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The linear discriminant analysis-maximum mutual information (LDA-MMI) method is used to maximize the posterior probabilities of all the belief score vectors [35], using objective function [36]: F MMI = ∑ ∀ i log p x i | P ( g ( i ) ) ∑ ∀ j p x i | λ j P ( j ), (28).
The mean (SD) belief score for the cohort was 30.7 (6.0) (Table 2).
Predictor variables included demographic information (such as age, years of experience, profession and higher degree qualification) and the baseline measures such as compliance classification (compliant vs non compliant), biomedical belief score, behavioural belief score, and knowledge score.
For both interventions, the Fear Avoidance Belief Score[ 34], modified to focus on the shoulder [ 35] will also be used.
The health belief score was significantly higher after intervention (p < 0.001), which was similar in the CFAWS method and in the SSS method.
Another significant aspect of this study is that a weighted scoring method based on CFA, or the CFAWS method is used to calculate the health belief score.
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Interestingly, students who maintained this belief scored more poorly on the final examination than students who considered evolution as the best explanation for the diversity of life.
➢ In the SSS method: Health Belief Score (HBS) = IS1+ IS2 + … + IS22 Two independent sample t-tests were used to test the difference in health belief scores between pre-intervention and post-intervention.
Women and men did not significantly differ in their belief scores.
Two independent sample t-tests of health belief scores showed that health belief scores were higher in the post-intervention than in the pre-intervention (p < 0.001) using either the CFAWS method or the SSS method.
Even though the difference between the mean beliefs scores for the low and high pain intensity groups was small, it is consistent with the degree of change in belief scores following the implementation of a successful public health intervention [ 17].
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