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Research Article
Open Access
Published: 21 December 2023
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International Journal of Coal Science & Technology Volume 10, article number 90, (2023)
1.
The First Affiliated Hospital of Anhui University of Science and Technology, Huainan, China
2.
Anhui University of Science and Technology, Huainan, China
3.
Shool of Mental Health, Bengbu Medical College, Bengbu, China
4.
Prevention and Treatment Hospital for Occupational Diseases, Huainan, China
In China, coal miners are the primary workforce in coal mining, and among all patients with occupational diseases, 90% suffer from pneumoconiosis. Therefore, the psychological problems resulting from the dual pressures of occupational stress and the high risk of occupational diseases among coal miners are significant factors that affect the development of physical and mental health and even production safety. The Crown–Crisp Experience Index (CCEI) is a multidimensional questionnaire that assesses the psychological state of patients. This study aims to test reliability and validity of Chinese version of the CCEI questionnaire using factor analysis, and apply it to coal miners. We recruited a total of 900 participants from different occupational stages in coal mining, including active miners, Coal Workers’ Pneumoconiosis (CWP) patients, and retired miners, to evaluate the reliability and validity of the Chinese version of the CCEI questionnaire. A questionnaire survey was conducted on three groups of 1000 individuals each, including active coal miners, retired coal miners, and pneumoconiosis patients, to determine the detection rate of psychological problems in each group. An analysis was performed for each group to explore the primary factors influencing anxiety. The exploratory factor analysis yielded six principal components that accounted for a total of 79.389% of variances. The confirmatory factor analysis showed that the Chi-square freedom ratio (χ2/df) was 1.843, the root mean square error approximation was less than 0.044, and the comparative fit index was 0.938 and Tucker–Lewis index (TLI) was 0.934. The Cronbach's alpha coefficient was 0.948, and the scale-level content validity index (S-CVI) was 0.88. Effective questionnaires were obtained from 98.5%, 96.9%, to 91.0% of pneumoconiosis patients, active miners, and retired miners, respectively, with the incidence rates of psychological problems being 21%, 35.8%, and 13.6%, respectively. Compared with retired miners, active miners showed higher levels of psychological problems in the dimensions of depressive symptoms, free-floating anxiety and somatic symptoms, whereas pneumoconiosis patients had higher levels of psychological problems in the dimensions of phobic anxiety and somatic symptoms. This study demonstrates that the Chinese version of the CCEI is highly reliable and valid and can be used as a screening tool to measure patients' anxiety and fear levels in coal minders. Miners face distinct psychological challenges at different stages and require targeted screening and interventions.
Coal Workers’ Pneumoconiosis (CWP) is a systemic disease characterized by the diffuse fibrosis of lung tissues, which is mainly caused by the long-term inhalation of mineral dust during occupational activities like coal mining (Qi et al. 2021). To reduce the occurrence of pneumoconiosis, strict exposure limits have been set, and personal protective equipment such as masks, goggles, and protective clothing have been implemented. Currently, the allowable exposure limit for respirable coal mine dust (RCMD) in China is 2.5 mg/m3, and with the upgrading of occupational protection measures, such as the use of masks, the incidence of pneumoconiosis in China has decreased in recent years (Decision of the ministry of emergency management on amending the coal mine safety regulations 2022). Despite a more than 50% reduction in the incidence rate of pneumoconiosis compared to 2012, there were still 11,809 new cases of occupational pneumoconiosis in China in 2021 (The National Health Commission released the 2021 2022). Pneumoconiosis is a chronic disease that can only be 100% cured through lung transplantation (Hall et al. 2019). Patients with pneumoconiosis may experience weakened lung function, decreased immunity, and are susceptible to respiratory infections (Bell and Mazurek 2020). Due to the prolonged and debilitating nature of the disease, patients are prone to negative emotions such as anxiety, fear, pessimism, and depression (Morrison et al. 2017). Miners are a high-risk group for pneumoconiosis, facing various work-related pressures and the risk of occupational disease. The resulting psychological problems not only affect the individual's quality of life but also pose a hidden danger to workplace safety. Therefore, timely identification of the psychological status of miners at different stages of their career and corresponding interventions can prevent adverse events, improve their quality of life, and enhance their well-being.
To assess the psychological state of patients, commonly used tools in China include the Self-rating Anxiety Scale (SAS) (Cheng et al. 2017), Self-rating Depression Scale (SDS) (Smith et al. 2018), and Depression Anxiety Stress Scale-21 (DASS-21) (Jiang et al. 2020), which are widely recognized internationally. However, these tools tend to focus on specific aspects of psychological problems. In contrast, the Somatic Symptom Scale SCL-90 provides a more comprehensive evaluation (Dang et al. 2021), but its extensive item list and lengthy survey process may lead to impatience among respondents, especially in China where outpatient services are heavily burdened due to limited medical resources (Li et al. 2020). Consequently, there is an urgent need to develop a measurement tool that can assess multiple aspects of psychology within a short timeframe, enabling medical professionals to quickly screen for issues in one or more domains.
