Translating developmental origins of health and disease in practice: health care providers’ perspectives
Bibliographic record
Abstract
Currently, there is limited knowledge on how health care providers perceive and understand the Developmental Origins of Health and Disease (DOHaD), which may impact how they inform patients and their families throughout the perinatal period. This qualitative descriptive study explored if and how health care providers counsel on in utero programming and future health outcomes with parents, both preconception and during pregnancy. One-on-one, semi-structured interviews were conducted with 23 health care providers from varying health disciplines including obstetrics and gynaecology, midwifery, paediatrics, endocrinology and internal medicine. Audiotaped interviews were transcribed verbatim and analysed using inductive thematic analysis. Three themes were identified: Knowledge about DOHaD, Counselling on DOHaD in Practice Settings and Impact of DOHaD on Health. Health care providers not only expressed excitement over the potential health benefits of DOHaD counselling but also indicated barriers to knowledge translation, including a lack of knowledge among providers and a disconnect between basic scientists and practitioners. All health care providers expressed concerns on how and when to introduce the concept of DOHaD when counselling patients and called for the development of practice guidelines. Counselling on DOHaD needs to be framed in a way that is empowering, minimising the potential of coercion and guilt. More interaction and collaboration are needed between health care providers and researchers to identify strategies to support knowledge translation generated from DOHaD research into practice 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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.048 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.022 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".