Talk:Evidence-based assessment/Instruments/General Behavior Inventory

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Links[edit source]

Zotero link

Translations Assessment Center names and thoughts[edit source]

TOpTraP - The Open TRAnslations Project TOpTrAC - The Open TRanslation Assessment Center ???

GBI results write-up[edit source]

First of all, a huge thank you for Dr. Youngstrom and all of you who have devoted so much time and effort into this exceptionally valuable resource. :0)

Will give me some feedback? I have placed below a write-up for a hypothetical case. Although the data I present below and my questions are in "case study" format, I primarily want to enhance my understanding of the GBI and I'm using a hypothetical case as the vehicle to solicit your insights and suggestions. In general, I find this method—case-based learning—to be one of the best ways for me (and others) to learn and understand.[1]

I'm looking for two types of feedback:

(1) Did I analyze and interpret the scores correctly? Did I miss any research articles with information relevant to this particular case (in terms of scoring and interpretation)?

(2) Did I explain the results accurately? (I intentionally do not explain terms such as "diagnostic likelihood ratio" because I have a detailed feedback session with the evaluee and explain terms as needed, and anyone else reading the report now or in the future should either know the terms or can easily look them up.)

Here is my GBI write-up. The hypothetical evaluee is a young adult. Thank you!

General Behavior Inventory (GBI)

Scoring method →

Scale ↓

Caseness Scoring Dimensional Scoring
Depression 17 64
Hypomanic-Biphasic 14 46

PATIENT’s caseness scores for both scales are above the cut-off scores provided in one study (cut-off scores: Hypomanic-Biphasic ≥ 13 and Depression ≥ 11) with a nonclinical college sample,[2] but below the cut scores in another study (cut-off scores: Hypomania-Biphasic ≥ 17 and Depression ≥ 23) with a combined college clinical-training clinic and community mental health center sample.[3]

Based on a third study, which used dimensional scoring with an older adolescent to young adult sample,[4] PATIENT’s Hypomanic-Biphasic dimensional score is 46, well above the cut-off score of 20, which yields a diagnostic likelihood ratio of 5.24 (when comparing bipolar disorder patients' GBI scores with those of ADHD patients).[5]

Without any data about a patient, we can say that the prior probability of a bipolar disorder diagnosis is 0.10, which is the estimated prevalence of yet-to-be-diagnosed bipolar disorder in our community mental health clinic. If a patient completes the GBI and has a Hypomanic-Biphasic dimensional score above 20, as is the case for PATIENT, then the probability that the patient has a bipolar disorder (in contrast to ADHD) increases from 0.10 to 0.37.[a] This figure (0.37) is known as the posterior probability, i.e., the probability of a bipolar disorder diagnosis after factoring in additional information, which in this instance are the patient's GBI results. This finding suggests the distinct possibility of a bipolar disorder diagnosis, although additional data must be considered before making a definitive diagnosis. Assuming an estimated 10% prevalence rate for undiagnosed bipolar spectrum disorders in our clinic, the likelihood of a bipolar disorder diagnosis for PATIENT is about 26%. Thus, PATIENT’s GBI results suggest a possible bipolar diagnosis, with a unipolar depression diagnosis being more likely—based solely on the GBI scores, i.e., not considering the results of the other assessment procedures.   - Mark D Worthen PsyD (talk) 18:41, 13 October 2021 (UTC)Reply[reply]

Note: I edited the above post on 4 June 2022.   - Mark D Worthen PsyD (talk) 22:51, 4 June 2022 (UTC)Reply[reply]

Note[edit source]

  1. Calculated using an online Bayesian calculator: http://psych.fullerton.edu/mbirnbaum/bayes/bayescalc.htm

References

  1. Thistlethwaite, J. E., Davies, D., Ekeocha, S., Kidd, J. M., MacDougall, C., Matthews, P., ... & Clay, D. (2012). The effectiveness of case-based learning in health professional education. A BEME systematic review: BEME Guide No. 23. Medical Teacher, 34(6), e421-e444.
  2. Depue, R. A., Krauss, S., Spoont, M. R., & Arbisi, P. (1989). General behavior inventory identification of unipolar and bipolar affective conditions in a nonclinical university population. Journal of Abnormal Psychology, 98(2), 117–126.
  3. Klein, D. N., Dickstein, S., Taylor, E. B., & Harding, K. (1989). Identifying chronic affective disorders in outpatients: Validation of the General Behavior Inventory. Journal of Consulting and Clinical Psychology, 57(1), 106–111.
  4. Pendergast, L. L., Youngstrom, E. A., Merkitch, K. G., Moore, K. A., Black, C. L., Abramson, L. Y., & Alloy, L. B. (2014). Differentiating bipolar disorder from unipolar depression and ADHD: The utility of the General Behavior Inventory. Psychological Assessment, 26(1), 195–206.
  5. Pendergast, et al. (2014), tbl 3, p. 202.

Incremental utility of GBI?[edit source]

It seems that unless you evaluate an adult in a setting with a high prevalence of bipolar disorders that the GBI does not offer incremental utility (cost/benefit consideration given incremental validity).

For example in our clinic (community mental health center) undiagnosed bipolar disorder prevalence is about 10%. I recently had a young adult with a Hypomanic-Biphasic dimensional score of 57. That's well above the cut-off of 20 from Pendergast, et al. (2014). Even if one compares to the clinical control group that score yields a probability of 0.36 for a bipolar diagnosis. That's higher than the prevalence (0.10) but when you're trying solve a differential diagnosis question it doesn't help that much since the corresponding probability against having bipolar is 0.64. (Do I understand that correctly?)

The cost: Hand-scoring the GBI requires careful attention to detail, entering Hypomanic-Biphasic items into a spreadsheet twice, since clerical or transcription errors are common, looking up the LR for the relevant comparison(s), and then computing the probability using a Bayesian calculator, which requires understanding how to do it and what it means (not easy for many of us without repeated practice), and then arriving at a posterior probability number that will still indicate that the odds are against a bipolar diagnosis.

What do you think? Are there flaws in my calculations, understanding, or analysis?

Thanks!   - Mark D Worthen PsyD (talk) 02:18, 26 January 2022 (UTC)Reply[reply]

I think I found the answer to my question by re-reading (again) the Pendergast et al. (2014) article, which states on p. 203:
Overall, the present results provide support for the diagnostic efficiency of the GBI as a method of discriminating between bipolar and other diagnoses in emerging adulthood. Given the prevalence of bipolar disorder in outpatient and community settings, low GBI scores may be decisive in excluding a bipolar diagnosis. High GBI scores would raise the posterior probability of a bipolar disorder into a moderate range, warranting additional systematic assessment ....
Thus, I was making the mistake of considering the GBI results to be diagnostic in and of themselves, as opposed to the proper interpretation: Whereas low GBI scores can reliably rule out bipolar disorder, high scores suggest the distinct possibility of a bipolar disorder, but further assessment is required. I knew the latter part ("further assessment is required") but I was trying to make the GBI a diagnostic instrument when it is actually a screening instrument. A bit embarrassing for me because I preach using screening instruments appropriately. I would not diagnose bipolar disorder without a semi-structured diagnostic interview and some other supporting data (medical & mental health records, collateral interview), but I did not distinguish screening from diagnostic assessment conceptually in my previous posts on this page.   - Mark D Worthen PsyD (talk) 22:38, 4 June 2022 (UTC)Reply[reply]

GBI Links[edit source]

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Assessment Center Links[edit source]