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Record W3047939073 · doi:10.1186/s40900-020-00218-1

Global Health in Preconception, Pregnancy and Postpartum Alliance: development of an international consumer and community involvement framework

2020· article· en· W3047939073 on OpenAlexaff
Heidi Bergmeier, Virginia Vandall‐Walker, Magdalena Skrybant, Helena Teede, Cate Bailey, Jo-Anna B. Baxter, Ana Luíza Vilela Borges, Jacqueline Boyle, Ayesha Everitt, Cheryce L. Harrison, Margely Herrera, Briony Hill, Brian Jack, Samuel L. Jones, Laura Jorgensen, Siew Lim, Cynthia Montanaro, Leanne M. Redman, Judith Stephenson, Hildrun Sundseth, Shakila Thangaratinam, Paula Thynne, Ruth Walker, Helen Skouteris

Bibliographic record

VenueResearch Involvement and Engagement · 2020
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsGuelph Wellington Seniors AssociationHospital for Sick ChildrenGuelph General HospitalSickKids FoundationCentre for Global Health ResearchAthabasca University
FundersNational Institute of General Medical SciencesNational Institute for Health and Care Research
KeywordsMultidisciplinary approachConceptual frameworkAlliancePregnancyMedicineGrey literaturePublic relationsNursingBusinessPsychologyPolitical scienceMEDLINESociology

Abstract

fetched live from OpenAlex

BACKGROUND: The goal of the Global Health in Preconception, Pregnancy and Postpartum (HiPPP) Alliance, comprising consumers and leading international multidisciplinary academics and clinicians, is to generate research and translation priorities and build international collaboration around healthy lifestyle and obesity prevention among women across the reproductive years. In doing so, we actively seek to involve consumers in research, implementation and translation initiatives. There are limited frameworks specifically designed to involve women across the key obesity prevention windows before (preconception), during and after pregnancy (postpartum). The aim of this paper is to outline our strategy for the development of the HiPPP Consumer and Community (CCI) Framework, with consumers as central to co-designed, co-implemented and co-disseminated research and translation. METHOD: The development of the framework involved three phases: In Phase 1, 21 Global HiPPP Alliance members participated in a CCI workshop to propose and discuss values and approaches for framework development; Phase 2 comprised a search of peer-reviewed and grey literature for existing CCI frameworks and resources; and Phase 3 entailed collaboration with consumers (i.e., members of the public with lived experience of weight/lifestyle issues in preconception, pregnancy and postpartum) and international CCI experts to workshop and refine the HiPPP CCI Framework (guided by Phases 1 and 2). RESULTS: The HiPPP CCI Framework's values and approaches identified in Phases 1-2 and further refined in Phase 3 were summarized under the following five key principles: 1. Inclusive, 2. Flexible, 3. Transparent, 4. Equitable, and 5. Adaptable. The HiPPP Framework describes values and approaches for involving consumers in research initiatives from design to translation that focus on improving healthy lifestyles and preventing obesity specifically before, during and after pregnancy; importantly it takes into consideration common barriers to partnering in obesity research during perinatal life stages, such as limited availability associated with family caregiving responsibilities. CONCLUSION: The HiPPP CCI Framework aims to describe approaches for implementing meaningful CCI initiatives with women in preconception, pregnancy and postpartum periods. Evaluation of the framework is now needed to understand how effective it is in facilitating meaningful involvement for consumers, researchers and clinicians, and its impact on research to improve healthy lifestyle outcomes.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.380
Threshold uncertainty score0.607

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 integrity0.0000.001
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 head0.187
GPT teacher head0.432
Teacher spread0.245 · 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 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

Citations13
Published2020
Admission routes1
Has abstractyes

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