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Record W4376601921 · doi:10.21203/rs.3.rs-2908418/v1

Evaluating the facilitators and constraints that informed the adaptation of Family Integrated Care to a Ugandan neonatal hospital unit: a qualitative study

2023· preprint· en· W4376601921 on OpenAlexaffabout
Olive Kabajassi, Anna Reiter, Abner Tagoola, Nathan Kenya‐Mugisha, Karel O’Brien, Matthew O. Wiens, Nancy Feeley, Jessica Duby

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsJewish General HospitalMcGill University
Fundersnot available
KeywordsReferralWorkforceFocus groupNeonatal intensive care unitNursingUnit (ring theory)Health careWorkloadMedicineIntervention (counseling)Qualitative researchPeer supportPsychologyFamily medicinePediatricsBusinessPolitical science

Abstract

fetched live from OpenAlex

Abstract Background: Family Integrated Care (FICare) is a model of care developed in a Canadian Neonatal Intensive Care Unit that engages parents to be active participants in their infant’s care team. FICare has the potential to have the greatest impact in low-income countries, where the neonatal mortality rate is disproportionately high and the health workforce is severely strained. This manuscript details the facilitators and constraints that informed the adaptation of FICare to a neonatal hospital unit in Uganda Methods: Focus groups of ten mothers and interviews of eight workers were conducted to identify facilitators and constraints to the implementation of FICare in Uganda. Transcripts were analyzed using inductive content analysis. An adaptation team of key stakeholders developed Uganda FICare in the Special Care Nursery in Jinja Regional Referral Hospital based on the results from the focus groups and interviews. Results: The potential to reduce the healthcare provider workload, the desire to empower mothers and the pursuit to improve neonatal outcomes were identified as key facilitators. Maternal difficulty in learning new skills, lack of trust from healthcare providers and increased maternal stress were cited as potential barriers. Uganda FICare focused on task-shifting important but often neglected patient care tasks from healthcare providers to mothers. Healthcare providers were taught how to respond to maternal concerns. All intervention material was adapted to prioritize images over text. Mothers familiar with FICare were encouraged to provide peer-to-peer support and guidance to mothers with newly hospitalized infants. Conclusions: Engaging stakeholders to identify the facilitators and constraints to local implementation is a key step in adapting an intervention to a new context. Uganda FICare shares the core values of the original FICare but is adapted to enhance its feasibility in low-resource settings.

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)0.019
metaresearch head score (Gemma)0.027
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 score0.019
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0110.008
Scholarly communication0.0030.004
Open science0.0020.007
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.274
GPT teacher head0.536
Teacher spread0.261 · 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

Citations0
Published2023
Admission routes2
Has abstractyes

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