Navigating formula shortages: associations of parental perspectives on transitioning to alternative infant formulas for cow's milk protein allergy during the 2022 national formula shortage
Bibliographic record
Abstract
The COVID-19 pandemic led to supply chain disruptions causing a severe shortage of infant formula. The shortage impacted parents of infants with cow's milk protein allergy (CMPA) who rely on specialized formulas. However, research on parent perspectives during formula shortages is limited. We aimed to understand the factors guiding parents' decisions when transitioning to alternative amino acid formula (AAF) or extensively hydrolyzed formula (eHF) during the national formula shortage. We conducted a survey using the ZSMoments platform and found that before the shortage, parents valued safety (83%), tolerability (78%), and reputability (78%) as primary factors in selecting eHFs and AAFs. Post-shortage, formula tolerability (86%), assurance (84%), and safety (80%) gained more importance. Among those switching eHF ( n = 54), health care provider recommendations (81%), reputability (78%), taste (78%), and tolerability (78%) were rated as “extremely important.” Among those switching AAF ( n = 26), top factors included tolerability (77%), assurance (73%), safety (73%), cost-effectiveness (73%), and formula trustworthiness (73%). These data suggest that parents carefully weigh various factors when managing their child's CMPA and transitioning to different AAF or eHF options.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".