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Job sectors. Accountancy, banking and finance. Business, consulting and management. Charity and voluntary work. Creative arts and design. Energy and utilities. Engineering and manufacturing. Environment and agriculture. Healthcare. Hospitality and events management. Information technology. Law. How to Write a Questionnaire Example. Whether it is a student questionnaire example or a marketing research questionnaire that you will create, here are some steps that can help you make a questionnaire in an easier and more efficient manner: Identify the purpose on why the questionnaire is needed to be created. Make sure that you are aware of all the variables that should be present within . We would like to show you a description here but the site won’t allow onlinenicedating.com more.
A cross-sectional psychometric study using confirmatory factor analysis. The original three-factor model was tested and modified using half-samples. Models were assessed using goodness-of-fit measures.
We administered a web-based survey from January to May to healthcare staff participating in initiatives aimed at delivering better care and reducing costs. A total of respondents completed the SEHC survey in full and were used in this study. The mean SEHC score was A one-factor model of job satisfaction had high loadings on all items, and demonstrated adequate model fit second half-sample RMSEA: 0. The SEHC appears to measure a single general job satisfaction construct.
The scale has adequate reliability and validity to recommend its use to assess satisfaction among multidisciplinary, U.
Our findings suggest that this survey is a good candidate for reduction to a short-form, and future research should validate this survey in other healthcare populations. As the world's population increases, the World Health Organizations predicts a global shortfall of In the United States U. Therefore, overcoming healthcare workforce shortages including recruitment and retention of healthcare staff has become a key priority [ 1 ].
Job satisfaction has been identified as an important factor in healthcare staff retention [ 4 — 6 ]. Job satisfaction of physicians and nurses has been found to affect quality of care, patient satisfaction and turnover [ 4 , 7 — 10 ].
Conversely, job dissatisfaction is associated with worse patient-provider ratios, longer wait times and staff burnout [ 6 , 11 ].
New models of healthcare are addressing healthcare workforce shortages by re-tooling the workforce to incorporate multidisciplinary teams [ 12 — 14 ]. Measuring job satisfaction is an important component to develop these new models because how well healthcare staff accept and adapt to new models of care is critical for staff retention.
However, little is known about assessing job satisfaction across multidisciplinary staff that include non-traditional healthcare team members such as medical assistants, lay-health workers and social workers.
While there are several existing job satisfaction instruments, often they are tailored to specific positions e. These instruments may be too specialized to adequately capture job satisfaction in multidisciplinary teams or too broad to be relevant to healthcare settings. To address this gap, the Satisfaction of Employees in Health Care SEHC survey was designed to assess job satisfaction among diverse staff in hospitals and health centers [ 20 ].
The SEHC was developed using items from five satisfaction surveys previously validated in multiple settings, literature review and stakeholder interviews; the survey was designed for use among clinical, technical and management healthcare staff in Ethiopia [ 20 ]. The item SEHC survey identified three dimensions of job satisfaction: i relationships with management and supervisors, ii job content and iii relationships with coworkers. We used this survey to assess job satisfaction in the U.
Two studies using the SEHC survey have been published [ 20 , 21 ]. However, both were conducted in Africa and one did not assess the survey's psychometric properties. Our primary objective in this paper was to assess the appropriateness of the SEHC as an instrument to measure job satisfaction for a broad range of healthcare employees across the U. We evaluated the factor structure, reliability and validity of the SEHC survey. Confirmatory factor analysis CFA was conducted on two randomly drawn half-samples to test the hypothesized factor structures.
CMS is the U. CMS funded the Health Care Innovation Awards Round One to encourage grassroots innovations in payment and delivery models targeting populations with the highest healthcare needs [ 22 , 23 ].
In July , awards were made to awardee projects across the U. Awards were given to a broad range of organizations, including healthcare providers, payers, local governments, public-private partnerships and multi-payer collaborative agreements, to implement innovations to reduce healthcare costs and utilization, and to improve patient satisfaction and quality of care.
These diverse projects varied in settings e. Awardee projects consisted of components such as care coordination, integrated care, workflow redesign, health information technology, and telemedicine.
A key component of the models was identifying new models of workforce development such as intensive staff training and recruitment and deployment of an expanded healthcare workforce including non-licensed support staff such as community health workers. We collected consistent job satisfaction information across these diverse projects for future evaluation of how satisfaction was associated implementation and success of awardee projects. To request participation in the web-based survey, we first emailed project directors to inform them of the SEHC survey and then sent another email to request survey distribution to all staff whose positions were funded, fully or partially, by the award.
