Abstract
Background:
The mental health status of community workers shows the characteristics of low job satisfaction, low self-efficacy and psychological resilience, and a high sense of burnout. This research aims to explore the relationship between noise sensitivity, burnout, and psychological resilience in community workers.
Methods and Material:
Convenience sampling was adopted to select 169 community workers from five communities as research objects for an anonymous questionnaire survey. A general questionnaire was used to collect the general information of the respondents. Noise sensitivity, burnout and psychological resilience scales were adopted to analyse the correlation amongst noise sensitivity, burnout and psychological resilience in community workers. Univariate and multivariate logistics regression analyses were used to analyse the influencing factors of job burnout and psychological resilience in community workers.
Results:
A total of 169 questionnaires were distributed, and after excluding 6 unqualified questionnaires, 163 valid questionnaires (96.45%) were collected. The scores on the noise sensitivity, burnout and psychological resilience scales were 63.80 ± 9.69, 78.57 ± 10.12 and 54.18 ± 8.77 points, respectively. The results of the correlation analysis showed that in community workers, the noise sensitivity score was negatively correlated with the psychological resilience score (P < 0.001) and positively correlated with the burnout score (P < 0.001). The burnout and psychological resilience scores of community workers showed statistical differences with different ages, working years and disposable monthly family income (P < 0.001). Multiple linear regression results revealed that noise sensitivity, age, working years and disposable monthly family income had an effect on burnout and psychological resilience scores (P < 0.001).
Conclusion:
In community workers, noise sensitivity is positively correlated with burnout and negatively correlated with psychological resilience. This study provides a certain research basis for conducting relevant psychological research and interventions.
Keywords: Burnout, community workers, multiple linear regression analysis, noise sensitivity, psychological research
INTRODUCTION
Although the team of community workers has grown in recent years with the continuous development of China’s economy, related research with large samples on the mental health of community workers remains in the initial stage.[1,2] The mental health status and professional level of community workers not only represent the administrative management level of grassroots organisations, they are also related to the vital interests of community residents. Burnout is a syndrome described as a state of exhaustion that can occur in a wide range of occupational settings, and the question as to whether reduced professional achievement is intrinsic to burnout, a consequence of cognitive dysfunction, or a consequence of burnout is unresolved.[3] Burnout is a work-related, stress-induced and psychological syndrome.[4] However, empirical research on the causes of these psychological traits is insufficient.
Any physiological or psychological stimulus that disrupts homeostasis can cause a stress response; these stimuli are called stressors.[5] Noise, which is defined as unwanted sound, is a main environmental stressor. As a chronic stressor, environmental noise causes interference, distraction and annoyance.[6] Perceived noise at work is closely associated with anxiety and depression.[7] Noise sensitivity, a measure for the individual perception of a given level and quality of noise, is seen as an aspect of personality.[8] A broad consensus exists that noise-sensitive individuals manifest greater physiological responses to workplace noise, especially if it interferes with cognitively demanding work, than less noise-sensitive people.[9] Subjective sensitivity to noise is highly correlated with the harmful effects of noise: sleep disorders, behavioural changes, cardiovascular diseases and psychological symptoms.[10] Given the nature of their work, community workers often face a variety of noises in the workplace. However, the distribution characteristics of noise sensitivity in this group have not been studied. Meanwhile, the correlation between noise sensitivity, burnout and psychological resilience among community workers remains unclear. In 2015, domestic scholars sinicised the noise sensitivity scale and tested its reliability and validity.[11] Using this tool, this study investigated the characteristic distribution of noise sensitivity in some community workers and analysed its relationship with burnout and psychological resilience. It aims to provide a valuable reference for promoting and improving community workers’ physical and mental health and their work quality. The results of this work are reported below.
MATERIAL AND METHODS
Research object
This study is a multicentre cross-sectional survey. By the convenience sampling was used as the sampling method. In accordance with the convenience of the researcher, potential respondents were selected randomly at the entrances of community offices or in various offices. If they met the inclusion criteria, they were selected as the samples for this study. The sample size of the cross-sectional study was calculated as n = 4s2/d2, where d was the allowable error and s was the estimate of the population standard deviation. The overall standard deviation estimate is s = 13, the allowable error is d = 2 and the sample size provided by the substitution formula is 169 copies. Convenience sampling was adopted to select 169 community workers from five communities with similar distances and noise levels as research objects for an anonymous questionnaire survey. The community was selected as the measurement site. The office area of community workers was used as the monitoring point, and the monitoring height was 1.2–1.5 m from the ground. Measurements were made when the windows in the direction affected by outdoor noise were closed to provide an objective basis for ensuring that the distance and noise level of each community were similar. A general questionnaire was used to collect the general information of the respondents. The revised job burnout scale and psychological resilience scale have good reliability and validity in China and can be used by community workers.[12,13] A total of 169 questionnaires were distributed. After six unqualified questionnaires were excluded, 163 valid questionnaires (96.45%) were collected. The sample included 79 males and 84 females, amongst whom 61, 67 and 35 employees have worked for 0–3, 4–8 and 8 years, respectively. This study did not require ethical approval and was exempted by the ethics committee of Jiangnan University.
