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Article

Psychometric Properties of the Chinese Version of the Core Symptom Index: A Study among Chinese Parents of Children with Autistic Spectrum Disorders

by
Yu Chang
1,
Bi**g He
1,
Justin DeMaranville
1,
Nahathai Wongpakaran
1,2,
Danny Wedding
1,3,4 and
Tinakon Wongpakaran
1,2,*
1
Multidisciplinary and Interdisciplinary School (MIdS), Chiang Mai University, Chiang Mai 50200, Thailand
2
Department of Psychiatry, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand
3
Department of Clinical and Humanistic Psychology, Saybrook University, Pasadena, CA 91103, USA
4
Department of Psychology, University of Missouri-Saint Louis, St. Louis, MO 63121, USA
*
Author to whom correspondence should be addressed.
Eur. J. Investig. Health Psychol. Educ. 2024, 14(7), 1902-1912; https://doi.org/10.3390/ejihpe14070126
Submission received: 26 May 2024 / Revised: 18 June 2024 / Accepted: 23 June 2024 / Published: 26 June 2024

Abstract

:
(1) Background: Parents of children with autism spectrum disorders often experience psychological distress, which can affect the quality of childcare they provide. It is crucial to screen for psychiatric symptoms among these parents. The core symptom index (CSI) is a widely recognized tool used to assess general symptoms, including depression, anxiety, and somatic issues. It has proven validity and reliability across diverse Thai populations. Given the cultural similarities between Thai and Chinese populations, the CSI has been successfully implemented within the Chinese population. Nevertheless, it is crucial to research its validity and reliability in the general Chinese population. This study aimed to investigate the psychometric properties of the Chinese version of the CSI among parents of children with autism spectrum disorders using confirmatory factor analysis (CFA). (2) Methods: A total of 794 Chinese parents raising children with autism participated in this study. All completed the CSI, along with the social inhibition subscale of the Interpersonal Problems Inventory and the Couple Satisfaction Index. Factorial validity was assessed using CFA to determine how well the bifactor three-factor model fits the data. Various structural models were compared using model fit indices. Convergent and discriminant validity were examined by exploring correlations with the social inhibition subscale and the Couple Satisfaction Index. Invariance testing of the CSI was conducted across multiple groups based on gender, age, and education using CFA. The reliability of the CSI was evaluated using McDonald’s omega coefficients. (3) Results: The bifactor model emerged as the best-fitting model for the data, suggesting that the total score of the CSI adequately represents overall psychiatric symptoms. The CSI exhibited significant correlations with the social inhibition subscale (r = 0.41, p < 0.01) and smaller correlation coefficients with the Couple Satisfaction Index (r = −0.16, p < 0.05), indicating both convergent and discriminant validity. The invariant test results support scalar invariance levels based on gender and age but only partial invariance for education. The Chinese version of the CSI demonstrated high consistency, with McDonald’s omega coefficients ranging between 0.86 and 0.95. (4) Conclusions: The bifactor model of the Chinese version of the CSI is validated, making it a suitable tool for measuring depression, anxiety, and somatization symptoms among parent(s) of children with autism spectrum disorders. Further research on other Chinese populations is encouraged.

