Psychological Distress and Sleep Disturbance Among Female Nurses: Anxiety or Depression?

Chueh, Ke‐Hsin; Chen, Kai‐Ren; Lin, Ya-Hui

doi:10.1177/1043659619881491

Cited by 35 publications

(34 citation statements)

References 31 publications

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“…In our primary analysis, frustration with technology was found to be associated with burnout independently of other markers of WLI. This association was not as strong as the one observed for difficulty sleeping, consistent with observations that sleep disturbance may itself be an indicator of psychological distress [ 55 ]. However, it was similar in magnitude to the associations for other items reflecting excessive workload or workplace inefficiencies, such as changing personal/family plans because of work, working a shift without any breaks, or arriving home late from work.…”

Section: Discussionsupporting

confidence: 80%

Frustration With Technology and its Relation to Emotional Exhaustion Among Health Care Workers: Cross-sectional Observational Study

Tawfik¹,

Sinha²,

Bayati³

et al. 2021

J Med Internet Res

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Background New technology adoption is common in health care, but it may elicit frustration if end users are not sufficiently considered in their design or trained in their use. These frustrations may contribute to burnout. Objective This study aimed to evaluate and quantify health care workers’ frustration with technology and its relationship with emotional exhaustion, after controlling for measures of work-life integration that may indicate excessive job demands. Methods This was a cross-sectional, observational study of health care workers across 31 Michigan hospitals. We used the Safety, Communication, Operational Reliability, and Engagement (SCORE) survey to measure work-life integration and emotional exhaustion among the survey respondents. We used mixed-effects hierarchical linear regression to evaluate the relationship among frustration with technology, other components of work-life integration, and emotional exhaustion, with adjustment for unit and health care worker characteristics. Results Of 15,505 respondents, 5065 (32.7%) reported that they experienced frustration with technology on at least 3-5 days per week. Frustration with technology was associated with higher scores for the composite Emotional Exhaustion scale (r=0.35, P<.001) and each individual item on the Emotional Exhaustion scale (r=0.29-0.36, P<.001 for all). Each 10-point increase in the frustration with technology score was associated with a 1.2-point increase (95% CI 1.1-1.4) in emotional exhaustion (both measured on 100-point scales), after adjustment for other work-life integration items and unit and health care worker characteristics. Conclusions This study found that frustration with technology and several other markers of work-life integration are independently associated with emotional exhaustion among health care workers. Frustration with technology is common but not ubiquitous among health care workers, and it is one of several work-life integration factors associated with emotional exhaustion. Minimizing frustration with health care technology may be an effective approach in reducing burnout among health care workers.

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Section: Discussionsupporting

confidence: 80%

Frustration With Technology and its Relation to Emotional Exhaustion Among Health Care Workers: Cross-sectional Observational Study

Tawfik¹,

Sinha²,

Bayati³

et al. 2021

J Med Internet Res

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“…Recent studies have shown that unhealthy lifestyles (poor sleep quality, depression, and conscious health impact, etc.) caused by busy work, high loads and high pressure will increase the intention of nursing staff to turnover and leave the job [ 5 ], and have found that especially the quality of sleep and depression have a great impact on the mental health and overall health of nursing staff [ 6 , 7 ].…”

Section: Introductionmentioning

confidence: 99%

Effects of an Adaptive Education Program on the Learning, Mental Health and Work Intentions of New Graduate Nurses

