User talk:Kbsutton8/sandbox2

Feedback from HGAPS Water Carriers
(leave comments here)

Ideas for sections that can be added
--Kbsutton8 (discuss • contribs) 00:12, 7 May 2021 (UTC)
 * Code
 * Codebook
 * Deidentified data
 * Future Directions for Research

Issues with Trello/OSF pdf links
7up 7down 10da self-report 10db self-report 10m self-report 10db PGBI Other questions for Eric!!
 * On the trello, one says caregiver Portuguese form, but there is not a caregiver version of the 7up 7down.
 * No english version on trello (there is one on osf)
 * No versions at all to be found
 * lots of language repeats(etc. 2 estonian, 2 latvians) How should we count that?
 * version in the trello does not match the assessment center/one in google drive (those are in numerical order). Which one should we use??
 * Figure out a policy for this. The trello one is based on the IRT ones. We will stay consistent within order.
 * Freeman, AJ paper 2011 on order of GBI questions. Embedded.
 * Which language translations are ready to be part of this.
 * Which assessment center link should we use. (I was thinking direct link of measures from the clinician side of the center)
 * Why is the OSF for the GBI private? Can we make it public?

General Edits

 * Copy edit whole page
 * Add more hyperlinks
 * List on discuss page what needs to be fixed in Assessment Center and OSF for GBI
 * Double check citations....

Versions Table Update

 * Languages (Update based on Josh's suggestions below)
 * PDF/Link (change to online link and switch to assessment center links)

Competitive Comparisons Section

 * Write more info

Scoring Information

 * Computer sections (currently just in person vs HGAPS links)

Reliablity and Validity

 * Validity in special populations
 * more data on original gbi

Additional Variations in Research

 * Fill them out... As much as we can. Need to find the articles for some of them.

Links

 * sections are listed on the "outline draft!" doc

Appendices

 * Can't think of more for this round. the code and codebook would be great, but I feel like that is not needed for this iteration

--Kbsutton8 (discuss • contribs) 00:36, 7 May 2021 (UTC) Updated Kbsutton8 (discuss • contribs) 20:46, 21 June 2021 (UTC)

Versions Table
Great work on the table. I've been thinking about what to do with the "Languages" column. We'd been considering listing the available languages, just putting a number, or something else. Here's a potential compromise: let's list up to some number (maybe 5?) of the actual languages available, linking to the actual forms (on OSF) when available; if more than that number are available, let's write "[N] More" as a hyperlink to the OSF page with all the translations ("N" = number of additional languages). The key here would be to order the listed languages by total number of world speakers. This way most people will be able to get the info that they need right away and the rest is just a click away.

For example:

I'm using this page to determine the order of the languages: List of Languages by Total Number of Speakers.

The links above might not be the ones we end up using, since it looks like the GBI part of OSF is still under construction. However, this gives an idea of what I'm thinking. Ideally, we'd link directly to the OSF page with the actual PDF (lowest level of the hierarchy), however some of the ones above link to the component (provides a little more information about the measure, but also requires additional clicks to get to the form).

Finally, if we include links to the PDFs like this in the language links, then we might be able to omit the "Link/PDFs" column.

Thoughts? Joshal (discuss • contribs) 15:20, 15 April 2021 (UTC)

Research Resources Section from Original Wikiversity Page
Scoring syntax to make all of the above scales is available in SPSS in the OTOPS project. We are working on making a version available in R as well.

The code will work with any informant or language, provided that the variable names are the same. Because there are different versions of the GBI available on the Internet, please be careful to check that the content and order of the items is the same in the version you are using as in the 73 (+6 validity items) version that we used as the basis for the code. A second caveat is to check whether item level scores are typed in as 0 to 3 (the newer format) versus 1 to 4 (the original format).

If your institution has a Qualtrics license, you can import these .QSF files and have the survey read to launch out of the box, or you can customize it for your project.

Set of QSF files here. (*** upload to OSF and drop link to here).

Supplemental Materials
Two papers that tested several short forms when used as parent report and as adolescent self report included supplemental materials that provided more detail about methods and results. These supplemental materials are published here so that they are freely accessible and archived (rather than having them only behind a publisher's paywall).

Factor Structure of the Short Forms
Tables

Rationale for the Ranking of Expected Criterion Correlations
Both papers had two samples, an academic clinic and a community mental health center, along with a large set of variables that could be used to examine the criterion validity of the short forms compared to the full length GBI scales.

Here is the detailed description of how the authors ranked the criterion correlations from what they expected to be largest to smallest:

The GBI scales were expected to show the highest correlation with the cognate rating scale on the Youth Self Report (YSR) because they were converging measures of the same trait, they were completed by the same informant (i.e., they shared method variance)(Podsakoff, MacKenzie, & Podsakoff, 2012), and they were continuous scales (not categorical variables, which would shrink the size of the observed correlation even when measuring the same construct) (Cohen, 1988).

