With the introduction of the long-term care insurance system in 2008, South Korea established a national certification system for care workers to obtain a higher level of function and knowledge than home helpers and life aids under the Elderly Welfare Law. Care workers provide physical and housekeeping support services for patients in home care and long-term care (LTC) facilities who are unable to perform activities of daily living due to geriatric conditions such as dementia and stroke (National Health Insurance Reserved, 2012). As care workers are a large portion of the workforce in LTC facilities, and are in daily contact with older adults to deliver various services, they play a significant role in the content and quality of care services (Kim, 2012).
Care workers provide clients support for meals and medications, personal hygiene, environmental management, and daily activities (Lee, 2010). Therefore, they are prone to burnout, which is characterized by emotional labor, depersonalization, and reduced personal achievement, all of which are experienced by employees who are mainly involved in interpersonal relationships (Freudenberger, 1997; Maslach & Jackson, 1981). Care workers' burnout may create negative attitudes and feelings toward clients, which causes deterioration of service quality and effectiveness. Eventually, this deterioration may lead to the interruption of service provision due to frequent absences and turnover (Lee, 2010). LTC institutions must reinvest the cost of hiring and training new employees, which leads to a waste of time, money, and manpower, and may hinder development of institutions and threaten patient safety (Lee, 2010).
Emotional labor, the process by which workers regulate and manage their feelings and expressions to fulfill the requirements of job performance and adaptation (Morris & Feldman, 1996), may have a significant relationship with burnout in care workers (Kim, Park, & Moon, 2012). Care workers are required to maintain a positive attitude toward patients and to meet their service needs. Therefore, care workers have a more lasting relationship, emotional ties, and close interactions with clients compared to individuals in other service occupations. This relationship causes care workers to experience emotional labor, wherein they are expected to suppress their personal negative emotions; act according to the demands of supervisors, clients, and their families; and maintain positive emotions (Choi, 2011). In addition, due to intensifying competition among other LTC hospitals, hospital organizations are forcing care workers to provide better health care and hospitality services, thereby increasing their emotional labor (Ko, 2014). Consequently, care workers experience burnout and feel limited in coping with stress, resulting in frequent turnover (Brotheridge & Grandey, 2002; Grandey, 2000; Hochschild, 1983).
Meanwhile—as there is a growing interest in the negative consequences caused by emotional labor—resilience, an individual's ability to overcome adversity and successfully adapt to life tasks in the face of stressful situations or difficulties (Connor, 2006; Garmezy, 1993; Kobasa, 1979), has been found to be a mitigating factor (Park & Lee, 2016). Resilience affects an individual's ability to overcome daily stress and maintain health, and ultimately enhances quality of life (Choi & Seok, 2013; Gillespie, Chaboyer, Wallis, & Grimbeek, 2007). In previous studies of other occupations, resilience was reported to be a controlling factor that directly reduced burnout and mitigated the consequences of psychological burnout, such as loss of achievement due to occupational stress (Jackson, Firtko, & Edenborough, 2007; Lim & Kwon, 2015).
As the number of older adults with chronic diseases receiving care and treatment in LTC hospitals rapidly increases, care workers' roles become prominent. Studies are needed to investigate the moderating effects of resilience on burnout caused by emotional labor. Previous studies in care workers have reported only on resilience, occupational stress, and organizational commitment (Hwang, 2015); studies on the moderating effects of resilience on burnout caused by emotional labor are rare. Therefore, the current study aimed to investigate the levels and correlations of burnout, emotional labor, and resilience among care workers in LTC hospitals, and the moderating effects of resilience on the relationship between emotional labor and burnout to provide scientific data for prevention and management of burnout.
Sample and Setting
Participants were care workers with >3 months of experience working in five LTC hospitals located in Busan, South Korea, who agreed to participate in the study. A total of 126 participants with completed data were included in the final analysis. The post-hoc power analysis was performed using G*power 184.108.40.206. A power of 0.8 was calculated for hierarchical multiple regression analysis with eight independent variables with a significance level (alpha) of 0.05 and an effect size of 0.15 (Kim, Jo, & Kim, 2013; Yoo, 2017). Therefore, it was feasible to interpret the results of this study.
