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Record W6902477489 · doi:10.6084/m9.figshare.c.5995589

The development of a patient decision aid to reduce decisional conflict about antidepressant use in pregnancy

2022· other· en· W6902477489 on OpenAlexaff

Bibliographic record

VenueFigshare · 2022
Typeother
Languageen
FieldMaterials Science
TopicThermal Expansion and Ionic Conductivity
Canadian institutionsUniversity of CalgaryWomen's College HospitalBC Children's HospitalUniversity of TorontoSickKids FoundationToronto General HospitalSunnybrook Health Science CentreUniversity of British ColumbiaHospital for Sick Children
Fundersnot available
KeywordsAntidepressantDepression (economics)PregnancyAntenatal depressionProcess (computing)Antidepressant medication

Abstract

fetched live from OpenAlex

Abstract Background People with moderate to severe depression in pregnancy must weigh potential risks of untreated or incompletely treated depression against the small, but uncertain risks of fetal antidepressant drug exposure. Clinical support alone appears insufficient for helping individuals with this complex decision. A patient decision aid (PDA) has the potential to be a useful tool for this population. The objective of our work was to use internationally recognized guidelines from the International Patient Decision Aids Standards Collaboration to develop an evidence-based PDA for antidepressant use in pregnancy. Methods A three-phased development process was used whereby, informed by patient and physician perspectives and evidence synthesis, a steering committee commissioned a web-based PDA for those deciding whether or not to start or continue antidepressant treatment for depression in pregnancy (Phase 1). A prototype was developed (Phase 2) and iteratively revised based on feedback during field testing based on a user-centred process (Phase 3). Results We developed a web-based PDA for people deciding whether to start or continue antidepressant use for depression in pregnancy. It has five interactive sections: (1) information on depression and treatment; (2) reasons to start/continue an antidepressant and to start/stop antidepressant medication; (3) user assessment of values regarding each issue; (4) opportunity to reflect on factors that contribute to decision making; and (5) a printable PDF that summarizes the user’s journey through the PDA. Conclusions This tool, which exclusively focuses on depression treatment with Selective Serotonin Reuptake Inhibitors and Serotonin–Norepinephrine Reuptake Inhibitors, can be used by individuals making decisions about antidepressant use to treat depression during pregnancy. Limitations of the PDA are that it is not for other conditions, nor other medications that can be used for depression, and in its pilot form cannot be used by women who do not speak English or who have a visual impairment. Pending further study, it has the potential to enhance quality of care and patient experience.

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)0.017
metaresearch head score (Gemma)0.072
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.017
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.072
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0150.004

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 head0.062
GPT teacher head0.303
Teacher spread0.242 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations0
Published2022
Admission routes1
Has abstractyes

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