What Is Left Unsaid: An Interpretive Description of the Information Needs of Parents of Children With Asthma
Bibliographic record
Abstract
Parents of children with asthma provide the vast majority of day-to-day asthma care. Understanding their information needs is an essential step to provide meaningful and effective family-centered asthma education. To gain insight into the information needs and information deficits of parents of children with asthma, we conducted an interpretive descriptive study to capture the perspectives of 21 parents from diverse backgrounds whose 23 children with asthma had a range of illness trajectories and management scenarios. Parents were purposively sampled from two asthma clinics and one pediatric emergency department in a large urban center in North America. Semi-structured interviews were conducted in 2011-2012. In data analysis, parents' self-identified information needs were distinguished from analysts' interpretations of information deficits. Participants' knowledge did not always reflect time since diagnosis, and information needs and deficits persisted for years. Parents often reported receiving little or no little or no education about asthma and its management. An asthma management information hierarchy was identified, starting with the most foundational, recognizing severity; followed by acute management; prevention versus crisis orientation; and knowing "about" asthma. In the absence of adequate and accurate education, parents' beliefs about the nature of asthma as an acute rather than chronic condition shaped their asthma management decisions and information-seeking behaviors. Information deficits were affected by interactions with health care providers. These parents' pervasive unmet information needs and deficits highlight the need for comprehensive, problem-oriented asthma education.
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 | 0.014 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".