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Record W2075289519 · doi:10.1186/1745-6215-15-3

Comparing the feasibility, acceptability, clinical-, and cost-effectiveness of mental health e-screening to paper-based screening on the detection of depression, anxiety, and psychosocial risk in pregnant women: a study protocol of a randomized, parallel-group, superiority trial

2014· article· en· W2075289519 on OpenAlexafffundabout
Dawn Kingston, Sheila McDonald, Anne Biringer, Marie‐Paule Austin, Sarah D. McDonald, Rebecca Giallo, Arto Öhinmaa, Gerri Lasiuk, Glenda MacQueen, Wendy Sword, Marie Lane-Smith, Sander Veldhuyzen van Zanten

Bibliographic record

VenueTrials · 2014
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsUniversity of TorontoMcMaster UniversityThe King's UniversityUniversity of CalgaryUniversity of Alberta
FundersCanadian Institutes of Health ResearchUniversity of AlbertaStrongChildren's Health Research Institute
KeywordsMedicinePsychosocialAnxietyMental healthRandomized controlled trialPsychiatryIntervention (counseling)Family medicineDepression (economics)

Abstract

fetched live from OpenAlex

BACKGROUND: Stress, depression, and anxiety affect 15% to 25% of pregnant women. However, substantial barriers to psychosocial assessment exist, resulting in less than 20% of prenatal care providers assessing and treating mental health problems. Moreover, pregnant women are often reluctant to disclose their mental health concerns to a healthcare provider. Identifying screening and assessment tools and procedures that are acceptable to both women and service providers, cost-effective, and clinically useful is needed. METHODS/DESIGN: The primary objective of this randomized, parallel-group, superiority trial is to evaluate the feasibility and acceptability of a computer tablet-based prenatal psychosocial assessment (e-screening) compared to paper-based screening. Secondary objectives are to compare the two modes of screening on: (1) the level of detection of prenatal depression and anxiety symptoms and psychosocial risk; (2) the level of disclosure of symptoms; (3) the factors associated with feasibility, acceptability, and disclosure; (4) the psychometric properties of the e-version of the assessment tools; and (5) cost-effectiveness. A sample of 542 women will be recruited from large, primary care maternity clinics and a high-risk antenatal unit in an urban Canadian city. Pregnant women are eligible to participate if they: (1) receive care at one of the recruitment sites; (2) are able to speak/read English; (3) are willing to be randomized to e-screening; and (4) are willing to participate in a follow-up diagnostic interview within 1 week of recruitment. Allocation is by computer-generated randomization. Women in the intervention group will complete an online psychosocial assessment on a computer tablet, while those in the control group will complete the same assessment in paper-based form. All women will complete baseline questionnaires at the time of recruitment and will participate in a diagnostic interview within 1 week of recruitment. Research assistants conducting diagnostic interviews and physicians will be blinded. A qualitative descriptive study involving healthcare providers from the recruitment sites and women will provide data on feasibility and acceptability of the intervention. We hypothesize that mental health e-screening in primary care maternity settings and high-risk antenatal units will be as or more feasible, acceptable, and capable of detecting depression, anxiety, and psychosocial risk compared to paper-based screening. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT01899534.

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)0.053
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.171
Threshold uncertainty score0.975

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0530.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.162
GPT teacher head0.467
Teacher spread0.305 · 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

Citations18
Published2014
Admission routes3
Has abstractyes

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