Research tool
Noise sensitivity scale
The original noise-sensitivity scale was developed by Weinstein et al.[14] It includes 21 questions and has an internal consistency reliability of 0.85 and retest reliability of 0.75. After sinicisation by domestic scholars, the noise sensitivity scale consisted of 21 questions.[11] This scale adopts a 6-point Likert scale, wherein 1–6 points respectively indicate completely agree, mostly agree, basically agree, basically disagree, mostly disagree and completely disagree. There are 14 questions in total that are reverse scored. A high score is indicative of the high noise sensitivity of the subject. The scale has an internal consistency coefficient of 0.866, split half reliability of 0.871 and retest coefficient of 0.743.
Job burnout scale
The Chinese version of job burnout scale revised by Li et al.[12] was adopted for investigation. The scale included three dimensions of emotional exhaustion (five items), cynicism (four items) and low sense of achievement (six items), with a total of 15 items. The 7-point Likert scoring method of 0–6 points was adopted, and positive scoring was used for the first two dimensions, with 0 point for ‘never’, 1 point for ‘rarely’, 2 points for ‘occasionally’, 3 points for ‘often’, 4 points for ‘frequently’, 5 points for ‘very frequently’ and 6 points for ‘daily’. The third dimension is scored in a negative direction. A higher score indicates more severe job burnout. According to the total score obtained by the scale, the degree of job burnout can be divided into three grades, namely, the degree of job burnout is not obvious (0–30), the degree of job burnout is obvious (31–45) and the degree of job burnout is serious (46–90). The higher the score, the more serious is the job burnout. Cronbach’s α coefficients of the three dimensions of the scale were 0.88, 0.83 and 0.82, respectively.
Psychological resilience scale
The psychological resilience scale was compiled by Connor et al[15] and sinicised by Yu et al.[13] It was tested on students, medical staff and postoperative patients. This scale includes 25 items in three dimensions, including fortitude (13 items), optimism (8 items) and strength (4 items). It adopts a 5-point Likert scale, wherein 1–5 points indicate ’never’ to ’always’. The total score ranges from 25 points to 125 points. A high score is indicative of the good psychological resilience of the subjects. This scale has a Cronbach’s α coefficient of 0.890.
Investigation method
Trained and assessed testers introduced the purpose and importance of the survey to the community workers in the laboratory; distributed questionnaires, which were filled in anonymously and recovered on the spot; and instructed respondents who provided incomplete contents to fill the questionnaire in again. A total of 169 questionnaires were distributed, and 163 valid questionnaires (96.45%) were recovered. The survey results and data were input into statistical software for analysis.
Statistical analysis
Data were inputted by two people into Excel 2010 software (Microsoft, Redmond, WA, USA) to ensure the accuracy of data entry. All statistical data were analysed by using SPSS 27.0 software (IBM, Amenk, NY, USA). Classification data were described by frequency. Count data were described by numerical numbers. Measurement data conforming to the normal distribution were expressed as mean plus or minus standard deviation (‘x ± s). Independent sample t-tests were performed, and correlations were determined through Pearson analysis. Multiple linear stepwise regression was used for multifactor regression. Statistical data were presented as cases or rates, and all statistical tests were performed as two-sided tests. P < 0.05 was deemed as a statistically significant difference.
RESULTS
Analysis of the noise sensitivity, burnout and psychology resilience scores of community workers
The scores on the noise sensitivity, burnout and psychological resilience scales were 63.80 ± 9.69, 78.57 ± 10.12 and 54.18 ± 8.77 points, respectively.
Correlation analysis of noise sensitivity, burnout and psychological resilience in community workers
In community workers, noise sensitivity is positively correlated with burnout and negatively correlated with psychological resilience (r = 0.655, r = −0.571, Pall < 0.001) [Figure 1].
Figure 1.
Correlation analysis of noise sensitivity, burnout and psychological resilience. (A) Correlation analysis of noise sensitivity and job burnout. (B) Correlation analysis of noise sensitivity and psychological resilience.
Comparison of the burnout scores of community workers with different characteristics
Statistically significant differences are found in the burnout scores of community workers with different ages, working years and disposable monthly family income (P < 0.001) but not in those of community workers with different genders, educational levels and marital status (P > 0.05) [Table 1].
Table 1.
