<p>An online
questionnaire was distributed to the target population (<i>N </i>= ~2000); 226 completed forms were received from respondents Missing values in all variables did not exceed
6% of cases. Missing data analysis was then followed with Little’s (1988) missing
completely at random test. The results were not significant, χ<sup>2</sup> (59)
= 73.340, <i>p</i> = .099, suggesting that
the values were missing entirely by chance. Thus, the missing values in the
dataset were estimated with the expectation–maximization algorithm. To examine
outliers among cases, data were evaluated for univariate and multivariate outliers
by examining Mahalanobis
distance for each participant. An outlier was defined as a Mahalanobis score
that was over than Mahal. Critical score cv = 55.32; univariate or
multivariate outliers were 31 cases with 13% (Tabachnik &
Fidell, 2013, McLachlan GJ. (1999).</p>
<p> </p>
<p>There were 16 face-to-face interviews with healthcare workers from several hospitals and medical centers in Jordan in which COVID-19 treatment was provided during the pandemic. Given that recalling these traumatic experiences might be traumatic for some HCWs, all interviews were conducted by experienced health social workers. The interviews were conducted in Arabic, and the interview transcripts were subsequently translated to English to facilitate reporting. The information obtained through interviews was subjected to thematic analysis, which consisted of six phases: familiarization, coding, searching for themes, reviewing themes, defining and naming themes, and writing up (Braun & Clarke, 2006). The 16 HCWs that took part in the interviews were predominantly female (<em>n</em> =10, 62.5%), worked as nurses (<em>n</em> =10, 62.5%), and were single (<em>n</em> = 7, 43.8%),</p>
Data was collected from a sample of Jordanian citizens who refused or are reluctant to take the Coronavirus COVID-19 Vaccine.<div><p><br></p><p><b></b></p></div>
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