The Crown–Crisp Experience Index (CCEI) is a quantitative assessment tool that measures patients' phobia levels using a questionnaire (Crown and Crisp 1966). This questionnaire has been widely employed in clinical studies on various conditions such as heart disease (Haines et al. 1987), tinnitus (Stephens and Hallam 1985), anorexia nervosa (Hsu and Crisp 1980), ovarian cancer (Poole et al. 2016), and even attention deficit hyperactivity disorder (ADHD) in children (Bolea-Alamañac et al. 2019). Therefore, in order to assess the psychological status of the miner population, the present study aims to localize and revise the CCEI questionnaire in Chinese and employ factor analysis to test its reliability and validity. The study further aims to investigate and compare anxiety and fear indices among active miners, CWP patients, and retired miners at different career stages, with the objective of laying a foundation for early identification of negative psychological states.
The Crown–Crisp Experience Index is a self-rating scale that was developed in 1966 by Crown and Crisp, psychiatry professors at Middlesex Hospital in London, UK (Crown and Crisp 1966). The questionnaire comprises six dimensions, each with eight items. The six dimensions assessed by the questionnaire are free-floating anxiety (FFA items 1, 7, 13, 19, 25, 31, 37, 43), phobic anxiety (PHO items 2, 8, 14, 20, 26, 32, 38, 44), obsessive–compulsive traits and symptoms (OBS items 3, 9, 15, 21, 27, 33, 39, 45), somatic symptoms (SOM items 4, 10, 16, 22, 28, 34, 40, 46), depressive symptoms (DEP items 5, 11, 17, 23, 29, 35, 41, 47), and hysterical traits and symptoms (HYS items 6, 12, 18, 24, 30, 36, 42, 48). The questionnaire is a concise tool for evaluating common phobias and anxiety disorders, such as claustrophobia, pathophobia, acrophobia, and demophobia levels. Each item has a score range of 0–2 points, and each dimension ranges from 0 to 16 points, with a total score of 0 to 96. The survey also includes "reversed items," where a higher score indicates a greater degree of anxiety and phobia.
In accordance with the principles of cross-cultural adaptation (Guillemin et al. 1993), the localization process of the Chinese version of CCEI is depicted in Fig. 1. A total of 15 experts, as shown in supplementary Table 1 in medical-related fields were invited to evaluate the expression and make it more idiomatic. The invitees completed relevant forms, and the first round of expert consultation was conducted. Controversial items underwent a second round of expert consultation. After two rounds, the expert judgment coefficient (Ca) was 0.93 and the familiarity degree coefficient (Cs) was 0.89, according to the formula authority coefficient (Cr) = (Ca + Cs)/2 (Li et al. 2021), resulting in an expert authority coefficient (Cr) of 0.91. This score is greater than 0.9 and indicates that the experts unanimously suggested deleting item 9, i.e. Do you think that “cleanliness is next to godliness?. Consequently, the questionnaire was reduced to 47 items across six dimensions. It is worth noting that cultural differences were taken into account throughout the localization process.
The localization process of the Chinese CCEI
In this study, we adopted convenience sampling to distribute a total of 30 questionnaires for pilot study, with 10 questionnaires each given to active miners, CWP patients, and retired miners, respectively. A 3-point scoring method was adopted; that is, answering “yes” tallies 2 points, “sometimes” 1 point, and “no” 0. For reverse items, the scoring is exactly the opposite. Given the low literacy levels and advanced age of the study subjects, the current investigation employed one-to-one surveys conducted by six trained research members, who carefully gathered and incorporated the subjects' opinions and suggestions regarding each questionnaire item. The questionnaire's format, content, item options, and completion time were reported to be reasonable. The questionnaire was found to take approximately 12–15 min to complete.
To ensure the reliability and validity of the questionnaire, the study followed the principle that the number of participants should be 5–10 times greater than the number of questionnaire items (Myers et al. 2011). We recruited a total of 900 coal mines from different occupational stages, including 300 active miners, 300 CWP patients, and 300 retired miners, to assess the reliability and validity of the Chinese version of the CCEI questionnaire. A questionnaire survey and subgroup analysis were conducted on three groups of 1000 individuals each, including active miners, CWP patients, and retired miners to explore the primary factors influencing anxiety.
A total of 900 questionnaires were distributed and collected from different occupational stages. Of these, 31 were incomplete and therefore excluded from analysis, leaving a total of 869 valid questionnaires. The survey's effective response rate was 96.6%, meeting the standard criteria for surveys. Additionally, 1000 individuals from each of the active miner, CWP patient, and retired miner groups were recruited, with valid responses obtained from 969, 985, to 910 individuals, respectively. The effective rates of the survey were 96.9%, 98.5%, and 91.0% for the coal miner, CWP patient, and retired miner groups, respectively.
The data input was performed by using Epidata 3.1 software, and subsequently, the data were randomly assigned into two groups. One group was used for exploratory factor analysis (EFA) through SPSS 22.0 (n = 435), while the other was used for confirmatory factor analysis (CFA) using AMOS 25.0 (n = 434). The reliability and validity of the study were evaluated using several statistical methods including Cronbach's alpha, composite reliability, and goodness of fit indices (McDonald and Ho 2002). In addition, the content validity index (CVI) and correlation coefficient were used to assess the reliability and validity of the Chinese version of the CCEI. The quantitative aspects of the study were described by the composition ratio, mean, standard deviation, and M (SD).
