Revision and Validation of the Parental Autonomy Support Scale Among Chinese College Students

Abstract

To revise the Parental Autonomy Support Scale (PASS) and to validate its psychometric properties in Chinese college students, this study recruited 738 Chinese college students, with 72 of them retested four weeks later. The Parental Psychological Control Scale (PPCS) and the Self-Esteem Scale (RSES) were used to evaluate the validity of the PASS. Results showed that the revised PASS contained a total of nine items measuring three dimensions: autonomous decision-making, transpositional thinking, and willingness to respect. Results showed that the three-factor ESEM model fitted the data well (TLI = 0.981, CFI = 0.994, RMSEA = 0.046). The PASS showed a significant negative correlation between the total score of the PASS and the total score of the PPCS (r = −0.344, p < .001), and a significant positive correlation of the PASS with the total score of the RSES (r = 0.297, p < .001). The composite reliability coefficient was 0.913 for the total score. The test-retest reliability coefficients were 0.827 for the total score and ranged from 0.626 to 0.744 for the three dimensions. The revised PASS is shown to have sound psychometric properties and thus can be used as a tool to measure the level of parental autonomy support among Chinese college students.

Keywords

parental autonomy support reliability validity college students

Parental autonomy support refers to the behavior of parents who encourage their children to express themselves, adopt their children’s views, accept their children’s feelings, and allow their children to participate in decision-making processes (Chirkov & Ryan, 2001; Mageau et al., 2015; Wang et al., 2007). Self-determination theory (SDT) states that the need for autonomy is a universal and foundational human need (Deci & Ryan, 1995; Harter, 1978; Zhao et al., 2016). The satisfaction of one’s need for autonomy has been shown to contribute to one’s well-being (Mouratidis et al., 2011) and mental health (Baard et al., 2004), and failure to fulfill this need has been seen to significantly influence issues of maladjustment and even psychopathology (Adie et al., 2008), and is positively associated with poor psychological well-being (Stebbings & Ntoumanis, 2012). One’s level of parental autonomy support is an important predictor of their individual autonomy development (McCurdy et al., 2020). Research has shown that parental autonomy support positively affects child development. For example, children with high levels of parental autonomy support tend to have better academic performance (Li et al., 2022; Su & Reeve, 2011; Vasquez et al., 2016; Zhang, 2021), a stronger sense of well-being (Downie et al., 2007; Lekes et al., 2010; Li et al., 2019), and a higher level of self-esteem (Barberis et al., 2021; Sun et al., 2022). In contrast, low levels of parental autonomy support are associated with a host of negative outcomes including poor parent-child relationships (Yao et al., 2022), poor psychological well-being (Zhang & Li, 2022), and increased problematic behaviors, such as internet addiction (Chen et al., 2018; Deng et al., 2022; Mishra, 2017).

Parental autonomy support was initially considered as the opposite end of the continuum to parental psychological control (Schaefer, 1965a). Schaefer (1965b) defined parental psychological control as parental dominance, aggression and rejection of children, and erratic teaching, whereas parental autonomy support has none of these characteristics. Other scales measuring parental autonomy support have treated parental autonomy support either as the same dimension as parental psychological control based on the above assumptions (e.g., Schaefer’s Children’s Report of Parental Behavior Inventory, naming this dimension Psychological Autonomy vs. Psychological Control; 1965a, 1965b), or by measuring only one’s level of parental psychological control (e.g., Barber’s Psychological Control Scale-Youth Self-Report, 1996). Barber, 2001 have pointed out that the correlation between parental psychological control and parental autonomy support was not high enough to argue that they belong to the same dimension, while Silk et al. (2003) also showed through confirmatory factor analysis that these two constructs should be measured separately.