Chen

Fang

Wang

et al. 2021

IJERPH

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Health care workers are at a higher risk of psychological distress than ordinary people. Stress affects physical and mental health, and can even produce an intention to leave. The current training for new graduate nurses (NGNs) during this transitional period mostly focuses on the cultivation of professional ability, with less attention to mental health or emotional feelings, and thus there are insufficient structured support strategies. As such, this study explores the effects of intervention through an appropriate education program on the learning, mental health and work intentions of new recruits during the transition period. A pre-test and post-test for a single group was designed for new nursing staff in a large teaching hospital in northern Taiwan. The test period was from May 2017 to December 2018, and a total of 293 cases were accepted. A three-month adaptive education program was provided and evaluated in terms of: care for learning, care for health, improving professional ability, and individualized guidance on satisfaction, mental health disturbance and work intention. The new graduate nurses who received gentle care and counseling showed a downward trend in their BSRS-5 scores and statistical differences over time (p < 0.001). The higher the BSRS-5 score, the easier it is for new graduate nurses in acute and intensive care units. There is a tendency for turnover leave (p = 0.03). After the intervention of the overall plan, the turnover rate of new graduate nurses within three months was 12.6%, and the one-year retention rate was 87.9%. The adaptive education program uses multiple support strategies to improve learning and professional abilities, to reduce psychological emotions, and thereby to increase retention. Today will face new medical challenges; the education programs will become more important across clinical care settings, and it will be important to rigorously validate their performance in helping NGNs.

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“…Family factors, such as being married, further increased the risk of night shift-related sleep impairment due to increased family responsibilities ( Booker et al, 2018 ). The majority of nurses were female; a study of female nurses found that psychological distress, especially depression, was associated with sleep disturbance ( Chueh et al, 2021 ). Meanwhile, menopause-related symptoms also greatly influenced sleep quality ( Pien et al, 2008 ).…”

Section: Introductionmentioning

confidence: 99%

Poor Sleep Quality in Nurses Working or Having Worked Night Shifts: A Cross-Sectional Study

2021

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Night shifts are part of clinical care. It is unclear whether poor sleep quality of nurses working both consecutive night shifts and day shifts after quitting night shifts is common. In this cross-sectional study, Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep quality as study outcome. Univariable and multivariable linear and logistic regressions were performed to compare PSQI score and prevalence of poor sleep quality between 512 nurses currently working consecutive night shifts and 174 nurses having worked night shifts in the past. The prevalence of poor sleep quality was 62.11% in nurses working consecutive night shifts and 55.75% in nurses having worked night shifts before. In multivariable regressions with adjustment for potential confounders, compared with nurses working consecutive night shifts, nurses having worked past night shifts reported decreased PSQI score [mean difference: −0.82 (95% CI: −1.27 to −0.38, p < 0.001)] and lower poor sleep quality [odds ratio (OR): 0.49 (95% CI: 0.29 to 0.80, p = 0.005)]. In nurses working consecutive night shifts, a rising curve that plateaued at the end was observed between years of consecutive night shifts and PSQI score, p = 0.004. To explore the change in PSQI score after quitting night shift, we constructed a hypothetical prospective cohort from the cross-sectional data. Here, 98 pairs of nurses with consecutive and past night shifts were matched for the number of night shift years, religion, marital status, living condition, hypertension, and hyperlipidemia. In each pair, a hypothetical change in PSQI score was calculated between the two types of nurses and hypothetical years after quitting night shifts was obtained from the matched nurse with past night shifts. A U-shaped curve between change in PSQI and years after quitting night shifts was observed, p = 0.007. The rising curve and U-shaped curve together formed an S-shaped curve, which mapped the change in sleep quality. These results based on the hypothetical cohort constructed from cross-sectional data suggested the presence of persistent poor sleep quality in night shift nurses. Also, we support early and continuous sleep hygiene education and reflection for an optimal strategy for when to cease working night shifts with regard to sleep-related problems.

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Psychological Distress and Sleep Disturbance Among Female Nurses: Anxiety or Depression?

Cited by 35 publications

References 31 publications

Frustration With Technology and its Relation to Emotional Exhaustion Among Health Care Workers: Cross-sectional Observational Study

Frustration With Technology and its Relation to Emotional Exhaustion Among Health Care Workers: Cross-sectional Observational Study

Effects of an Adaptive Education Program on the Learning, Mental Health and Work Intentions of New Graduate Nurses

Poor Sleep Quality in Nurses Working or Having Worked Night Shifts: A Cross-Sectional Study

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