Burnout. Burnout was assessed using the Maslach Burnout Inventory (MBI) scale developed by Maslach and Jackson (1981), which was translated into Korean by Choi and Chung (2003) and modified by Lee (2016). The MBI scale comprises three subscales with a total of 22 items, including nine items on emotional exhaustion, five on depersonalization, and eight on personal accomplishment. Each item is rated on a 5-point Likert scale. The total score is calculated by summing raw scores, with higher scores indicating greater burnout. Item scores are calculated by dividing total scores by the number of items. In the current study, the tool was found to have a Cronbach's alpha of 0.80.
Emotional Labor. Emotional labor was assessed using the Emotional Labor Scale, which was originally developed by Morris and Feldman (1996), translated into Korean by Kim (1998), and modified by Kim, Park, and Moon (2014). The tool comprises three subdomains with a total of nine items, including three on frequency of emotional display, three on attentiveness to required display rules, and three on emotional dissonance. Each item is rated on a 5-point Likert scale. The total score is calculated by summing raw scores, with higher scores indicating greater emotional labor. Item scores are calculated by dividing total scores by the number of items. In the current study, the tool was found to have a Cronbach's alpha of 0.73.
Resilience. Resilience was assessed using the Korean version of the Connor–Davidson Resilience Scale (K-CD-RISC), which was developed by Connor and Davidson (2003) and modified by the researchers (Y.M., S.Y.S.). The scale comprises five subdomains with a total of 25 items, including nine items on hardiness, eight on tolerance of negative affect, four on optimism, two on social support, and two on spirituality. Each item is rated on a 5-point Likert scale. The total score is calculated by summing raw scores, with higher scores indicating greater resilience. Item scores are calculated by dividing total scores by the number of items. In the current study, the tool was found to have a Cronbach's alpha of 0.90.
The current study was approved by the Inje University Institutional Review Board. The data collection period was May 1 to July 1, 2017. After explaining the purpose, contents, and ethical considerations of the study to department managers, chief nurses, or head nurses in five LTC hospitals located in Busan, approval for data collection was obtained. The researcher (Y.M.) visited units to explain the purpose, contents, and ethical considerations of the study to care workers. Care workers who agreed to participate in the study were asked to complete a set of self-reported questionnaires, which took approximately 15 to 20 minutes to complete. Each completed set of questionnaires was sealed in an individual envelope and collected by the researcher.
Collected data were analyzed using SPSS version 23.0. General characteristics of participants were analyzed using descriptive statistics. Levels of burnout, emotional labor, and resilience were analyzed using descriptive statistics. Differences in burnout, emotional labor, and resilience according to general characteristics of participants were analyzed using t tests and one-way analysis of variance (ANOVA). A post-hoc test was performed using Scheffe's test. Correlations between burnout, emotional labor, and resilience were analyzed using Pearson's correlation coefficient. Effects of emotional labor on burnout were analyzed using hierarchical multiple regression analysis, and moderating effects of resilience were analyzed according to Baron and Kenny (1986).
General Characteristics of Participants
Mean age of the 126 female care workers who participated in the current study was 59.23 (SD = 5.46) years. Of participants, 84% were married, 65% identified as Buddhist, and 60% were high school graduates. The mean number of children of each individual was 2.09 (SD = 0.69 children). Participants' mean total experience as care workers was 4.25 (SD = 2.93) years and mean work experience in the current hospital was 2.2 (SD = 2.1) years. Most (82%) participants were dispatched workers employed by sub-contractors (i.e., outsourcing partners, centers). Mean working hours per day was 11.84 (SD = 0.86) hours. Mean monthly income in 10,000 Korean Won was 150.14 (SD = 15.41 10,000 Korean Won). In terms of diagnoses of patients, which was a multiple response item, the proportion of patients with dementia was highest (15%), followed by those with stroke (15%), Parkinson's disease (14%), and diabetes (13%). The mean number of patients per care worker was 12.58 (SD = 5.31 patients), and most care workers (52%) had 10 to 19 patients. Most participants (96%) had a care worker's certificate. Mean score for health status, as rated by participants, was 6.62 (SD = 1.85) on a scale of 0 to 10, with higher scores indicating better health status. Preparing for the future (i.e., preparing funds for children's education, purchasing a house, and retirement) was the most common working motivation (40%), followed by family livelihood (21%), psychological reward (21%), and ability to participate in leisure and social activities (18%) (Table 1).
