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What are the Programs that are included in these 12 data sets and if there are programs that are represented more than once are they weighted accordingly?

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I saw the note about the mod table and also noted you had screenshot the under review draft table from the under review paper. Here is the mod table

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Supplemental  Table 18. Meta-Analytic Post-Intervention Moderator Results by Outcome Domain

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Here is the final published paper with tables

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Here is the final published paper with tables

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Cipriano et al 2023 State of the Evidence for SEL

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what are the ks and ns for each group? Is there a place I can review those before Friday? Thank you!

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Would love to see these caterpillar plots with the effect size labeled.

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Think that the most compelling moderators for the SEL field are the minutes of student facing instruction and number of discrete sessions. The most compelling moderator for the meta-analytic methods field is control group type.

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Perhaps a more appropriate comparison to Cipriano would be just the effects for the US? That would require re analyzing Cipriano....

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For some groups on some outcomes, SEL programs may have negative effects

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I'm curious, why are the prediction intervals for some of these groups so small (e.g., mixed race students)?

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interesting: 1) no effect/negative effects for Hispanic and African American youth outcomes on family relationships and prosocial behaviors. 2) positive effect for discipline and school functioning for Hispanic, African American, and Native students. Curious how SEL may have impacted school staff on decisions that influence discipline and school functioning. 3) negative effect for family relationships and prosocial behaviors for White students;

Questions: 1) why does graph for Native Hawaiian students not have 95% CI? 2) were discipline outcomes not available for different SES variables? 3) what influenced the CI spread variability?

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It's interesting that for each group, the effects on SEL skills is quite small or negative. I.e., it's at the bottom of the pack in each caterpillar plot.

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Are all of the outcomes in one model? Or are these separate models for each outcome?

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Hard to resist comparing specific groups to one another

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Hard to resist comparing specific groups to one another

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Especially when the plots are next to one another. Something to consider for the manuscript

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The outcomes in the vertical columns are sorted differently across subgroups, making it difficult to compare the results at a glance. It might be helpful to visualize the results in the same domain order. OR can we show the results by combining one plot (showing the subgroup results together in each domain)

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Claire: Based on the conversation about SEL skills and measurement --> maybe we should determine what measures are used and see if that moderates effects?

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Showing the sample size of each subgroup (student N)

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Showing the sample size of each subgroup (student N)

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The number of samples in each group is expected to differ greatly. This may be influencing the intervals displayed in the graph. Including the student sample sizes alongside the table would be beneficial.

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What is the appropriate data set to compare to, to offer context?

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What is the appropriate data set to compare to, to offer context?

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Josh: Could we compare each the effects observed here to the effects observed in the U.S.-based analysis from the Yale team study?

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Would be interesting to see how these IPD estimates compare to marginal means for race/SES categories from the Yale team’s dataset if those are available

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A need for descriptive analysis of the studies

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A need for descriptive analysis of the studies

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What are the programs? What theories ground those programs? What measures were included in each domain?

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Theory about race and/or SES and the different outcome domains

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Theory about race and/or SES and the different outcome domains

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What does theory suggest our hypotheses should be about these relationships, within group? How does that relate to the measurements used?

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How to think about this sample of studies?

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How to think about this sample of studies?

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Rebecca: We should be careful about positioning these effects as the "truth" in relation to what we observed from a broader group of studies. Rather, we should be thinking of this sample as a way to dig into the narrative -- what are the possible explanations that are coming up from these data?

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This is really fascinating work!

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In my dissertation I look at the actual measures included in the SEL Skills domain and find a lot of heterogeneity. It would be great to look at the outcomes that make up SEL Skills in your data. Happy to help if that would be useful!