1. Introduction

Autism spectrum disorder (ASD) is a significant global public health concern, imposing a substantial burden on affected families and society due to associated health challenges, especially during the COVID-19 pandemic [1,2]. Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by social communication difficulties and repetitive, restricted behaviors and interests. As its symptoms usually appear in early childhood, raising a child with ASD not only causes distress, anxiety, and depression for caregivers but also affects family cohesion and parental relationships. Studies have shown that compared to parent(s) of children with other intellectual disabilities, parent(s) of children with autism is/are more likely to experience high levels of stress, fatigue, depression, and anxiety [3]. Additionally, since children with autism often exhibit emotional and behavioral problems, these parents face enormous caregiving burdens and pressures [4,5,6,7,8,9]. These challenges can lead to a higher likelihood of psychopathological symptoms in this/these parent(s), decreased family cohesion and parental well-being, and increased negative parenting behaviors and can hinder the effectiveness of early intervention programs [10,11]. Early detection, accurate diagnosis, and effective treatment can help alleviate their distress and improve their quality of life. Therefore, it is crucial to screen parent(s) raising children with autism for psychiatric conditions.
To identify parent(s) who are at risk of develo** mental health issues, one practical approach is to utilize self-report questionnaires. The common psychiatric symptoms that can be captured by many screening scales include anxiety, depression, and somatization. One commonly used scale includes the Symptom Checklist-90 (SCL-90), which is a widely used self-report questionnaire designed to assess psychological symptoms and distress [12]. It consists of 90 items that measure 9 primary symptom dimensions: Somatization, Obsessive–Compulsive, Interpersonal Sensitivity, Depression, Anxiety, Hostility, Phobic Anxiety, Paranoid Ideation, and Psychoticism. However, due to its length and some symptoms, it has been shown to have poor discriminatory ability.
One of the brief version scales based on SCL-90 is the 18-item brief symptom index (BSI) [13,14,15]. The Chinese version of the 18-item BSI has been proven to be valid and reliable [16,17]. A study found that the three-factor and bi-factor models best fit the studied data. [16]. Another brief psychiatric symptom scale used in the Chinese population is the core symptom index (CSI), consisting of 15 measures of depression, anxiety, and somatization symptoms in epidemiologic studies. The CSI was developed initially among a Thai sample. Recent research has indicated that the CSI is psychometrically adequate. However, the first-order three-factor solution of the CSI appeared to fit the Thai sample adequately, and the bifactor model (Figure 1) was shown to fit the older Thai sample the best, allowing the CSI to be used as a single construct of psychiatric symptoms.
The CSI has been used in various populations and settings, including the general population, older residents in long-term care facilities, clinical outpatients, late adolescents, and adults [18,19,20,21,22]. The CSI has shown that the bifactor model fits best with older Thai adults. The use of the CSI among the Chinese population of parent(s) of children with ASD has some merit. First, both the CSI and BSI address similar symptoms, including anxiety, depression, and somatization, but their brevity enhances compliance. The advantage of the CSI over the BSI is that it originates from a sample with a similar Asian culture (Chinese and Thai), reducing cultural biases, particularly in somatization [23,24,25].
A study of the CSI among 803 older participants revealed that the three-factor model exhibited a fair level of fit, with CFI and TLI values higher than 0.9, and an RMSEA value less than 0.08. Additionally, the SRMR was less than 0.06, and the ratio of χ2 to df was greater than 3. The bifactor model of the CSI demonstrated the best-fit statistics across all models, producing a lower BIC value, indicating its statistical superiority. The common variance index showed that 61% was explained by the general factors in the bifactor model (>0.50), whereas the specific factors accounted for only 11.5% to 16.5% of the common variance. The results indicated that most items were stronger measures of general factors than specific factors.
In addition to the factor structure, the concept of measurement invariance is crucial in evaluating the quality of a measurement. In the original Thai version, measurement invariance was found to be problematic across sexes and education levels, which may be due to the older sample and the insufficient sample size. The CSI has been translated into Chinese and used with Chinese businessmen. However, the Chinese version of the CSI has yet to be evaluated in terms of its psychometric properties.
It is important for clinicians and researchers to use the Chinese version of the CSI only if its psychometric properties have been established. These properties include factorial validity, good reliability, and established measurement invariance. Until now, there has been no study on its validity and reliability across different Chinese populations, especially among parents of children with autism. The authors hypothesize that both the three-factor and bifactor models would fit the data of parents of children with autism spectrum disorder (ASD) well. It is vital for the CSI to exhibit good reliability to ensure reproducibility and established measurement invariance to confirm that it can be equally applied to different groups, such as different genders, without biases. The authors outlined the study to test our hypotheses by exploring the factor structure of the CSI, its internal consistency, convergent and discriminant validity, and measurement invariance.

2. Materials and Methods

This study utilized a validation survey design involving parent(s) of children with ASD. The study involved 1030 participants. Any incomplete data, such as the absence of a medical certificate confirming ASD diagnosis in children and incomplete questionnaires, were carefully excluded. The final sample size was 794 participants aged between 23 and 45. Ethical approval for this research was obtained from the Research Ethics Committee, the Faculty of Medicine, Chiang Mai University (approval number: PSY-2566-0523).

