8 resultados para Job Diagnostic Survey
em DigitalCommons@The Texas Medical Center
Resumo:
This dissertation focuses on the leadership styles of managers, the impact these leadership styles have on the job satisfaction of staff nurses, and the proclivity of nurses to consider unionization. The aims of the dissertation include conducting a literature review on topics of leadership style, job satisfaction, and unionization; identifying and elucidating pertinent constructs with respect to shared interrelationships and how they could be measured; and developing a means of assessing if and to what extent transformational and transactional leadership styles affect nurse proclivity to unionize.^ The instrumentation selected includes the Multifactor Leadership Survey, Job Satisfaction Survey, and a newly created Union Preference Survey. Each survey instrument was evaluated as to its appropriateness to administer at a non-consultant level within a health care facility. Options other than self-administering the survey instruments include online access for participants, which provides confidentiality and encourages more responses. ^ The next part of the dissertation is a plan for health care facilities to use the survey tool by administering it themselves. The plan provides a general description of the survey tool, administering the instrument, rating the instrument, and leadership development. Integration of the three surveys is presented in a non-statistical format by coordinating the results of the three survey instrument responses. Recommendations are presented on how to improve leadership development warranted for improvement.^ The conclusions reached are that nurses’ preference for unions is influenced by the leadership style of direct report managers, as rated by staff nurses, and the nurses’ job satisfaction, which is in turn in part dependent on their managers’ leadership style. Thus, changes in leadership style can have a profound impact on nurse job satisfaction and on nurses’ preference for unionization.^
Resumo:
Aim: To determine the relationship between nurse leader emotional intelligence and registered nurse job satisfaction. ^ Background: Nurse leaders influence the work environments of nurses working at the bedside. Nursing leadership plays an important role in fostering work environments that attract and retain nurses. ^ Methods: A non-experimental, predictive design study conducted in 5 hospitals evaluated relationships between 31 nurse leaders and 799 registered nurses. The nurse leaders were administered the MSCEIT and MBTI. The registered nurses participated in the 2010 NDNQI RN Job Satisfaction Survey. ^ Measurements and Results: The sample population completed two online instruments, the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) and the Myers Brigg Trait Inventory (MBTI). Nurse leader demographic data was collected consisting of age, sex, race, educational level, certification status and years in the profession of nursing. The relationships among characteristics of the nurse leader and staff nurses were examined using regression analysis and stepwise deletion. The results from the MBTI were obtained electronically from CPP. Inc. and the results of MSCEIT were obtained electronically from MHS, Inc. The nurse leader response rate was 46% and the NDNQI RN Job Satisfaction response rate was 62%. The sample of 31 nurse leaders were 65 percent female and 67.7% were White, 12.9% Black, and 19.4% Hispanic. The most prevalent MBTI type was ESTJ (19.35%), followed by ENFJ and ISFJ (9.68% each). The nurse leader sample was primarily extroverts (n=20), sensing (n=18), thinking (n=16) and judging (n=19). The nurse leaders' overall MSCEIT scores ranged from 69 to 111 (implying a range from those who should consider development to competent) with a mean score of 89.84 (consider improvement). The nurse leaders scored highest in the MSCEIT Facilitating subscale with scores ranging from 69 to 121 (consider development to strength) and a mean score of 95.19 (low average score). The overall mean MSCEIT mean scores for the entire sample ranged from 89.90 to 95.19 (consider emotional intelligence improvement to low average score) Overall, staff nurse participants in the NDNQI RN Job Satisfaction Survey were moderately satisfied with the nurse leaders as noted by a mean t score of 55.03 of 60 and this score was consistent with the comparison hospitals that participated in the 2010 NDNQI RN Job Satisfaction Survey (American Nurses Association, 2010). Staff nurses gave nurse leaders a mean score of 4.50 for patient assignments appropriate, and rated a mean score of 4.35 and moderately agreeing to recommend the hospital to a friend. ^ Conclusions: Future research is needed to determine if there is a relationship between nurse leader emotional intelligence ability and registered nurse job satisfaction. Additional research is also needed to determine what to measure in regards to nurse leader emotional intelligence, ability or behavior. Another issue that emerged in the examination of EI is the moderating relationship between the nurse leaders span of control and staff nurse satisfaction on the NDNQI. ^
Resumo:
This study of ambulance workers for the emergency medical services of the City of Houston studied the factors related to shiftwork tolerance and intolerance. The EMS personnel work a 24-hour shift with rotating days of the week. Workers are assigned to A, B, C, D shift, each of which rotate 24-hours on, 24-hours off, 24-hours on and 4 days off. One-hundred and seventy-six male EMTs, paramedics and chauffeurs from stations of varying levels of activity were surveyed. The sample group ranged in age from 20 to 45. The average tenure on the job was 8.2 years. Over 68% of the workers held a second job, the majority of which worked over 20 hours a week at the second position.^ The survey instrument was a 20-page questionnaire modeled after the Folkard Standardized Shiftwork Index. In addition to demographic data, the survey tool provided measurements of general job satisfaction, sleep quality, general health complaints, morningness/eveningness, cognitive and somatic anxiety, depression, and circadian types. The survey questionnaire included an EMS-specific scaler of stress.