The 869 samples used to test the reliability and validity of the questionnaire were drawn from three groups: 292 active miners, 290 CWP patients, and 287 retired miners. The nature of the work under investigation is specific to certain settings, thus the survey participants were restricted to males aged 25–94, with a mean (SD) age of 55.35 (15.74) years. The majority of miners are exhibit low levels of education, as shown in supplementary Table 2).
The Kaiser–Meyer–Olkin (KMO) measure and Bartlett's test of sphericity for the Coal Workers' Pneumoconiosis Cognitive Emotion Inventory (CCEI) questionnaire yielded a value of 0.904, exceeding the threshold of 0.9, indicating suitability for factor analysis. Varimax with Kaiser normalization is then applied to extract 6 factors from 47 items (Fig. 2). The six factors are: DEP (items 5, 11, 17, 23, 29, 35, 41, 47), FFA (items 1, 7, 13, 20, 25, 31, 37, 43), PHO (items 2, 8, 14, 19, 26, 32, 38, 44), SOM (items 4, 10, 16, 22, 28, 34, 40, 46), HYS (items 6, 12, 18, 24, 30, 36, 42, 48), and OBS (items 3, 15, 21, 27, 33, 39, 45). According to the study, a total of 79.389% variance is explained. We have recoded the items in the questionnaire. The detailed information of six factors is shown in Table 1, including FFA (items from FFA1 to FFA8), PHO ((items from PHO1 to PHO8), OBS (items from OBS1 to OBS7), SOM (items from SOM1 to SOM8), DEP (items from DEP1 to DEP8), HYS (items from HYS1 to HYS8).
Scree plot of CCEI
Item | Component | ||||||
|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | ||
1 → FFA1 | Do you often feel upset for no obvious reason ? | 0.216 | 0.259 | 0.222 | 0.821 | 0.008 | 0.146 |
7 → FFA2 | Have you felt as though you might faint ? | 0.138 | 0.112 | 0.112 | 0.857 | − 0.034 | 0.074 |
13 → FFA3 | Do you feel uneasy and restless? | 0.012 | 0.044 | 0.127 | 0.831 | − 0.085 | 0.056 |
20 → FFA4 | Do you feel uneasy travelling on buses or the Underground even if they are not crowded? | 0.181 | 0.146 | 0.134 | 0.868 | − 0.028 | 0.111 |
25 → FFA5 | Would you say you were a worrying person? | 0.180 | 0.089 | 0.127 | 0.869 | − 0.056 | 0.128 |
31 → FFA6 | Do you often feel “strung − up” inside? | 0.260 | 0.127 | 0.104 | 0.775 | 0.000 | 0.148 |
37 → FFA7 | Have you ever had the feeling you are “going to pieces”? | 0.223 | 0.123 | 0.134 | 0.825 | 0.015 | 0.146 |
43 → FFA8 | Do you have bad dreams which upset you when you wake up? | 0.138 | 0.046 | 0.086 | 0.851 | − 0.038 | 0.106 |
2 → PHO1 | Do you have an unreasonable fear of being in enclosed spaces such as shops, lifts, etc0.? | − 0.170 | − 0.173 | 0.064 | − 0.114 | 0.795 | 0.024 |
8 → PHO2 | Do you find yourself worrying about getting some incurable illness? | − 0.004 | − 0.070 | 0.080 | − 0.062 | 0.852 | − 0.107 |
14 → PHO3 | Do you feel more relaxed indoors? | 0.036 | − 0.024 | 0.029 | − 0.055 | 0.875 | 0.050 |
19 → PHO4 | Do you sometimes feel really panicky? | 0.009 | − 0.035 | 0.100 | − 0.054 | 0.880 | 0.021 |
26 → PHO5 | Do you dislike going out alone? | 0.060 | − 0.001 | 0.150 | − 0.005 | 0.875 | 0.008 |
32 → PHO6 | Do you worry unduly when relatives are late coming home? | 0.033 | − 0.027 | 0.121 | − 0.008 | 0.883 | 0.006 |
38 → PHO7 | Are you scared of heights? | 0.074 | 0.012 | 0.136 | 0.052 | 0.851 | 0.051 |
44 → PHO8 | Do you feel panicky in crowds? | 0.036 | − 0.008 | 0.057 | 0.030 | 0.894 | 0.006 |
3 → OBS1 | Do people ever say you are too conscientious ? | 0.847 | 0.154 | 0.177 | 0.203 | 0.007 | 0.230 |
15 → OBS2 | Do you find that silly or unreasonable thoughts keep recurring in your mind? | 0.855 | 0.185 | 0.161 | 0.186 | 0.013 | 0.173 |
21 → OBS3 | Are you happiest when you are working? | 0.798 | 0.199 | 0.180 | 0.214 | 0.043 | 0.169 |
27 → OBS4 | Are you a perfectionist? | 0.822 | 0.189 | 0.214 | 0.215 | 0.022 | 0.215 |
33 → OBS5 | Do you have to check things you do to an unnecessary extent? | 0.821 | 0.157 | 0.168 | 0.152 | 0.018 | 0.210 |
