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Record W4387104589 · doi:10.3329/bjog.v37i1.68627

Developing a group Model of ANC-PNC through human-centered Design (HCD) to Improve MNCH of first-time Mothers (FTMs) in Bangladesh

2023· article· en· W4387104589 on OpenAlexaff
ATM Rezaul Karim, Farzana Islam, Israt Nayer, Sk Zinnat Ara Nasreen, Petra Sillanpää

Bibliographic record

VenueBangladesh Journal of Obstetrics & Gynaecology · 2023
Typearticle
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsImpact
Fundersnot available
KeywordsFocus groupStakeholderService providerNursingInfluencer marketingService (business)Service delivery frameworkMedicinePsychologyPublic relationsBusinessMarketing

Abstract

fetched live from OpenAlex

Objective: First-time parenthood is a complex and emotional journey. The gap between demand and quality services for maternal, newborn and child health (MNCH) and family planning (FP) are significant. Lack of time, awareness, and social support are critical challenges of meeting the service requirement for the young and first-time mothers, especially working mothers in urban areas. Objective of the study was to design an intervention model for the young pregnant women and their partners for improving the quality and use of MNCH and FP services and information. Methods: Using a human-centered design (HCD) approach, we conducted 27 in-depth interviews, 10 focus group discussions, and eight mock sessions with first-time mothers, partners, family members, community influencers and service providers in Tongi, Gazipur. During phase 1, we explored the current realities of life and experience of services, both ideal and existing, from perspectives of a diverse set of stakeholders including both health care providers and care seekers. During phase 2, we designed, tested, and iterated the “group model” of antenatal Care through a series of mock sessions, interviews and consultation with service providers and authorities. We recorded, transcribed, and translated the data for collaborative synthesis and analysis process to generate insight and opportunities for optimizing service delivery and uptake. Results: The study findings spoke for the need of providing group sessions for first time parents, social support from peers and family members and capacity development of the service providers. After careful consideration of the stakeholder needs and preferences, the national guidelines and the local implementing partner’s available resources, we arrived at the recommended group model inclusive of five Group Antenatal Care (GANC) and two group Postnatal Care (GPNC) for mothers. All the pregnant women underwent through clinical checkups by medically trained professionals, mainly midwives and doctors. The group model also includes two GANC and one GPNC for fathers, as well as informative sessions for companions. The prototype model included five GANC and two GPNC sessions for mothers, two GANC and one GPNC session for fathers, and informative sessions for companions. The sessions included pregnant women of close gestational age, use of visual aids to support session facilitation, and activities to support group bonding and information retention. Conclusions: The Group Model offering 5 ANC and 2 PNC for women, 2 GANC and 1 GPNC for male partners, and sessions for caregivers was developed in line with the national and WHO recommendation. This model found a feasible approach that involved partners and caregivers in the process and increased MNCH and social support during the voyage of the pregnancy journey. Bangladesh J Obstet Gynaecol, 2022; Vol. 37(1): 14-23

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)0.023
metaresearch head score (Gemma)0.014
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.122

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.004
Scholarly communication0.0030.001
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.111
GPT teacher head0.380
Teacher spread0.268 · 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 routes1
Has abstractyes

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