Introduction: COVID-19 pandemic causes drastic changes in workplaces that are likely to increase quite quitting among employees. Although quite quitting is not a new phenomenon, there is no instrument to measure it.Aim: 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 performed exploratory and confirmatory factor analysis to assess the “Quiet Quitting” Scale (QQS) factorial structure. We checked the concurrent validity of the QQS using four other scales, i.e., “Job Satisfaction Survey” (JSS), “Copenhagen Burnout Inventory” (CBI), “Single Item Burnout” (SIB) measure, 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 JSS, CBI, SIB, and turnover intention confirming that the concurrent validity of the QQS was very good. Cronbach’s alpha and McDonald’s Omega of the QQS were 0.803 and 0.806 respectively. Intraclass correlation coefficient for the total QQS score was 0.993 (p < 0.001). Cohen’s kappa for the nine items ranged from 0.836 to 0.945 (p < 0.001 in all cases). Conclusions: QQS, a three-factor nine-item scale, has robust psychometric properties. QQS is a brief, easy-to-administer, valid, and reliable 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.
The aim of the study was to examine the impact of moral resilience on quiet quitting, job burnout, and turnover intention among nurses. A cross-sectional study was implemented in Greece in November 2023. The revised Rushton Moral Resilience Scale was used to measure moral resilience among nurses, the Quiet Quitting Scale to measure levels of quiet quitting, and the single-item burnout measure to measure job burnout. Moreover, a valid six-point Likert scale was used to measure turnover intention. All multivariable models were adjusted for the following confounders: gender, age, understaffed department, shift work, and work experience. The multivariable analysis identified a negative relationship between moral resilience and quiet quitting, job burnout, and turnover intention. In particular, we found that increased response to moral adversity and increased moral efficacy were associated with decreased detachment score, lack of initiative score, and lack of motivation score. Additionally, personal integrity was associated with reduced detachment score, while relational integrity was associated with reduced detachment score, and lack of initiative score. Moreover, response to moral adversity was associated with reduced job burnout. Also, increased levels of response to moral adversity were associated with lower probability of turnover intention. Moral resilience can be an essential protective factor against high levels of quiet quitting, job burnout, and turnover intention among nurses. This study was not registered.
<sec><title>Background</title><p>There is an absence of valid and specific psychometric tools to assess TikTok addiction. Considering that the use of TikTok is increasing rapidly and the fact that TikTok addiction may be a different form of social media addiction, there is an urge for a valid tool to measure TikTok addiction.</p></sec><sec><title>Objective</title><p>To develop and validate a tool to measure TikTok addiction.</p></sec><sec><title>Methods</title><p>First, we performed an extensive literature review to create a pool of items to measure TikTok addiction. Then, we employed a panel of experts from different backgrounds to examine the content validity of the initial set of items. We examined face validity by performing cognitive interviews with TikTok users and calculating the item-level face validity index. Our study population included 429 adults who have been TikTok users for at least the last 12 months. We employed exploratory and confirmatory factor analysis to examine the construct validity of the TikTok Addiction Scale (TTAS). We examined the concurrent validity by using the Bergen Social Media Addiction Scale (BSMAS), the Patient Health Questionnaire-4 (PHQ-4), and the Big Five Inventory-10 (BFI-10). We used Cronbach's alpha, McDonald's Omega, Cohen's kappa, and intraclass correlation coefficient to examine reliability.</p></sec><sec><title>Results</title><p>We found that the TTAS is a six-factor 15-item scale with robust psychometric properties. Factor analysis revealed a six-factor structure, (1) salience, (2) mood modification, (3) tolerance, (4) withdrawal symptoms, (5) conflict, and (6) relapse, which accounted for 80.70% of the total variance. The concurrent validity of the TTAS was excellent since we found significant correlations between TTAS and BSMAS, PHQ-4, and BFI-10. Cronbach's alpha and McDonald's Omega for the TTAS were 0.911 and 0.914, respectively.</p></sec><sec><title>Conclusion</title><p>The TTAS appears to be a short, easy-to-use, and valid scale to measure TikTok addiction. Considering the limitations of our study, we recommend the translation and validation of the TTAS in other languages and populations to further examine the validity of the scale.</p></sec>
