Psychometric Properties of the Acceptance and Action Questionnaire–II for Chinese College Students and Elite Chinese Athletes

Abstract

The purpose of the present study was to examine the psychometric properties of the Chinese version of the Acceptance and Action Questionnaire–II (AAQ-II) across two samples of Chinese college students (n = 183 and n = 366) and a sample of elite Chinese athletes (n = 330). Exploratory and confirmatory factor analyses supported the existence of a unidimensional AAQ-II. Adequate internal consistency reliability, test–retest reliability (one-month interval), factorial validity, and nomological validity with mindfulness, well-being, positive and negative affect/mood for both students and athletic samples were demonstrated. The AAQ-II also showed incremental validity in college students in explaining variances of well-being, positive and negative affect, anxiety, and depression, beyond the mindfulness measure. Most important, factorial invariance of the AAQ-II was demonstrated across male and female college students as well as across male and female athletes. Partial factorial invariance was also demonstrated across adolescent and adult athletes. Overall, results of this study suggest that the Chinese version of the AAQ-II may be a useful self-report measure of experiential avoidance in Chinese college students and elite Chinese athletes.

Keywords

Acceptance and Action Questionnaire experiential avoidance reliability validity Chinese version

In recent years, a growing research interest has been focused on experiential avoidance (EA) as a risk factor influencing people’s mental health and behavioral effectiveness during their lifetime (Powers, Vörding, & Emmelkamp, 2009). EA refers to the attempt to alter, control, or avoid the experiences such as thoughts, feelings, memories, and bodily sensations when people are unwilling to remain in contact with them, particularly with negative private events (Hayes et al., 2004; Hayes, Strosahl, & Wilson, 1999). Although the EA phenomenon is viewed as a basic component of the human condition, it may prevent people from committing to their values and pursing their life-long goals (Hayes, Wilson, Gifford, Follette, & Strosahl, 1996).

Acceptance and commitment therapy (ACT; Hayes et al., 1999) was developed specifically for decreasing EA and increasing experiential acceptance. Experiential acceptance, the opposite of EA, is defined as the willingness to make full contact with experiences without changing or altering them (Hayes, Luoma, Bond, Masuda, & Lillis, 2006). In ACT, individuals are encouraged to accept private experiences that can help them engage in value-based behavior. It has been preliminarily demonstrated that EA acts as a mediator between coping and psychological consequences, such as depression, anxiety, stress, and well-being (Costa & Pinto-Gouveia, 2011; Fledderus, Bohlmeijer, & Pieterse, 2010). Likewise, EA was found to mediate the effect of the ACT intervention on psychological distress, pain-related disability, and life satisfaction (Fledderus, Bohlmeijer, Fox, Schreurs, & Spinhoven, 2013; Hayes, Levin, Plumb-Vilardaga, Villatte, & Pistorello, 2013; Wicksell, Olsson, & Hayes, 2010).

The concept of EA was first introduced into sport context through the mindfulness-acceptance-commitment approach (MAC; Gardner & Moore, 2004, 2007), which is an integration and adaptation of ACT (Hayes et al., 1999) and mindfulness-based cognitive therapy (MBCT; Segal, Williams, & Teasdale, 2002). One emphasis of the MAC program is acceptance. Acceptance is the willingness to fully experience cognitions, emotions, and physiological states, not for the purpose of reducing discomfort, but rather for achieving long-term value-based goals (Gardner & Moore, 2004). The decrease of EA (the increase of experiential acceptance) in MAC interventions was found in a case study of diving athletes (Schwanhausser, 2009), in an open trial study of college students (Hasker, 2010), and in a randomized control trial study of college students (Lutkenhouse, Gardner, & Moore, 2007; as cited in Gardner & Moore, 2012). Likewise, a four-session adapted ACT intervention was found to be effective in educating athletes to accept private events they typically tried to avoid and to make a commitment to their rehabilitation (Mahoney & Hanrahan, 2011).

Measurement of Experiential Avoidance

Reliable and valid measures to examine the process and underlying mechanisms of ACT and ACT-based interventions (e.g., MAC) are required. The most commonly used self-report measure of EA has been the Acceptance and Action Questionnaire (AAQ; Hayes et al., 2004). However, the original AAQ has two limitations. The first limitation is the low internal consistency (Cronbach’s alpha), which reached only a satisfactory level of .70 (Hayes et al., 2004). This might be caused by unnecessary item complexity or subtlety of the concepts of the AAQ (Bond et al., 2011). The second limitation is that it is unclear whether the AAQ is a 9-item or 16-item single-factor model (Hayes et al., 2004) or it is a 16-item, two-factor model (Bond & Bunce, 2003). Accordingly, the AAQ-II was developed with the purpose of overcoming these limitations (Bond et al., 2011). A seven-item unidimensional AAQ-II was obtained through exploratory factor analysis and validated by three confirmatory factor analyses. Bond et al. (2011) stated that the AAQ-II also measures psychological inflexibility, which is described as the dominance of internal events over contingencies in determining value-directed actions preventing people from making full contact with the present moment. They further suggested that psychological inflexibility is a broader concept than EA. The AAQ-II demonstrated adequate internal consistency across six samples (α = .78–.88), adequate test–retest reliability (.81 and .79 for 3 and 12 months, respectively), and satisfactory convergent, concurrent, and discriminative validity.

