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Record W2938923002 · doi:10.1002/da.22896

Hoarding: A meta‐analysis of age of onset

2019· review· en· W2938923002 on OpenAlexaff
Brian A. Zaboski, Olivia A. Merritt, Anna P. Schrack, Cindi Gayle, Melissa L. González, Lisa A. Guerrero, Julisa A. Dueñas, Noam Soreni, Carol A. Mathews

Bibliographic record

VenueDepression and Anxiety · 2019
Typereview
Languageen
FieldPsychology
TopicObsessive-Compulsive Spectrum Disorders
Canadian institutionsMcMaster University Medical CentreMcMaster UniversityEducation and Early Childhood Development
Fundersnot available
KeywordsHoarding (animal behavior)Hoarding disorderAge of onsetPathologicalMeta-analysisEpidemiologyPsychiatryPsychologyPopulationClinical psychologyMedicineCompulsive behaviorInternal medicineDisease

Abstract

fetched live from OpenAlex

Hoarding disorder is present in 2-6% of the population and can have an immense impact on the lives of patients and their families. Before its inclusion the Diagnostic and Statistical Manual of Mental Disorders, 5th edition, pathological hoarding was often characterized as a symptom of obsessive-compulsive disorder, and several different diagnostic assessment methods were used to identify and characterize it. Although the age of onset of pathological hoarding is an important epidemiological measure, as clarifying the age of onset of hoarding symptoms may allow for early identification and implementation of evidence-based treatments before symptoms become clinically significant, the typical age of onset of hoarding is still uncertain. To that end, this study is a systematic review and meta-analysis of research published in English between the years 1900 and 2016 containing information on age of onset of hoarding symptoms. Twenty-five studies met inclusion criteria. The mean age of onset of hoarding symptoms across studies was 16.7 years old, with evidence of a bimodal distribution of onset. The authors conclude by discussing practice implications for early identification and treatment.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.021
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0100.031
Bibliometrics0.0030.004
Science and technology studies0.0010.000
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.072
GPT teacher head0.382
Teacher spread0.310 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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

Citations56
Published2019
Admission routes1
Has abstractyes

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