2.1. Participants

The participants comprised general Chinese parent(s) with children diagnosed with ASD. An online survey was employed as the chosen means to generate the invitations and gather data. The inclusion criteria included (1) residing in mainland China, (2) having one or more children with a diagnosis of ASD, and (3) being able to read and write Chinese proficiently and independently complete the research questionnaire. The exclusion criteria included individuals being unable to participate online. Upon completion of the socio-demographic information, the participants proceeded with the subsequent measurements described below. The total number of participants was 794, with an equal distribution of men and women. The participants’ ages ranged from 23 to 45 years, with a mean age of 35.83 (SD: 3.26). Most participants were employed (94.1%), lived in urban areas (68.4%), had at least a high school level of education (86.9%), and had a monthly family income between RMB 3001 and 10,000 (83.7%).

2.2. Procedure

Parents of children with ASD were invited to participate in the study. The ASD diagnoses for the children were made by doctors in hospitals and were confirmed by medical records issued by the respective hospitals. The researchers advertised the study on major Chinese social media platforms, including WeChat, Sina, QQ, ** comprehensive mental health screening programs specifically for parents of children with autism. This tool facilitates healthcare professionals in swiftly obtaining effective results, aiding in the early detection of psychological distress in participants. Tailored support plans can then be devised, promoting timely intervention. This will enhance the well-being of caregivers, strengthen family cohesion, and contribute to more effective parenting and caregiving strategies.

4.2. Limitations

Be aware of the following limitations that must be addressed. Firstly, the study sample was restricted to individuals aged 23 to 45 years old and parent(s) of children with ASD. As a result, the findings may not be generalizable to other age groups or populations. Secondly, the data were collected during the COVID-19 pandemic, and the policy of home isolation in China may have influenced individuals’ responses to the items. Thirdly, modern measurement theory scholars have criticized classical test theory for the “inherent defects” of the mathematical models it is based on. Therefore, it is necessary to test the CSI according to modern measurement theory. In the future, further verification of the difficulty and discrimination of the Chinese version of the CSI in item response theory may be necessary. Lastly, the data collection did not cover the primary healthcare field, so its applicability may be limited to certain specific populations or disease conditions.

5. Conclusions

This study indicates that the CSI serves as a reliable and valid instrument for measuring general psychological distress among Chinese parents of autistic children, making it an effective screening tool for psychological symptoms. The bi-factor model accurately captures the underlying structure of the CSI. Moreover, the CSI demonstrates measurement invariance across diverse backgrounds, indicating that CSI scores can accurately reflect variations in psychological symptoms among Chinese parents of autistic children. Additionally, this study underscores the significance of evaluating the general factor and adopting a holistic approach to understanding parental distress rather than solely focusing on individual dimensions. Based on our findings, we recommend using the CSI in mental health screening programs for parents of children with autism. This tool helps healthcare professionals quickly detect psychological distress, allowing for timely intervention and tailored support plans that enhance parental well-being, strengthen family cohesion, and improve parenting and caregiving strategies. Further research on psychometric property should be confirmed by modern theory, such as item response theory or Rasch measurement theory.

Author Contributions

Conceptualization and methodology, Y.C., T.W., N.W., B.H., J.D. and D.W.; software, Y.C., T.W. and N.W.; validation, Y.C., T.W. and N.W.; formal analysis, Y.C., T.W. and N.W.; investigation, Y.C., J.D., T.W. and N.W.; resources, Y.C., T.W., N.W. and B.H.; data curation, Y.C., T.W. and N.W.; writing—original draft preparation, Y.C., T.W., N.W., B.H., J.D. and D.W.; writing—review and editing, Y.C., T.W., N.W., B.H., J.D. and D.W.; visualization, Y.C. and T.W.; supervision, T.W.; project administration, T.W.; funding acquisition, Y.C., T.W. and N.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

This study was conducted following the Declaration of Helsinki and approved by the Institutional Review Board (or Ethics Committee) of the Faculty of Medicine, Chiang Mai University (EC: PSY-2566–0523, approval date: 30 October 2023).

Informed Consent Statement

Informed consent was obtained from all the subjects involved in the study.