39 → OBS6 | Does it irritate you if your normal routine is disturbed? | 0.833 | 0.166 | 0.123 | 0.168 | − 0.004 | 0.158 |
45 → OBS7 | Do you find yourself worrying unreasonably about things that do not really matter? | 0.859 | 0.198 | 0.199 | 0.174 | 0.031 | 0.168 |
4 → SOM1 | Are you troubled by dizziness or shortness of breath ? | 0.184 | 0.826 | 0.069 | 0.102 | − 0.085 | 0.183 |
10 → SOM2 | Do you often feel sick or have indigestion? | 0.192 | 0.815 | 0.084 | 0.138 | − 0.008 | 0.090 |
16 → SOM3 | Do you sometimes feel tingling or pricking sensations in your body, arms or legs? | 0.091 | 0.854 | 0.085 | 0.075 | − 0.057 | 0.127 |
22 → SOM4 | Has your appetite got less recently? | 0.142 | 0.889 | 0.133 | 0.124 | − 0.047 | 0.131 |
28 → SOM5 | Do you feel unduly tired and exhausted? | 0.103 | 0.813 | 0.161 | 0.083 | − 0.045 | 0.105 |
34 → SOM6 | Can you get off to sleep alright at the moment? | 0.175 | 0.882 | 0.131 | 0.104 | − 0.031 | 0.131 |
40 → SOM7 | Do you often suffer from excessive sweating or fluttering of the heart? | 0.148 | 0.872 | 0.116 | 0.114 | − 0.051 | 0.120 |
46 → SOM8 | Has your sexual interest altered? | 0.195 | 0.845 | 0.141 | 0.137 | − 0.026 | 0.141 |
5 → DEP1 | Can you think as quickly as you used to ? | 0.149 | 0.147 | 0.058 | 0.111 | − 0.010 | 0.862 |
11 → DEP2 | Do you feel that life is too much effort? | 0.216 | 0.189 | 0.196 | 0.137 | 0.049 | 0.820 |
17 → DEP3 | Do you regret much of your past behaviour? | 0.172 | 0.165 | 0.097 | 0.110 | − 0.002 | 0.849 |
23 → DEP4 | Do you wake unusually early in the morning? | 0.242 | 0.166 | 0.123 | 0.185 | 0.029 | 0.819 |
29 → DEP5 | Do you experience long periods of sadness? | 0.239 | 0.151 | 0.099 | 0.133 | 0.015 | 0.863 |
35 → DEP6 | Do you have to make a special effort to face up to a crisis or difficulty? | 0.233 | 0.234 | 0.219 | 0.159 | 0.056 | 0.849 |
41 → DEP7 | Do you find yourself needing to cry? | 0.257 | 0.241 | 0.188 | 0.173 | 0.031 | 0.798 |
47 → DEP8 | Have you lost your ability to feel sympathy for other people? | − 0.001 | − 0.066 | 0.065 | − 0.005 | − 0.050 | 0.694 |
6 → HYS1 | Are your opinions easily influenced ? | 0.194 | 0.147 | 0.820 | 0.168 | 0.102 | 0.127 |
12 → HYS2 | Have you, at any time in your life, enjoyed acting? | 0.168 | 0.143 | 0.853 | 0.111 | 0.150 | 0.164 |
18 → HYS3 | Are you normally an excessively emotional person? | 0.199 | 0.106 | 0.847 | 0.130 | 0.124 | 0.125 |
24 → HYS4 | Do you enjoy being the centre of attention? | 0.114 | 0.125 | 0.862 | 0.087 | 0.104 | 0.111 |
30 → HYS5 | Do you find that you take advantage of circumstances for your own ends? | 0.177 | 0.113 | 0.812 | 0.126 | 0.112 | 0.129 |
36 → HYS6 | Do you often spend a lot of money on clothes? | 0.170 | 0.159 | 0.859 | 0.130 | 0.106 | 0.161 |
42 → HYS7 | Do you enjoy dramatic situations? | 0.192 | 0.123 | 0.826 | 0.125 | 0.071 | 0.077 |
48 → HYS8 | Do you sometimes find yourself posing or pretending? | 0.072 | 0.043 | 0.856 | 0.158 | 0.086 | 0.077 |
Eigenvalue | 6.629 | 6.580 | 6.427 | 6.295 | 6.109 | 6.067 | |
Total variance explained (%) | 13.810 | 13.708 | 13.390 | 13.114 | 12.727 | 12.640 | |
Structural Equation Modeling (SEM) is a statistical modeling approach that involves the analysis of the relationships between latent variables and observed variables, which are measured by multiple indicators (Alavi et al. 2020). In this study, a total of 47 observed variables were used, with FFA, PHO, OBS, SOM, DEP, and HYS serving as latent variables. AMOS 25.0 was utilized to construct a path diagram to confirm the theoretical structure of exploratory factor analysis (Fig. 3). Confirmatory factor analysis fit indices presented in Table 2. The estimation results of the parameters indicate that the six dimensions of the CCEI scale exhibit CR value exceeding 0.6 and AVE value exceeding 0.5, and the correlation coefficients among the factors are lower than the AVE value, as shown in Table 3.
