How to interpret ordinal logistic regression beta, confidence interval, and chi square p value?

[#1]

https://www.jmp.com/support/help/en/15.2/index.shtml#page/jmp/example-of-ordinal-logistic-regression...

Here, what do the beta and the significant p-value indicate? For every unit increase in duration ...? 

[#2]

Continuous exposure / independent variable, 3 ordinal dependant variables / outcomes

[#3]

Have you examined the JMP documentation about the Logistic platform? Do you have training in using a logistic regression model?

The same linear predictor is used in logistic regression as would be used in ordinary least squares regression with a continuous response. But the response is the the logit, or log odds, not the original counts. In this case, the odds are the probability of an event divided by the probability of no event. So the coefficient represents the change in the logit for each unit change in the predictor.

The scatter plot converts the predicted logit to the predicted probability. Three levels of your response translate into two logistic curves.

The inferential statistics provided for the estimate of each parameter are provided to help you decide if the term is statistically significant.

[#4]

So what does the beta tell me? If beta is positive, for every unit increase in the predictor, there is increasing odds of a lower ordered category?

[#5]

Increasing log odds.