Abstract Introduction Adequate dental restoration including the use of implants is critical in healthy eating habits of diabetic patients and appropriate metabolic control. Aim To investigate the relationship between diabetes mellitus and dental implants stabilization and osseointegration. Methods A retrospective study was conducted in a private dental clinic in Athens. Data collection referred to the period between January 2016 and August 2021. During this time period, all cases related to implant placement in diabetic patients at the clinic were recorded. In particular, 93 implants were recorded in 36 diabetic patients. During the same time period, 93 implant cases involving non-diabetics at the clinic were randomly taken from the clinic records to provide the comparison group. The implant stability quotient was measured immediately after implant placement and after four months. Results The mean value of the implant stability quotient immediately after implant placement was 75.97 in non-diabetics and 76.85 in diabetics (p=0.42). The mean value of the implant stability quotient after four months was 78.92 in non-diabetics and 78.44 in diabetics (p=0.58). The mean value of the implant stability quotient in non-diabetics increased statistically significantly in the first four months from 75.97 to 78.92 (p<0.001). The mean value of the implant stability quotient in diabetics increased statistically significantly in the first four months from 76.85 to 78.44 (p=0.011). No implant loss was recorded in both diabetics and non-diabetics (p=1). According to multivariate analysis, patients who did not have bio-materials placed during implantation, patients who had not undergone previous surgical procedures and patients who had implants placed in the mandible had better implant stability. Conclusions The stability of the implants increased statistically significant in the first four months of implant placement. No relationship was found between diabetes mellitus and dental implants stabilization and osseointegration. However, studies with a larger sample size and longer follow-up of patients are needed to better clarify the risks and benefits of dental implants in diabetic patients.
Abstract Background: Continuous education is crucial to improve nurses’ knowledge and keep them update to new information. Aim: To evaluate the effectiveness of an e-learning activity regarding research methodology and fragility fractures in a sample of nurses. Moreover, we investigated the impact of demographic characteristics on knowledge level of nurses. Methods: We conducted a before-after study with a convenience sample of nurses working in different clinical settings. We conducted an e-learning activity regarding research methodology and fragility fractures. We developed 10 questions to assess the knowledge level of nurses before and after the e-learning activity. We created an online form of the questionnaire with Google forms. Our nurses completed the study questionnaire before and after the e-learning activity to assess differences in their knowledge. Additionally we measured overall evaluation, material evaluation, and educators’ evaluation in a scale from 0 to 10 with higher values indicating higher levels of evaluation. Results: Study population included 93 nurses. Among our sample, 86% (n=80) were females and 14% (n=13) were males. Mean age of nurses was 37.1 years, while mean years of experience was 13.6. Percentage of correct answers was improved after the e-learning activity for all questions. Moreover, we found a statistically significant improvement in eight questions (p<0.05) and a marginal statistically significant improvement in two questions (p<0.10). Mean knowledge score before the e-learning activity was 5.5, while after the e-learning activity improved to 7.6 (p<0.001). Conclusions: Effectiveness of the e-learning activity was very high, since nurses improved their knowledge in all fields. Continuous education is essential for nurses to improve their knowledge and thus provide high quality of healthcare especially in fragility fracture patients.
Abstract We developed and validated a self-assessment instrument to measure COVID-19 pandemic-related burnout in the general population. We assessed the psychometric properties of the COVID-19 burnout scale (COVID-19-BS). Exploratory and confirmatory factor analysis identified three factors for the COVID-19-BS; emotional exhaustion, physical exhaustion, and exhaustion due to measures against the COVID-19. Cronbach’ s alpha coefficients for the three factors and the COVID-19-BS ranged from 0.860 to 0.921. Kaiser-Meyer-Olkin value was 0.945 and p-value for Bartlett test was <0.001 indicating highly acceptable values. Convergent validity results indicated a significant positive correlation between COVID-19-BS and anxiety and depression. Known-groups analysis identified the ability of COVID-19-BS to discriminate groups according to gender, chronic condition, and health status. Our findings indicate that the final 13-item model of COVID-19-BS is a brief, easy to administer, valid and reliable scale for assessing COVID-19-related burnout in the general public.