^ A conceptual model of Shiftwork Tolerance was presented to identify the key factors examined in the study. An extensive list of 265 variables was reduced to 36 key variables that related to: (1) shift schedule and demographic/lifestyle factors, (2) individual differences related to traits and characteristics, and (3) tolerance/intolerance effects. Using the general job satisfaction scaler as the key measurement of shift tolerance/intolerance, it was shown that a significant relationship existed between this dependent variable and stress, number of years working a 24-hour shift, sleep quality, languidness/vigorousness. The usual amount of sleep received during the shift, general health complaints and flexibility/rigidity (R$\sp2$ =.5073).^ The sample consisted of a majority of morningness-types or extreme-morningness types, few evening-types and no extreme-evening types, duplicating the findings of Motohashi's previous study of ambulance workers. The level of activity by station was not significant on any of the dependent variables examined. However, the shift worked had a relationship with sleep quality, despite the fact that all shifts work the same hours and participate in the same rotation schedule. ^
Resumo:
In response to growing concern for occupational health and safety in the public hospital system in Costa Rica, a research program was initiated in 1995 to evaluate and improve the safety climate in the national healthcare system through regional training programs, and to develop the capacity of the occupational health commissions in these settings to improve the identification and mitigation of workplace risks. A cross-sectional survey of 1000 hospital-based healthcare workers was conducted in 1997 to collect baseline data that will be used to develop appropriate worker training programs in occupational health. The objectives of this survey were to: (1) describe the safety climate within the national hospital system, (2) identify factors associated with safety climate focusing on individual and organizational variables, and (3) to evaluate the relationship between safety climate and workplace injuries and safety practices of employees. Individual factors evaluated included the demographic variables of age, gender, education and profession. Organizational factors evaluated included training, psychosocial work environment, job-task demands, availability of protective equipment and administrative controls. Work-related injuries and safety practices of employees included the type and frequency of injuries experienced and reported, and compliance with established safety practices. Multivariate regression analyses demonstrated that training and administrative controls were the two most significant predictors of safety climate. None of the demographic variables were significant predictors of safety climate. Safety climate was inversely and significantly associated with workplace injuries and positively and significantly associated with safety practices. These results suggest that training and administrative controls should be included in future training efforts and that improving safety climate will decrease workplace injuries and increase safety practices. ^
Resumo:
A census of 925 U.S. colleges and universities offering masters and doctorate degrees was conducted in order to study the number of elements of an environmental management system as defined by ISO 14001 possessed by small, medium and large institutions. A 30% response rate was received with 273 responses included in the final data analysis. Overall, the number of ISO 14001 elements implemented among the 273 institutions ranged from 0 to 16, with a median of 12. There was no significant association between the number of elements implemented among institutions and the size of the institution (p = 0.18; Kruskal-Wallis test) or among USEPA regions (p = 0.12; Kruskal-Wallis test). The proportion of U.S. colleges and universities that reported having implemented a structured, comprehensive environmental management system, defined by answering yes to all 16 elements, was 10% (95% C.I. 6.6%–14.1%); however 38% (95% C.I. 32.0%–43.8%) reported that they had implemented a structured, comprehensive environmental management system, while 30.0% (95% C.I. 24.7%–35.9%) are planning to implement a comprehensive environmental management system within the next five years. Stratified analyses were performed by institution size, Carnegie Classification and job title. ^ The Osnabruck model, and another under development by the South Carolina Sustainable Universities Initiative, are the only two environmental management system models that have been proposed specifically for colleges and universities, although several guides are now available. The Environmental Management System Implementation Model for U.S. Colleges and Universities developed is an adaptation of the ISO 14001 standard and USEPA recommendations and has been tailored to U.S. colleges and universities for use in streamlining the implementation process. In using this implementation model created for the U.S. research and academic setting, it is hoped that these highly specialized institutions will be provided with a clearer and more cost-effective path towards the implementation of an EMS and greater compliance with local, state and federal environmental legislation. ^
Resumo:
Delays in diagnosis of pulmonary tuberculosis have detrimental effects on the health of the ailing patient as well as the people around him or her. These effects are magnified in highly-travelled parts of the world. Identifying factors predictive of diagnostic delay is challenging, as these vary widely by culture and geography. Predictors of delay for tuberculosis patients living in the Northeastern Mexican city of Matamoros, a binationally-transited area, have yet to be described. Using secondary analysis of a retrospective survey, this study sought to identify predictors of diagnostic delay in a sample of culture-positive tuberculosis patients in Matamoros. Sociodemographic, behavioral, and health-related factors were measured and compared. Using bivariate and step-wise regression analyses at an alpha level of 0.05, the author found the following to be statically significant predictors for this sample (R 2=0.171): prior treatment of diabetes, recurrence of tuberculosis, and having ever used cocaine. A question assessing knowledge of immunocompromised subgroups was also identified as a predictor, although its implications are unclear. Notably, the instrument did not distinguish between patient and health system delay. In summary, more research should be conducted in the Matamoros area in order to fully understand the dynamics of delayed diagnosis and its application to public health practice.^
