Niu Protocol #8 Clustering & Time Series

Niu Protocol #8 Clustering & Time Series

by Grace -
Number of replies: 2

Describe the study design you will employ in order to determine if your intervention has had an effect on the outcome variable of interest.

My study is based on the idea that regular use of a depression screening tool by primary care providers will lead to more referrals for late life depression which will then lead to improved mental health outcomes for geriatric patients. The outcome variable of interest would be lower depression scores over the course of a year. In order to measure this, I would use a pre-post- design.  I would look at depression scores among the patient population prior to the dissemination of the preliminary research findings via education programs and then see if they decreased over time. I would also want to have control clinic where the intervention is not used and see how depression scores among older patients compare.

At first, I considered having the outcome variable be the number of referrals made by primary care providers. I considered looking at the average number of referrals being made before and after the intervention. However, as I thought more about it and examined the literature, I did not think it would be feasible to track referrals since there is an additional step of which patients followed up with the referrals.

Define the unit-of-analysis for your main outcome evaluation, the minimum meaningful effect size, and the sample size necessary to detect this effect size.

The unit-of-analysis for my main outcome evaluation is at the patient level.  The primary study outcome is depression scores over time.  For a sample size calculation, I calculated about 650 participants each would be required in the intervention clinic and the control clinic in order to detect a 95% chance and an effect size of 0.10 in the mean score of a depression screening questionnaire. To compensate for patient attrition, I would aim for 875 patients in each clinic. 

In reply to Grace

Re: Niu Protocol #8 Clustering & Time Series

by Heidi Moseson -

Hi Grace,

That's an interesting point about the difficulty of tracking referrals - and shows that you've definitely thought hard about how this could realistically be measured. Does a lower depression score indicate more depression? In other words, would a drop in depression scores indicate that physicians are diagnosing more depression in the elderly? It seems like that would be what you want to see, if you're tool is helping physicians to remember to carefully screen for depression....Trying to get a handle on the measures....

Looking forward to hearing more tomorrow.

 

In reply to Grace

Re: Niu Protocol #8 Clustering & Time Series

by Purba Chatterjee -

Hi Grace,

Nice job! Since your outcome of interest will be measured over the course of the year, I was wondering if interrupted time series may be another option for you to consider with three measures prior and three measures post intervention as change in depression scores are likely to happen gradually over the course of the year.

-purba