Data Availability Statement

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Mutluer, T.; Doenyas, C.; Aslan Genc, H. Behavioral implications of the COVID-19 process for autism spectrum disorder, and individuals’ comprehension of and reactions to the pandemic conditions. Front. Psychiatry 2020, 11, 561882. [Google Scholar] [CrossRef]
  2. Patrick, S.W.; Henkhaus, L.E.; Zickafoose, J.S.; Lovell, K.; Halvorson, A.; Loch, S.; Letterie, M.; Davis, M.M. Well-being of parents and children during the COVID-19 pandemic: A national survey. Pediatrics 2020, 146, e2020016824. [Google Scholar] [CrossRef]
  3. Giallo, R.; Wood, C.E.; Jellett, R.; Porter, R. Fatigue, wellbeing and parental self-efficacy in mothers of children with an autism spectrum disorder. Autism 2013, 17, 465–480. [Google Scholar] [CrossRef] [PubMed]
  4. Hodge, D.; Hoffman, C.D.; Sweeney, D.P. Increased Psychopathology in Parents of Children with Autism: Genetic Liability or Burden of Caregiving? J. Dev. Phys. Disabil. 2011, 23, 227–239. [Google Scholar] [CrossRef]
  5. Lee, G.K.; Lopata, C.; Volker, M.A.; Thomeer, M.L.; Nida, R.E.; Toomey, J.A.; Chow, S.Y.; Smerbeck, A.M. Health-related quality of life of parents of children with high-functioning autism spectrum disorders. Focus Autism Other Dev. Disabil. 2009, 24, 227–239. [Google Scholar] [CrossRef]
  6. Mugno, D.; Ruta, L.; D’Arrigo, V.G.; Mazzone, L. Impairment of quality of life in parents of children and adolescents with pervasive developmental disorder. Health Qual. Life Outcomes 2007, 5, 22. [Google Scholar] [CrossRef] [PubMed]
  7. Schnabel, A.; Youssef, G.J.; Hallford, D.J.; Hartley, E.J.; McGillivray, J.A.; Stewart, M.; Forbes, D.; Austin, D.W. Psychopathology in parents of children with autism spectrum disorder: A systematic review and meta-analysis of prevalence. Autism 2020, 24, 26–40. [Google Scholar] [CrossRef]
  8. Yirmiya, N.; Shaked, M. Psychiatric disorders in parents of children with autism: A meta-analysis. J. Child Psychol. Psychiatry 2005, 46, 69–83. [Google Scholar] [CrossRef]
  9. Tsai, C.-H.; Chen, K.-L.; Li, H.-J.; Chen, K.-H.; Hsu, C.-W.; Lu, C.-H.; Hsieh, K.-Y.; Huang, C.-Y. The symptoms of autism including social communication deficits and repetitive and restricted behaviors are associated with different emotional and behavioral problems. Sci. Rep. 2020, 10, 20509. [Google Scholar] [CrossRef] [PubMed]
  10. Crowell, J.A.; Keluskar, J.; Gorecki, A. Parenting behavior and the development of children with autism spectrum disorder. Compr. Psychiatry 2019, 90, 21–29. [Google Scholar] [CrossRef]
  11. Celik, H.; Acikel, S.B.; Ozdemir, M.A.F.; Aksoy, E.; Oztoprak, U.; Ceylan, N.; Yuksel, D. Evaluation of the clinical characteristics of children with autism spectrum disorder and epilepsy and the perception of their parents on quality of life. Epilepsy Res. 2021, 172, 106599. [Google Scholar] [CrossRef] [PubMed]
  12. Derogatis, L.R.; Lipman, R.S.; Covi, L. SCL-90: An outpatient psychiatric rating scale–preliminary report. Psychopharmacol. Bull. 1973, 9, 13–28. [Google Scholar] [PubMed]
  13. Derogatis, L.R. Brief symptom inventory. Eur. J. Psychol. Assess. 1993, 13, 595–605. [Google Scholar] [CrossRef]
  14. Asner-Self, K.K.; Schreiber, J.B.; Marotta, S.A. A cross-cultural analysis of the Brief Symptom Inventory-18. Cult. Divers. Ethn. Minor. Psychol. 2006, 12, 367. [Google Scholar] [CrossRef] [PubMed]
  15. Recklitis, C.J.; Parsons, S.K.; Shih, M.-C.; Mertens, A.; Robison, L.L.; Zeltzer, L. Factor structure of the brief symptom inventory—18 in adult survivors of childhood cancer: Results from the childhood cancer survivor study. Psychol. Assess. 2006, 18, 22. [Google Scholar] [CrossRef]
