Introduction COVID-19 pandemic causes drastic changes in workplaces that are likely to increase quite quitting among employees. Although quiet quitting is not a new phenomenon, there is no instrument to measure it. Objective To develop and validate an instrument assessing quiet quitting among employees. Methods We identified and generated items through an extensive literature review and interviews with employees. We carried out the content validity by content experts and we calculated the content validity ratio. We checked face validity by conducting cognitive interviews with employees and calculating the item-level face validity index. We conducted exploratory and confirmatory factor analysis to investigate the quiet quitting scale (QQS) factorial structure. We checked the concurrent validity of the QQS using four other scales, i.e., Copenhagen burnout inventory (CBI), single item burnout (SIB) measure, job satisfaction survey (JSS) and a single item to measure turnover intention. We estimated the reliability of the QQS measuring Cronbach's alpha, McDonald's omega, Cohen's kappa and intraclass correlation coefficient. Results After expert panel review and item analysis, nine items with acceptable corrected item-total correlations, inter-item correlations, floor and ceiling effects, skewness and kurtosis were retained. Exploratory factor analysis extracted three factors, namely detachment, lack of initiative and lack of motivation, with a total of nine items. Confirmatory factor analysis confirmed this factorial structure for QQS. We found statistically significant correlations between QQS and CBI, SIB, JSS and turnover intention confirming that the concurrent validity of the QQS was great. Cronbach's alpha and McDonald's omega of the QQS were 0.803 and 0.806 respectively. Conclusion QQS, a three-factor nine-item scale, has robust psychometric properties. QQS is an easy-to-administer, brief, reliable and valid tool to measure employees' quiet quitting. We recommend the use of the QQS in different societies and cultures to assess the validity of the instrument.

Nurses experience high levels of job burnout and low levels of job satisfaction, while the COVID-19 pandemic has deteriorated working conditions. In this context, our aim was to compare levels of job burnout and job satisfaction among nurses and other healthcare workers (HCWs) after the COVID-19 pandemic. Moreover, we investigated the influence of demographics and job characteristics on burnout and satisfaction. We conducted a cross-sectional study with 1760 HCWs during June 2023. We used the single-item burnout measure and the “Job Satisfaction Survey”. In our sample, 91.1% of nurses experienced high levels of burnout, while the respective percentage for the other HCWs was 79.9%. Nurses’ satisfaction was lower than other HCWs. In particular, 61.0% of nurses experienced low levels of satisfaction, while the respective percentage for the other HCWs was 38.8%. Multivariable analysis identified that nurses, HCWs with an MSc/PhD diploma, shift workers, and those who considered their workplace as understaffed had higher burnout score and lower satisfaction score. Our results showed that the nursing profession was an independent factor of burnout and satisfaction. Several other demographic and job characteristics affected burnout and satisfaction. Policy makers, organizations, and managers should adopt appropriate interventions to improve work conditions.

As turnover intention is a strong determinant of actual turnover behavior, scholars should identify the determinants of turnover intention. In this context, the aim of this study was to assess the effect of quiet quitting on nurses’ turnover intentions. Additionally, this study examined the impact of several demographic and job characteristics on turnover intention. A cross-sectional study with 629 nurses in Greece was conducted. The data were collected in September 2023. Quiet quitting was measured with the “Quiet Quitting” scale. In this study, 60.9% of nurses were considered quiet quitters, while 40.9% experienced high levels of turnover intention. Multivariable regression analysis showed that higher levels of quiet quitting increased turnover intention. Moreover, this study found that turnover intention was higher among females, shift workers, nurses in the private sector, and those who considered their workplace understaffed. Also, clinical experience was associated positively with turnover intention. Since quiet quitting affects turnover intention, organizations, policymakers, and managers should address this issue to improve nurses’ intentions to stay at their jobs.