Because of the strong need for a robust and stable AAQ-II, which is related to the underlying ACT theory (Bond et al., 2011), some research has been conducted to further evaluate the psychometric properties of the AAQ-II. In McCracken and Zhao-O’Brien (2010), factor analysis revealed a unitary factor structure, in a sample of patients undergoing pain management. A satisfactory internal consistency (α = .89) was achieved, and the AAQ-II was significantly correlated with depression, pain-related anxiety, physical disability, and social disability. In Gloster, Klotsche, Chaker, Hummel, and Hoyer (2011), the single-factor model of the AAQ-II provided an adequate model fit for the data, in two German help-seeking samples and two nonclinical samples, after adding two correlated residuals (between Items 2 and 5 and Items 3 and 4). Across these four groups, the internal consistency ranged from .84 to .97, and the test–retest reliability ranged from .74 to .85. The German version of the AAQ-II was significantly correlated with psychological symptomatology and the Big Five personality traits (Gloster et al., 2011). Fledderus, Voshaar, ten Klooster, and Bohlmeijer (2012) obtained a single-factor model of the AAQ-II with satisfactory model fit in a sample of Dutch adults with mild to moderate levels of depression and anxiety, after adding correlated residuals (between Items 2 and 5). The unidimensional nature and satisfactory reliability in comparing three age groups was further supported in subsequent IRT analyses. Significant correlations between the Dutch version of the AAQ-II and anxiety, depression, and mindfulness were demonstrated (Fledderus et al., 2012). More recently, Pennato, Berrocal, Bernini, and Rivas (2013) examined the AAQ-II through exploratory factor analysis using a sample of Italian adults from the general population and showed that the internal consistency was satisfactory (α =.83), and test–retest reliability over a 12-month period was modest (r = .61). The Italian version of the AAQ-II showed a significant correlation with mindfulness, well-being, anxiety, and depression (Pennato et al., 2013).

Although the psychometric properties of the AAQ-II have been preliminarily established in both general and clinical populations, they are yet to be examined in an athletic population. Given the importance of decreasing EA to improve sport performance and the general well-being of athletes (Gardner & Moore, 2004), we need additional information regarding the psychometric evidence and construct validity of the AAQ-II in an athletic sample, in order to adequately inform conceptual and intervention considerations in a sport context (Hagger & Chatzisarantis, 2009). In addition, although the measurement/factorial invariance across subgroups is necessary for making valid comparisons of group means and pooling data across groups together, the factorial invariance of the AAQ-II across males and females is yet to be established. This may be due to the small sample size (McCracken & Zhao-O’Brien, 2010), or the predominance of male or female participants (Gloster et al., 2011), that prevent the further invariant comparison between these subsamples. Moreover, the investigation of the psychometric properties of the AAQ-II in an adolescent sample is lacking. Although the Avoidance and Fusion Questionnaire for Youth (Greco, Lambert, & Baer, 2008) has been developed specifically for adolescents and has been extended to adult population (Fergus et al., 2012), further examination of the AAQ-II in an adolescent sample is warranted and necessary to generalize its utility in the wider population.

Purposes of the Current Study

Given the potential importance of EA for mental health, as well as its wide application, the examination of the AAQ-II in a Chinese general and sport context can provide evidence for the robustness of the measurement of EA. In addition, an investigation of this construct in a Chinese context from a measurement perspective can inform us of the generality of the AAQ-II in an Eastern culture. Moreover, with the introduction of ACT and ACT-based treatments (e.g., MAC) to Chinese general and athletic populations (Zeng, Liu, & Yu, 2011; Zhang, Bu, & Si, 2012), a reliable and valid measure for assessing the change process and the underlying change mechanism is becoming increasingly important. Therefore, the primary purpose of the current study was to examine the psychometric properties of the AAQ-II in two samples of Chinese college students and a sample of elite Chinese athletes who were all competing at regional, national, or international levels at the time of data collection.

In this study, we first aimed to explore the number of potential factors through exploratory factor analysis (EFA) using a sample of Chinese college students. Second, we aimed to examine whether the unidimensional factor model of the AAQ-II was supported by another sample of Chinese college students and a sample of elite Chinese athletes. Third, we sought to establish the nomological validity, by exploring the relationship between EA and mindfulness, subjective well-being, and affect/mood in both Chinese college students and elite Chinese athletes. Consistent with previous findings in other populations (Bond et al., 2011; Fledderus et al., 2012; Gloster et al., 2011), we expected negative associations between EA and mindfulness, subjective well-being, and positive affect/mood. Likewise, we also expected positive associations between EA and negative affect/mood. Fourth, we attempted to investigate the incremental validity of the AAQ-II beyond the mindfulness measure (i.e., Mindful Attention Awareness Scale [MAAS]), in a sample of Chinese college students. Based on previous studies (Gloster et al., 2011; McCracken & Zhao-O’Brien, 2010), we expected that the AAQ-II could make an additional contribution to the prediction of all the outcome measure scores (i.e., well-being, positive and negative affect/mood) while controlling for the MAAS. The final objective was to examine the gender and age-related invariance (i.e., adolescence and adults) of the measurement model. We hypothesized that the measurement model would remain invariant across male and female students, across male and female athletes, and across the adolescent and adult athletes.