Comparison of the burnout scores of community workers with different characteristics
| Characteristics | Number | Burnout score | t/F | P |
|---|---|---|---|---|
| Gender | ||||
| Male | 79 | 79.16 ± 9.57 | 0.724 | 0.471 |
| Female | 84 | 78.01 ± 10.65 | ||
| Age | ||||
| 20–30 | 73 | 73.24 ± 9.70 | 29.348 | <0.001 |
| 31–40 | 65 | 81.65 ± 7.46 | ||
| >40 | 25 | 86.36 ± 6.87 | ||
| Educational level | ||||
| Primary school and below | 14 | 78.57 ± 9.81 | 0.196 | 0.820 |
| Junior/senior high school | 58 | 77.76 ± 10.34 | ||
| College or above | 91 | 79.09 ± 10.11 | ||
| Marital status | ||||
| Married | 132 | 78.95 ± 9.90 | 0.980 | 0.328 |
| Unmarried | 31 | 76.97 ± 11.06 | ||
| Working years | ||||
| 0–3 | 61 | 71.58 ± 9.82 | 39.341 | <0.001 |
| 4–8 | 67 | 80.88 ± 7.73 | ||
| >8 | 35 | 86.37 ± 6.39 | ||
| Disposable monthly family income | ||||
| <5000 | 29 | 63.83 ± 3.38 | 85.769 | <0.001 |
| 5001–10,000 | 101 | 80.26 ± 7.94 | ||
| >10001 | 33 | 86.36 ± 6.59 |
Multiple linear regression analysis of the influencing factors of burnout
Burnout score was taken as the dependent variable, and the significant variables of univariate and Pearson analyses were selected as independent variables. The results of multiple linear regression show that noise sensitivity, age, working years and disposable monthly family income enter the model (P < 0.001) [Table 2].
Table 2.
Influencing factors of burnout
| Partial regression coefficient | Standard error | Standard regression coefficient | t | P | |
|---|---|---|---|---|---|
| Constant quantity | 5.344 | 3.152 | - | 6.583 | <0.001 |
| Noise sensitivity | 0.153 | 0.039 | 0.158 | 3.455 | <0.001 |
| Age | 0.352 | 0.153 | 0.156 | 2.574 | <0.001 |
| Working years | 0.103 | 0.035 | 0.093 | 3.031 | <0.001 |
| Disposable monthly family income | 0.315 | 0.253 | 0.531 | 0.413 | <0.001 |
Comparison of the psychological resilience scores of community workers with different characteristics
Statistical differences are found in the psychological resilience scores of community workers with different ages, working years and disposable monthly family income (P < 0.001) but not in those of community workers with different genders, educational levels and marital status (P > 0.05) [Table 3].
Table 3.
Comparison of the psychological resilience scores of community workers with different characteristics
| Number | Psychological resilience | t/F | P | |
|---|---|---|---|---|
| Gender | ||||
| Male | 79 | 53.75 ± 7.97 | 0.617 | 0.538 |
| Female | 84 | 54.60 ± 9.49 | ||
| Age | ||||
| 20–30 | 73 | 58.96 ± 8.41 | 33.705 | <0.001 |
| 31–40 | 65 | 51.69 ± 6.71 | ||
| >40 | 25 | 47.08 ± 5.54 | ||
| Educational level | ||||
| Primary school and below | 14 | 54.07 ± 8.96 | 0.545 | 0.581 |
| Junior/senior high school | 58 | 55.14 ± 9.24 | ||
| College or above | 91 | 53.60 ± 8.47 | ||
| Marital status | ||||
| Married | 132 | 53.93 ± 8.68 | 0.759 | 0.449 |
| Unmarried | 31 | 55.26 ± 9.18 | ||
| Working years | ||||
| 0–3 | 61 | 60.11 ± 8.54 | 33.246 | <0.001 |
| 4–8 | 67 | 52.49 ± 6.72 | ||
| >8 | 35 | 47.09 ± 5.41 | ||
| Disposable monthly family income | ||||
| <5000 | 29 | 66.28 ± 5.08 | 75.347 | <0.001 |
| 5001–10,000 | 101 | 53.03 ± 6.85 | ||
| >10,001 | 33 | 47.09 ± 5.58 |
Multiple linear regression of the influencing factors of psychological resilience
Psychological resilience scores were taken as the dependent variable, and the significant variables of univariate and Pearson analyses were taken as independent variables. The results of multiple linear regression show that noise sensitivity, age, working years and disposable monthly family income enter the model (P < 0.001) [Table 4].
Table 4.