In January , 94 awardee project directors were sent emails. The same email requests were sent in April to the directors of the remaining 14 awardee projects that had been fielding other surveys when the initial email was sent. Project directors were sent two reminder emails. Each awardee project was provided with a unique web link that employees used to access the survey. The survey was open to employees from January to May The last 2 items were global staff satisfaction measures that asked whether the respondent would recommend the health facility to other workers item 19 , and how the respondent would rate the health facility as a place to work item Item 20 was on a point scale with 1 being worst and 10 being best.
We rescaled responses 0— so that they were comparable across items. The total SEHC score was the mean of the first 18 items, with higher scores reflecting higher levels of satisfaction. Respondents also completed a short questionnaire requesting their position type, time at their current position and if they had a non-traditional healthcare position care coordinator, case manager, community health worker or patient navigator. Respondents were not asked to report their age or gender.
CFA is a form of structural equation modeling used to test hypothesized factor structures formulated via theory or suggested by prior empirical research. We used CFA to perform two rounds of psychometric analyses. We split our sample into randomly drawn halves so that we could use the first half-sample for exploratory purposes and the second half-sample for confirmatory purposes. We then used output from this model to identify ways of simplifying and improving model fit.
We added covariances between error terms if modification indices were Two authors J. We then conducted another round of psychometric analysis with the second half-sample to confirm the factor structure we developed in the first round of analyses. We assessed the fit of the models using multiple indices since each index provides information on a different aspect of model fit. Although reported, we did not use the chi-squared test to evaluate fit because of its sensitivity to large sample sizes [ 26 ].
Comparative fit of different models was evaluated with the chi-squared difference test. Differences in characteristics and survey responses between the two half-samples were tested using the chi-squared test and t -test, as appropriate. The respondents who completed the first 18 SEHC items were included in the psychometric analyses.
At the awardee project level, approximately one-third of respondents worked at academic institutions, more than two-fifths were in a community-based setting, and more than three-fifths were in urban settings. Table 1 Demographic characteristics for healthcare staff respondents. There were no statistically significant differences in the individual and organizational characteristics between the two randomly divided half-samples.
The mean total SEHC score was Mean item scores ranged from Mean scores and SDs for the global satisfaction items 19 and 20 were Model fit indices are presented in Table 3 and standardized factor loadings of all tested models are presented in Appendix III.
Table 3 Summary of model fit statistics. However, this model did not converge Model 0a. We fit a model that allowed the three factors to be correlated Model 1a. This model did not fit the data well e. Evaluation of Model 1a showed high correlations between the factors correlation of Factor 1 with Factor 2: 0. The high correlations between factors helped explain why Model 0a which specified that the factors were uncorrelated did not converge and suggested that a more parsimonious solution could be obtained.
We then refit the data to a one-factor model Model 2a. Fit diagnostics also revealed nine significant hypothesized covariances between error terms. The coefficient was 0. The correlations between the total SEHC score and the global staff satisfaction items items 19 and 20 using the total sample were high 0.
This study collected data from a diverse group of healthcare staff in the U. The present findings provide strong evidence that a single construct underlies job satisfaction as measured by the SEHC items. Although this is not consistent with the original orthogonal three-factor structure proposed by Alpern et al. The structural results were influenced by allowing for correlated response errors that are common in self-report instruments like the SEHC.
Our one-factor model is more parsimonious than the original three-factor model. Our one-factor model also exhibits greater validity than the three-factor model as exhibited by the stronger correlations of the total SEHC score with the two global satisfaction items.
The large factor loadings indicate a considerable amount of redundancy among items, suggesting that the SEHC may be a good candidate for reduction to a shorter version that still retains the psychometric properties of the full instrument. Differences in our factor structure compared to the structure developed by Alpern et al. Between our sample and Alpern et al.
In particular, the two samples had a similar proportion of responses from licensed providers. While Alpern et al. Responses to the items also were largely positive among Malawian nurses. However, Malawian nurses were more likely than U. Differences in responses may reflect the inherent differences in healthcare organizations in the U. New healthcare models of workforce development are being designed and tested to address the increasing healthcare workforce shortfalls across the world.
Measuring how changes in the workplace affect job satisfaction will be important to consider when implementing innovations since healthcare work environments have been found to be associated with job satisfaction and burnout [ 27 ].
Pulling relevant items from previously validated job satisfaction surveys, the SEHC is the first job satisfaction survey to be validated for a wide range of staff on healthcare teams and healthcare settings, such as research analysts and community health workers.
Given the current mix of healthcare staff and the projected increased use of non-clinical staff to free up clinician time in the U. Having one short item survey for all healthcare staff can allow healthcare organizations to monitor staff satisfaction across all levels without overburdening staff and analysts with multiple surveys or fielding several non-comparable surveys.
This study had several notable limitations.