2021
DOI: 10.1080/10503307.2021.2001070
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Exploring Therapist Self-Efficacy Change Profiles Using Latent Growth Curve Analysis

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Cited by 5 publications
(16 citation statements)
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“…The main data analyses composed of three parts. First, we tested the LGCM with the full sample to examine the initial intercepts and growth slopes for the HS, SM, and CH subscales, as was done in Li, Wu, et al (2022). Second, accounting for the individual differences, we utilized the GMM analyses to identify latent classes of therapist trainees who might have different profiles of CSE initial levels and change trends.…”
Section: Methodsmentioning
confidence: 99%
See 4 more Smart Citations
“…The main data analyses composed of three parts. First, we tested the LGCM with the full sample to examine the initial intercepts and growth slopes for the HS, SM, and CH subscales, as was done in Li, Wu, et al (2022). Second, accounting for the individual differences, we utilized the GMM analyses to identify latent classes of therapist trainees who might have different profiles of CSE initial levels and change trends.…”
Section: Methodsmentioning
confidence: 99%
“…We constructed the same LGCM (Figure 1, Panel a) as in Li, Wu, et al (2022) with the full sample to examine the initial level and growth trend for the HS, SM, and CH subscales of CASES. The latent intercepts of i_HS, i_SM, and i_CH represented the initial level of HS, SM, and CH at T1 (the beginning of the practicum), and the latent slopes of s_HS, s_SM, and s_CH quantified the extent of linear increases from T1 to T2 and T2 to T3 for the three subscales.…”
Section: Main Analysesmentioning
confidence: 99%
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