Study 1

Method

Participants

The participants were 183 Chinese college students (69 females and 114 males) who attended physical education (PE) courses at a Hong Kong public university. The average age was 20.43 years (SD = 1.26; range = 19–27 years).

Measurement and Procedure

Following the steps for the transcultural validation of psychometric instruments (Hambleton, 2001, 2005), the instrument (AAQ-II; Bond et al., 2011) was translated into Chinese by two bilingual experts through a committee approach (i.e., reaching an agreement through discussion) and then back translated into English by two other experts.

The Chinese-translated seven-item AAQ-II (Bond et al., 2011) was administrated in the teaching venue before the PE class started. The items of the AAQ-II were rated on a 7-point Likert-type scale from 1 (never true) to 7 (always true) and took approximately 2 to 3 minutes to complete. Written informed consent was collected from all students, who were informed of their voluntary role in completing the questionnaire, as well as the confidentiality of the data handling.

Data Analysis

To identify the underlying dimensions of mindfulness, the AAQ-II items were analyzed using EFA with Mplus 7 (Muthén & Muthén, 1998–2012). The number of items was determined with parallel analysis (PA) in Mplus 7 and further evaluated using the model fit indices. For model fit evaluation, the following fit indices were estimated: (a) the comparative fit index (CFI), (b) the Tucker–Lewis index (TLI), (c) the root mean square error of approximation (RMSEA), and (d) the standardized root mean square residual (SRMR). Generally, values of the CFI and TLI exceeding .90 indicate a good fit and exceeding .95 indicate an excellent fit (Hu & Bentler, 1999). For the SRMR and RMSEA, the criterion for a good model fit is <.05, .05 ≤ SRMR and RMSEA < .08 indicate a reasonable fit, .08 ≤ SRMR and RMSEA < .10 indicate a mediocre fit, and >.10 indicates a poor fit (Browne & Cudeck, 1993).

Item analysis was carried out to assess homogeneity of the items, and three criteria were used, namely, interitem correlation, corrected item-total correlation, and internal consistency reliability using composite reliability (rho [ρ]; Raykov, 1997).

Results

Based on the result of parallel analysis (mean eigenvalue) using Mplus seven the initial EFA with 7 items revealed that a unifactor solution existed as only one eigenvalue was greater than one. The unifactor model indicates a marginal model fit, χ²(14) = 66.33, CFI = .92, TLI = .88, SRMR = .049, RMSEA (90% confidence interval [CI]) = .143 (.110, .179), all items had large factor loadings (λ > .60). Although the model fit improved slightly in a two-factor model, χ²(8) = 31.85, CFI = .96, TLI = .91, SRMR = .027, RMSEA (90% CI) = .128 (.083, .176), three items suffered large cross-loadings (λ > .30), leaving two items primarily loading onto each factor, which was unacceptable. Therefore, the unidimensional structure of the AAQ-II was deemed to be the most appropriate.

Based on the standardized factor loadings, a moderate to high composite reliability (ρ = .89) was achieved. The interitem correlation was from .37 to .69, falling within the recommended range of .15 to .50 (Clark & Watson, 1995). The corrected item–total correlation of the AAQ-II items was from .60 to .77. Taken together, these data support the reliability of the seven-item unidimensional model from an item-level perspective.

Study 2

Method

Participants and Procedure

The participants were 366 Chinese college students (232 females and 134 males) who attended PE courses at a Hong Kong public university. The average age was 20.32 years (SD = 1.22; range = 18–25 years).

The packages of questionnaires were administrated in a teaching venue in a single session taking approximately 15 minutes. Written informed consent was collected from all students, who were informed of their voluntary role in completing the questionnaire, as well as the confidentiality of the data handling. Four cohorts, of 85 college students, were randomly selected from 17 cohorts (small classes), to complete the AAQ-II again over a one-month interval assessing the test–retest reliability.

Measurements

The Chinese-translated seven-item AAQ-II (Bond et al., 2011), as outlined in Study 1, was used.

The MAAS (Brown & Ryan, 2003) is a unidimensional scale with 15 items measuring levels of awareness or attention. These items are rated on a 6-point Likert-type scale from 1 (almost always) to 6 (almost never), and higher scores indicate more mindfulness. The MAAS has good internal consistency (α =.82) and good test–retest reliability over a one-month time period (r = .81). A translated version of the MAAS demonstrated adequate reliability and validity among a Chinese student sample (Deng et al., 2012).

The Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988) is a 20-item scale, with 10 positive and 10 negative affective descriptors that has demonstrated sound internal consistency and convergent and discriminant validity. Participants rated their feelings concerning the affective descriptors during the previous week. Responses were scored on a 5-point Likert-type scale from 1 (very slightly or not at all) to 5 (extremely). Higher scores on the two dimensions of positive and negative affect indicate higher levels of positive and negative affect, respectively. A Chinese translation of the PANAS demonstrated adequate reliability and validity among a Chinese sample (Huang, Yang, & Ji, 2003).

The Satisfaction with Life Scale (SWLS; Diener, Emmons, Larsen, & Griffin, 1985) is a five-item measure that is widely used to represent the cognitive evaluation of subjective well-being. All items on the SWLS are scored on 7-point Likert-type scale (1 = strongly disagree to 7 = strongly agree). A translated version of the SWLS demonstrated adequate reliability and validity among a Chinese sample (Xiong & Xu, 2009).

The State–Trait Anxiety Inventory (STAI; Spielberger, Gorsuch, Lushene, Vagg, & Jacobs, 1983) is a 40-item self-report instrument that consists of a 20-item state anxiety scale and a 20-item trait anxiety scale. It measures both state and trait anxiety using a 4-point Likert-type scale (1 = not at all to 4 = very much so). A translated version of the STAI demonstrated adequate reliability and validity among a Chinese sample (Li & Qian, 1995). Only the trait anxiety scale inventory (TAI) was used in the current study since our aim was to explore a stable relationship between EA and anxiety.

The short form Beck Depression Inventory (BDI-13; Beck & Beamesderfer, 1974) assesses the current severity of depression symptoms.¹ The 13 items are rated on a 4-point scale (from 0 to 3) with possible total scores ranging from 0 to 39 and higher scores indicating greater severity. A translated version of the BDI-13 demonstrated adequate reliability and validity among a Chinese sample (Zheng & Zheng, 1987).

Data Analysis

Confirmatory factor analysis (CFA) was conducted to test the factor structure of the AAQ-II using Mplus 7 (Muthén & Muthén, 1998–2012). Identical to Study 1, four model fit indices (i.e., CFI, TLI, SRMR, and RMSEA) were used to evaluate the models. The intraclass correlation coefficient (ICC) was used to estimate the test–retest reliability index of the AAQ-II.

Results

Factor Structure of the AAQ-II in Chinese College Students

The skewness and kurtosis ranged between −1 and 1 indicating that the data are univariately normally distributed. A maximum-likelihood CFA was conducted using Mplus 7 to verify the unidimensional AAQ-II. A marginal fit was shown but indicated room for improvement, χ²(14) = 117.66, CFI = .91, TLI = .87, SRMR = .051, RMSEA (90% CI) = .142 (.119, .167). After adding the residual covariance between Items 1 and 4, the goodness-of-fit statistics improved substantially, reaching a satisfactory level except for the RMSEA, χ²(13) = 77.55, CFI = .95, TLI = .91, SRMR = .043, RMSEA (90% CI) = .116 (.092, .142). All the AAQ-II items loaded significantly (p < .001) on the factor, with completely standardized loadings ranging from .55 to .81(see Table 1).

Table 1.

Item Means (M), Standard Deviations (SD), Factor Loadings (FL), and Skewness and Kurtosis Values of the AAQ-II in Chinese College Students (Study 2).

English Item Original and Chinese Translation	M	SD	FL	Skewness	Kurtosis
1. My painful experiences and memories make it difficult for me to live a life that I would value	3.21	1.15	.55	.16	−.11
痛苦的經驗和記憶讓我很難去過一種我覺得有價值的生活	3.21	1.15	.55	.16	−.11
2. I’m afraid of my feelings	3.40	1.19	.70	.17	−.37
我自己的感覺讓我感到害怕	3.40	1.19	.70	.17	−.37
3. I worry about not being able to control my worries and feelings	3.63	1.29	.81	.20	−.35
我擔心無法控制自己的憂慮和感受	3.63	1.29	.81	.20	−.35
4. My painful memories prevent me from having a fulfilling life	3.07	1.20	.73	.39	−.15
痛苦的記憶阻礙我擁有充實的生活	3.07	1.20	.73	.39	−.15
5. Emotions cause problems in my life	3.41	1.34	.79	.30	.01
情緒給我的生活帶來問題	3.41	1.34	.79	.30	.01
6. It seems like most people are handling their lives better than I am	3.57	1.38	.66	.35	−.27
好像大多數人都能夠比我更好地處理自己的生活	3.57	1.38	.66	.35	−.27
7. Worries get in the way of my success	3.54	1.30	.72	.33	−.05
憂慮阻礙我的成功	3.54	1.30	.72	.33	−.05

Note. Items © 2011 by the Association for Behavioral and Cognitive Therapies. Reprinted with permission of the publisher. All factor loadings are statistically significant at p < .001. AAQ-II = Acceptance and Action Questionnaire–II.

