I have data from a questionnaire study structured like so:

• Age - Ordinal (18-24, 25-34, 35-44, 45-54, 55+)
• Gender - Nominal (Male, Female)
• AnxietyType - Nominal (Self-diagnosed, Professionally diagnosed)
• AnxietyYears - Scale
• ChronicPain - Nominal (No, Yes)
• Response - Ordinal (Strongly Agree, Agree, Neutral, Disagree, Strongly disagree)

I am using SPSS to run an ordinal logistic regression with 'response' as my dependent variable and the other 5 as my independent variables.

When putting the data into SPSS I have coded it as follows:

• Age - (18-24, 0) (25-34, 1) (35-44, 2) (45-54, 3) (55+, 4)
• Gender - (Male, 0) (Female, 1)
• AnxietyType - (Self-diagnosed, 0) (Professionally diagnosed, 1)
• AnxietyYears - Scale
• ChronicPain - (No, 0) (Yes, 1)
• Response - (Strongly Agree, 1) (Agree, 2) (Neutral, 3) (Disagree, 4) (Strongly disagree, 5)

When I run the regression, this is my output with a significant result highlighted in yellow (attached).

From what I've read and understood about interpreting the results of an ordinal logistic regression, this is saying that:

"The odds ratio of being in a higher category of the dependent variable for males versus females is 2.244" which is saying that males are more likely to agree more strongly than females.

However, when I create a graph looking at the split of responses between males and females it shows that females are actually more likely to agree more strongly than males (see attached).

I would be grateful if anyone could help me to understand what I'm doing wrong - either in my modelling or my interpretation.