AbstractBackground: Quiet quitting has emerged during the COVID-19 pandemic and its consequences for healthcare organizations and services have been expected. Objective: To identify levels of quiet quitting among clinical nurses in Greece. Moreover, we examined the impact of demographic and job characteristics on quiet quitting.Methods: We conducted an online cross-sectional study in Greece. We collected our data in February 2024. We obtained a convenience sample of nurses who have been working in clinical settings. We used the “Quiet Quitting” Scale (QQS) to measure levels of quiet quitting among nurses in our study. Moreover, we measured gender, age, educational level, job sector, understaffed workplace, shift work, and years of clinical experience. Results: Applying the suggested cut-off point we found that seven out of ten nurses (68.2%, n=620) can be considered as quiet quitters, while three out of ten (31.8%, n=289) can be considered as non-quiet quitters. We found that males experienced higher levels of quiet quitting than females (adjusted coefficient beta = 0.216, 95% CI = 0.093 to 0.339, p-value = 0.001). Additionally, shift workers (adjusted coefficient beta = 0.182, 95% CI = 0.091 to 0.272, p-value < 0.001) and nurses who have been working in understaffed workplaces (adjusted coefficient beta = 0.134, 95% CI = 0.006 to 0.262, p-value = 0.040) showed higher levels of quiet quitting. Decreased years of clinical experience were associated with increased quiet quitting (adjusted coefficient beta = -0.008, 95% CI = -0.012 to -0.004, p-value < 0.001). Conclusions: In our sample, nurses reported high levels of quiet quitting. Gender, shift work, an understaffed workplace, and clinical experience had an impact on quiet quitting. Healthcare organizations and managers should pay attention to quiet quitting in order to improve nurses’ productivity and patients’ outcomes.
Background: Measuring work engagement is essential to understand employee’s working conditions. Aim: To translate and validate the “Utrecht Work Engagement Scale” (3 items version) in Greek. Methods: Study population included 83 nurses in Greece. We performed our study during August 2024. We employed the forward-backward method to translate and adapt the “Utrecht Work Engagement Scale” (UWES-3) in Greek language. We examined the construct validity of the UWES-3 by performing confirmatory factor analysis. We examined the concurrent validity of the UWES-3 using the “Quiet Quitting Scale” (QQS), the single item burnout measure, and the single item turnover intention measure. We examined the reliability of the UWES-3 by calculating Cronbach’s alpha. We performed a test-retest study to evaluate reliability of the UWES-3. Results: The UWES-3 showed very good psychometric properties. Our confirmatory factor analysis confirmed the one-factor structure of the UWES-3. Concurrent validity of the Greek version of the UWES-3 was very good. We found a negative correlation between UWES-3 and QQS (r = -0.632, p-value < 0.001), single item burnout measure (r = -0.303, p-value = 0.005), and single item turnover intention measure (r = -0.299, p-value = 0.006). We found that the UWES-3 had very good reliability since Cronbach’s coefficient alpha was 0.924. Moreover, intraclass correlation coefficient for the total score was very high (0.995, 95% confidence interval [0.992 to 0.997], p-value < 0.001). Conclusions: The Greek version of the “Utrecht Work Engagement Scale” is a reliable and valid tool to measure the nursing practice environment.
<abstract><sec> <title>Introduction</title> <p>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.</p> </sec><sec> <title>Objective</title> <p>To develop and validate an instrument assessing quiet quitting among employees.</p> </sec><sec> <title>Methods</title> <p>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.</p> </sec><sec> <title>Results</title> <p>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.</p> </sec><sec> <title>Conclusion</title> <p>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.</p> </sec></abstract>
Background/Objectives: The nursing work environment, encompassing accessible resources and established processes, might affect nurses’ professional behavior. Our aim was to examine the effect of nurses’ work environments on quiet quitting and work engagement among nurses. Methods: We performed a cross-sectional study with nurses in Greece. We used the “Practice Environment Scale-5” to measure nurses’ work environments, the “Quiet Quitting Scale” to measure quiet quitting, and the “Utrecht Work Engagement Scale-3” to measure work engagement among nurses. We developed multivariable regression models adjusted for gender, age, understaffed wards, shift work, and work experience. Results: The study population included 425 nurses. The mean age of the nurses was 41.1 years. After controlling for confounders, we found that lower nurse participation in hospital affairs, less collegial nurse–physician relationships, worse nursing foundations for quality of care, and lower levels of nurse manager ability, leadership, and support were associated with higher levels of quiet quitting among nurses. Moreover, our multivariable analysis identified a positive association between nurse manager ability, leadership, and support, collegial nurse–physician relationships, nursing foundations for quality of care, and work engagement among nurses. Conclusions: Our findings highlight the poor work environment, elevated levels of quiet quitting, and moderate work engagement among nurses. Moreover, we found that a poor nurses’ work environment was associated with higher levels of quiet quitting. Moreover, our findings showed that nurses’ work environments had a positive impact on work engagement. The ongoing endeavor to enhance all aspects of nurses’ working conditions by healthcare organization administrations is essential for optimizing nurses’ performance, facilitating organizational operations, and ensuring service quality.
