The purpose of this study was to investigate the effects of aromatherapy on sleep quality.

This is a systematic review of randomized controlled trial studies (PROSPERO registration number CRD42017064519). In this study, the PICO were adults and the elderly, aromatherapy intervention, a comparative intervention with the control and placebo oil groups, and sleep. The selected articles were in English, Korean, and Chinese.

The results of the meta-analysis showed that the effect sizes of the experimental group were 1.03 (n=763, SMD=1.03, 95% CI 0.66 to 1.39) (Z=5.47, p<.001). In the aromatherapy intervention group, the effect size of sleep was statistically significant (Q_B=9.39, df=2, p=.009), with a difference of 0.77 for inhalation, 1.12 for oral intake and 2.05 for massage. A post-analysis showed that the effect of massage on sleep was significantly greater than the inhalation method. The regression coefficient of the intervention period, B=0.01 (Z=1.43, p=.154), also showed that the longer the intervention period, the larger the effect size; however, it was not statistically significant.

A total of 23 literature analyses showed that aromatherapy is effective in improving quality of sleep, and the massage method is more effective in improving quality of sleep than the inhalation method. A meta-ANOVA showed that the aromatherapy intervention affected the high heterogeneity of the effect size. Thus, future research with stricter control in methods and experimental procedures is necessary.

This study aimed to develop and test a structural model for sleep quality in female shift work nurses. The hypothetical model was constructed on the basis of Spielman's 3P model of insomnia and previous research related to the sleep quality of shift nurses.

This cross-sectional study used structural equation modeling and recruited 285 female shift work nurses from four general and university hospitals with over 300 beds located in C and J cities in Gyeongsangnamdo. Data were collected from September 27 to October 20, 2016, and then analyzed using descriptive statistics, Pearson's correlation, and structural equation modeling. The study used SPSS/Win 18.0 and AMOS 18.0 in processing the data.

The final model showed good fit to the empirical data: χ²/df=2.19, SRMR=.07, RMSEA=.07, AGFI=.85, TLI=.91, GFI=.93, GFI=.89, NFI=.87. The factors that influenced sleep quality were sleep hygiene (β=.32), perceived shift work status (β=−.16), stress response (β=.16), shift work experience (β=.15), perceived health status (β=−.14), and circadian rhythm (β=−.13) explaining 36.0% of the variance.

The model of sleep quality of the shift work nurses constructed in this study is recommended as a model to understand and predict the sleep quality of shift work nurses. The results suggest that strategies for improving the sleep quality of shift work nurses should focus on sleep hygiene, perceived health status, stress response, circadian rhythm, perceived shift work status, and shift work experience.