Exploring the Factor Structure of the Job Demands-Resources Measure With Patient Violence on Direct Care Workers in the Home Setting

2017 ◽  
Vol 25 (2) ◽  
pp. 257-274 ◽  
Author(s):  
Ha Do Byon ◽  
Donna Harrington ◽  
Carla L. Storr ◽  
Jane Lipscomb
Keyword(s):  
Factor Analysis ◽  
Factor Structure ◽  
Factor Model ◽  
Job Demands ◽  
Direct Care ◽  
Direct Care Workers ◽  
Home Setting ◽  
Patient Violence ◽  
Measurement Framework ◽  
Care Workers

Background and Purpose: Workplace violence research in health care settings using the Job Demands-Resources (JD-R) framework is hindered by the lack of comprehensive examination of the factor structure of the JD-R measure when it includes patient violence. Is patient violence a component of job demands or its own factor as an occupational outcome? Method: Exploratory factor analysis and confirmatory factor analysis were conducted using a sample of direct care workers in the home setting (n = 961). Results: The overall 2-construct JD-R structure persisted. Patient violence was not identified as a separate factor from job demands; rather, two demand factors emerged: violence/emotional and workload/physical demands. Conclusions: Although the three-factor model fits the data, the two-factor model with patient violence being a component of job demands is a parsimonious and effective measurement framework.

Language Barrier as a Risk Factor for Injuries From Patient Violence Among Direct Care Workers in Home Settings: Findings From a U.S. National Sample

2017 ◽  
Vol 32 (5) ◽  
pp. 858-868 ◽  
Author(s):  
Ha Do Byon ◽  
Shijun Zhu ◽  
George J. Unick ◽  
Carla L. Storr ◽  
Jane Lipscomb
Keyword(s):  
Estimating Equation ◽  
National Sample ◽  
Language Barrier ◽  
Direct Care ◽  
Direct Care Workers ◽  
Medical Attention ◽  
Home Setting ◽  
Patient Violence ◽  
Care Workers ◽  
National Probability Sample

This study explored potential risk factors for injuries from patient violence among direct care workers in U.S. homes (DCWHs). A national probability sample of 3,377 DCWHs including home health and personal care aides was analyzed using complex sample analysis and generalized estimating equation. Injury from violence was defined as a work-related injury sustained by aggression, violence, or abuse that was reported to the agency, required medical attention or resulted in absenteeism from work. An association between suffering an injury from patient violence and having a language barrier with patients was noted (OR = 4.44; 95% CI = 1.57, 12.56; p = .005). Findings illuminate the importance of homecare providers to match language between DCWHs and patients to reduce patient violence and improve quality of care in the home setting.

Factorial Structure of the Therapist Adherence Measure-Revised (TAM-R) Within Multisystemic Therapy

2020 ◽  
Vol 36 (2) ◽  
pp. 427-431
Author(s):  
Aurelie M. C. Lange ◽  
Marc J. M. H. Delsing ◽  
Ron H. J. Scholte ◽  
Rachel E. A. van der Rijken
Keyword(s):  
Factor Analysis ◽  
Factor Structure ◽  
Factor Model ◽  
Multisystemic Therapy ◽  
Model Fit ◽  
Validity And Reliability ◽  
Adherence Measure ◽  
Therapist Adherence ◽  
Confirmatory Factor ◽  
The Us

Abstract. The Therapist Adherence Measure (TAM-R) is a central assessment within the quality-assurance system of Multisystemic Therapy (MST). Studies into the validity and reliability of the TAM in the US have found varying numbers of latent factors. The current study aimed to reexamine its factor structure using two independent samples of families participating in MST in the Netherlands. The factor structure was explored using an Exploratory Factor Analysis (EFA) in Sample 1 ( N = 580). This resulted in a two-factor solution. The factors were labeled “therapist adherence” and “client–therapist alliance.” Four cross-loading items were dropped. Reliability of the resulting factors was good. This two-factor model showed good model fit in a subsequent Confirmatory Factor Analysis (CFA) in Sample 2 ( N = 723). The current finding of an alliance component corroborates previous studies and fits with the focus of the MST treatment model on creating engagement.