Internal Consistency and Test–Retest Reliability of the AAQ-II in Chinese College Students

Based on the standardized factor loadings of the final solution, the composite reliability of the AAQ-II was ρ = .88, indicating satisfactory reliability. The test–retest reliability for the AAQ-II using ICC was adequate (r = .86; p < .01).

Nomological Validity of the AAQ-II in Chinese College Students: Correlations Between the AAQ-II and Other Measures

The results of nomological validity of the AAQ-II in Chinese college students are summarized in Table 2. As predicted, the AAQ-II scores significantly negatively correlated with scores on MAAS, suggesting that higher levels of EA are associated with lower levels of mindfulness; AAQ-II significantly negatively correlated with both measures of positive affect and life satisfaction, suggesting that individuals with positive affect and high satisfaction with life also tend to possess lower levels of EA. The negative affect, anxiety, and depression were significantly positively correlated with AAQ-II, suggesting that higher levels of EA may also be an indication of psychological disorders.

Table 2.

Means (M), Standard Deviations (SD), and Cronbach’s α coefficients of All the Measures and Pearson’s Correlations Between the AAQ-II and Other Measures in Chinese College Students (Study 2).

Scales	M	SD	Cronbach’s α	AAQ-II
AAQ-II	23.83	6.72	.88	—
PANAS–PA	28.78	6.18	.83	−.15***
PANAS–NA	26.38	7.07	.85	.54***
MAAS	3.81	.61	.83	−.39***
SWLS	22.37	5.28	.85	−.41***
TAI	47.69	7.73	.85	.60***
BDI	8.07	6.33	.89	.51***

Note. AAQ-II = Acceptance and Action Questionnaire–II; PANAS = Positive and Negative Affect Schedule; PA = positive affect; NA = negative affect; MAAS = Mindful Attention Awareness Scale; SWLS = Satisfaction with Life Scale; TAI = Trait Anxiety Inventory; BDI = Beck Depression Inventory.

***

p < .001.

Incremental Validity of the AAQ-II in Chinese College Students

Results from the hierarchical multiple regressions, examining the incremental validity of the AAQ-II, are presented in Table 3. The AAQ-II explained a significant portion of variance, beyond the contribution of MAAS, in positive affect, negative affect, subjective well-being, anxiety, and depression. The reversed hierarchical analyses mainly revealed the same results, in that, the MAAS adds unique explained variance, beyond AAQ-II, in explaining negative affect, well-being, anxiety, and depression, except for positive affect; the MAAS did not explain additional variance beyond AAQ-II. Therefore, results suggest that the MAAS and the AAQ-II are both uniquely related to positive affect, negative affect, subjective well-being, anxiety, and depression.

Table 3.

Hierarchical Regression Analysis for Positive Affect (PA), Negative Affect (NA), Well-Being (SWLS), Anxiety (TAI), and Depression (BDI) With Mindfulness (MAAS) and Experiential Avoidance (AAQ-II) in Chinese College Students (Study 2).

	Step 1		Step 2
Dependent Variables and Predictors	Beta	Adjusted R²	Beta	Adjusted R²
PA
MAAS	.15**		.10
AAQ-II			−.11*
		.02**		.03*
NA
MAAS	−.37***		−.12***
AAQ-II			.47***
		.13***		.32***
SWLS
MAAS	.27***		.13*
AAQ-II			−.36***
		.07***		.18***
TAI
MAAS	−.51***		−.33***
AAQ-II			.47***
		.26***		.45***
BDI
MAAS	−.35***		−.18***
AAQ-II			.44***
		.12***		.28***

Note. PANAS = Positive and Negative Affect Schedule; PA = positive affect; NA = negative affect; MAAS = Mindful Attention Awareness Scale; SWLS = Satisfaction with Life Scale; TAI = Trait Anxiety Inventory; BDI = Beck Depression Inventory; AAQ-II = Acceptance and Action Questionnaire–II.

p < .05. **p < .01. ***p < .001.

Factorial Invariance of the AAQ-II in Chinese College Students

A sequential model testing approach was employed, via multisample CFA, to examine whether the AAQ-II displayed invariance across gender (see Dimitrov, 2010). As can be seen in Table 4, the chi-square differences between increasingly constrained models are all not statistically significant, thus indicating the measurement (weak, strong, and strict) and structural invariance across male and female college students. Further support came from the change to the CFI ≥ −.01 (Cheung & Rensvold, 2002), between increasingly constrained models across male and female students.

Table 4.

Testing for Factorial (Measurement and Structural) Invariance of the AAQ-II Across Male and Female Students (Study 2).

