significant differences in favor of the posttest phase in strategies for the learning and social skills of the participants. Conclusions: Although the program did not obtain the expected results, these outcomes agree with the other studies that investigate intervention programs that use service-learning and peer mentoring methodologies.
{"title":"Improvement of the Learning Strategies of University Students through a Program Based on Service-Learning","authors":"Mirian Hervás Torres","doi":"10.3390/psych5020021","DOIUrl":"https://doi.org/10.3390/psych5020021","url":null,"abstract":"Background: Currently, educational attainment has risen significantly among young people, causing changes in the labor market where skills have become more important. Thus, tertiary education has become an “essential vehicle” to develop high-level skills that would boost students’ professional, social, and personal lives. Methods: The aim of the survey is to study the effects of an intervention program based on two methodologies, service-learning and peer mentoring, to enhance the learn-to-learn and social skills of undergraduate students. The sample was composed of 69 undergraduate students of four different degrees. The methodological design adopted was quasi-experimental pretest–posttest. The intervention consisted of 955 mentoring sessions (878 one-to-one and 77 in groups) among the undergraduate students and students in compulsory education. The undergraduate students participated as mentors. Before, they had three sessions of training. Weekly mentoring sessions were spread out during out-of-school time for 90 min each. Results: The results show a few statistically significant differences in favor of the posttest phase in strategies for the learning and social skills of the participants. Conclusions: Although the program did not obtain the expected results, these outcomes agree with the other studies that investigate intervention programs that use service-learning and peer mentoring methodologies.","PeriodicalId":93139,"journal":{"name":"Psych","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48433659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Amayra Tannoubi, F. Quansah, J. Hagan, M. Srem-Sai, T. Bonsaksen, N. Chalghaf, Ghada Boussayala, Chiraz Azaiez, Haifa Snani, F. Azaiez
The present study validated the University Student Engagement Inventory (USEI) in the Arabic language (A) by assessing its factor structure, construct validity, reliability, and concurrent validity. A total of 864 Tunisian Physical Education and Sport students provided data which was used to perform exploratory and confirmatory factor analyses, using samples comprising 366 (aged 19–25 years) and 498 (aged 19–26 years) students, respectively. The A-USEI, grade-point average (GPA), and Physical Education Grit (PE–Grit) scales were completed via online surveys. The exploratory factor analysis revealed that the A-USEI had three dimensions. The confirmatory factor analysis indicated that the second-order model was more suitable than the first-order multi-factor model. Using the indicators for the second-order model, the three factors showed good reliability, with their average variance extracted (AVE) values reflecting sufficient validity. The correlation analyses between the two scales’ scores and the A-USEI scores showed a moderate correlation, confirming the adapted scale’s concurrent validity. The study concludes that A-USEI is a valid tool for assessing student engagement among Arabic students. In addition, the practical implications and directions for future research are discussed.
{"title":"Adaptation and Validation of the Arabic Version of the University Student Engagement Inventory (A-USEI) among Sport and Physical Education Students","authors":"Amayra Tannoubi, F. Quansah, J. Hagan, M. Srem-Sai, T. Bonsaksen, N. Chalghaf, Ghada Boussayala, Chiraz Azaiez, Haifa Snani, F. Azaiez","doi":"10.3390/psych5020022","DOIUrl":"https://doi.org/10.3390/psych5020022","url":null,"abstract":"The present study validated the University Student Engagement Inventory (USEI) in the Arabic language (A) by assessing its factor structure, construct validity, reliability, and concurrent validity. A total of 864 Tunisian Physical Education and Sport students provided data which was used to perform exploratory and confirmatory factor analyses, using samples comprising 366 (aged 19–25 years) and 498 (aged 19–26 years) students, respectively. The A-USEI, grade-point average (GPA), and Physical Education Grit (PE–Grit) scales were completed via online surveys. The exploratory factor analysis revealed that the A-USEI had three dimensions. The confirmatory factor analysis indicated that the second-order model was more suitable than the first-order multi-factor model. Using the indicators for the second-order model, the three factors showed good reliability, with their average variance extracted (AVE) values reflecting sufficient validity. The correlation analyses between the two scales’ scores and the A-USEI scores showed a moderate correlation, confirming the adapted scale’s concurrent validity. The study concludes that A-USEI is a valid tool for assessing student engagement among Arabic students. In addition, the practical implications and directions for future research are discussed.","PeriodicalId":93139,"journal":{"name":"Psych","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44745475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. Rusch, Katherine E. Venturo-Conerly, Gioia Baja, P. Mair
This article is an introduction to Cluster Optimized Proximity Scaling (COPS) aimed at practitioners, as well as a tutorial on the usage of the corresponding R package cops. COPS is a variant of multidimensional scaling (MDS) that aims at providing a clustered configuration while still representing multivariate dissimilarities faithfully. It subsumes most popular MDS versions as special cases. We illustrate the ideas, use, flexibility and versatility of the method and the package with data from clinical psychology on how modules of the Modular Approach to Therapy for Children (MATCH) are used by clinicians in the wild. We supplement the COPS analyses with density-based hierarchical clustering in the original space and faceting with support vector machines. We find that scaling with COPS gives a sensible and insightful spatial arrangement of the modules, allows easy identification of clusters of modules and provides clear facets of modules corresponding to the MATCH protocols. In that respect COPS works better than both standard MDS and clustering.
