Clinical and exercise professional opinion of return-to-running readiness after childbirth: an international Delphi study and consensus statement
Bibliographic record
Abstract
Female athletes have identified a lack of guidance as a barrier to successfully returning to running postpartum, and existing guidelines are vague. Our aim was to define the current practice of determining postpartum run-readiness through a consensus survey of international clinicians and exercise professionals in postpartum exercise to assist clinicians and inform sport policy changes.A three-round Delphi approach was used to gain international consensus from clinicians and exercise professionals on run-readiness postpartum. Professionals who work with postpartum runners participated in an online survey to answer open-ended questions about the following postpartum return-to-running topics: definitions (runner and postpartum), key biopsychosocial milestones that runners need to meet, recommended screening, timeline to initiate running, support items, education topics and factors that contribute to advising against running. Consensus was defined as ≥75% participant agreement.One hundred and eighteen professionals participated in round I, 107 participated in round II (response rate 90.6%) and 95 participated in round III (response rate 80.5%). Responses indicated that, following a minimum 3-week period of rest and recovery, an individualised timeline and gradual return to running progression can be considered. Screening for medical and psychological concerns, current physical capacity, and prior training history is recommended prior to a return to running.This study proposes recommendations for the initial guidance on return-to-running postpartum, framed in the context of current research and consensus from professionals. Future research is needed to strengthen and validate specific recommendations and develop guidelines for best practice when returning-to-running after childbirth.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".