There are two distinct theoretical perspectives on the study of parental autonomy support: separation-individuation theory and self-determination theory (McCurdy et al., 2020). Separation-individuation theory (Blos & Chen, 1979 2007; Mahler et al., 1975) starts from the premise that healthy autonomy development involves psychological and emotional distance between adolescents and their parents. According to this perspective, the ideal endpoint in terms of autonomy development is for adolescents to be able to solve problems and make decisions on their own, rather than relying on their parents. However, this theory fails to recognize that adolescents must not only behave independently but also authentically (Soenens et al., 2009). As a result, autonomy researchers have increasingly framed their work using self-determination theory (SDT; Deci & Ryan, 2000). According to SDT, being autonomy-supportive is to show consideration for young adults’ distinct internal frame of reference, honoring their unique needs and feelings. Autonomy-supportive parents give their children the opportunity to be active agents and feel a sense of ownership of their behaviors (Soenens et al., 2007). The Parental Autonomy Support Scale (PASS) acknowledged the SDT and was first developed and used by Wang et al. (2007). The original PASS consists of eight items which were selected from measures used in prior research (McPartland & Epstein, 1977; Robbins, 1994; Steinberg et al., 1992). Four items tapped choice making and four tapped opinion exchange. All of the items measure the children’s perception of the level of parental support they receive. The sample of this study was 373 seventh graders in the United States and 433 seventh graders in China. The participants took part in two questionnaire sessions in the fall (Wave 1) and again in the spring (Wave 2) when they were in seventh grade. Cheung and Pomerantz (2011) revised the PASS by adding four items selected from the above three studies (McPartland & Epstein, 1977; Robbins, 1994; Steinberg et al., 1992) but did not specify the dimension to which each item belonged. The sample of this study was 374 seventh graders in the United States and 451 seventh graders in China. The data were collected at four time points: fall of seventh grade (Wave 1), spring of seventh grade (Wave 2), fall of eighth grade (Wave 3), and spring of eighth grade (Wave 4). The psychometric properties of the PASS of the above two studies (Cheung & Pomerantz, 2011; Wang et al., 2007) are shown in Table 1. In particular, the PASS showed cross-cultural measurement equivalence across the United States and China. As such, the PASS has been a preferred choice in numerous Chinese studies. On October 18, 2022, a search was done on journal article headings for “parental autonomy support,” using the Chinese National Knowledge Infrastructure (the largest Chinese academic paper database and academic electronic resources integrator, including more than 95% of officially published Chinese journal articles). In total, 10 relevant journal articles were returned, of which one study used the eight-item PASS, and the remaining nine used the 12-item PASS to measure parental autonomy support, suggesting that the measure is recognized for its validity and used within a Chinese research context.

Table 1.

Psychometric Properties of the PASS in Wang et al. (2007) and Cheung and Pomerantz (2011).

	Reliability		Validity
	Cronbach’s α	Test-rest reliability	Concurrent validity evidence based on external variables	Measurement invariance
Wang et al. (2007)
US	0.87–0.89	0.60	r_PPC = −0.35∼-0.30	Metric invariance between waves and countries
China	0.89–0.90	0.61	r_PPC = −0.31∼-0.28
Cheung and Pomerantz (2011)
US	0.87–0.89	-	r_PI = 0.29–0.48	Metric invariance across countries and waves
China	0.88–0.89	-	r_PI = 0.25–0.28

Note. PPC = parents’ psychological control; PI = parents’ involvement in children’s learning.

In terms of the psychometrics of the PASS, however, there are still two major research gaps in the relevant research. First, the factor structure of the 12-item PASS has not yet been validated systematically, and the number of dimensions the PASS measures after adding the additional four items remains unclear. Second, most of the existing studies involving parental autonomy support variables have only focused on primary and secondary school students, and few studies have examined the effects of parental autonomy support on college students. College students are typically experiencing major transitions and challenges in their lives, and their behaviors and emotions are still affected by their parents (Arnett, 2000). Meanwhile, parents of college students need to balance giving their children more autonomy than ever before while still maintaining a close and supportive relationship with their children, which is a great challenge (Aquilino, 2006). These changes may be further magnified in Chinese culture due to its longstanding emphasis on children showing obedience to their parents (Wei et al., 2022). “Filial piety” is a primary virtue in the traditional Chinese culture, referring to children being expected to respect and obey their parents’ choices and wishes. However, with the rapid economic developments and social-cultural transformations that have been taking place in contemporary China, autonomy support has become more important among the younger generation (Ma et al., 2022; Nalipay et al., 2020). Therefore, validating the PASS within Chinese college students may allow researchers to better understand the current state of parental support in the Chinese context, and reveal how parental autonomy support correlates with other variables.

The goal of the present study, then, was to document the psychometric properties of the Chinese version of the PASS among Chinese college students. Specifically, we investigated the factor structure, concurrent validity, internal consistency, and stability of the PASS to determine whether the PASS was applicable in a Chinese college student context.