{"title":"COPS in Action: Exploring Structure in the Usage of the Youth Psychotherapy MATCH","authors":"T. Rusch, Katherine E. Venturo-Conerly, Gioia Baja, P. Mair","doi":"10.3390/psych5020020","DOIUrl":"https://doi.org/10.3390/psych5020020","url":null,"abstract":"This article is an introduction to Cluster Optimized Proximity Scaling (COPS) aimed at practitioners, as well as a tutorial on the usage of the corresponding R package cops. COPS is a variant of multidimensional scaling (MDS) that aims at providing a clustered configuration while still representing multivariate dissimilarities faithfully. It subsumes most popular MDS versions as special cases. We illustrate the ideas, use, flexibility and versatility of the method and the package with data from clinical psychology on how modules of the Modular Approach to Therapy for Children (MATCH) are used by clinicians in the wild. We supplement the COPS analyses with density-based hierarchical clustering in the original space and faceting with support vector machines. We find that scaling with COPS gives a sensible and insightful spatial arrangement of the modules, allows easy identification of clusters of modules and provides clear facets of modules corresponding to the MATCH protocols. In that respect COPS works better than both standard MDS and clustering.","PeriodicalId":93139,"journal":{"name":"Psych","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49417252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Walter P. Vispoel, Hyeryung Lee, Tingting Chen, Hyeri Hong
Generalizability theory provides a comprehensive framework for determining how multiple sources of measurement error affect scores from psychological assessments and using that information to improve those assessments. Although generalizability theory designs have traditionally been analyzed using analyses of variance (ANOVA) procedures, the same analyses can be replicated and extended using structural equation models. We collected multi-occasion data from inventories measuring numerous dimensions of personality, self-concept, and socially desirable responding to compare variance components, generalizability coefficients, dependability coefficients, and proportions of universe score and measurement error variance using structural equation modeling versus ANOVA techniques. We further applied structural equation modeling techniques to continuous latent response variable metrics and derived Monte Carlo-based confidence intervals for those indices on both observed score and continuous latent response variable metrics. Results for observed scores estimated using structural equation modeling and ANOVA procedures seldom varied. Differences in reliability between raw score and continuous latent response variable metrics were much greater for scales with dichotomous responses, thereby highlighting the value of doing analyses on both metrics to evaluate gains that might be achieved by increasing response options. We provide detailed guidelines for applying the demonstrated techniques using structural equation modeling and ANOVA-based statistical software.
{"title":"Using Structural Equation Modeling to Reproduce and Extend ANOVA-Based Generalizability Theory Analyses for Psychological Assessments","authors":"Walter P. Vispoel, Hyeryung Lee, Tingting Chen, Hyeri Hong","doi":"10.3390/psych5020019","DOIUrl":"https://doi.org/10.3390/psych5020019","url":null,"abstract":"Generalizability theory provides a comprehensive framework for determining how multiple sources of measurement error affect scores from psychological assessments and using that information to improve those assessments. Although generalizability theory designs have traditionally been analyzed using analyses of variance (ANOVA) procedures, the same analyses can be replicated and extended using structural equation models. We collected multi-occasion data from inventories measuring numerous dimensions of personality, self-concept, and socially desirable responding to compare variance components, generalizability coefficients, dependability coefficients, and proportions of universe score and measurement error variance using structural equation modeling versus ANOVA techniques. We further applied structural equation modeling techniques to continuous latent response variable metrics and derived Monte Carlo-based confidence intervals for those indices on both observed score and continuous latent response variable metrics. Results for observed scores estimated using structural equation modeling and ANOVA procedures seldom varied. Differences in reliability between raw score and continuous latent response variable metrics were much greater for scales with dichotomous responses, thereby highlighting the value of doing analyses on both metrics to evaluate gains that might be achieved by increasing response options. We provide detailed guidelines for applying the demonstrated techniques using structural equation modeling and ANOVA-based statistical software.","PeriodicalId":93139,"journal":{"name":"Psych","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45207775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Stevens’s classification of scales into nominal, ordinal, interval, and ratio types is among the most controversial yet resilient ideas in psychological and educational measurement. In this essay, I challenge the notion that scale type is essential for the development of measures in these fields. I highlight how the concept of scale type, and of interval-level measurement in particular, is variously interpreted by many researchers. These (often unstated) differences in perspectives lead to confusion about what evidence is appropriate to demonstrate interval-level measurement, as well as the implications of scale type for research in practice. I then borrow from contemporary ideas in the philosophy of measurement to demonstrate that scale type can only be established in the context of well-developed theory and through experimentation. I conclude that current notions of scale type are of limited use, and that scale type ought to occupy a lesser role in psychometric discourse and pedagogy.