An investigation into the factor structure of the Cognitive Therapy Scale – Revised (CTS-R) in a CBT training sample

2021 ◽  
pp. 1-11
Author(s):  
Sarah Beale ◽  
Silia Vitoratou ◽  
Sheena Liness
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Cognitive Therapy ◽  
Exploratory Factor Analysis ◽  
Factor Structure ◽  
Factor Model ◽  
Single Factor ◽  
Behaviour Therapy ◽  
Cognitive Behaviour ◽  
Confirmatory Factor

Abstract Background: Effective monitoring of cognitive behaviour therapy (CBT) competence depends on psychometrically robust assessment methods. While the UK Cognitive Therapy Scale – Revised (CTS-R; Blackburn et al., 2001) has become a widely used competence measure in CBT training, practice and research, its underlying factor structure has never been investigated. Aims: This study aimed to present the first investigation into the factor structure of the CTS-R based on a large sample of postgraduate CBT trainee recordings. Method: Trainees (n = 382) provided 746 mid-treatment audio recordings for depression (n = 373) and anxiety (n = 373) cases scored on the CTS-R by expert markers. Tapes were split into two equal samples counterbalanced by diagnosis and with one tape per trainee. Exploratory factor analysis was conducted. The suggested factor structure and a widely used theoretical two-factor model were tested with confirmatory factor analysis. Measurement invariance was assessed by diagnostic group (depression versus anxiety). Results: Exploratory factor analysis suggested a single-factor solution (98.68% explained variance), which was supported by confirmatory factor analysis. All 12 CTS-R items were found to contribute to this single factor. The univariate model demonstrated full metric invariance and partial scalar invariance by diagnosis, with one item (item 10 – Conceptual Integration) demonstrating scalar non-invariance. Conclusions: Findings indicate that the CTS-R is a robust homogenous measure and do not support division into the widely used theoretical generic versus CBT-specific competency subscales. Investigation into the CTS-R factor structure in other populations is warranted.

scholarly journals Turnover Intention Among Direct Care Workers of Older Adults in Chinese Hospitals and Nursing Homes

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 86-86
Author(s):  
Zhenzhen Zhang ◽  
Shuangshuang Wang ◽  
Nengliang (Aaron) Yao ◽  
Zhang Zhenzhen
Keyword(s):  
Job Satisfaction ◽  
Nursing Homes ◽  
Turnover Intention ◽  
Aged Care ◽  
Identity Transformation ◽  
Direct Care ◽  
Retention Rates ◽  
Direct Care Workers ◽  
Care Workers ◽  
The Government

Abstract High retention rates among direct care workers (DCWs) affect the quality of aged care. However, limited research has explored factors associated with retention in the Chinese aged care industry. This study compared turnover intention and job satisfaction among DCWs in Chinese hospitals and nursing homes. A total 370 DCWs from 7 hospitals (297 contractual, 73 non-contractual) and 311 DCWs from 7 nursing homes (27 contractual, 284 non-contractual) located in Fujian, China were recruited to fill out a questionnaire. Overall, DCWs from hospitals reported lower turnover intention (20.5 % vs 37.0%) and higher levels of job satisfaction (31.1% vs 16.4%) than DCWs from nursing homes. Specifically, contractual DCWs from hospitals indicated lower turnover intention (14.8%) than non-contractual DCWs from hospitals (43.8%) and both types of DCWs from nursing homes (36.3% and 44.4%). Higher job satisfaction was associated with lower turnover intention, but did not mediate the association between DCW types and turnover intention. Findings suggested that the government and institutions should help DCWs complete the identity transformation from non-contractual DCWs to contractual DCWs to enhance job security and benefits. For nursing home DCWs, licensing and registration requirements shall meet the standards for hospital DCWs. Attention is also to be paid to working conditions and staff welfare of DCWs, including social insurance, pensions, and trainings, to improve job satisfaction and reduce turnover intention.

scholarly journals Evaluation of the Factor Structure of the Adolescent Stress Questionnaire in Chinese Adolescents

