Page 169 - Ana Mlekuž in Igor Ž. Žagar, ur. • Raziskovanje v vzgoji in izobraževanju: Izobraževanje učiteljic in učiteljev za raziskovalno učenje in poučevanje. Ljubljana: Pedagoški inštitut, 2024. Digitalna knjižnica, Dissertationes 48

longitudinal analysis of covid-19 anxiety and mental well-being during lockdown ...
3.1 Descriptive Results
Means, standard deviations and correlations between the scales used at
four time-points (mental well-being, COVID-19 anxiety) and the time-in-
variant covariates (emotional self-efficacy, practicing mindfulness) are pre-
sented in Table 27. The descriptive statistics for mental well-being show that
participants reported a gradual increase in levels of mental well-being from
T1 to T3, followed by a decrease at T4, while the levels of COVID-19 anxie-
ty decreased from T1 to T4. Skewness and kurtosis values were considered
acceptable for all included variables, and therefore no variables needed to
be transformed.
Mental well-being was positively connected to emotional self-efficacy
at all time-points except for t4, and it was only positively correlated with
practicing mindfulness in T3. COVID-19 anxiety was negatively correlated
with emotional self-efficacy in T1, and was not connected with practicing
mindfulness at all (see Table 27).

Table 27: Descriptive statistics and correlations between mental well-being, COVID-19
anxiety and selected covariates
Emotional Practicing
M SD Skewness Kurtosis
self-efficacy mindfulness
Mental well-being (T1) 3.72 0.59 0.18 -0.89 .69*** .07
Mental well-being (T2) 3.77 0.63 -0.01 0.12 .61*** .21
Mental well-being (T3) 3.91 0.64 -0.51 0.38 .65** .48*
Mental well-being (T4) 3.83 0.82 -1.04 0.04 .40 -.16
COVID-19 anxiety (T1) 2.58 0.96 0.23 -0.72 -.41** .01
COVID-19 anxiety (T2) 2.24 0.82 0.14 -0.94 -.21 .16
COVID-19 anxiety (T3) 1.98 0.73 0.38 0.18 -.23 .03
COVID-19 anxiety (T4) 1.69 0.81 1.08 0.72 .24 .20
M 3.73 0.78
SD 0.61 0.42
Skewness 0.05 -1.38
Kurtosis -0.22 -0.09
Notes: *p < .05, **p < .01, ***p < .001.

3.2 Latent Growth Curve Models

3.2.1 Unconditional LGC models
Unconditional LGC models (measurement model, without covariates)
were used to calculate the intra-individual differences in the growth path

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