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Record W3120649585 · doi:10.3386/w28334

Family Spillover Effects of Marginal Diagnoses: The Case of ADHD

2021· report· en· W3120649585 on OpenAlexaff
Petra Persson, Xinyao Qiu, Maya Rossin‐Slater

Bibliographic record

VenueNational Bureau of Economic Research · 2021
Typereport
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsMcGill University
Fundersnot available
KeywordsSpillover effectMedical diagnosisAttention deficit hyperactivity disorderPsychologyClinical psychologyMedicineEconomicsPathology

Abstract

fetched live from OpenAlex

The health care system commonly relies on information about family medical history in the allocation of screenings and in diagnostic processes. At the same time, an emerging literature documents that treatment for "marginally diagnosed" patients often has minimal impacts. This paper shows that reliance on information about relatives' health can perpetuate marginal diagnoses across family members, thereby raising caseloads and health care costs, but without improving patient well-being. We study Attention Deficit Hyperactivity Disorder (ADHD), the most common childhood mental health condition, and document that the younger siblings and cousins of marginally diagnosed children are also more likely to be diagnosed with and treated for ADHD. Moreover, we find that the younger relatives of marginally diagnosed children have no better adult human capital and economic outcomes than the younger relatives of those who are less likely to be diagnosed. Our analysis points to a simple adjustment to physician protocol that can mitigate these marginal diagnosis spillovers.

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.

How this classification was reachedexpand

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)0.011
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.767
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
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 head0.524
GPT teacher head0.656
Teacher spread0.133 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2021
Admission routes1
Has abstractyes

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