Methods

Participants

A total of 738 Chinese college students were randomly selected from a university in Guangdong Province using a convenience sampling approach. Investigators sent a Sojump link (https://www.wjx.cn/; a Chinese online survey platform) to potential subjects who were enrolled in the researchers’ classes. Students who agreed to participate in the study would complete and submit the web-based questionnaire on-site under the supervision of the researchers. All participants gave their informed consent before completing the questionnaire. Of the subjects, 290 were male and 448 were female; 425 were freshmen, 172 were sophomores, 108 were juniors, and 33 were seniors. The mean age was 19.87 years, SD = 1.50 years. Afterward, 72 students were randomly selected to assess the test-retest reliability of the PASS four weeks after they had first completed the questionnaire. These 72 students had a mean age of 19.85 years, SD = 1.34 years. At both time points, the students were asked to provide the last four digits of their cell phone number to match the collected data to examine the test-retest reliability.

Measures

The Parental Autonomy Support Scale (PASS)

The PASS consists of 12 items. Four items measured choice making (items 1, 4, 9, and 11; e.g., “My parents allow me to make choices whenever possible”), four items measured opinion exchange (items 2, 5, 7, and 10; e.g., “My parents encourage me to share my thoughts and opinions when it comes to decisions which affect me”). The remaining four items (items 3, 6, 8, and 12; e.g., “My parents do not get angry at me even when we disagree on something”) did not have a specified dimension (Cheung & Pomerantz, 2011; Wang et al., 2007). The original PASS had already been developed and tested in both English and Chinese languages, so the Chinese language version of the measure was used in this study. Respondents rate each item on a scale ranging from 1 (not at all true) to 5 (very true) with regard to the extent to which their parents use autonomy-supportive practices. Final scores with higher numbers indicate greater parental support for autonomy. The researchers in this study obtained authorization from the original authors of the PASS to revise the scale.

The Parental Psychological Control Scale (PPCS)

Research has shown that parental psychological control is significantly and negatively related to parental autonomy support. The PPCS was originally developed by Wang et al. (2007). The correlation coefficients between the PPCS and the PASS in the study of Wang et al. (2007) can be found in Table 1. The 10-item PPCS assesses three dimensions: guilt induction, love withdrawal, and authority assertion. Each item is scored on a scale ranging from 1 (not at all) to 4 (fully), with higher total scores representing higher levels of parental psychological control. The Cronbach’s α coefficient of the total score in this study was .867, and .727, .874, and .783 for the three dimensions, respectively.

The Rosenberg Self-Esteem Scale (RSES)

Research has shown that parental autonomy support is significantly and positively related to children’s self-esteem levels (Deci & Ryan, 1995). The Self-Esteem Scale was developed by Rosenberg (2015) and later revised by Wang et al. (2010) to be used in the context of Chinese adolescents. The scale has a unidimensional structure with 10 items. Each item is rated on a scale ranging from 1 (strongly disagree) to 4 (strongly agree). Five of the items are negatively rated, requiring reverse scoring. Higher total scores indicate higher levels of self-esteem. In a sample of 386 Chinese undergraduate students, Gong and Wang (2021) found that the correlation between perceived parental autonomy support and the student’s level of self-esteem was 0.290. Yan et al. (2021) validated the RSES in the context of Chinese college students. The Cronbach’s α coefficient of the total scale score was .871 in this study.

Statistical Analysis

SPSS 23.0 was used for item analysis and correlation analysis. Mplus 8.3 was used to construct exploratory structural equation modeling (ESEM) and estimate the composite reliability (i.e., ω coefficient). The ESEM was adopted in this study specifically instead of confirmatory factor analysis (CFA), as CFA relies on the highly restrictive Independent Cluster Model (ICM), in which cross-loadings between items and non-target factors are fixed at exactly zero. Due to the fallible nature of indicators (Morin et al., 2016), however, empirical research has indicated that it is difficult to achieve a reasonable fit of measurements assessing multidimensional constructs within the ICM-CFA framework (e.g., Marsh et al., 2009; Wang et al., 2019). Instead, ESEM allows cross-loadings, which can result in more accurate factor loadings and factor correlations (Asparouhov & Bengt, 2009; Marsh et al., 2014).