Path diagram of each dimension
Index | χ2 | df | P | χ2/df | CFI | TLI | RMSEA(90%CI) |
|---|---|---|---|---|---|---|---|
CFA | 1878.471 | 1019 | 0.00 | 1.843 | 0.938 | 0.934 | 0.038(0.041–0.047) |
Criterion | – | – | < 0.05 | < 3 | > 0.9 | > 0.9 | < 0.1– |
Path diagram | Unstd | S.E | t-value | STD | CR | AVE | ||
|---|---|---|---|---|---|---|---|---|
FFA1 | ⭠ | FFA | 1.000 | 0.813 | 0.928 | 0.617 | ||
FFA2 | ⭠ | FFA | 0.862 | 0.067 | 12.921 | 0.775 | ||
FFA3 | ⭠ | FFA | 0.947 | 0.070 | 13.581 | 0.764 | ||
FFA4 | ⭠ | FFA | 0.952 | 0.070 | 13.686 | 0.769 | ||
FFA5 | ⭠ | FFA | 1.007 | 0.071 | 14.235 | 0.786 | ||
FFA6 | ⭠ | FFA | 1.053 | 0.071 | 14.934 | 0.795 | ||
FFA7 | ⭠ | FFA | 1.012 | 0.068 | 14.915 | 0.807 | ||
FFA8 | ⭠ | FFA | 0.921 | 0.069 | 13.395 | 0.770 | ||
PHO1 | ⭠ | PHO | 1.000 | 0.790 | 0.922 | 0.596 | ||
PHO2 | ⭠ | PHO | 0.883 | 0.067 | 13.101 | 0.721 | ||
PHO3 | ⭠ | PHO | 0.880 | 0.067 | 13.084 | 0.736 | ||
PHO4 | ⭠ | PHO | 0.934 | 0.067 | 13.948 | 0.810 | ||
PHO5 | ⭠ | PHO | 0.763 | 0.066 | 11.622 | 0.731 | ||
PHO6 | ⭠ | PHO | 0.966 | 0.068 | 14.303 | 0.794 | ||
PHO7 | ⭠ | PHO | 0.958 | 0.067 | 14.367 | 0.806 | ||
PHO8 | ⭠ | PHO | 1.012 | 0.069 | 14.703 | 0.782 | ||
OBS1 | ⭠ | OBS | 1.000 | 0.831 | ||||
OBS2 | ⭠ | OBS | 0.849 | 0.062 | 13.798 | 0.764 | ||
OBS3 | ⭠ | OBS | 0.920 | 0.062 | 14.786 | 0.78 | ||
OBS4 | ⭠ | OBS | 0.967 | 0.060 | 16.030 | 0.793 | ||
OBS5 | ⭠ | OBS | 0.942 | 0.061 | 15.538 | 0.779 | ||
OBS6 | ⭠ | OBS | 1.017 | 0.061 | 16.735 | 0.889 | ||
OBS7 | ⭠ | OBS | 1.125 | 0.066 | 16.462 | 0.865 | 0.933 | 0.665 |
SOM1 | ⭠ | SOM | 1.000 | 0.708 | ||||
SOM2 | ⭠ | SOM | 0.985 | 0.070 | 13.992 | 0.813 | ||
SOM3 | ⭠ | SOM | 0.822 | 0.070 | 11.741 | 0.769 | ||
SOM4 | ⭠ | SOM | 0.989 | 0.070 | 14.088 | 0.767 | ||
SOM5 | ⭠ | SOM | 1.019 | 0.071 | 14.263 | 0.79 | ||
SOM6 | ⭠ | SOM | 1.050 | 0.072 | 14.568 | 0.792 | ||
SOM7 | ⭠ | SOM | 1.074 | 0.072 | 14.923 | 0.795 | ||
SOM8 | ⭠ | SOM | 0.554 | 0.069 | 8.003 | 0.639 | 0.916 | 0.579 |
DEP1 | ⭠ | DEP | 1.000 | 0.673 | ||||
DEP2 | ⭠ | DEP | 1.229 | 0.139 | 8.823 | 0.702 | ||
DEP3 | ⭠ | DEP | 0.898 | 0.121 | 7.432 | 0.660 | ||
DEP4 | ⭠ | DEP | 1.324 | 0.145 | 9.156 | 0.732 | ||
DEP5 | ⭠ | DEP | 1.289 | 0.142 | 9.071 | 0.716 | ||
DEP6 | ⭠ | DEP | 1.421 | 0.150 | 9.501 | 0.766 | ||
DEP7 | ⭠ | DEP | 1.184 | 0.137 | 8.672 | 0.694 | ||
DEP8 | ⭠ | DEP | 1.421 | 0.150 | 9.451 | 0.748 | 0.891 | 0.507 |
HYS1 | ⭠ | HYS | 1.000 | 0.720 | ||||
HYS2 | ⭠ | HYS | 0.999 | 0.079 | 12.585 | 0.776 | ||
HYS3 | ⭠ | HYS | 1.093 | 0.078 | 14.023 | 0.793 | ||
HYS4 | ⭠ | HYS | 1.014 | 0.078 | 13.069 | 0.760 | ||
HYS5 | ⭠ | HYS | 0.912 | 0.076 | 12.038 | 0.752 | ||
HYS6 | ⭠ | HYS | 1.038 | 0.077 | 13.549 | 0.783 | ||
HYS7 | ⭠ | HYS | 1.018 | 0.106 | 10.525 | 0.628 | ||
HYS8 | ⭠ | HYS | 0.840 | 0.074 | 11.325 | 0.762 | 0.910 | 0.560 |
The internal consistency of the questionnaire and each dimension was evaluated using Cronbach's α coefficient, as shown in Table 4, with values ranging from 0.899 to 0.936, exceeding the threshold of 0.90. Split-half reliability was also assessed and found to be greater than 0.8, indicating excellent internal consistency of the questionnaire (Terwee et al. 2007).