General Characteristics of Participants (N = 126)
Levels of Burnout, Emotional Labor, and Resilience
As measured using the MBI, mean burnout score of participants was 2.45 (SD = 0.41) of 5, with higher scores indicating higher levels of burnout. In regards to the MBI subscales, all of which were rated on 5-point Likert scales with higher scores indicating higher levels of the item, mean score for personal accomplishment was highest (2.57 [SD = 0.59]), followed by emotional exhaustion (2.50 [SD = 0.57]), and depersonalization (2.16 [SD = 0.61]).
Mean emotional labor score was 2.67 (SD = 0.52) of 5, with higher scores indicating greater levels of emotional labor. By subscale, all of which were rated on 5-point Likert scales with higher scores indicating higher levels of the item, mean score for attentiveness to required display rules was highest (2.84 [SD = 0.6]), followed by frequency of emotional display (2.82 [SD = 0.73]), and emotional dissonance (2.35 [SD = 0.69]).
Mean resilience score was 3.61 (SD = 0.5) of 5, with higher scores indicating greater resilience. By subscale, all of which were rated on 5-point Likert scales with higher scores indicating higher levels of the item, mean score for tolerance of negative affect was highest (3.79 [SD = 0.62]), followed by social support (3.74 [SD = 0.78]), optimism (3.61 [SD = 0.65]), hardiness (3.54 [SD = 0.62]), and spirituality (3.04 [SD = 0.79]) (Table 2).
Degree of Burnout, Emotional Labor, and Resilience (N= 126)
Difference in Burnout by General Characteristics
The level of burnout according to the general characteristics of participants was significantly different based on items, including number of patients (F = 4.76, p = 0.01), health status (t = 3.17, p = 0.002), and working motivation (F = 4.59, p = 0.004). Burnout was higher in participants with >20 patients compared to participants with 10 to 19 patients. Burnout was higher in individuals with a health status score <6 compared to those with a score of >6. In addition, burnout was higher in participants whose working motivation was family livelihood compared to those whose working motivation was to prepare for the future or for psychological reward. No other general characteristics had a statistically significant relationship with burnout.
Correlation Between Burnout, Emotional Labor, and Resilience
Burnout had a significant positive correlation with emotional labor (r = 0.30, p = 0.001), and a significant negative correlation with resilience (r = −0.33, p < 0.001).
Effects of Emotional Labor on Burnout and Moderating Effects of Resilience
When the three variables of participant characteristics that had a significant bivariate relationship with burnout (number of assigned patients, health status, and working motivation) were input to the first step of a hierarchical regression model predicting burnout (Model 1), the model explained 21% of the variance in burnout (F = 7.78, p < 0.001). In Model 1, health status (β = −0.38, p < 0.001) and the working motivation of family livelihood (β = 0.32, p = 0.003) were found to have significant effects on burnout. When the emotional labor variable was added into Model 2 to investigate the effect of emotional labor on burnout, the variable added 8% to the explained variance, for a total of 29% (F = 13.91, p < 0.001). In Model 2, emotional labor (β = 0.28, p < 0.001) was found to have a significant effect on burnout. When the resilience variable was added into Model 3 to investigate the effect of emotional labor and resilience on burnout, this variable added 5% to the explained variance, for a total of 34% (F = 10.74, p = 0.001). In Model 3, emotional labor (β = 0.24, p = 0.001) and resilience (β = −0.24, p = 0.001) were found to have significant effects on burnout. When the interaction term between emotional labor and resilience was added to Model 4 to investigate the moderating effect of resilience in the relationship between emotional labor and burnout, this variable added 2% to the explained variance, for a total of 36% (F = 4.68, p = 0.033). In Model 4, high emotional labor (β = 0.25, p = 0.001) and low resilience (β = −0.22, p = 0.004) were found to have significant effects on burnout. In addition, resilience showed a moderating effect in the relationship between emotional labor and burnout (Table 3).
Moderating Effects of Resilience on the Relationship between Burnout and Emotional Labor (N= 126)
The current study investigated the levels and correlations of burnout, emotional labor, and resilience, and the moderating effects of resilience in the relationship between emotional labor and burnout among care workers working in LTC hospitals. The results showed that emotional labor had a significant effect on burn-out, and resilience had a moderating effect in the relationship between emotional labor and burnout.