Both the traditional method of measurement invariance (MI) and the equivalence testing (ET) were used to assess whether the PASS had measurement invariance across genders. MI is commonly assessed by performing a battery of χ² tests and/or calculating a set of fitness indices differences (such as ΔRMSEA and ΔCFI) using multi-group structural equation modeling (Lai, 2020). However, under conventional null hypothesis testing, one cannot claim MI with sufficient confidence even if all test statistics are not significant. Moreover, the differences in the model indices across models could only suggest a descriptive statistical conclusion, but not an inferential one (Yuan et al., 2016). In this study, ET was adopted to study MI in place of more traditional methods, as ET informs researchers of the size of the possible error specification. If the size of the error specification (e.g., RMSEAt) is smaller than the acceptable value (e.g., RMSEAe), then the measurements of the groups can be considered actually equal with 95% confidence. In the present study, Mplus 8.3 was used to conduct the traditional MI tests, and R was used to complete the measurement equivalence analysis based on ESEM (Yuan et al., 2016). All analyses were done using the total sample, with the exception of the retest reliability, which was based on the retest sample.

Results

Item Analysis

Three methods were used for the item analysis. First, based on their total scores, participants in both the top and bottom 27% were selected as the high and low subgroups, and independent sample t-tests were conducted on the scores of each item for both the high and the low subgroups. The results showed that all of the items differed significantly between the high and low subgroups (p < .001), indicating that there was good discrimination between all items.

Second, the item score and the total score correlation tests were performed on all 12 PASS items, and the results revealed that the correlation between all items and the total score was >0.30, with correlation α coefficients ranging from .530 to .787 (p < .001).

Third, the Cronbach’s α coefficients of the deleted items were examined. If the Cronbach’s α coefficient of the remaining items increased after the deletion of that item, then it was determined that the item itself should be deleted. As a result, Item 6 (“My parents allow me to make my own choices about the things I want to do in my life”) was deleted, leaving 11 items.

Validity

Exploratory Structural Equation Modeling

ESEM was performed based on Geomin rotation to explore the one-factor, two-factor, and three-factor model fitness of the PPAS. The three newly added items (after Item 6 had been removed) were each assigned to one of the two existing factors based on the content of the items: Item 3 (“My parents do not insist that I do things their way”) and Item 12 (“My parents do not insist that I ask permission for everything that I do”) were assigned to the choice making dimension, while Item 8 (“My parents do not get angry at me even when we disagree on something”) was placed in the opinion exchange dimension. The results showed that both the two- and three-factor model fits were satisfactory: two-factor model TLI = 0.960, CFI = 0.975, RMSEA = 0.064; three-factor model TLI = 0.986, CFI = 0.994, RMSEA = 0.037 (see Table 2). The three-factor model significantly outperformed the two-factor model with regards to ΔCFI = 0.019 and ΔRMSEA = −0.027. Therefore, the PPAS was considered to have three dimensions.

Due to the presence of cross-loadings in ESEM, items with poor psychometric properties such as low target factor loadings (λ < 0.4) or small differences between target and non-target factor loadings (e.g., <0.2) were removed to obtain a clear factor loading matrix (Schaefer et al., 2015). Therefore, Item 2 (“My parents listen to my opinions or perspectives when I have a problem”) and Item 8 were removed. The factor loading matrix for the remaining nine items is shown in Table 3. The three dimensions were named choice making, opinion exchange, and willingness to respect, based on the items making up each dimension. The correlations among the factors ranged from 0.427 to 0.731. The fit indices of ESEM were TLI = 0.981, CFI = 0.994, and RMSEA = 0.046.

Table 2.

The Fitness Indices of the Competitive Models of the PASS.

	χ²	df	χ²/df	TLI	CFI	SRMR	RMSEA (90%CI)
One-factor model	308.421	44	7.010	0.919	0.935	0.041	0.090 [0.081, 0.100]
Two-factor model	136.521	34	4.015	0.960	0.975	0.024	0.064 [0.053, 0.075]
Three-factor model	50.401	25	2.016	0.986	0.994	0.013	0.037 [0.022, 0.052]

Measurement Invariance

Analyses were performed in the following order: configural MI, metric MI, scalar MI, and finally latent mean MI. The traditional MI test takes the difference between CFI and/or RMSEA of adjacent models not exceeding 0.01 as the equivalence criterion (Chen, 2007; Cheung & Rensvold, 2002), while in ET, if the fit index RMSEAt calculated from the model parameters of two adjacent steps is less than its corresponding critical value RMSEAe, this indicates that the latter step of the model parameter cross-group equivalence assumption holds and the probability of making this inference to make an error does not exceed 0.05 (Yuan & Chan, 2016).