Model	χ²	df	Model Comparison	Δ χ²	Δ df	CFI	Δ CFI^a	RMSEA
M0	90.666	26				.945		.117
M1	94.086	32	M1–M0	3.42	6	.948	.003	.103
M2	102.171	38	M2–M1	8.085	6	.946	−.002	.096
M3	114.652	45	M3–M2	12.481	7	.941	−.005	.092
M4	102.923	40	M4–M2	.752	2	.947	.001	.093

Note. AAQ-II = Acceptance and Action Questionnaire–II; χ² = conventional chi-square fit statistic (under maximum-likelihood estimation); CFI = comparative fit index; RMSEA = root mean square error of approximation; M0 = baseline model (no invariance imposed); M1 = invariant factor loadings; M2 = invariant factor loadings and invariant intercepts; M3 = invariant factor loadings, invariant intercepts, and invariant residual variances; M4 = invariant slopes, invariant intercepts, and invariant factor variances.

ΔCFI ≤ −.01 signals lack of invariance targeted by the respective comparison of nested models (Cheung & Rensvold, 2002).

Study 3

Method

Participants and Procedure

Participants were 330 elite Chinese athletes (177 females and 153 males) aged between 12 and 27 years (M = 18.67 years, SD = 3.1), who were recruited from three provincial sports training centers in China. Athletes were involved in both individual sports (n = 209), such as archery, athletics, badminton, fencing, gymnastics, rowing, shooting, swimming, table tennis, tennis, weight lifting, wrestling, and wushu, and team sports (n = 11) such as basketball, handball, and water polo.

Convenience sampling was used to recruit participants for this study. Coaches and team managers were contacted directly, and the purpose and nature of the study was explained to acquire permission for approaching the athletes. A package of questionnaires, taking approximately 10 minutes to complete, was administered prior to, or after, their regular training sessions. Written informed consent was collected from all athletes, who were informed of their voluntary role in completing the questionnaire, as well as the confidentiality of the data handling. Adopting a convenience sampling method, 27 athletes from two sports were invited to complete the AAQ-II again one month after the first assessment to evaluate the test–retest reliability of the AAQ-II.

Measurements

The Chinese-translated seven-item AAQ-II (Bond et al., 2011) as outlined in Study 1, was used.

The Training and Competition Well-being Scale (TCWS; Zhang & Liang, 2002) is a six-item scale used to assess Chinese athletes’ subjective well-being in their training and competitions. All items on the TCWS are scored on 7-point Likert-type scale (1 = strongly disagree to 7 = strongly agree). The internal consistency of the TCWS is α = .75.

The Sport Competition Anxiety Test (SCAT; Martens, Vealey, & Burton, 1990) is a 15-item self-report instrument measuring one’s tendency to perceive competitive situations as threatening. The SCAT uses a 3-point Likert-type scale (i.e., hardly ever, sometimes, and often) and has an internal consistency of approximately .89 for females and .88 for males (Ostrow & Ziegler, 1978). A translated version of the SCAT demonstrated adequate reliability and validity among a Chinese athletic sample (Zhu, 1993).

The abbreviated Profile of Mood States inventory (POMS; Grove & Prapavessis, 1992) is a well-validated 40-item tool. It has seven subscales: anger, confusion, depression, esteem, fatigue, tension, and vigor. Five of the subscales (i.e., anger, confusion, depression, fatigue, and tension) reflect negative moods and two (i.e., esteem and vigor) identify positive moods. The abbreviated POMS uses a 5-point Likert-type scale (0 = not at all to 4 = extremely) and has an average internal consistency of .80. A translated version of the abbreviated POMS demonstrated adequate reliability and validity among a Chinese athletic sample (Zhu, 1992).

Data Analysis

Data analysis was identical to that of Study 2.

Results

Factor Structure of the AAQ-II in Elite Chinese Athletes

As the data are univariately normally distributed, a maximum-likelihood CFA was conducted to further verify the unidimensional AAQ-II in athletic population. Results of the CFA suggested a relatively good fit to the data but indicated room for improvement, χ²(14) = 62.39, CFI = .94, TLI = .92, SRMR = .04, RMSEA (90% CI) = .102 (.077, .129). An excellent fit to the data was produced after adding the residual covariance between Items 2 and 3, and Items 1 and 4, χ²(12) = 29.99, CFI = .98, TLI = .96, SRMR = .03, RMSEA (90% CI) = .067 (.037, .098). Items of the AAQ-II final solution loaded significantly (p < .01) on the factor, with completely standardized loadings ranging from .60 to .75.

Internal Consistency and Test–Retest Reliability of the AAQ-II in Elite Chinese Athletes

Based on the standardized factor loadings of the final solution, the composite reliability of the AAQ-II in the athletic population was p = .85, indicating satisfactory reliability. The test–retest reliability for the AAQ-II in the athletic population using ICC was adequate (r = .74; p < .001).

Nomological Validity of the AAQ-II in Elite Chinese Athletes: Correlations Between the AAQ-II and Other Measures

The results of nomological validity of the AAQ-II in elite Chinese athletes are summarized in Table 5. As predicted, the AAQ-II scores significantly negatively correlated with scores on esteem, vigor, and well-being suggesting that athletes with positive mood and high satisfaction with life also tend to act with lower levels of EA. Anger, confusion, depression, fatigue, tension, and anxiety were significantly positively correlated with the AAQ-II suggesting that higher levels of EA are also related to mood disturbance.

