MétaCan
Menu
Back to cohort
Record W4288077325 · doi:10.3389/fpsyg.2022.911629

Integrating multi-informant reports of youth mental health: A construct validation test of Kraemer and colleagues’ (2003) Satellite Model

2022· article· en· W4288077325 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueFrontiers in Psychology · 2022
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsnot available
FundersInstitute of Education SciencesFulbright Canada
KeywordsPsychologyMental healthTest (biology)Construct (python library)Construct validityApplied psychologyClinical psychologyPsychometricsPsychiatryComputer science

Abstract

fetched live from OpenAlex

Accurately assessing youth mental health involves obtaining reports from multiple informants who typically display low levels of correspondence. This low correspondence may reflect situational specificity . That is, youth vary as to where they display mental health concerns and informants vary as to where and from what perspective they observe youth. Despite the frequent need to understand and interpret these informant discrepancies , no consensus guidelines exist for integrating informants’ reports. The path to building these guidelines starts with identifying factors that reliably predict the level and form of these informant discrepancies, and do so for theoretically and empirically relevant reasons. Yet, despite the knowledge of situational specificity, few approaches to integrating multi-informant data are well-equipped to account for these factors in measurement, and those that claim to be well-positioned to do so have undergone little empirical scrutiny. One promising approach was developed roughly 20 years ago by Kraemer and colleagues (2003). Their Satellite Model leverages principal components analysis (PCA) and strategic selection of informants to instantiate situational specificity in measurement, namely components reflecting variance attributable to the context in which informants observe behavior (e.g., home/non-home), the perspective from which they observe behavior (e.g., self/other), and behavior that manifests across contexts and perspectives (i.e., trait ). The current study represents the first construct validation test of the Satellite Model. A mixed-clinical/community sample of 134 adolescents and their parents completed six parallel surveys of adolescent mental health. Adolescents also participated in a series of simulated social interactions with research personnel trained to act as same-age, unfamiliar peers. A third informant ( unfamiliar untrained observer ) viewed these interactions and completed the same surveys as parents and adolescents. We applied the Satellite Model to each set of surveys and observed high internal consistency estimates for each of the six-item trait (α = 0.90), context (α = 0.84), and perspective (α = 0.83) components. Scores reflecting the trait , context , and perspective components displayed distinct patterns of relations to a battery of criterion variables that varied in the context, perspective, and source of measurement. The Satellite Model instantiates situational specificity in measurement and facilitates unifying conceptual and measurement models of youth mental health.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.604
Threshold uncertainty score0.522

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.075
GPT teacher head0.415
Teacher spread0.341 · 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