The sample size was (n=57) with a 100% response rate. MRI is a highly specialized field and therefore the number of respondents, related to the specialty and working within the study setting, is considerably small.
Of the respondents to the study 53.6 %, n=30 were male and 47.4%, n=27 were female (see Table 3) (see Figure 2).
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84% of the study sample were in the age group 25-44 years (n=48), followed by the age group 45-59 years, n=6, 11% and only three respondents were under age 25 years 5% (see Figure 3).
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3- Years of Experience:
Of the respondents n=26 have 1-5 years of experience 45.6%, representing the largest group, followed by respondents who have 6-10 years of experience, n=14, 24%, followed by 11-20 years of experience, n=11, 19%. Only 2 respondents had more than 20 years of experience, 3.5% (see Figure 4).
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4- Hours of work:
70.2%, n=40 respondents work on a full-time basis with paid overtime, which denotes a shortage in the MRITs in NGHA hospitals. Seventeen respondents work full time with no overtime 29.8% (see Figure 5).
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5- Disability Status:
56 respondents did not have any disabilities 98%, one respondent had a disability 1.8% (see Table 4).
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6- Location of Work:
38 respondents work in NGHA of Riyadh, 67%, representing the highest proportion, followed by 11%, n=6 in Jeddah and Madinah each, n=4 respondents in Dammam, 7% and n=3 respondents in Al-Ahsa 4% (see Figure 6).
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21 respondents did not have responsibilities for dependents 36.8%, n=13 respondents have responsibilities towards school-age children 22.8%, and n=8 respondents have babies and young children 14%. Four respondents 7% have elderly relatives or friend’s dependent on them (see Figure 7).
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Frequencies and percentages for all sociodemographic data were calculated (See Table 5).
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The Level of QWL for MRITs
Mean and standard deviation were calculated for the study responses. The One-Sample T-test was used to identify the degree of QWL for each subscale and identify the overall degree of QWL for MRITs (see Table 6).
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The study sample of MRIT’s was found to have a high level of QWL. The overall mean for study responses was (3.31/5.00); four subscales were statistically significant at the level of (p<0.01). The study responses were higher than the average approval level of (3), which confirms that QWL for MRITs was high (see Table 6) (see Figure 8).
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The highest scores among the six dimensions of WRQoL-2 were found for WCS, followed by GWB, SAW and lastly HWI. All four dimensions were high for MRITs, as the mean for them ranged between 3.28-3.60. The evaluation rate was between 65.6% to 70.2%. All were statistically significant at (p <0.05).
The Level of JCS for MRITs
The One-Sample T-test was conducted for statements 1, 3, 8, 11, 18, 20 as corresponding to JCS on the WRQoL-2 Scale. The mean for the responses was (3.59/5), indicating a high level of JCS for the study sample. This was significantly correlated at (p <0.01). (see Table 7).
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Correlation Between QWL and JCS for MRITs
Using Pearson’s Correlation Coefficient, we found a positive correlation between JCS and the other subscales of WRQoL-2 (GWB, HWI, CAW, WCS and SAW) (see Table 8). There was a statistically significant correlation between JCS and all subscales at the (p <0.01) level. This means that when work conditions, well-being, control at work, etc. improve, there is an increase in job and career satisfaction. There was an inverse correlation between SAW and JCS as the significance level was a negative value at (p <0.01) level (see Table 8). When "Stress at Work" increases, JCS decreases.
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QWL and Gender: There were no statistically significant differences at the level of significance (p<0.05) for the subscales HWI, CAW, WCS and SAW. The overall score of WRQoL-2 was not statically significant for gender. We found statistically significant differences for the subscales JCS, GWB according to gender variable (p<0.01); in favor of male gender (see Table 9).
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QWL and Age: Using the ANOVA test, we found a statistically significant difference between the overall level of WRQoL-2 and Age. The HWI, CAW and WCS subscales were statistically significant by age group at (p <0.01). The JCS, GWB and SAW subscales did not return any significance (see Table 10).
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To identify differences between age groups for the HWI, CAW, WCS subscales, Scheffe’s post hoc test was conducted (see Table 11). There was a significant difference among the study respondents in regard to HWI, CAW, WCS in the 45-59 years group. This indicates a correlation between QWL and older age.
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