Table 5.

Means (M), Standard Deviations (SD), and Cronbach’s α coefficients of All the Measures and Pearson’s Correlations Between the AAQ-II and Other Measures in Elite Chinese Athletes (Study 3).

Scales	M	SD	Cronbach’s α	AAQ-II
AAQ-II	21.90	7.80	.86	—
POMS–Anger	6.53	5.39	.87	.40***
POMS–Confusion	5.47	3.46	.73	.48***
POMS–Depression	5.46	4.35	.80	.48***
POMS–Esteem	7.75	3.29	.67	−.16***
POMS–Fatigue	7.81	3.88	.75	.28***
POMS–Tension	6.93	4.23	.76	.49***
POMS–Vigor	10.88	4.46	.82	−.23***
TCWS	23.32	6.12	.69	−.36***
SCAT	19.21	3.58	.74	.46***

Note. AAQ-II = Acceptance and Action Questionnaire–II; POMS = abbreviated Profile of Mood States; TCWS= Training and Competition Well-being Scale; SCAT= Sport Competition Anxiety Test.

***

p < .001.

Factorial Invariance of the AAQ-II in Elite Chinese Athletes

A sequential-model testing approach, identical to those of Study 2, was employed, via multisample CFA, to examine whether the AAQ-II displayed invariance across gender and age group, in elite Chinese athletes. The athletes were divided into two age-groups, namely, adolescent (<18 years) and adult (≥18 years). For male and female athletes, the changes in chi-square were not significant, and the changes in CFI were less than −.01. Therefore, it can be concluded that the model is invariant between increasingly constrained models across male and female athletes. For adolescent and adult athletes, the partial factorial invariance of the AAQ-II was supported, with the factor loading and residual variances of Item 1 freely estimated (see Table 6).

Table 6.

Testing for Factorial (Measurement and Structural) Invariance of the AAQ-II Across Male and Female Athletes and Across Adolescent and Adult Athletes (Study 3).

Model	χ²	df	Model Comparison	Δχ²	Δdf	CFI	ΔCFI^a	RMSEA
Gender
M0	50.653	24				.968		.082
M1	61.430	30	M1–M0	10.777	6	.963	−.005	.080
M2	73.092	36	M2–M1	11.662	6	.956	−.007	.079
M3	79.969	43	M3–M2	6.877	7	.956	0	.072
M4	77.371	39	M4–M2	4.279	3	.955	−.001	.077
Age-group
M0	50.653	24				.968		.082
M1	66.780	30	M1–M0	16.127*	6	.958	−.01	.086
M1P	51.778	29	M1P–M0	1.125	5	.974	.006	.069
M2	58.190	35	M2–M1P	7.537	6	.974	0	.063
M3	75.388	42	M3–M2	17.198*	7	.962	−.012	.069
M3P	67.572	41	M3P–M2	9.382	6	.970	−.004	.063
M4	60.770	38	M4–M2	2.58	3	.974	.0	.060

Note. AAQ-II = Acceptance and Action Questionnaire–II; χ² = conventional chi-square fit statistic (under maximum-likelihood estimation); CFI = comparative fit index; RMSEA = root mean square error of approximation; M0 = baseline model (no invariance imposed); M1 = invariant factor loadings; M1P = partially invariant factor loadings (free factor loading of Item 1); M2 = invariant factor loadings and invariant intercepts; M3 = invariant factor loadings, invariant intercepts, and invariant residual variances; M3P = invariant factor loadings, invariant intercepts, and partially invariant residual variances (free residual variances of Item 1); M4 = invariant slopes, invariant intercepts, and invariant factor variances.

ΔCFI ≤ −.01 signals lack of invariance targeted by the respective comparison of nested models (Cheung & Rensvold, 2002).

p < .05.

Discussion

The AAQ-II was developed by Bond et al. (2011) to assess EA as conceptualized within ACT (Hayes et al. 1999). The current study was designed to examine the psychometric properties of the Chinese version of the seven-item AAQ-II among Chinese college students and elite Chinese athletes. A single-factor structure of the AAQ-II was found through the EFA and was further confirmed by two independent confirmatory factor analyses. The internal consistency, test–retest reliability, nomological validity, incremental validity of the AAQ-II on well-being, and positive and negative affect, beyond the contribution of the MAAS, factorial invariance across gender, and partial factorial invariance across adolescent and adult athletes were supported.