{"title":"Scale Type Revisited: Some Misconceptions, Misinterpretations, and Recommendations","authors":"L. Feuerstahler","doi":"10.3390/psych5020018","DOIUrl":"https://doi.org/10.3390/psych5020018","url":null,"abstract":"Stevens’s classification of scales into nominal, ordinal, interval, and ratio types is among the most controversial yet resilient ideas in psychological and educational measurement. In this essay, I challenge the notion that scale type is essential for the development of measures in these fields. I highlight how the concept of scale type, and of interval-level measurement in particular, is variously interpreted by many researchers. These (often unstated) differences in perspectives lead to confusion about what evidence is appropriate to demonstrate interval-level measurement, as well as the implications of scale type for research in practice. I then borrow from contemporary ideas in the philosophy of measurement to demonstrate that scale type can only be established in the context of well-developed theory and through experimentation. I conclude that current notions of scale type are of limited use, and that scale type ought to occupy a lesser role in psychometric discourse and pedagogy.","PeriodicalId":93139,"journal":{"name":"Psych","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47956414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-29DOI: 10.1101/2023.03.29.23287904
Luke Hughes, Anika R Petrella, L. Fern, R. Taylor
Background: Leadership during the COVID-19 pandemic often manifested as a command-and-control style of leadership which had detrimental emotional impacts on staff particularly the nursing workforce. Organisational responsibility for staff wellbeing would be necessary in another pandemic and leadership emerged as a key indicator of the overall health of an organisation and its workforce. Leadership can have detrimental effects on staff wellbeing or it can greatly boost their ability to handle a crisis. We sought to explore the interrelationship between leadership and nurses wellbeing in an inner-city university hospital during the initial wave of the pandemic. Methods: Secondary analysis of interview data collected during a hospital-wide evaluation of barriers and facilitators to changes implemented to support the surge of COVID-19 related admissions during wave 1. Data were collected through semi-structured video interviews between May and July 2020. Interviews were analysed using Framework analysis Results: Thirty-one nurses participated including matrons (n=7), sisters (n=8) and specialist nursing roles (n=16). Three overarching themes were identified: impact on nurses, personal factors and organisational factors. The impact on nurses manifested as distress and fatigue. Coping and help-seeking behaviours were found to be the two personal factors which underpinned nurses wellbeing. The organisational factors that impacted nurses wellbeing included decision-making, duty and teamwork. Conclusions: The wellbeing of the workforce is pivotal to the health service, and it is mutually beneficial for patients, staff, and leaders. Addressing how beliefs and misconceptions around wellbeing are communicated, and accessing psychological support is a key priority to support nurses during pandemics.
{"title":"Who is responsible for nurse wellbeing in a crisis? A single centre perspective","authors":"Luke Hughes, Anika R Petrella, L. Fern, R. Taylor","doi":"10.1101/2023.03.29.23287904","DOIUrl":"https://doi.org/10.1101/2023.03.29.23287904","url":null,"abstract":"Background: Leadership during the COVID-19 pandemic often manifested as a command-and-control style of leadership which had detrimental emotional impacts on staff particularly the nursing workforce. Organisational responsibility for staff wellbeing would be necessary in another pandemic and leadership emerged as a key indicator of the overall health of an organisation and its workforce. Leadership can have detrimental effects on staff wellbeing or it can greatly boost their ability to handle a crisis. We sought to explore the interrelationship between leadership and nurses wellbeing in an inner-city university hospital during the initial wave of the pandemic. Methods: Secondary analysis of interview data collected during a hospital-wide evaluation of barriers and facilitators to changes implemented to support the surge of COVID-19 related admissions during wave 1. Data were collected through semi-structured video interviews between May and July 2020. Interviews were analysed using Framework analysis Results: Thirty-one nurses participated including matrons (n=7), sisters (n=8) and specialist nursing roles (n=16). Three overarching themes were identified: impact on nurses, personal factors and organisational factors. The impact on nurses manifested as distress and fatigue. Coping and help-seeking behaviours were found to be the two personal factors which underpinned nurses wellbeing. The organisational factors that impacted nurses wellbeing included decision-making, duty and teamwork. Conclusions: The wellbeing of the workforce is pivotal to the health service, and it is mutually beneficial for patients, staff, and leaders. Addressing how beliefs and misconceptions around wellbeing are communicated, and accessing psychological support is a key priority to support nurses during pandemics.","PeriodicalId":93139,"journal":{"name":"Psych","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46359072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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