Item | Item number | Cronbach's Alpha | Split-half reliability |
|---|---|---|---|
Chinese CCEI | 47 | 0.948 | 0.952 |
FFA | 8 | 0.958 | 0.919 |
PHO | 8 | 0.954 | 0.899 |
OBS | 7 | 0.967 | 0.942 |
SOM | 8 | 0.962 | 0.917 |
DEP | 8 | 0.957 | 0.938 |
HYS | 8 | 0.962 | 0.929 |
Content validity index (CVI) is sub-divided into item-level CVI (I-CVI) and scale-level CVI (S-CVI). Typically, the validity is based on expert comment. I-CVI equals to the number of the experts scoring 4 or 5 for the importance of the research/total number of the experts. S-CVI equals to the number of items with a 4 or 5 scores/total number of items. In this research, the results show that I-CVI is 0.73–1.00, S-CVI is 0.88, all greater than 0.7, indicating good content validity (Zhong et al. 2020).
In order to further clarify the actual application of the scale, we compared the detection rates of psychological disorders among miners, pneumoconiosis patients, and retired miners (supplementary Table 3). The detection rates of psychological disorders in active miners, pneumoconiosis patients and retired miners were 35.8%, 21.0%, and 13.6%, respectively. In addition, in order to further understand the proportion of factors affecting psychological problems in different populations, we conducted a subgroup analysis for each group. Taking 20% as the cut-off value, it shows that the psychological barriers among miners mainly focus on DEP, FFA and SOM dimensions, and the positive rates are 35.1%, 36.4% and 33.2%, respectively. The pneumoconiosis population mainly focused on PHO and SOM, and the positive detection rates were 39.5% and 29.2%, respectively. The detection rate of retired miners is below 20% in all dimensions, as shown in Fig. 4.
The detection rate of mental disorders a The detection of the total score of the three groups of mental disorders; b The detection of psychological disorders in each dimension of the active miners; c The detection of psychological disorders in each dimension of CWP: d The detection of each dimension of retired miner detection of mental disorders
Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) are widely recognized as reliable methods for evaluating the stability and structural validity of questionnaires. EFA assesses the relationship between observed and latent variables through factor loading (DeVon et al. 2007), and the sampling adequacy is first determined using Kaiser–Meyer–Olkin before data analysis. A result greater than 0.90 indicates that the sample is suitable for factor analysis. In conducting EFA, the cumulative variance contribution rate of the common factors must exceed 60%, and the factor load of each item on its common factor must be greater than 0.4, indicating that each item reflects the information of a particular dimension. In this study, the factor load of each item and its dimensions exceeded 0.5, except for item 19, which was transferred from FFA to PHO, and item 20, which was transferred from PHO to FFA, based on content relevance. The communalities of each dimension and the CCEI were all greater than 0.5, indicating that the components were adequately explained.
Confirmatory Factor Analysis (CFA) is a reliable method for testing the structural assumptions of an established model by evaluating goodness of fit (Bagozzi et al. 1981). For ease of identification, the serial numbers of each item were recoded. The results of the CFA indicate that the fit indices in Table 2 are consistent with the reference values. In conjunction with the results in Table 3, each item has a loading above 0.6 under its respective factor, with CR values greater than 0.8 and AVE greater than 0.5. This indicates that the items in the CCEI scale have a certain degree of discrimination, and the model has an ideal structure capable of identifying the degree of response of different investigators.
Table 4 shows that the reliability indicators of the Chinese version of the CCEI are higher compared to the original study conducted by Crown and Crisp in 1966, which may be attributed to the significant increase in sample size in this study. The Cronbach's α coefficients of the total questionnaire and each dimension were all greater than 0.9, and the split-half reliability coefficients obtained by grouping odd and even numbered items were all greater than 0.8, indicating good internal consistency of the questionnaire (Boparai et al. 2018).
Content validity is typically assessed through expert reviews, which serve as an indication of the accuracy of the measured content or topic (Hayes and Preacher 2010). In general, content validity is established based on experts' comments, with I-CVI representing the number of experts who score 4 or 5 for the importance of the research divided by the total number of experts, and S-CVI representing the number of items with a score of 4 or 5 divided by the total number of items (Egger-Rainer 2018). In this study, both I-CVI and S-CVI exceeded 0.7, indicating that the Chinese CCEI has strong content validity.