First, both the male and female baseline models were tested, and the configural equivalence constraint model fit well according to the traditional method (see Table 4), indicating configural equivalence. Second, metric, scalar, and latent mean equivalence tests were performed. Both ΔCFI and ΔRMSEA were less than 0.01, and the results supported metric invariance, scalar invariance, and latent mean equivalence. Third, the results of ET showed that the RMSEAt corresponding to metric, scalar, and latent mean equivalence (0.064, 0.105, and 0.061, respectively) did not exceed the adjusted cutoff values of RMSEAe (0.103, 0.122, and 0.114, respectively), which also supported metric equivalence, scalar equivalence, and latent mean equivalence.

Table 3.

ESEM Factor Loading Matrix and Factor Correlations of the PPCS.

		Choice making	Opinion exchange	Willingness to respect
1 My parents allow me to make choices whenever possible		0.594 ^***	0.020	0.199
3 My parents do not insist that I do things their way		0.570 ^***	0.271^**	−0.007
4 My parents allow me to decide things for myself		0.578 ^***	−0.010	0.341^**
5 My parents are usually willing to consider things from my point of view		0.200^**	0.662 ^***	0.019
7 My parents explain why they want me to do something		0.001	0.754 ^***	−0.035
9 My parents let me make my own plans for things I want to do		0.177^*	−0.012	0.697 ^***
10 My parents encourage me to give my ideas and opinions when it comes to decisions about me		0.011	0.168^*	0.663 ^***
11 My parents trust me to do what they expect without checking up on me		−0.046	0.187	0.582 ^***
12 My parents do not insist that I ask permission for everything that I do		0.071	0.028	0.620 ^***
Factor correlation	Opinion exchange	0.427^***
Factor correlation	Willingness to respect	0.638^***	0.731^***

Note. ^*, p < .05; ^**, p < .01; ^***, p < .001.

Validity Evidence Based on External Variables

The validity of the revised version of the PASS was examined by comparing its results to those of the PPCS and the RSES. The results showed that the total score of the PASS was significantly negatively correlated with the total score of the PPCS and the scores of each of its dimensions, while it was significantly positively correlated with the total score of the RSES, as shown in Table 5.

Table 4.

Measurement Invariance Test Based on ESEM Across Gender.

MI	Conventional MI				Measurement equivalence
MI	RMSEA	CFI	ΔRMSEA	ΔCFI	Δχ²	Δdf	RMSEAt	RMSEAe
Configural (male)	0.064	0.988
Configural (female)	0.050	0.993
Configural invariance	0.056	0.991
Metric invariance	0.049	0.988	0.007	0.007	27.078	18	0.064	0.103
Scalar invariance	0.051	0.985	0.002	0.003	15.062	6	0.105	0.122
Latent mean invariance	0.047	0.985	0.004	0.000	9.665	9	0.061	0.114

Reliability

The composite reliability for the total score of the scale was 0.913 (Fu, Wen, & Wang, 2022; Raykov & Marcoulides, 2011). Pearson’s correlation coefficient was 0.827 (p < .001) for the test-retest sample (n = 72). The test-retest reliability coefficients of the abovementioned three dimensions were .744, .626, and .727 (p < .001), respectively. The mean differences in the total and dimension scores between the two tests were not statistically significant.

Table 5.

Correlation Matrix of the PPCS and the Criteria.

	PPCS_T	PPCS_GI	PPCS_LW	PPCS_AA	RSES_T
PASS_T	−0.344^***	−0.216^***	−0.338^***	−0.281^***	0.297^***
Choice making	−0.320^***	−0.229^***	−0.322^***	−0.236^***	0.241^***
Opinion exchange	−0.252^***	−0.133^**	−0.262^***	−0.248^***	0.227^***
Respect for the will	−0.298^***	−0.193^***	−0.297^***	−0.255^***	0.296^***

Note. PASS_T = the total score of the PASS; PPCS_T = the total score of the PPCS; RSES_T = the total score of the RSES; PPCS_GI = guilt induction; PPCS_LW = love withdrawal; PPCS_AA = authority assertion. ^**, p < .01; ^***, p < .001.

Discussion

This study explored the psychometric properties of the PASS among Chinese college students. The original version of the PASS was developed for use in primary and secondary school students. For primary and secondary school students, parental autonomy support includes parents providing their children with encouragement and opportunities, and allowing their children to participate in decision-making (Ryan & Deci, 2017). In contrast, for college students, parental support includes not only providing their children with choices, but also showing respect for their children’s decisions, development, and supporting their sense of self (McCurdy et al., 2020). Item 6 of the original PASS (“My parents allow me to make my own decisions about what I want to do in my life”) was removed due to poor performance, while Item 1 (“My parents allow me to make my. Own choices whenever possible”) was retained, as it suggests that parental autonomy support for college children is still reflected through parents providing their thoughts on their children’s choices, but with less weight or expectation.

