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Record W4280549969 · doi:10.1186/s12911-022-01870-1

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

2022· article· en· W4280549969 on OpenAlexafffund
Neesha Hussain‐Shamsy, Sarah Somerton, Donna E. Stewart, Sophie Grigoriadis, Kelly Metcalfe, Tim F. Oberlander, Carrie Schram, Valerie H. Taylor, Cindy‐Lee Dennis, Simone N. Vigod

Bibliographic record

VenueBMC Medical Informatics and Decision Making · 2022
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsUniversity of CalgaryWomen's College HospitalSunnybrook Health Science CentreCanada Research ChairsBC Children's HospitalUniversity of TorontoToronto General HospitalUniversity Health NetworkSickKids FoundationUniversity of British ColumbiaHospital for Sick Children
FundersCanadian Institutes of Health Research
KeywordsAntidepressantMedicineDepression (economics)PsychiatryPopulationPregnancyAntenatal depression

Abstract

fetched live from OpenAlex

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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.958
Threshold uncertainty score0.436

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0000.001
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 head0.052
GPT teacher head0.358
Teacher spread0.306 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations8
Published2022
Admission routes2
Has abstractyes

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