MétaCan
Menu
Back to cohort
Record W2182494650 · doi:10.24095/hpcdp.28.4.05

Costs associated with mood and anxiety disorders, as evaluated by telephone survey

2008· article· en· W2182494650 on OpenAlexafffundvenueabout
Scott B. Patten, Jeanne V.A. Williams, Craig Mitton

Bibliographic record

VenueChronic diseases in Canada · 2008
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsUniversity of British Columbia, Okanagan CampusKelowna General HospitalUniversity of British ColumbiaUniversity of Calgary
FundersFondation pour la Recherche MédicaleMichael Smith Health Research BC
KeywordsMedicineAnxietyPsychiatryMoodTelephone interviewMood disordersRespondentActivity-based costingFamily medicineEnvironmental health

Abstract

fetched live from OpenAlex

Costing studies are central to health policy decisions. Available costing estimates for mood and anxiety disorders in Canada may, however, be out of date. In this study, we estimated a set of direct health care costs using data collected in a provincial telephone survey of mood and anxiety disorders in Alberta. The survey used random digit dialing to reach a sample of 3394 household residents aged 18 to 64. A telephone interview included items assessing costs without reference to whether these were incurred by the respondent, government or a health plan. The survey interview also included the Mini Neuropsychiatric Diagnostic Interview (MINI). Costs for antidepressant medications appear to have increased since the last available estimates were published. Surprisingly, most medication costs for antidepressants were incurred by respondents without an identified disorder. Also, an unexpectedly large proportion of medication costs were for psychotropic medications other than antidepressants and anxiolytic-sedative-hypnotics. These results suggest that major changes have occurred in the costs associated with antidepressant treatment. Available cost-of-illness data may be outdated, and some assumptions made by previous studies may now be invalid.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.092
GPT teacher head0.329
Teacher spread0.237 · 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 designObservational
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

Citations4
Published2008
Admission routes4
Has abstractyes

Explore more

Same venueChronic diseases in CanadaSame topicHealth Systems, Economic Evaluations, Quality of LifeFrench-language works237,207