Getting Help During Active Pain Crises in Sickle Cell Disease: Patient and Caregiver Perspectives in Canada
Bibliographic record
Abstract
Plain Language SummaryWhat is this summary about?This is a plain language summary of an article originally published in Patient Preference and Adherence. This study aimed to identify the notable symptoms and impacts of sickle cell disease from the point of view of individuals living with sickle cell disease and their caregivers. The study also sought to understand the factors involved in individuals living with sickle cell disease’ and caregivers’ decisions and preferences if and when they seek care during a pain crisis. This summary describes: the symptoms experienced by adolescents and adults living with sickle cell disease and their severity; the treatments they and their caregivers prefer to use when they are experiencing a pain crisis; and the factors that go into deciding when and whether individuals living with sickle cell disease and their caregivers should seek outside help -- to go to a hospital, for example - during a pain crisis.What were the results?Individuals living with sickle cell disease undergoing an acute pain crisis and their caregivers consider many factors when deciding whether to seek care at a medical facility. These include: The intensity of their symptomsIf the facility has a treatment plan for them already in placeIf the facility has long wait timesIf the facility has an understanding and compassionate staffThe individual's age and ability to manage their daily responsibilities Racial bias, shown in the actions and lack of empathy of Emergency Department staff toward individuals living with sickle cell disease, frequently factored into the individuals' and caregivers’ decision-making and hinders their ability to get the treatment needed during a pain crisis.What do the results mean?There is a need for a unified care team at medical facilities that treats all individuals living with sickle cell disease with the same high level of empathy and treatment quality and for a strong support system for individuals living with sickle cell disease outside of the hospital or clinic.This is an abstract of the Plain Language Summary of Publication article.View the full Plain Language Summary PDF of this article to read the full-textLink to original article here
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.010 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".