• Factors Related to Job Performance and Job Satisfaction in Certified Nursing Assistants

      Simpson, Marjorie; Resnick, Barbara (2010)
      Background: Certified Nursing Assistant (CNA) are responsible for assisting long-term care (LTC) residents in activities of daily living (ADLs) such as bathing, dressing, mobility, and feeding. When CNAs provide too much ADL assistance, functional decline and disability often result. LTC facilities are mandated to provide quality care that enables residents to maintain their highest level of physical well-being (OBRA, 1987). However, poor CNA job performance and job satisfaction are common obstacles in the LTC industry, influencing the quality of care and care outcomes of LTC residents. Purpose: The purpose of this study was to test a hypothesized model of factors related to CNA job performance and job satisfaction using path analysis procedures. The Core Self-Evaluations (CSE) model and Social Cognitive Theory served as the theoretical framework for the study. Methods: This was a secondary data analysis that utilized baseline data obtained from the 504 CNAs, employed in 12 LTC facilities, who participated in the Res-Care study (Resnick et al., 2007). Results: The majority of CNAs were female (93%) and African American (89%). The average CNA age was 39 (SD=12.1). Path analysis results showed that age and self-efficacy (challenges associated with restorative care) were positively related to CNA job satisfaction. Self-esteem was negatively related to CNA job satisfaction and positively related to self-efficacy. None of the variables in the model were related to CNA job performance. Fit statistics showed a good fit of the model to the data (χ<super>2</super> = 9.3, df= 6, χ<super>2</super>/df ratio = 21.6, RMSEA =.03[.00 - .07], CFI = .99). Conclusions: The findings provided partial support for the hypothesized model and utility of the CSE model and Social Cognitive Theory in CNAs. The negative relationship between CNA self-esteem and job satisfaction could have been due to confounding work-related variables. Future research should examine the mediating and moderating effects of job characteristics and organizational characteristics on CNA self-esteem and job satisfaction.
    • A Meta-Analysis of Transformational Leadership and Subordinate Nursing Personnel Organizational Commitment, Job Satisfaction, and Turnover Intentions

      Barlow, Kathleen; Geiger-Brown, Jeanne (2013)
      Background: The ANA and ANCC have identified transformational leadership as the style of leadership essential for nursing personnel to meet the challenges of the 21st century health care environment. Personnel shortages and escalating clinical demands on staff require nurse leader attention to organizational commitment, job satisfaction, and turnover intentions to retain high quality staff. While there are many correlational studies examining the relationship between transformational leadership and nursing personnel organizational commitment, job satisfaction, and turnover intentions, results are inconsistent. Additionally, there is little information about factors which may account for variations in these relationships. Aims: The aims of this study were: 1) to examine the overall magnitude of effects between transformational leadership (TFL) and nursing personnel organizational commitment (OC), job satisfaction (JS), and turnover intentions (TI) across a sample of studies, and 2) to evaluate variability in the magnitude of effects according to selected moderator variables. Methods: Search strategies included accessing computerized databases, emailing researchers, consulting experts, and footnote-chasing. Two independent, qualified reviewers reached consensus on inclusion criteria for selected studies, data extraction, and quality ratings. Data analysis was conducted using Comprehensive Meta-Analysis (Biostat, 2005) statistical software. Results: A total of 28 studies (k = 28) with 9,572 nursing personnel met the inclusion criteria for this meta-analysis. Pooled effect size estimates demonstrated statistically significant effect size relationships between TFL and OC (k = 14, MWES = .292), JS (k = 22, MWES = .596), and TI (k = 5, MWES = -.307). Sub-group analyses indicated significant heterogeneity across studies according to type of TFL instrumentation, subordinate nursing personnel patient care position, number of research sites, century of study, and type of publication. Sensitivity analysis showed significant variability according to higher and lower quality ratings for studies. Conclusion: Transformational leadership plays an important role to varying degrees in nursing personnel commitment to the organization, satisfaction at work, and staff retention. Nurse leaders can use knowledge of factors impacting relationships between TFL and subordinate nursing personnel OC, JS, and TI to inform organizational decision-making and maximize retention of quality subordinate nursing personnel
    • Nurses' work environment and job satisfaction

