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Record W2041935893 · doi:10.1108/ebhrm-02-2013-0001

Part-time versus full-time work: an empirical evidence-based case of nurses in Spain

2014· article· en· W2041935893 on OpenAlexaff
Ronald J. Burke, Simón L. Dolan, Lisa Fıksenbaum

Bibliographic record

VenueEvidence-based HRM a Global Forum for Empirical Scholarship · 2014
Typearticle
Languageen
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsYork University
Fundersnot available
KeywordsFull-timePsychologyAbsenteeismNursingContext (archaeology)Work engagementSpouseWork (physics)Applied psychologyMedicineSocial psychology

Abstract

fetched live from OpenAlex

Purpose – The purpose of this paper is to examine the reasons given by nurses for working part-time; compare the work experiences, satisfactions, and psychological well-being of nursing staff working full-time vs part-time; and identify possible antecedents and sources of leverage to encourage part-time nurses to work full-time. Design/methodology/approach – An online survey was developed, pre-tested and validated, and sent to the regional associations of nurses in Spain for distribution to their members. Data collection involved a cross-sectional design. A total of 2,094 valid questionnaires were completed online. The majority of responding nurses were located in Catalunya and Gipuzkoa. Respondents were given 15 reasons and asked to indicate the extent to which each played a role in their decision to work part-time. Job context and job content scales bearing multi items reliable measures were also employed. All scales met the criteria of reliability. Findings – Nurses working full-time included more males, were older, had longer nursing experience (both job and unit tenure), reported higher levels of both job resources (autonomy, self-development opportunities), higher levels of positive work attitudes (job involvement, affective commitment, work engagement), more medication use, and a higher intention to quit. Full-time and part-time nursing staff were similar on marital status, levels of social support (supervisor, co-worker, spouse, and family), self-reported absenteeism, levels of burnout, levels of psychological well-being (psychosomatic symptoms, self-reported health), and potential accident propensity. Some of the more concrete results include: first, reasons for working part-time were varied with some being voluntary (going to school) and others involuntary (poor health). Second, different clusters of individuals likely exist (e.g. students, caretakers, transitioning to retirement or other career options). Third, part-time nursing staff tended to report a more negative workplace (less autonomy, fewer opportunities for self-development) and less favorable work attitudes (less engagement, job involvement, and affective commitment) than their full-time counterparts. Research limitations/implications – First, all data were collected using self-report questionnaires, raising the possibility of response set tendencies. Second, all data were collected at one point in time, making it difficult to determine cause-effect relationships. Third, although the sample was very large, it was not possible to determine its representativeness or a response rate given the data collection procedure employed. Fourth, the large sample size resulted in relatively small mean differences reaching levels of statistical significance. Fifth, many of the nurse and work/organizational outcomes were themselves significantly correlated inflating the number of statistically significant relationships reported. Finally, it is not clear to what extent the findings apply to Spain only. Practical implications – Health care organizations interested in encouraging and supporting part-time nursing staff to consider working full-time may have some sources of leverage. Part-time nursing staff indicated generally lower levels of commitment involvement and engagement compared to their full-time colleagues. Part-time nursing staff in this study reported lower levels of job resources, such as autonomy and self-development opportunities. Increasing nursing staff input into decision making, increasing levels of nursing staff empowerment, increasing supervisory development that in supporting and respecting the nursing staff contributions, reducing levels of workplace incivility, and improving nursing work team functioning would make the work experiences of part-time nursing staff more meaningful and satisfying. In addition, offering more flexible work schedules and tackling the stereotype associated with working only part-time would also address factors associated with working part-time. A more long-term strategy would involve enhancing both the psychological and physical health of nursing staff through the introduction of a corporate wellness initiative. Increasing the work ability of nursing staff by improving their psychological and physical well-being addresses a common factor in the part-time work decision. Social implications – There is a call in the paper for Spanish authorities to consider implementing the “Magnet hospital program” which is one model that has been shown to improve nurse and patient outcomes and is one solution to the shortage of hospital nurses in attracting them to work on a full-time basis. The process of Magnet recognition involves implementing 14 evidence-based standards. Originality/value – Experts claim that the part-time phenomenon is a growing trend and is there to stay. The authors still do not know sufficiently about the HR implications for having a large workforce of part-time employees. In this paper, a tentative attempt was made to better understand this phenomenon, especially when there is a shortage of qualified nurses in the health sector. Several promising research directions follow from this investigation. First, nurses working part-time need to be polled to identify factors that would encourage and support them should they desire to change to full-time work. Second, the authors learn more about the relatively low levels of involvement, commitment, and engagement of part-time nurses, a phenomenon that most organizations wish to minimize.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.027
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.601
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.003
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.173
GPT teacher head0.466
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations20
Published2014
Admission routes1
Has abstractyes

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