  16. Geng, Y.; Ni, X.; Wang, Y.; Fan, J.; Qian, Y.; Li, X. Factor Structure and Measurement Invariance of the Brief Symptom Inventory-18 Among Chinese Adults. Front. Psychol. 2022, 13, 882815. [Google Scholar] [CrossRef] [PubMed]
  17. Li, M.; Wang, M.C.; Shou, Y.; Zhong, C.; Ren, F.; Zhang, X.; Yang, W. Psychometric Properties and Measurement Invariance of the Brief Symptom Inventory-18 among Chinese Insurance Employees. Front. Psychol. 2018, 9, 519. [Google Scholar] [CrossRef] [PubMed]
  18. Mao, B.; Kanjanarat, P.; Wongpakaran, T.; Permsuwan, U.; O’Donnell, R. Factors Associated with Depression, Anxiety, and Somatic Symptoms among International Salespeople in the Medical Device Industry: A Cross-Sectional Study in China. Healthcare 2023, 11, 2174. [Google Scholar] [CrossRef]
  19. Pongpitpitak, N.; Wongpakaran, N.; Wongpakaran, T.; Nuansri, W. Buffering Effect of Perseverance and Meditation on Depression among Medical Students Experiencing Negative Family Climate. Healthcare 2022, 10, 1895. [Google Scholar] [CrossRef]
  20. Wongpakaran, T.; Wongpakaran, N. Detection of suicide among the elderly in a long term care facility. Clin. Interv. Aging 2013, 8, 1553–1559. [Google Scholar] [CrossRef]
  21. Wongpakaran, N.; Wongpakaran, T.; Lerttrakarnnon, P.; Jiraniramai, S.; Sirirak, T.; Assanangkornchai, S.; Taemeeyapradit, U.; Tantirangsee, N.; Lertkachatarn, S.; Arunpongpaisal, S.; et al. Prevalence, clinical and psychosocial variables of depression, anxiety and suicidality in geriatric tertiary care settings. Asian J. Psychiatr. 2018, 41, 38–44. [Google Scholar] [CrossRef] [PubMed]
  22. Wongpakaran, N.; Wongpakaran, T.; Lertkachatarn, S.; Sirirak, T.; Kuntawong, P. Core Symptom Index (CSI): Testing for bifactor model and differential item functioning. Int. Psychogeriatr. 2019, 31, 1769–1779. [Google Scholar] [CrossRef] [PubMed]
  23. Dreher, A.; Hahn, E.; Diefenbacher, A.; Nguyen, M.H.; Böge, K.; Burian, H.; Dettling, M.; Burian, R.; Ta, T.M.T. Cultural differences in symptom representation for depression and somatization measured by the PHQ between Vietnamese and German psychiatric outpatients. J. Psychosom. Res. 2017, 102, 71–77. [Google Scholar] [CrossRef] [PubMed]
  24. Kirmayer, L.J.; Young, A. Culture and somatization: Clinical, epidemiological, and ethnographic perspectives. Psychosom. Med. 1998, 60, 420–430. [Google Scholar] [CrossRef] [PubMed]
  25. Kirmayer, L.J. Cultural variations in the clinical presentation of depression and anxiety: Implications for diagnosis and treatment. J. Clin. Psychiatry 2001, 62 (Suppl. 13), 22–28, discussion 29–30. [Google Scholar]
  26. Wongpakaran, N.; Wongpakaran, T.; Wedding, D.; Mirnics, Z.; Kovi, Z. Role of Equanimity on the Mediation Model of Neuroticism, Perceived Stress and Depressive Symptoms. Healthcare 2021, 9, 1300. [Google Scholar] [CrossRef]
  27. Wongpakaran, N.; Wongpakaran, T.; Kuntawong, P. Evaluating hierarchical items of the geriatric depression scale through factor analysis and item response theory. Heliyon 2019, 5, e02300. [Google Scholar] [CrossRef] [PubMed]
  28. Horowitz, L.M.; Rosenberg, S.E.; Baer, B.A.; Ureño, G.; Villaseñor, V.S. Inventory of interpersonal problems: Psychometric properties and clinical applications. J. Consult. Clin. Psychol. 1988, 56, 885–892. [Google Scholar] [CrossRef] [PubMed]
  29. Sun, Q.-w.; Jiang, G.-r.; Zhang, Q.-j. A report on the application of Inventory of Interpersonal Problems (IIP-32) to 1498 college students. Chin. J. Clin. Psychol. 2010, 18, 466–468. [Google Scholar]
  30. Cui, M.; Fincham, F.D.; Pasley, B.K. Young adult romantic relationships: The role of parents’ marital problems and relationship efficacy. Pers. Soc. Psychol. Bull. 2008, 34, 1226–1235. [Google Scholar] [CrossRef]
