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Record W4376619664 · doi:10.1037/spq0000540

Examining utility and impact of social, emotional, and behavioral screening to identify and address needs.

2023· article· en· W4376619664 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSchool Psychology · 2023
Typearticle
Languageen
FieldPsychology
TopicBehavioral and Psychological Studies
Canadian institutionsEducation and Early Childhood Development
FundersSociety for the Study of School Psychology
KeywordsPsycINFOIntervention (counseling)Clinical psychologyPsychologyFace validityMedicineMEDLINEPsychometricsFamily medicinePsychiatry

Abstract

fetched live from OpenAlex

Along with increased attention to universal screening for identifying social, emotional, and behavioral (SEB) concerns is the need to ensure the psychometric adequacy of tools available. Nearly all extant tests of universal SEB screening validity focus on traditional inferential forms with little to no study of the consequences of actions following those inferences, or consequential validity proposed under Messick's unified validity theory. This study examines one facet of consequential validity (i.e., utility) of results from one popular screening tool in six elementary schools in one large U.S. district. The schools identified students who were receiving SEB supports on a monthly form throughout one school year. Screening identified 991 students with SEB risk, of which 91 (9%) were receiving intervention prior to screening. After screening, schools provided intervention to an additional 66 students (7%). Unaddressed SEB risk remained after screening for 84% of screener-identified students. Latent profile analyses detected five patterns of risk with those students demonstrating the most risk and predominately externalizing concerns being most likely to receive intervention after screening. Study schools also provided intervention to students with elevated low risk after screening, but this profile was the largest group leaving 708 students with unaddressed SEB risk after screening. Results provide evidence of universal SEB screening interpretation to identify unaddressed SEB risk but insufficient use to provide intervention services at a rate that substantially reduced unaddressed SEB risk. Future research and practice directions for advancing the consequential validity of universal SEB screening are recommended and measurement limitations discussed. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.092
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.444
GPT teacher head0.504
Teacher spread0.060 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it