      Chen, Yao-Mei; Johantgen, Mary E. (2008)
      Background. Transforming nurses' work environment has become a concern for nurses, hospital administrators, policy makers, and consumers. Magnet Hospital accreditation is increasingly recognized as a symbol of hospitals that promote a positive nursing work environment which supports quality patient care and nurse satisfaction. While research from nursing, organizational, patient safety, and occupational health perspectives has examined many work environment factors, no research has simultaneously examined the effect of Magnet hospital attributes and occupational health models on nurse satisfaction. Purposes. (1) explore the relative influence of the Magnet hospital attributes and psychosocial work environment models on nurses' job satisfaction, and (2) identify the potential moderation effects of occupational health models. Methods. Using a cross-sectional design, the study examined baseline data from the European Nurses Early Exit (NEXT) Study, a multi-country study of nurses' work conditions and turnover conducted between 2002 and 2005. Registered staff nurses working in acute care settings from 31 hospitals in Belgium and Germany (N=3182) were studied. Measurement models were established using structural equation modeling and a multilevel approach that accounts for the nesting of nurses within hospitals. Magnet hospital attributes [MH] and job satisfaction [JS] were modeled as latent factors and demand-control-support [DCS] and effort-reward imbalance [ERI] were modeled as latent classes. Analysis was conducted with Mplus 4.21 and SPSS 12.0. Results. Consistent with findings in other countries, about 70% of these European hospital nurses reported high job demand and 40% reported high job strain. Variation in satisfaction was significantly explained by most MH attributes. At the individual level, personnel policies (primarily representing pay and organizational support) had the strongest influence on satisfaction. At the hospital level, management style had the strongest influence. When the occupational health models (DCS and ERI) and MH models were examined simultaneously, no moderation effects were found. The main effect of ERI had the strongest influence on JS as compared to DCS and MH, supporting the imbalance between nurses high work demands (effort) and control and support (reward). Conclusion. While the Magnet hospital attributes evolved in the U.S., they are relevant to European hospital nursing practice in Belgium and Germany. Likewise, these hospital nurses face high demands and experience high job strain, which must be addressed by nursing leaders and hospital administrators. Hospital nurse environment research must use multilevel modeling to better isolate the effects at the individual, work group, and hospital level.
    • Work stress/strain, low job satisfaction, and intent to leave home health care nursing among Home Health Care Registered Nurses (HHC RNs)

      Barker, Dorothy Paxson; Lipscomb, Jane (2011)
      Background: The U.S. shortage of Home Health Care (HHC) Registered Nurses (RNs) is growing and the demand for HHC RNs is estimated to increase 109% by 2020. Factors associated with this shortage of HHC nurses include job stress/strain and low job satisfaction. Predictors of intent to leave their present HHC nursing position are not clear. To date, no published studies have been found that apply the effort-reward imbalance (ERI) model to HHC RNs. Purpose: The purpose of this study was to measure the level of job stress/strain associated with a low job satisfaction and intent to leave reported by HHC RNs practicing in the state of Maryland. Methods: This is a secondary analysis of the data collected from 794 HHC RNs participating in a 2006 study exploring hazard exposures in homecare. A mixedmethods analysis was conducted including quantitative and qualitative analysis. Results: Of the 206 HHC RNs that provided a narrative, 27.2% (n=56) reported an intent to leave or had already left their HHC positions. The six most frequent categories reported in the HHC RNs narratives included; negative organizationaltraits, work stress, love homecare, overwhelming paperwork, inadequate financial compensation, nurse attrition/intent to leave. Logistic regression analysis demonstrated reward as a significant predictor of good job satisfaction for all groups. Overcommitment and effort were significant predictors of low job satisfaction. Elevated ERI scores were reported for respondents with (77.2%) and without (35.0%) narratives indicating the respondents with narratives reported a higher incidence of elevated ERI scores compared to those without narratives. Conclusions: Many HHC RNs noted improvement is needed in their work environment. Job strain/stress is evident among HHC RNs and aspects of effort, reward, and overcommitment were found to be associated with low job satisfaction but no association with intent to leave.
    • Work-related and personal factors influencing job satisfaction and intent to leave among certified nursing assistants in nursing homes

      Choi, JiSun; Johantgen, Mary E. (2010)
      Background: In response to the rapid growth of the aging population and the decline of the nuclear family, varied levels of long-term care have developed. Yet, it has been difficult to recruit and retain the "pink collar" workers who care for the residents. Moreover, there has been little methodologically strong research to try and understand the complex factors influencing job satisfaction and intent to leave. Aim: The aims of this study were: 1) to examine the influence of relevant work-related and personal factors on job satisfaction among Certified Nursing Assistants (CNAs) working in nursing homes, 2) to examine the influence of relevant work-related and personal factors, and job satisfaction on intent to leave among CNAs working in nursing homes, and 3) to identify the latent groups of CNAs that have different relationships among the factors and intent to leave. Methods: A descriptive correlational design was used to conduct a secondary data analysis from two linked databases: the 2004 National Nursing Home Survey and the 2004 National Nursing Assistant Survey. Two-level logistic regression modeling and two-level mixture modeling were performed using Stata 10.0/IC and Mplus 5.0. Results: Job satisfaction was significantly associated with intent to leave. Supportive supervision was a significant predictor of both CNAs' job satisfaction and intent to leave. While personal factors (age, education, and job history) were related to intent to leave, but not to job satisfaction. The mixture models explored the latent classes for intent to leave. Distinct differences in the relationships among the factors and CNA intent to leave were found between two classes; one class reflected CNAs where supportive supervision was a significant effect on intent to leave while for the other group, there was no significant relationship. Conclusion: Findings corroborate the results from previous studies that showed supportive supervision or compensation significantly contribute to higher job satisfaction and less intent to leave among CNAs working in nursing homes. Yet this study found that all CNAs do not respond to the motivators in the same way. Multilevel mixture modeling is a promising analytical technique that would provide more useful data.