Resumo:
Existing data, collected from 1st-year students enrolled in a major Health Science Community College in the south central United States, for Fall 2010, Spring 2011, Fall 2011 and Spring 2012 semesters as part of the "Online Navigational Assessment Vehicle, Intervention Guidance, and Targeting of Risks (NAVIGATOR) for Undergraduate Minority Student Success" with CPHS approval number HSC-GEN-07-0158, was used for this thesis. The Personal Background and Preparation Survey (PBPS) and a two-question risk self-assessment subscale were administered to students during their 1st-year orientation. The PBPS total risk score, risk self-assessment total and overall scores, and Under Representative Minority Student (URMS) status were recorded. The purpose of this study is to evaluate and report the predictive validity of the indicators identified above for Adverse Academic Status Events (AASE) and Nonadvancement Adverse Academic Status Events (NAASE) as well as the effectiveness of interventions targeted using the PBPS among a diverse population of health science community college students. The predictive validity of the PBPS for AASE has previously been demonstrated among health science professions and graduate students (Johnson, Johnson, Kim, & McKee, 2009a; Johnson, Johnson, McKee, & Kim, 2009b). Data will be analyzed using binary logistic regression and correlation using SPSS 19 statistical package. Independent variables will include baseline- versus intervention-year treatments, PBPS, risk self-assessment, and URMS status. The dependent variables will be binary AASE and NAASE status. ^ The PBPS was the first reliable diagnostic and prescriptive instrument to establish documented predictive validity for student Adverse Academic Status Events (AASE) among students attending health science professional schools. These results extend the documented validity for the PBPS in predicting AASE to a health science community college student population. Results further demonstrated that interventions introduced using the PBPS were followed by approximately one-third reduction in the odds of Nonadvancement Adverse Academic Status Events (NAASE), controlling for URMS status and risk self-assessment scores. These results indicate interventions introduced using the PBPS may have potential to reduce AASE or attrition among URMS and nonURMS attending health science community colleges on a broader scale; positively impacting costs, shortages, and diversity of health science professionals.^
Resumo:
This investigation compares two different methodologies for calculating the national cost of epilepsy: provider-based survey method (PBSM) and the patient-based medical charts and billing method (PBMC&BM). The PBSM uses the National Hospital Discharge Survey (NHDS), the National Hospital Ambulatory Medical Care Survey (NHAMCS) and the National Ambulatory Medical Care Survey (NAMCS) as the sources of utilization. The PBMC&BM uses patient data, charts and billings, to determine utilization rates for specific components of hospital, physician and drug prescriptions. ^ The 1995 hospital and physician cost of epilepsy is estimated to be $722 million using the PBSM and $1,058 million using the PBMC&BM. The difference of $336 million results from $136 million difference in utilization and $200 million difference in unit cost. ^ Utilization. The utilization difference of $136 million is composed of an inpatient variation of $129 million, $100 million hospital and $29 million physician, and an ambulatory variation of $7 million. The $100 million hospital variance is attributed to inclusion of febrile seizures in the PBSM, $−79 million, and the exclusion of admissions attributed to epilepsy, $179 million. The former suggests that the diagnostic codes used in the NHDS may not properly match the current definition of epilepsy as used in the PBMC&BM. The latter suggests NHDS errors in the attribution of an admission to the principal diagnosis. ^ The $29 million variance in inpatient physician utilization is the result of different per-day-of-care physician visit rates, 1.3 for the PBMC&BM versus 1.0 for the PBSM. The absence of visit frequency measures in the NHDS affects the internal validity of the PBSM estimate and requires the investigator to make conservative assumptions. ^ The remaining ambulatory resource utilization variance is $7 million. Of this amount, $22 million is the result of an underestimate of ancillaries in the NHAMCS and NAMCS extrapolations using the patient visit weight. ^ Unit cost. The resource cost variation is $200 million, inpatient is $22 million and ambulatory is $178 million. The inpatient variation of $22 million is composed of $19 million in hospital per day rates, due to a higher cost per day in the PBMC&BM, and $3 million in physician visit rates, due to a higher cost per visit in the PBMC&BM. ^ The ambulatory cost variance is $178 million, composed of higher per-physician-visit costs of $97 million and higher per-ancillary costs of $81 million. Both are attributed to the PBMC&BM's precise identification of resource utilization that permits accurate valuation. ^ Conclusion. Both methods have specific limitations. The PBSM strengths are its sample designs that lead to nationally representative estimates and permit statistical point and confidence interval estimation for the nation for certain variables under investigation. However, the findings of this investigation suggest the internal validity of the estimates derived is questionable and important additional information required to precisely estimate the cost of an illness is absent. ^ The PBMC&BM is a superior method in identifying resources utilized in the physician encounter with the patient permitting more accurate valuation. However, the PBMC&BM does not have the statistical reliability of the PBSM; it relies on synthesized national prevalence estimates to extrapolate a national cost estimate. While precision is important, the ability to generalize to the nation may be limited due to the small number of patients that are followed. ^