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Record W2038664970 · doi:10.5402/2011/708318

Mothers with Serious Mental Illness: Their Experience of “Hitting Bottom”

2011· article· en· W2038664970 on OpenAlexaff
Phyllis Montgomery, Sharolyn Mossey, Patricia Hill Bailey, Cheryl Forchuk

Bibliographic record

VenueISRN Nursing · 2011
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsWestern UniversityLawson Health Research InstituteLaurentian University
Fundersnot available
KeywordsNature versus nurtureTop-down and bottom-up designMental illnessPsychological interventionNarrativePerspective (graphical)PsychologyMental healthDevelopmental psychologyMedicinePsychotherapistPsychiatrySociologyEngineering

Abstract

fetched live from OpenAlex

This study sought to understand the experience of "hitting bottom" from the perspective of 32 mothers with serious mental illness. Secondary narrative analysis of 173 stories about experiences related to hitting bottom were identified. Enactment of their perceived mothering roles and responsibilities was compromised when confronted by the worst of illness. Subsequent to women's descent to bottom was their need for a timely and safe exit from bottom. An intense experience in bottom further jeopardized their parenting and treatment self-determination and, for some, their potential for survival. The results suggest that prevention of bottom is feasible with early assessment of the diverse issues contributing to mothers' vulnerabilities. Interventions to lessen their pain may circumvent bottom experiences. Healing necessitates purposeful approaches to minimize the private and public trauma of bottom experiences, nurture growth towards a future, and establish resources to actualize such a life.

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.293
Teacher spread0.266 · 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 designQualitative
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

Citations33
Published2011
Admission routes1
Has abstractyes

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