The reliability and validity of the Chinese version of the seven-item AAQ-II is satisfactory. With the single-factor structure supported in the current study, the internal consistency reliability of the translated version of the seven-item AAQ-II was adequate for both Chinese college students (ρ = .88) and athletes (ρ = .85). The test–retest reliability found in the current study indicated that the total score of the AAQ-II was relatively stable across an average period of one month for both college students (r = .86) and athletes (r = .74). This finding is in line with Bond et al. (2011) who have shown that the AAQ-II total score is reasonably stable across periods of 3 months (r = .81) and 12 months (r = .79). With regard to the nomological validity of the AAQ-II in both Chinese college students and elite Chinese athletes, it was found to be strongly and positively correlated with measures tapping different forms of psychological maladjustment, including symptoms of anxiety, depression, and negative affect, and negatively associated with mindfulness, life satisfaction, and positive affect. These findings are consistent with that of previous research (Bond et al., 2011; Fledderus et al., 2012; Gloster et al., 2011). Consistent with the findings of previous literature (Fledderus et al., 2012; Gloster et al., 2011), the AAQ-II explained a significant proportion of variance in positive and negative affect and subjective well-being beyond the contribution of mindfulness in Chinese college students. This justifies the use of the Chinese version of the AAQ-II in mindfulness and acceptance-based intervention studies. The findings of the current study corroborate with findings from previous studies to confirm that the AAQ-II, as a measure of EA, is a psychometrically sound inventory and significantly related to counseling relevant variables (e.g., depression, anxiety, positive and negative affect, and subjective well-being). Furthermore, it may suggest that EA is a universal construct that may be conceptually equal across cultures. Nonetheless, future research should investigate further as to whether EA is a universal construct, through analyzing the cross cultural differences for item-level statistics (e.g., interitem correlations, item–total correlations, and internal consistencies) and composite score level (e.g., means, standard deviations), and by confirming the unidimensionality of the internal structure through multigroup confirmatory factor analyses, and by providing further evidence of validity that is in line with the ACT model and previous research (Hayes et al., 2006, 2013).

The demonstration of factorial invariance across gender in both samples, as well as partial factorial invariance across age-related groups, has made an original contribution to the existing literature. Therefore, it is suggested that EA maintains its structure and meaning equivalent across gender and age when measured using the AAQ-II. In other words, we can conclude that the items share similar meaning across males and females, as well as across adolescent and adult athletes. In addition, the inclusion of adolescent athletes in the current study extends the methodological considerations of previous studies, regarding the psychometric properties of the AAQ-II, since the validation of the AAQ-II has yet to be examined in an adolescent population (e.g., Bond et al., 2011; Fledderus et al., 2012; Gloster et al., 2011). Importantly, the invariance results may guide future use of the AAQ-II in Chinese, in general and sporting contexts. For example, the AAQ-II can be applied to a greater range of athletes, and the meaningful comparison of the means between adolescent and adult athletes is warranted. Given that gender invariance and partial age-related invariance have been established in Chinese college students and elite Chinese athletes, and the original AAQ-II has been translated into German, Dutch, and Italian, future research should examine the factorial invariance of the AAQ-II across populations.

The present study has several limitations. First, it is possible that the AAQ-II might suffer item contents overlap since the between-item residual covariances were revealed for both Chinese college students and elite Chinese athletes. Future research should be conducted to examine the construct validity of the AAQ-II. Second, as the samples consisted of Chinese college students and elite Chinese athletes, the results are limited to be generalized to other general adult populations (e.g., people with low education) and clinical populations. As EA is related to many psychological disorders, it is necessary to examine the factor structure in a clinical Chinese population. Third, the predominantly individual sport athletes preclude the examination of invariance across individual and team sport athletes. Caution should be taken when extrapolating the findings to team sport athletes. Finally, the discriminative validity of the AAQ-II with other similar constructs has not been investigated, such as coping (Karekla & Panayiotou, 2011) and thought suppression. Therefore, further research is warranted to examine whether EA is a unique or overlapping construct in predicting subjective well-being and psychological distress.

Notwithstanding these limitations, the current study has provided important information about the psychometric properties of the Chinese version of the AAQ-II. The results are consistent with that of the earlier studies that examined the psychometric properties of the AAQ-II (Bond et al., 2011; Fledderus et al., 2012; Gloster et al., 2011; Pennato et al., 2013). The current study has not only provided the empirical evidence of a reliable and valid instrument to measure EA for experimental and interventional studies but also offered possibilities for research to examine the utility of the AAQ-II for cross-cultural comparison. Overall, it suggests that the Chinese version of the seven-item AAQ-II is a useful tool for exploring EA in large population-based studies.

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) received no financial support for the research, authorship, and/or publication of this article.

Notes

Author Biographies

Chun-Qing Zhang is a doctoral candidate of Sport & Exercise Psychology at the Hong Kong Baptist University. His current research interests include mindfulness- and acceptance- based therapies, emotion regulation, self-control, and exercise behaviour.

Pak-Kwong Chung is professor of Department of Physical Education, Hong Kong Baptist University. His research interest is in sport psychology, health and fitness.

Gangyan Si is associate professor of Sport & Exercise Psychology at the Hong Kong Institute of Education. His research interests include applied sport psychology service, cultural sport psychology, exercise psychology, and mindfulness- and acceptance- based therapies.

Jing Dong Liu is a postdoctoral fellow at the Hong Kong Baptist University. His research interests include sport and exercise psychology, behaviour change, and school psychology.

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