The mean burnout score of participants was 2.45 (SD = 0.41) of 5. Previous studies found the burn-out score of care workers working in LTC facilities to be 2.27 (SD = 0.43) (Moon, 2010), and those in home care services to be 2.24 (SD = 0.49) (Kim et al., 2014). In other words, burnout was higher in care workers working in LTC hospitals compared to those in LTC facilities and home care service. This pattern may be because more patients with severe diseases are in LTC hospitals; thus, care workers in LTC hospitals more often experience the deaths of their patients. Therefore, to reduce burnout among care workers in LTC hospitals, it is necessary to assign additional manpower for patients with severe diseases to reduce the number of assigned patients. It is also necessary to develop and apply strategies that will enable care workers to accept patients' deaths and cope with the resulting negative psychological problems.
The level of burnout according to participants' general characteristics was different based on the number of assigned patients. Specifically, burnout was higher in participants with >20 patients compared to those with 10 to 19 patients. This finding supports results of the study by Yoo (2017), and one can infer that higher burnout is a result of caring for more patients at the same time. Lower health status scores were associated with higher burnout in the current study, which is consistent with results of the study by Kim et al. (2013). Care workers may neglect their physical and mental health due to various demands, including others' basic desires in daily life. Care workers' interest in their own health is hampered by the nature of their work, which requires constant observation and care of patients' health statuses. As all participants of the current study were women, and there was a high proportion of married participants ≥60 years old, continued attention to the health status of care workers is needed. In addition, burnout was higher in participants whose working motivation was family livelihood compared to those whose working motivation was to prepare for the future or psychological reward, which is consistent with results of the study by Kim et al. (2013). This result may be because when care work is regarded as a means of maintaining a basic life, responsibility and pride as a care worker are lowered and the work intensity and stress are highly felt.
The mean emotional labor score of participants was 2.67 (SD = 0.52) of 5, with higher scores indicating higher levels of emotional labor. Previous studies found the emotional labor score among care workers in LTC facilities to be 2.76 (SD = 0.71) (Lee, 2017), and among care workers in home care services to be 2.74 (SD = 0.66) (Kim et al., 2014). In other words, the score for emotional labor among care workers in LTC hospitals was lower compared to that of care workers in LTC facilities and home care services. Care workers who work in LTC facilities (Lee, 2017) and home care services (Kim et al., 2014) are mostly in their 40s and 50s, with a common total work experience of <3 years, whereas participants of the current study were ≥60 years old and had a total work experience of >5 years. Participants in the current study, who were older and had more career experience than those in other studies, may have become more familiar with emotional labor through various workplaces and life experiences, or may have had increased stress thresholds to tolerate emotional labor situations, resulting in lower levels of burnout. However, repetitive studies of care workers with similar sociodemographic characteristics are needed for an accurate understanding of emotional labor among care workers in the future.
The mean resilience score of current participants was 3.61 (SD = 0.5) of 5, with higher scores indicating higher resilience. Because previous studies did not use the same tools as the current study, it was difficult to compare results of the current study to previous studies. The level of resilience of participants in the current study may be higher compared to nurses working in hospitals, as care workers with a relatively higher mean age may have relatively high abilities to strengthen self-control according to the needs of a situation, as they have accumulated knowledge from various life experiences.
Analyzing the relationship between burnout, emotional labor, and resilience showed that burnout had a significant positive correlation with emotional labor. This result is consistent with results of studies by Kim et al. (2014) and Youn, Kwon, and Kang (2016), which investigated the relationship between burnout and emotional labor in care workers in LTC hospitals and facilities and home care services. In addition, the current study found that burnout had a significant negative correlation with resilience, which is consistent with results of a study of nurses on the relationship between burnout and resilience (Kang & Lim, 2015).
In the hierarchical multiple regression analyses, the emotional labor variable was input to Model 1 to investigate effects of emotional labor on burnout (Model 2). Results showed that emotional labor had a significant effect on burnout. This result is consistent with results of a study by Kim et al. (2012), which reported that an increase in emotional labor was associated with an increase in burnout. This finding suggests that burnout in care workers can be reduced if appropriate interventions are provided to care workers by developing strategies to reduce emotional labor. If care workers can develop effective coping skills through education about how to control and manage their emotions in work environments where various interactions with patients occur, they may be able to reduce their burnout.