  31. Kline, R. Principles and Practice of Structural Equation Modeling; The Guilford Press: New York, NY, USA; London, UK, 2011. [Google Scholar]
  32. Wells, C.S. Assessing Measurement Invariance for Applied Research; Cambridge University Press: Cambridge, UK, 2021. [Google Scholar]
  33. Chen, F.F. Sensitivity of goodness of fit indexes to lack of measurement invariance. Struct. Equ. Model. A Multidiscip. J. 2007, 14, 464–504. [Google Scholar] [CrossRef]
  34. Parker, G.; Cheah, Y.C.; Roy, K. Do the Chinese somatize depression? A cross-cultural study. Soc. Psychiatry Psychiatr. Epidemiol. 2001, 36, 287–293. [Google Scholar] [CrossRef]
  35. Wong, R.; Wu, R.; Guo, C.; Lam, J.K.; Snowden, L.R. Culturally Sensitive Depression Assessment for Chinese American Immigrants: Development of a Comprehensive Measure and a Screening Scale Using an Item Response Approach. Asian Am. J. Psychol. 2012, 3, 230–253. [Google Scholar] [CrossRef]
Figure 1. The first-order three-factor model (left) and the bifactor model of the Core Symptom Index (right). Latent variables: anxiety, depression, and somatic (somatization). Observed variables: A12–A15: anxiety indicators; D2–D7: depression indicators, S1–S11; somatic indicators. Paths and loadings: Arrows from latent and observed variables indicate factor loadings. Double-headed arrows between latent variables indicate covariances. e1–e15 represent the observed variables’ residual variances. First-order three-factor model (left): This model contains only specific factors without a general factor. Observed variables load onto a single specific factor, and the model includes covariances among the specific factors. Bifactor model (right): This model contains general and specific factors. Observed variables load onto both the general factor and their respective specific factors.
Figure 1. The first-order three-factor model (left) and the bifactor model of the Core Symptom Index (right). Latent variables: anxiety, depression, and somatic (somatization). Observed variables: A12–A15: anxiety indicators; D2–D7: depression indicators, S1–S11; somatic indicators. Paths and loadings: Arrows from latent and observed variables indicate factor loadings. Double-headed arrows between latent variables indicate covariances. e1–e15 represent the observed variables’ residual variances. First-order three-factor model (left): This model contains only specific factors without a general factor. Observed variables load onto a single specific factor, and the model includes covariances among the specific factors. Bifactor model (right): This model contains general and specific factors. Observed variables load onto both the general factor and their respective specific factors.
Ejihpe 14 00126 g001
Table 1. Descriptive statistics, skewness, and kurtosis of the CSI items (n = 794).
Table 1. Descriptive statistics, skewness, and kurtosis of the CSI items (n = 794).
CSI ItemMeanSDVarianceSkewnessKurtosis
1. Ringing or buzzing in the ear(s)0.8931.0291.1511.0280.042
2. Suicidal idea0.6550.9720.9441.4021.057
3. Palpitation1.0531.0271.0530.776−0.068
4. Crying1.3401.1301.2750.455−0.781
5. Self-blaming1.6281.1491.3190.076−1.097
6. Feeling lonely1.3291.1241.2610.407−0.799
7. Depressed1.5311.1521.3250.119−1.105
8. Trouble catching your breath0.9661.0261.050.812−0.220
9. Hot or cold spells0.9271.0681.1380.9730.069
10. Feeling numb or tingling0.8881.0881.1831.0280.106
11. Fullness in the head or nose0.9671.0641.1300.808−0.387
12. Discomfort when in a crowd1.2291.1631.3500.476−0.944
13. Upset when being left alone1.3071.1821.3940.407−1.017
14. Feeling agitated1.3481.1511.3220.352−0.937