Influencing factors in psychological resilience analysis
| Partial regression coefficient | Standard error | Standard regression coefficient | t | P | |
|---|---|---|---|---|---|
| Constant quantity | 5.758 | 3.176 | - | 5.867 | <0.001 |
| Noise sensitivity | 0.127 | 0.040 | 0.110 | 3.427 | <0.001 |
| Age | 0.255 | 0.153 | 0.153 | 3.846 | <0.001 |
| Working years | 0.365 | 0.199 | 0.155 | 4.308 | <0.001 |
| Disposable monthly family income | 0.103 | 0.035 | 0.093 | 3.031 | <0.001 |
DISCUSSION
In this study, the scores on the noise sensitivity, burnout and psychological resilience scales were 63.80 ± 9.69, 78.57 ± 10.12 and 54.18 ± 8.77 points, respectively, amongst which those on noise sensitivity were higher than those on other scale. For community workers, noise sources mainly originate from traffic, community residents and campus construction. Environmental noise exposure is thought to affect the brain and cognition.[16] When the body is exposed to a high-intensity noise environment for a long time, the auditory system is damaged first and the nervous, cardiovascular and digestive systems are affected to varying degrees. Traffic noise exposure is a clearly underestimated environmental risk factor and contributes substantially to the development of cardiometabolic complications, such as ischaemic heart disease, hypertension and heart failure.[17,18] Therefore, the diversity of community noise and adverse effects of noise may be the reason for the generally high noise sensitivity scores of the community workers included in this survey.
Burnout is a form of occupational stress that manifests over time.[19] It is a psychological syndrome of exhaustion, cynicism and inefficacy in the workplace.[20] Community workers with high levels of noise sensitivity face great pressure from noise during their work. Such pressure promotes their negative emotions and further increases their job burnout levels. The results of this study show that noise sensitivity, age, working years and disposable monthly family income are the factors affecting job burnout in community workers. Young community workers are in the growth stage of their career and face multiple pressures (career, economy and family) that lead to the high probability of burnout.
As burnout in young and middle-aged cadres increases, their subjective well-being deteriorates and their burnout further aggravates. Thus, burnout is often caused by numerous factors. Additionally, this study finds that household disposable monthly income has a great effect on burnout likely because community workers with tight family finances who are worried about losing their jobs are in an anxious state. Anxiety sensitivity can cause the persistence and reinforcement of existing anxiety symptoms.[21] Therefore, their noise sensitivity is high, resulting in tiredness at work and being affected by burnout. The psychological counselling of community workers with burnout should be emphasised and the external environment of their practice should be optimised by, for example, reducing noise in the working environment, increasing environmental control measures and providing human protection and health monitoring.
Many studies have indicated that psychological resilience is the capacity of an individual to overcome and bounce back from adversity and expresses the ability to react positively despite difficulties, turning them into opportunities for growth.[22,23] The results of this study imply that noise sensitivity, age, working years and family disposable income have direct effects on the psychological resilience of community workers. Exposure to adverse circumstances—such as poverty or life events like job loss, serious injury or bereavement—is a robust predictor of disruptions in psychological functioning.[24] When an individual faces adversity, their brain and body work cooperatively to adapt to this condition.[25] Some people who are highly sensitive to noise and who have been exposed to noise for a long time have poor physiological and psychological conditions, which reduce their ability to respond to positive things and lead to their low level of psychological resilience. Guaranteeing the working environment of community workers, strengthening the management of office environment noise and improving policies and regulations can help community workers adapt to stressful situations actively and enhance their psychological resilience.
This study has some limitations, such as bias due to the subjectivity of questionnaire filling, inadequate consideration of family income and living habits and inability to verify causal relationships in cross-sectional studies. Considering differences in corporate culture and management, job resources and demands and individual coping styles, the findings of this study need to be extrapolated carefully to petrochemical operators and other industry personnel.
CONCLUSION
The results show that in community workers, noise sensitivity is positively correlated with burnout and negatively correlated with psychological resilience. This study provides a certain research basis for conducting relevant psychological studies and interventions.
Availability of Data and Materials
The data used to support the findings of this study are available from the corresponding author upon request.
Author Contributions
F.C. and J.L.: Designed the research, analyzed the data, and wrote the manuscript. F.C. and W.X.: Organized the experiments, collected samples and carried out the experiment. W.X. and Z.B.Y.: Helped with data collation and analysis. J.L. and Z.B.Y.: Provided overall supervision of the project and quality control, reviewed and revised the manuscript. All authors contributed to editorial changes in the manuscript. All authors read and approved the final manuscript. All authors have participated sufficiently in the work and agreed to be accountable for all aspects of the work.
Ethics Approval and Consent to Participate
This study did not require ethical approval and was exempted by the ethics committee of Jiangnan University. This article collects questionnaires anonymously, so there is no need for the respondents to sign an informed consent form.
Funding
This study was supported by the General Project of Philosophy and Social Science Research of Colleges and Universities in Jiangsu Province (2021SJA0851).
Financial support and sponsorship
Nil.
Conflict of Interest
There are no conflicts of interest.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data used to support the findings of this study are available from the corresponding author upon request.