The ESEM results showed that the three-factor model was the optimal factor structure, with the three dimensions being choice making, opinion exchange, and willingness to respect. The three-factor ESEM model showed high target factor loadings (all >0.5) and low cross-factor loadings (all <0.4). The multi-group comparisons (traditional MI tests) and ET were adopted to examine the MI, and both results indicated that the PASS has configural, metric, scalar, and latent mean equivalence. In particular, this study performed the very first ET on the PASS based on ESEM, providing empirical study results and arguing the case for broader adoption of applying ESEM for ET.

Results showed that PASS results negatively correlated with those of the PPCS (r = −0.344). It is generally understood that one’s level of perceived parental psychological control is negatively related to their level of perceived parental autonomy support (e.g., Liga et al., 2020; Mageau et al., 2015; Wang et al., 2007). Compared to the correlation coefficients (r = −0.31∼-0.28, see Table 1) between the PASS and the PPCS using Chinese adolescents as subjects in the study of Wang et al. (2007), the correlation coefficient found in the present study was generally consistent. Moreover, the correlation in the present study was marginally, if not significantly, higher than in the study of Wang et al. (2007). Although the items used in the PASS and PPCS were different in the two studies mentioned above, the results may indicate that Chinese college students perceive their parents’ autonomy-supportive and controlling behaviors to be more incompatible than Chinese adolescents perceive them to be. Meanwhile, the positive correlation between the PASS and the RSES (r = 0.297; Gong & Wang, 2021) supported the theory that parental autonomy support—parenting practices that highlight children’s autonomy and independent decision-making will promote young adults’ self-esteem (Deci & Ryan, 1995).

Regarding the reliability coefficients, the composite reliability of the PASS based on the ESEM was 0.913. The test-retest reliability after four weeks was 0.827, indicating that the scale also has good internal consistency and stability. The composite reliability of the total score in the present study was slightly higher than the Cronbach’s α coefficients of the total score (0.87–0.90, see Table 1) in the studies of Wang et al. (2007) and Cheung and Pomerantz (2011). This result gives evidence that the α coefficient is more likely to underestimate the internal consistency of the measurement (e.g., Green & Yang, 2009), while the composite reliability more correctly reflects the internal consistency (e.g., Raykov & Marcoulides, 2011). The test-retest reliability in the present study was evidently higher than that in the study of Wang et al. (2007). This is most likely due to the different test-retest intervals between the two studies (Aiken & Groth-Marnat, 2006). Because the test-retest procedures take into account measurement errors resulting from differences in both environmental and personal conditions, the test-retest reliability tends to be higher when the test-retest interval is short (e.g., a few weeks). Conversely, the test-retest reliability tends to be lower when the test-retest interval is longer (months or years).

To summarize, the revised version of the PASS was found to have good reliability and validity among Chinese college students, as well as measurement invariance across genders. The present study yields valuable evidence that parental autonomy support continues to affect adult children in college and university. The validation of the PASS constitutes an additional step toward a better understanding of autonomy-supportive parenting in a Chinese cultural context. Another advantage of the PASS is that it is relatively short—containing only nine items—such that it can easily be included in longitudinal work or administered to large samples using relatively few resources.

We must note that there are some limitations to this current study. First, the sample used in this study was not globally representative, as all participants came from the same geographical area, so it remains to be known whether the scale is applicable to the broader national population. Moreover, as the present study was conducted within a Chinese cultural context, it still remains to explore whether the results of this current study are applicable to other countries or cultures. (2) Although the three dimensions of the PASS contain a relatively even number of items, the opinion exchange dimension includes only two items, which can easily lead to low internal consistency and stability; this should be improved in future studies. (3) ET is a relatively newly emerged method of measurement equivalence testing, which theoretically determines the rate of type I error for the conclusions. However, this method is controversial, such as the rationality of using the RMSEAe as a critical value (Wang et al., 2020). Nonetheless, in this study, both the traditional MI test method and ET verified the measurement invariance of the PASS, giving more credibility and reliability to our conclusions.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Humanities and Social Science Fund of Ministry of Education of China (23YJC190026) and the Planning Project of Philosophy and Social Science of Guangdong Province (GD21YXL04).

ORCID iD

Yuanshu Fu

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