When the interaction term between emotional labor and resilience was input to Model 3 to investigate the moderating effect of resilience in the relationship between emotional labor and burnout (Model 4), the results showed that resilience had a significant moderating effect in the relationship between emotional labor and burnout. This finding indicates that resilience serves as a protective factor for burnout; thus, individuals with higher resilience are less likely to experience burnout even if the level of emotional labor is high. Because there are few related previous studies, it is difficult to directly compare the results of the current study with any previous study. However, results of a previous study of child care teachers regarding the relationship between emotional labor and burnout showed significant mediating effects of resilience, along with superficial acting, on burnout (Choi & Seok, 2013).
Individuals with high resilience cope successfully with stress or crisis situations (Dyer & McGuinness, 1996). Likewise, if care workers can use resilience to reduce stress or burnout from emotional labor, the quality of care service will increase. Therefore, it is necessary to develop and apply resilience enhancement programs so that care workers can develop and strengthen their resilience through learning and training to prevent and manage burnout. A study by Sood, Prasad, Schroeder, and Varkey (2011) reported that stress decreased and resilience was improved in physicians who used stress management and resilience improvement programs. Foureur, Besley, Burton, Yu, and Crisp (2013) reported that when a mindfulness-based stress reduction intervention was developed and implemented with nurses and midwives, participants' stress and anxiety were alleviated and individual and workplace resilience increased. These results indicate that resilience is an operable concept that can be enhanced through well-organized programs, and that resilience enhancement programs may be effective in improving care workers' resilience and alleviating burnout associated with work. Therefore, specific and systematic efforts to improve care workers' resilience should be continued.
The current study identified factors affecting burnout among care workers, and the results can be used as baseline data for developing effective strategies to prevent care worker turnover due to burnout. The current study is significant in that it identified the moderating effect of resilience in the relationship between emotional labor and burnout. This finding also provides scientific evidence for further studies regarding burnout reduction among care workers. Education programs that develop positive interpersonal relationships and effective communication can be provided to care workers to improve resilience and ultimately reduce burnout.
The current study investigated the levels of and relationship between burnout, emotional labor, and resilience, and analyzed the moderating effects of resilience in the relationship between emotional labor and burn-out in care workers. Results showed that emotional labor in care workers has a significant effect on burnout, and that resilience has a moderating effect on the relationship between emotional labor and burnout. To alleviate burnout in care workers, emotional labor should be recognized as a significant mental health problem, and comprehensive management interventions for care workers' health maintenance and promotion should be developed. Resilience can serve as a moderating effect in the relationship between emotional labor and burnout, and ultimately contribute to the prevention and intervention of burnout in care workers, thereby increasing their psychological well-being and quality of care service. Repetitive and extended studies are needed to identify variables affecting burnout in care workers and investigate the moderating effects of resilience. Studies are also needed to verify the effectiveness of management measures to cope with emotional labor.
