DClinPsy Portfolio Volume 1 of 3 - University of Hertfordshire ...

% within Body
mass index USA 35.7% 42.9% 21.4% 100.0%
Underweight Count 18 2 1 21
% within Body
mass index USA 85.7% 9.5% 4.8% 100.0%
Total Count 68 17 11 96
% within Body
mass index USA 70.8% 17.7% 11.5% 100.0%
As can be seen from Table 29 above 74% of those in the low risk group are a healthy
BMI weight with 26% of the healthy BMI being in the moderate or high risk groups
combined. The overweight group has 64% in the moderate and high risk groups
combined as opposed to 36% in the low risk group. The underweight group result appears
perhaps more paradoxical with 86% in the low risk group and only 29% in the at risk
group. A Chi-square test of independence found that there was a significant association,
Chi-square = 11.30, (df = 4), p = 0.02, with a Contingency Coefficient 0.33.
Section IV – A multivariate analysis of predictors of eating disorder risk
As predicted, the two key factors of the ACT model – inflexibility and body image
acceptance – were both found to be significantly associated with the EDR groups (see
section II). However, it was also found that these two factors were themselves
considerably correlated (r = -.55). It was therefore important to determine whether each
factor would still be a significant predictor in its own right in relation to the EDR groups
when controlled for by the other factor. This was achieved by a logistic regression
analysis using the low EDR group (n = 68) and the moderate and high EDR groups
(grouped together n = 28) as the criterion variable and the total scores of the Body Image
Acceptance Questionnaire (BIAAQ) and the Avoidance and Fusion Questionnaire
(AFQY) measuring inflexibility as the two predictors. This model was significant, LR =
12.2, df = 2, p = .002, Nagelkerke R-squared = .21, however, only inflexibility turned out
to be a significant predictor (p = .01), but not body image acceptance (p = .76), which
was therefore discarded from further analysis (see Table 31).
Table 31: Results of the logistic regression analysis (1)
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