Miners working underground are all male. The results of the comparison among active miners, CWP patients, and retired miners show that the highest detection rate of psychological problems in active miners is 35.8%, mainly focusing on the dimensions of DEP, FFA, and SOM. The main reasons for the high prevalence of psychological issues in active miners are likely due to the harsh operating environment underground and the pressure from work management. These findings are consistent with the research reported by Ailing Fu et al. (2022). The second is the detection rate of psychological disorders in CWP patients, which is 21%, mainly focusing on the dimensions of PHO and SOM. According to the national policy (Shi et al. 2020), once pneumoconiosis is diagnosed, patients can enjoy free medical treatment, which largely eliminates patients’ concerns. But pneumoconiosis will have the symptoms of respiratory disorder and hypoxia. For those suffering from pneumoconiosis, they are worried that they will not get timely help, especially when they live alone, which will cause fear to patients. It is worth noting that the detection rate of psychological problems in retired miners without pneumoconiosis is only 13.6%, which is lower than the incidence of psychological problems in the general elderly. It shows that the quality of life of retired miners is quite satisfactory after retiring from their posts. On the one hand, they are out of the high-risk occupational environment, and can freely spend their time while receiving monthly pensions. Compared with the stress during work, it is a state from bitter to sweet. This study suggests that miners have different psychological problems at different career stages. Coal operators should pay attention to the psychological problems of miners and formulate targeted psychological intervention measures to improve the mental health and quality of life of miners.
The dimensions as well as the questionnaire in this study enjoy sound internal consistency and good structural validity and reliability. It thus can be used as one of the measurement tools to assess the phobia indexes of coal miners at different periods of their working and retirement life. Though this study is based on coal miners, it is expected the Chinese CCEI can be applied to other types of patients in the future, for whom it is critical to assess psychological problems in a short period of time.
It should be noted that this study has some limitations. The limitations may include: (1) Although the sample size is relatively considerable, the study focuses on the population of only one city, which may have potential environmental impacts. (2) The questionnaires involved in this study are all men, and whether it can be applied to the female population still needs to be further explored.
| [1] | Alavi M, Visentin DC, Thapa DK, Hunt GE, Watson R, Cleary M (2020) Chi-square for model fit in confirmatory factor analysis. J Adv Nurs 76(9):2209–2211. https://doi.org/10.1111/jan.14399 |
| [2] | Bagozzi RP, Fornell C, Larcker DF (1981) Canonical correlation analysis as a special case of a structural relations model. Multivar Behav Res 16(4):437–454. https://doi.org/10.1207/s15327906mbr1604_2 |
| [3] | Bell JL, Mazurek JM (2020) Trends in Pneumoconiosis deaths—United States, 1999–2018. MMWR. Morbidity and mortality weekly report, 69(23), 693–698. https://doi.org/10.15585/mmwr.mm6923a1 |
| [4] | Bolea-Alamañac B, Davies S, Evans J, Joinson C, Pearson R, Skapinakis P, Emond A (2019) Does maternal somatic anxiety in pregnancy predispose children to hyperactivity? Eur Child Adolesc PsyChiatry 28(11):1475–1486. https://doi.org/10.1007/s00787-019-01289-6 |
| [5] | Boparai JK, Singh S, Kathuria P (2018) How to design and validate a questionnaire: a guide. Curr Clin Pharmacol 13(4):210–215. https://doi.org/10.2174/1574884713666180807151328 |
| [6] | Cheng SH, Sun ZJ, Lee IH, Lee CT, Chen KC, Tsai CH, Yang YK, Yang YC (2017) Factors related to self-reported social anxiety symptoms among incoming university students. Early Interv Psychiatry 11(4):314–321. https://doi.org/10.1111/eip.12247 |
| [7] | Crown S, Crisp AH (1966) A short clinical diagnostic self-rating scale for psychoneurotic patients. The Middlesex Hospital Questionnaire (M.H.Q). Br J Psychiatry J Mental Sci 112(490):917–923. https://doi.org/10.1192/bjp.112.490.917 |
| [8] | Dang W, Xu Y, Ji J, Wang K, Zhao S, Yu B, Liu J, Feng C, Yu H, Wang W, Yu X, Dong W, Ma Y (2021) Study of the SCL-90 Scale and changes in the Chinese Norms. Front Psychiatry 11:524395. https://doi.org/10.3389/fpsyt.2020.524395 |
| [9] | Decision of the ministry of emergency management on amending the coal mine safety regulations (2022). Bulletin of the State Council of the People's Republic of China 1765(10):52–57. https://doi.org/10.3969/j.issn.1000-4335.2022.02.038 |
| [10] | DeVon HA, Block ME, Moyle-Wright P, Ernst DM, Hayden SJ, Lazzara DJ, Savoy SM, Kostas-Polston E (2007) A psychometric toolbox for testing validity and reliability. J Nurs Scholarsh off Publ Sigma Theta Tau Int Honor Soc Nurs 39(2):155–164. https://doi.org/10.1111/j.1547-5069.2007.00161.x |