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General Characteristics of Participants (N = 126)
|Age (years) (mean [SD])||59.23 (5.46)|
| <50||9 (7)|
| 50 to 54||15 (12)|
| 55 to 59||28 (22)|
| ≥60||74 (59)|
|Marital status (n, %)|
| Married||106 (84)|
| Widowed||14 (11)|
| Divorced||4 (3)|
| Separated||1 (1)|
| Never married||1 (1)|
|Number of children (mean [SD])||2.09 (0.69)|
| <3||98 (78)|
| ≥3||28 (22)|
|Religion (n, %)|
| Buddhist||82 (65)|
| Protestant||17 (14)|
| Catholic||3 (2)|
| None||24 (19)|
|Education level (n, %)|
| Completed elementary school||6 (5)|
| Completed middle school||38 (30)|
| Completed high school||75 (60)|
| Completed college||7 (6)|
|Total work experience (years) (mean [SD])||4.25 (2.93)|
| <1||15 (12)|
| 1 to <3||31 (25)|
| 3 to <5||30 (24)|
| ≥5||50 (40)|
|Work experience in current hospital (years) (mean [SD])||2.20 (2.10)|
| <1||40 (32)|
| 1 to <3||47 (37)|
| 3 to <5||26 (21)|
| ≥5||13 (10)|
|Employment status (n, %)|
| Full-time||23 (18)|
| Othera||103 (82)|
|Working hours per day (mean [SD])||11.84 (0.86)|
| <12||7 (6)|
| ≥12||119 (94)|
|Monthly income (10,000 Korean Won) (mean [SD])||150.14 (15.41)|
| <100||2 (2)|
| 100 to <150||29 (23)|
| ≥150||95 (75)|
|Diagnoses of older patientsb (n, %)|
| Dementia||115 (15)|
| Stroke||110 (15)|
| Parkinson's disease||103 (14)|
| Diabetes||98 (13)|
| Hypertension||87 (11)|
| Arthritis||86 (11)|
| Respiratory disease||84 (11)|
| Cancer||76 (10)|
| Other||2 (0)|
|Number of assigned older patients (mean [SD])||12.58 (5.31)|
| <10||41 (33)|
| 10 to 19||65 (52)|
| ≥20||20 (16)|
|Certificatec (n, %)|
| Care worker||126 (96)|
| Nurse aid||3 (2)|
| Other||2 (2)|
|Health statusd (mean [SD])||6.62 (1.85)|
|Working motivation (n, %)|
| Preparing for the futuree||50 (40)|
| Family livelihood||27 (21)|
| Psychological reward||27 (21)|
| Leisure and social activities||22 (18)|
Degree of Burnout, Emotional Labor, and Resilience (N= 126)
|Variable||Mean Score (SD)||Score Range||Item Mean Score (SD)||Item Score Range||Minimum Score||Maximum Score|
|Burnouta||54.0 (9.1)||1 to 110||2.5 (0.4)||1 to 5||1.4||3.3|
| Emotional exhaustion||22.5 (5.2)||1 to 45||2.5 (0.6)||1 to 5||1.2||3.7|
| Depersonalization||10.8 (3.1)||1 to 25||2.2 (0.6)||1 to 5||1.0||3.6|
| Personal accomplishment||20.6 (4.8)||1 to 40||2.6 (0.6)||1 to 5||1.3||5.0|
|Emotional laborb||24.1 (4.8)||1 to 45||2.7 (0.5)||1 to 5||1.1||4.0|
| Frequency of emotional display||8.5 (2.2)||1 to 15||2.8 (0.7)||1 to 5||1.0||5.0|
| Attentiveness to required display rules||8.5 (1.8)||1 to 15||2.8 (0.6)||1 to 5||1.0||4.3|
| Emotional dissonance||7.1 (2.1)||1 to 15||2.4 (0.7)||1 to 5||1.0||4.0|
|Resiliencec||90.3 (12.7)||1 to 125||3.6 (0.5)||1 to 5||2.6||4.9|
| Hardiness||31.9 (5.6)||1 to 45||3.5 (0.6)||1 to 5||2.4||5.0|
| Tolerance of negative affect||30.3 (5.0)||1 to 40||3.8 (0.6)||1 to 5||2.3||5.0|
| Optimism||14.5 (2.6)||1 to 20||3.6 (0.6)||1 to 5||2.3||5.0|
| Social support||7.5 (1.6)||1 to 10||3.7 (0.8)||1 to 5||2.0||5.0|
| Spirituality||6.1 (1.6)||1 to 10||3.0 (0.8)||1 to 5||1.0||5.0|
Moderating Effects of Resilience on the Relationship between Burnout and Emotional Labor (N= 126)
|Variable||Model 1||Model 2||Model 3||Model 4|
|β||tTest||p Value||β||t Test||p Value||β||t Test||p Value||β||t Test||p Value|
|Number of assigned older patients||−0.01||−0.12||0.902||−0.01||−0.18||0.854||0.01||0.23||0.814||0.01||0.24||0.808|
| Family livelihood||0.32||3.00||0.003||0.30||2.94||0.004||0.30||3.07||0.003||0.27||2.79||0.006|
| Preparing for the future||0.01||0.13||0.890||0.01||0.14||0.888||0.01||0.11||0.911||0.02||0.27||0.788|
| Psychological reward||−0.03||−0.36||0.713||−0.02||−0.19||0.843||−0.01||−0.16||0.873||−0.00||−0.03||0.972|
|Emotional labor x resilience||−0.16||−2.16||0.033|
|F (p value)||7.78 (<0 .001)||13.91 (<0.001)||10.74 (0.001)||4.68 (0.033)|