As part of my doctoral thesis I have completed a logistic regression to assess the impact of some parenting variables on recovery from a diagnosis. I have so far used teaching notes, a variety of text books and the internet to help me analyse the results. I am a clinician foremost and stats is most definitely not my strong point hence why I am asking (begging, haha) for help!

This is what I have got so far...

The model was significant, x 2 (1, n = 57) = 8.73, p < 0.01, indicating that the model was able to distinguish between participants who did and those who did not recover from their diagnoses. The Hosmer-Lemeshow Goodness of Fit Test (p = 0.76) supported the model. The model as a whole explained between 14.2% (Cox and Snell R square) and 29% (Nageklkerke R Squared) of the variance in recovery from diagnoses, and correctly classified 89.5% of cases. The role of the parenting behaviour was significant to the model (p = 0.03). The odds ratio for the parent behaviour was 1485.02 indicating that presence of the parent behaviour meant the participants were 1485% times more likely to retain their diagnosis than if the parent behaviour was not present.

So these are my questions

1) In the last sentence, have I interpreted the odds ratio into percentages correctly?

2) Why is the Odds ratio so high?! I have checked for incorrect data and although there are some missing, the rest is all correct. I have spent a bit of time researching high or's on the internet, and have found that high OR's can suggest multicollinearity, however in this case VIF and tolerance values did not suggest any problems with multicollinearity. I have asked around at Uni to see if anyone else can help but no-one seems to be able to explain it, and I cant find an answer on any previous threads.

Any advice would be very very gratefully received, and if you are able to explain it in very simple terms so there is a hope of my non-stats brain understanding it I would be even more appreciative.