Table 1
ESEM and CFA Factor Solutions of 20-Item ASQ.
| Factor loadings | |||
|---|---|---|---|
| Items | Concealing | Adjusting | Tolerating |
| Concealing | |||
| C1 People usually can’t tell how I am feeling inside. | 0.439/0.188 | –0.301 | 0.040 |
| C2 I often suppress my emotional reactions to things. | 0.352/0.395 | –0.092 | 0.266 |
| C3 I am good at hiding my feelings. | 0.732/0.677 | 0.066 | –0.023 |
| C4 People usually can’t tell when I am upset. | 0.605/0.541 | –0.036 | 0.042 |
| C5 People usually can’t tell when I am sad. | 0.616/0.572 | 0.032 | –0.010 |
| C6 I can act in a way that people don’t see me being upset. | 0.635/0.708 | 0.115 | 0.069 |
| C7 I could easily fake emotions. | 0.403/0.552 | 0.189 | 0.057 |
| C8 I can hide my anger well if I have to. | 0.347/0.680 | 0.433 | 0.001 |
| Adjusting | |||
| A1 I have my emotions well under control. | 0.280 | 0.332/0.639 | 0.257 |
| A2 I can avoid getting upset by taking a different perspective on things. | 0.308 | 0.115/0.544 | 0.375 |
| A3 I am able to let go of my feelings. | –0.181 | 0.175/0.363 | 0.501 |
| A4 I can calm down very quickly. | 0.150 | 0.574/0.693 | 0.149 |
| A6 I know exactly what to do to get myself into a better mood. | 0.000 | 0.723/0.719 | 0.083 |
| A7 I can get into a better mood quite easily. | –0.082 | 0.883/0.782 | 0.057 |
| Tolerating | |||
| T1 I can tolerate having strong emotions. | 0.343 | 0.353 | 0.227/0.694 |
| T2 It’s ok if people see me being upset. | –0.149 | –0.026 | 0.525/0.237 |
| T3 It’s ok to feel negative emotions at times. | 0.044 | –0.109 | 0.645/0.372 |
| T4 I can tolerate being upset. | 0.191 | 0.384 | 0.339/0.692 |
| T5 There is nothing wrong with feeling very emotional. | –0.131 | 0.008 | 0.622/0.339 |
[i] Note. Factor loadings of the ESEM solution appear before the slash and factor loadings of the ICM-CFA solution after the slash. All parameters are completely standardized. The ICM-CFA model has an independent cluster structure in which each of the ASQ items is allowed to load on only one single latent factor and all non-target loadings are constrained to be zero. For clarity, these ICM-CFA non-target zero loadings are not displayed.
Table 2
Summary of Goodness-of-Fit Statistics for the Models Tested.
| Scale | Model | χ2 | df | χ2/df | p(χ2) | CFI | TLI | RMSEA | 90% CI RMSEA |
|---|---|---|---|---|---|---|---|---|---|
| 20-Item ASQ | ICM-CFA | 3992.361 | 167 | 23.906 | 0.000 | 0.761 | 0.728 | 0.120 | [0.116, 0.123] |
| 20-Item ASQ | ESEM | 1930.925 | 133 | 14.518 | 0.000 | 0.888 | 0.840 | 0.092 | [0.088, 0.096] |
| 16-Item ASQ | ICM-CFA | 1724.249 | 101 | 17.072 | 0.000 | 0.860 | 0.834 | 0.100 | [0.096, 0.104] |
| 16-Item ASQ | ESEM | 555.691 | 75 | 7.409 | 0.000 | 0.959 | 0.934 | 0.063 | [0.058, 0.068] |
| 16-Item ASQ | ESEM MI | 767.954 | 240 | 3.200 | 0.000 | 0.954 | 0.954 | 0.053 | [0.048, 0.057] |
[i] Note. ICM-CFA = independent clusters model – confirmatory factor analysis; ESEM = exploratory structural equations modeling; MI = measurement invariance across genders; CFI = comparative fit index; TLI = Tucker-Lewis Index; RMSEA = root mean square error of approximation; 90% CI RMSEA = 90 percent confidence interval RMSEA.
Table 3
ESEM (and ICM-CFA) Factor Correlations for the 20-Item and 16-Item ASQ.
| Factor correlations | |||
|---|---|---|---|
| 20-Item ASQ | |||
| Factor | Concealing | Adjusting | Tolerating |
| Concealing | 1.00/1.00 | 0.57/0.54 | 0.60/0.20 |
| Adjusting | 0.25/0.22 | 1.00/1.00 | 0.93/0.39 |
| Tolerating | 0.18/0.14 | 0.33/0.26 | 1.00/1.00 |
[i] Note. ICM-CFA factor correlations appear above the diagonal, ESEM factor correlations below the diagonal. Numbers before the slash indicate factor correlations of the 20-item ASQ, numbers after the slash of the 16-item ASQ.
Table 4
ESEM and CFA Factor Solutions of 16-Item ASQ.
| Factor loadings | |||
|---|---|---|---|
| Items | Concealing | Adjusting | Tolerating |
| Concealing | |||
| C1 People usually can’t tell how I am feeling inside. | 0.444/0.224 | –0.295 | 0.084 |
| C2 I often suppress my emotional reactions to things. | 0.327/0.353 | –0.039 | 0.216 |
| C3 I am good at hiding my feelings. | 0.713/0.678 | 0.090 | –0.027 |
| C4 People usually can’t tell when I am upset. | 0.622/0.561 | –0.024 | 0.056 |
| C5 People usually can’t tell when I am sad. | 0.626/0.590 | 0.033 | 0.015 |
| C6 I can act in a way that people don’t see me being upset. | 0.647/0.715 | 0.127 | 0.102 |
| C7 I could easily fake emotions. | 0.418/0.543 | 0.205 | 0.039 |
| C8 I can hide my anger well if I have to. | 0.354/0.665 | 0.431 | 0.037 |
| Adjusting | |||
| A1 I have my emotions well under control. | 0.213 | 0.341/0.522 | 0.146 |
| A4 I can calm down very quickly. | 0.157 | 0.576/0.677 | 0.093 |
| A5 I can get out of a bad mood very quickly. | 0.093 | 0.611/0.713 | 0.159 |
| A6 I know exactly what to do to get myself into a better mood. | 0.022 | 0.722/0.761 | 0.108 |
| A7 I can get into a better mood quite easily. | –0.060 | 0.886/0.838 | 0.092 |
| Tolerating | |||
| T2 It’s ok if people see me being upset. | –0.137 | 0.029 | 0.441/0.385 |
| T3 It’s ok to feel negative emotions at times. | 0.085 | –0.052 | 0.594/0.644 |
| T5 There is nothing wrong with feeling very emotional. | –0.199 | 0.015 | 0.748/0.693 |
[i] Note. Factor loadings of the ESEM solution appear before the slash and factor loadings of the ICM-CFA solution after the slash. All parameters are completely standardized. The ICM-CFA model has an independent cluster structure in which each of the ASQ items is allowed to load on only one single latent factor and all non-target loadings are constrained to be zero. For clarity, these ICM-CFA non-target zero loadings are not displayed.