The YSR Internalizing score was expected to show the highest correlation because of the shared method variance: both it and the GBI were completed by the same person. They would be expected to correlate r ~.3 to .4 even if they measured different constructs, due to response set, mood congruent biases, and other factors unrelated to the trait (Podsakoff et al., 2012). Further, Internalizing and Externalizing correlate r ~.6 in the standardization sample (Achenbach & Rescorla, 2001) and also in our samples. Finally, the 28-item and 10-item GBI versions included some “mixed” items, and so they had depression content embedded in them. The 7 Up, in contrast, was “purer” and showed lower correlations with Internalizing in both samples (though still > .4).

The YSR Externalizing score was the best available converging measure for the mania scales in the two samples, but it was not expected to show quite as high criterion correlations as the depression-Internalizing coefficients. A meta-analysis (Youngstrom, Genzlinger, Egerton, & Van Meter, 2015) of diagnostic accuracy shows that Externalizing is not as strongly associated with bipolar disorder as the GBI is: The effect size was r ~.45 for parent ratings on measures like the GBI, versus r ~.34 for measures such as the CBCL Externalizing; r ~.26 for GBI versus r ~ .13 for YSR correlations with diagnoses. The Externalizing score does not include items asking about grandiosity, inflated self-esteem, elevated or expansive mood, or decreased need for sleep without fatigue – the “handle” symptoms that are more specific to hypomania and mania (Craney & Geller, 2003; Youngstrom, Birmaher, & Findling, 2008). Put simply, Externalizing is not as good a measure of the mania construct as the GBI scales are, so the criterion correlation with it is not going to be stellar.

Next, the youth and parent correlations use different sources, eliminating the shared method variance component. Meta-analyses find that parent-youth agreement about the same trait in the youth hovers in the r ~.2 to .3 range (Achenbach, McConaughy, & Howell, 1987; De Los Reyes et al., 2015), exactly what we see in the Academic sample and similar to the estimates in the Community sample.

For the correlations with the diagnoses and interview-based severity ratings: Meta-analyses have established that parent report is significantly more strongly related to youth diagnoses than youth self-report is (Stockings et al., 2015; Youngstrom et al., 2015). Converting the effect sizes from Youngstrom et al. 2015 into correlations yields an estimate of r ~ .45 for parent ratings and corresponding youth diagnoses, versus .26 for youth ratings and their own diagnoses. The same pattern will hold for the YMRS and CDRS-R as the diagnoses – they were based on the same interview as the KSADS diagnoses, and so they correlate with the diagnosis r > .9. Because of attenuation artifacts when using a categorical variable (i.e., diagnosis) instead of a continuous one (i.e., severity on the YMRS or CDRS-R), we would expect the correlations with diagnosis to be about 80% of the size of the correlation with the severity rating (Cohen, 1988).

Depression scores were expected to show a small to moderate correlation with age as well as with female sex based on normative data (e.g., patterns in Internalizing scores in the standardization sample for the ASEBA; Achenbach & Rescorla, 2001). Anxiety diagnoses were expected to show a small to moderate correlation with depression scales due to overlapping symptoms (e.g., the tripartite model of depression and anxiety) (Chorpita & Daleiden, 2002; Watson, Clark, et al., 1995; Watson, Weber, et al., 1995).

Last in the rankings were some demographic variables (e.g., race) and unrelated diagnoses that were expected to have near-zero correlation coefficients.

Deleted text from old page
Info below is copy and pasted from the old wikiversity page:

The changes in odds (or diagnostic likelihood ratios) associated with scores on six different tests (the P-GBI, the P-YMRS, the Achenbach CBCL, TRF, and YSR, and the self-report GBI) based on a large sample of outpatients, and an update based a more recent review is available. We also are including a table here that is based on these likelihood ratios, estimating the probability that a child has bipolar disorder assuming a base rate of 5% in combination with a test score in the particular range. We chose the 5% base rate estimate for three reasons: (1) because other colleagues are estimating that 5% of the youths evaluated at outpatient academic research centers meet criteria for a bipolar spectrum disorder (e.g., 6-7% of outpatient cases evaluated in the TEAM multi-site NIMH grant; Geller et al., 2002); (2) because 5% is low enough to serve as a reminder that bipolar disorder is likely to be rare in community mental health, outpatient, and private practice settings, yet high enough to act as a reminder that the disorder can occur and should be assessed; (3) because a 5% base rate will be reduced to negligible probabilities by low or moderate scores on good tests, and raised to intermediate probabilities (30% to 50% range) by high scores on the same tests.

If bipolar disorder is substantially more rare or more common at your site than 5%, we strongly recommend using a rate compared to benchmarks from similar settings as the starting point.

--Kbsutton8 (discuss • contribs) 23:42, 13 May 2021 (UTC)