15. Feeling the urge to do things1.5431.1871.4070.106−1.07
SD = Standard deviation.
Table 2. Comparison of fit indices among the CSI models.
Table 2. Comparison of fit indices among the CSI models.
Modelχ2dfχ2/dfRMSEASRMRTLICFI
Unidimensional model1280.5179014.2280.1290.0640.8340.858
First-order model667.659857.8540.0930.0500.9140.930
Higher-order factor model652.186847.7640.0920.0490.9150.932
Bifactor model440.364755.8710.0780.0390.9390.956
df = degree of freedom, RMSEA = root mean square error of approximation, SRMR = standardized root mean square residual, TLI = Tucker–Lewis Index, CFI = comparative fit index.
Table 3. Standardized factor loadings for the CSI bi-factor model.
Table 3. Standardized factor loadings for the CSI bi-factor model.
ItemDescriptionAnxietyDepressionSomatizationGlobal
A12Discomfort when in a crowd0.124 ** 0.805 ***
A13Upset when being left alone0.315 *** 0.814 ***
A14Feeling agitated0.300 *** 0.770 ***
A15Feeling the urge to do things0.351 *** 0.751 ***
D2Suicidal idea 0.214 *** 0.705 ***
D4Crying −0.343 *** 0.676 ***
D5Self-blaming −0.396 *** 0.694 ***
D6Feeling lonely −0.100 ** 0.809 ***
D7Depressed −0.506 *** 0.715 ***
S3Palpitation 0.137 ***0.691 ***
S8Trouble catching breath 0.261 ***0.750 ***
S9Hot or cold spells 0.524 ***0.697 ***
S10Feeling numb or tingling 0.512 ***0.612 ***
S1Ringing or buzzing in the ear(s) 0.374 ***0.649 ***
S11Fullness in the head or nose 0.359 ***0.690 ***
A = anxiety, D = depression, S = somatization. ** p < 0.01 and *** p < 0.001.
Table 4. Invariance test results of CSI’s multi-group CFA.
Table 4. Invariance test results of CSI’s multi-group CFA.
Modelχ2 (df)p-ValueCFITLIRMSEAΔCFIΔTLIΔRMSEAInterpretation
Sex
Configural591.335 (152) <0.001 0.948 0.9280.060
Metric 642.640 (177) <0.001 0.945 0.935 0.058 0.0030.0070.002Accept
Scalar 643.091 (178) <0.001 0.945 0.935 0.057 0.0000.0000.001Accept
Age
Configural581.098 (150) <0.001 0.950 0.930 0.060
Metric 637.664 (664) <0.001 0.946 0.936 0.0580.0040.0060.002Accept
Scalar 685.727 (191) <0.001 0.943 0.937 0.0570.0030.0010.001Accept
Education
Configural549.041 (150) <0.001 0.950 0.931 0.058
Metric 654.799 (176) <0.001 0.940 0.929 0.059 0.0100.0020.001Accept
Scalar 827.039 (191) <0.001 0.921 0.913 0.065 0.0190.0160.006Reject
Partial invariance751.414 (186) <0.001 0.930 0.921 0.062 0.0100.0080.003Accept
Note: χ2 (df): Chi-Square value and degrees of freedom, CFI: comparative fit index, TLI: Tucker–Lewis index, RMSEA: root mean square error approximation.
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Chang, Y.; He, B.; DeMaranville, J.; Wongpakaran, N.; Wedding, D.; Wongpakaran, T. Psychometric Properties of the Chinese Version of the Core Symptom Index: A Study among Chinese Parents of Children with Autistic Spectrum Disorders. Eur. J. Investig. Health Psychol. Educ. 2024, 14, 1902-1912. https://doi.org/10.3390/ejihpe14070126

AMA Style

Chang Y, He B, DeMaranville J, Wongpakaran N, Wedding D, Wongpakaran T. Psychometric Properties of the Chinese Version of the Core Symptom Index: A Study among Chinese Parents of Children with Autistic Spectrum Disorders. European Journal of Investigation in Health, Psychology and Education. 2024; 14(7):1902-1912. https://doi.org/10.3390/ejihpe14070126

Chicago/Turabian Style

Chang, Yu, Bi**g He, Justin DeMaranville, Nahathai Wongpakaran, Danny Wedding, and Tinakon Wongpakaran. 2024. "Psychometric Properties of the Chinese Version of the Core Symptom Index: A Study among Chinese Parents of Children with Autistic Spectrum Disorders" European Journal of Investigation in Health, Psychology and Education 14, no. 7: 1902-1912. https://doi.org/10.3390/ejihpe14070126

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