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longitudinal analysis of covid-19 anxiety and mental well-being during lockdown ...
included answers 1 and 2 from Inner and/or Body exercises) and 0 (not prac-
ticing mindfulness, which included answers 3, 4, and 5).
2.3 Procedure
The COVID-19 epidemic in Slovenia was first declared on the 12th of March
2020, and most restrictive measures were put into effect on the 16th of
March 2020 (e.g., closing of schools; cancelling public transport; closing of
non-essential service activities such as bars and restaurants; limiting the
movement of people outside the municipality of residence; closure of coun-
try borders). The epidemic lasted until the 15th of May 2020. The study be-
gan at the peak of the restrictive measures in effect during the first lock-
down in Slovenia. The restrictive measures were unchanged for the first
two weeks of the study, and then they were gradually loosened (e.g., re-
moving the limit on movement outside municipalities, reopening some
non-essential service activities such as hairdressers and restaurants, and
opening public transport, but schools remained closed, as did the coun-
try’s borders). The first measurement (T1) started on the 8th of April 2020.
After completing the questionnaire battery at T1, participants were asked
if they were willing to participate in follow-up questionnaires, and those
who agreed left their email addresses (stored separately from the respons-
es to provide anonymity), to receive the questionnaire battery again. Par-
ticipants received the follow-up batteries in seven-day intervals upon com-
pletion of T1; meaning that there is some overlap between the time waves
depending on when the participant completed the survey for the first time.
Data collection at the fourth measurement (T4) ended on the 13th of May
2020, before the end of the first epidemic. Participants with completed data
from at least two measurements are included in the analyses. Consent for
data collection was indicated by reading a description of the study and con-
tinuing to fill out the questionnaire battery.
2.4 Data analysis
After examining the descriptive statistics, correlations and reliabilities us-
ing IBM SPSS Statistics 27, the raw data was plotted, and the trajectories
suggested linear changes over time. We employed the latent growth curve
(LGC) models to examine the longitudinal change over time using Mplus
(Version 8.5). A robust maximum likelihood (MLR) algorithm was used to
handle missing data and assess parameters in the model. We retained all
participants in the analyses when using the maximum likelihood algori-
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