2018 ◽  
Vol 122 (6) ◽  
pp. 2366-2395
Author(s):  
Tianpeng Ye ◽  
Naixue Cui ◽  
Wen Yang ◽  
Jianghong Liu
Keyword(s):  
Factor Analysis ◽  
Factor Structure ◽  
Behavioral Problems ◽  
Romantic Relationship ◽  
Factor Model ◽  
Chinese Adolescents ◽  
School Students ◽  
Cross Cultural Differences ◽  
Distinct Factor ◽  
Adolescent Stress

This study evaluated the psychometric properties of the Chinese version of Adolescent Stress Questionnaire ( ASQ-CN) in a sample of Chinese middle school students ( N = 420; 52.14% boys and 47.86% girls). Iterated principal factor analysis and multiple-group principal components cluster analysis supported a six-factor model with 42 items out of 58 items in the ASQ-CN. The internal consistency was from .82 to .90. Girls reported lower stress levels in one subscale, Stress of romantic relationship, whereas no gender differences were found in the other five subscales. Compared with other studies of the ASQ in Westernized countries, the ASQ-CN showed a distinct factor structure that may be explained by cross-cultural differences. Scales constructed from factor analysis related negatively to measures of mindfulness and positively to a measure of behavioral problems, suggesting that they were valid for Chinese adolescent stress. The study did not support a higher order construct of the ASQ-CN. Altogether, our findings suggest that the ASQ-CN is adequate for assessing stressors in Chinese adolescents.

scholarly journals Empirical Approach to Developing an Optimal Socioeconomic Status Index for Health Surveillance

2022 ◽  
Author(s):  
Jordana LaFantasie ◽  
Francis Boscoe
Keyword(s):  
Socioeconomic Status ◽  
Factor Analysis ◽  
Factor Structure ◽  
Factor Model ◽  
Health Surveillance ◽  
Cancer Surveillance ◽  
Income Poverty ◽  
One Dimensional ◽  
Indicator Variables ◽  
Statistical Consistency

The association between multi-dimensional deprivation and public health is well established, and many area-based indices have been developed to measure or account for socioeconomic status in health surveillance. The Yost Index, developed in 2001, has been adopted in the US for cancer surveillance and is based on the combination of two heavily weighted (household income, poverty) and five lightly weighted (rent, home value, employment, education and working class) indicator variables. Our objectives were to 1) update indicators and find a more parsimonious version of the Yost Index by examining potential models that included indicators with more balanced weights/influence and reduced redundancy and 2) test the statistical consistency of the factor upon which the Yost Index is based. Despite the usefulness of the Yost Index, a one-factor structure including all seven Yost indicator variables is not statistically reliable and should be replaced with a three-factor model to include the true variability of all seven indicator variables. To find a one-dimensional alternative, we conducted maximum likelihood exploratory factor analysis on a subset of all possible combinations of fourteen indicator variables to find well-fitted one-dimensional factor models and completed confirmatory factor analysis on the resulting models. One indicator combination (poverty, education, employment, public assistance) emerged as the most stable unidimensional model. This model is more robust to extremes in local cost of living conditions, is comprised of ACS variables that rarely require imputation by the end-user and is a more parsimonious solution than the Yost index with a true one-factor structure.

scholarly journals It Is Time to Resolve the Direct Care Workforce Crisis in Long-Term Care

2020 ◽  
Author(s):  
Kezia Scales
Keyword(s):  
Long Term Care ◽  
The United States ◽  
Direct Care ◽  
Direct Care Workers ◽  
Term Care ◽  
Home Health Aides ◽  
Emerging Trends ◽  
Care Workers ◽  
Direct Care Workforce

Abstract Nearly 4.6 million direct care workers—including personal care aides, home health aides, and nursing assistants—provide daily support to older adults and people with disabilities across a range of settings in the United States, predominantly in long-term care (LTC). Even as the population grows older and drives up demand for LTC, the sector continues its decades-long struggle to fill direct care positions and stabilize this essential workforce. Recent events and emerging trends have converged, however, to produce new opportunities to address this longstanding workforce crisis, including the unprecedented attention generated by the coronavirus disease 2019 (COVID-19) pandemic and the systemic shifts to managed care and value-based payment in LTC. This Forum article outlines the pressing direct care workforce challenges in LTC before describing these potential levers of change, emphasizing the importance of not just expanding the workforce but also maximizing direct care workers’ contributions to the delivery of high-quality services for a growing and evolving population of LTC consumers.

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