| [11] | Egger-Rainer A (2018) Determination of content validity of the epilepsy monitoring unit comfort questionnaire using the content validity index. J Nurs Meas 26(2):398–410. https://doi.org/10.1891/1061-3749.26.2.398 |
| [12] | Fu A, Zhao T, Gao X, Li X, Liu X, Liu J (2022) Association of psychological symptoms with job burnout and occupational stress among coal miners in Xinjiang, China: A cross-sectional study. Front Public Health 10:1049822. https://doi.org/10.3389/fpubh.2022.1049822 |
| [13] | Guillemin F, Bombardier C, Beaton D (1993) Cross-cultural adaptation of health-related quality of life measures: literature review and proposed guidelines. J Clin Epidemiol 46(12):1417–1432. https://doi.org/10.1016/0895-4356(93)90142-n |
| [14] | Haines AP, Imeson JD, Meade TW (1987) Phobic anxiety and ischaemic heart disease. Br Med J (clin Res Ed) 295(6593):297–299. https://doi.org/10.1136/bmj.295.6593.297 |
| [15] | Hall NB, Blackley DJ, Halldin CN, Laney AS (2019) Current review of pneumoconiosis among US coal miners. Curr Environ Health Rep 6(3):137–147. https://doi.org/10.1007/s40572-019-00237-5 |
| [16] | Hayes AF, Preacher KJ (2010) Quantifying and testing indirect effects in simple mediation models when the constituent paths are nonlinear. Multivar Behav Res 45(4):627–660. https://doi.org/10.1080/00273171.2010.498290 |
| [17] | Hsu LK, Crisp AH (1980) The Crown–Crisp experiential index (CCEI) profile in anorexia nervosa. Br J Psychiatry J Mental Sci 136:567–573. https://doi.org/10.1192/bjp.136.6.567 |
| [18] | Jiang LC, Yan YJ, Jin ZS, Hu ML, Wang L, Song Y, Li NN, Su J, Wu DX, Xiao T (2020) The depression anxiety stress Scale-21 in Chinese hospital workers: reliability, latent structure, and measurement invariance across genders. Front Psychol 11:247. https://doi.org/10.3389/fpsyg.2020.00247 |
| [19] | Li Y, Gong W, Kong X, Mueller O, Lu G (2020) Factors associated with outpatient satisfaction in tertiary hospitals in China: a systematic review. Int J Environ Res Public Health 17(19):7070. https://doi.org/10.3390/ijerph17197070 |
| [20] | Li FX, Hou YL, Zhou LS, Dong Y, Zhao JW, Li ZX (2021) The status and model of children primary nephrotic syndrome in continuing nursing. Ann Palliat Med 10(3):2398–2407. https://doi.org/10.21037/apm-19-480 |
| [21] | McDonald RP, Ho MH (2002) Principles and practice in reporting structural equation analyses. Psychol Methods 7(1):64–82. https://doi.org/10.1037/1082-989x.7.1.64 |
| [22] | Morrison EJ, Novotny PJ, Sloan JA, Yang P, Patten CA, Ruddy KJ, Clark MM (2017) Emotional problems, quality of life, and symptom burden in patients with lung cancer. Clin Lung Cancer 18(5):497–503. https://doi.org/10.1016/j.cllc.2017.02.008 |
| [23] | Myers ND, Ahn S, Jin Y (2011) Sample size and power estimates for a confirmatory factor analytic model in exercise and sport: a Monte Carlo approach. Res Q Exerc Sport 82(3):412–423. https://doi.org/10.1080/02701367.2011.10599773 |
| [24] | Poole EM, Kubzansky LD, Sood AK, Okereke OI, Tworoger SS (2016) A prospective study of phobic anxiety, risk of ovarian cancer, and survival among patients. Cancer Causes Control CCC 27(5):661–668. https://doi.org/10.1007/s10552-016-0739-0 |
| [25] | Qi XM, Luo Y, Song MY, Liu Y, Shu T, Liu Y, Pang JL, Wang J, Wang C (2021) Pneumoconiosis: current status and future prospects. Chin Med J 134(8):898–907. https://doi.org/10.1097/CM9.0000000000001461 |
| [26] | Shi P, Xing X, Xi S, Jing H, Yuan J, Fu Z, Zhao H (2020) Trends in global, regional and national incidence of pneumoconiosis caused by different aetiologies: an analysis from the Global Burden of Disease Study 2017. Occup Environ Med 77(6):407–414. https://doi.org/10.1136/oemed-2019-106321 |
| [27] | Smith CA, Armour M, Lee MS, Wang LQ, Hay PJ (2018) Acupuncture for depression. Cochrane Database Syst Rev 3(3):CD004046. https://doi.org/10.1002/14651858.CD004046.pub4 |
| [28] | Stephens SD, Hallam RS (1985) The Crown–Crisp experiential index in patients complaining of tinnitus. Br J Audiol 19(2):151–158. https://doi.org/10.3109/03005368509078968 |
| [29] | Terwee CB, Bot SD, de Boer MR, van der Windt DA, Knol DL, Dekker J, Bouter LM, de Vet HC (2007) Quality criteria were proposed for measurement properties of health status questionnaires. J Clin Epidemiol 60(1):34–42. https://doi.org/10.1016/j.jclinepi.2006.03.012 |
| [30] | The National Health Commission released the 2021 (2022) National Occupational Disease Report. Occupational health and emergency rescue 40(04):416. http://www.nhc.gov.cn/guihuaxxs/s3586s/202207/51b55216c2154332a660157abf28b09d.shtml |
| [31] | Zhong Z, Shi S, Duan Y, Shen Z, Zheng F, Ding S, Luo A (2020) The development and psychometric assessment of chinese medication literacy scale for hypertensive patients (C-MLSHP). Front Pharmacol 11:490. https://doi.org/10.3389/fphar.2020.00490 |
17 January 2023
16 April 2023
10 August 2023
https://doi.org/10.1007/s40789-023-00641-1
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