MétaCan
Menu
Back to cohort
Record W1981567771 · doi:10.1371/journal.pone.0047815

Attitudes toward Infection Prophylaxis in Pediatric Oncology: A Qualitative Approach

2012· article· en· W1981567771 on OpenAlexafffund
Caroline Diorio, Deborah Tomlinson, Katherine Boydell, Dean A. Regier, Marie‐Chantal Ethier, Amanda Alli, Sarah Alexander, Adam Gassas, Jonathan Taylor, Charis Kellow, Denise Mills, Lillian Sung

Bibliographic record

VenuePLoS ONE · 2012
Typearticle
Languageen
FieldMedicine
TopicNeutropenia and Cancer Infections
Canadian institutionsMcMaster UniversityCanadian Centre for Applied Research in Cancer ControlSickKids FoundationInstitute for Clinical Evaluative SciencesHospital for Sick Children
FundersCanadian Institutes of Health ResearchPediatric Oncology Group of Ontario
KeywordsMedicineThematic analysisQualitative researchFamily medicineInfection controlHealth professionalsIntensive care medicineHealth careNursing

Abstract

fetched live from OpenAlex

BACKGROUND: The risks and benefits of infection prophylaxis are uncertain in children with cancer and thus, preferences should be considered in decision making. The purpose of this report was to describe the attitudes of parents, children and healthcare professionals to infection prophylaxis in pediatric oncology. METHODS: THE STUDY WAS COMPLETED IN THREE PHASES: 1) An initial qualitative pilot to identify the main attributes influencing the decision to use infection prophylaxis, which were then incorporated into a discrete choice experiment; 2) A think aloud during the discrete choice experiment in which preferences for infection prophylaxis were elicited quantitatively; and 3) In-depth follow up interviews. Interviews were recorded verbatim and analyzed using an iterative, thematic analysis. Final themes were selected using a consensus approach. RESULTS: A total of 35 parents, 22 children and 28 healthcare professionals participated. All three groups suggested that the most important factor influencing their decision making was the effect of prophylaxis on reducing the chance of death. Themes of importance to the three groups included antimicrobial resistance, side effects of medications, the financial impact of outpatient prophylaxis and the route and schedule of administration. CONCLUSION: Effect of prophylaxis on risk of death was a key factor in decision making. Other identified factors were antimicrobial resistance, side effects of medication, financial impact and administration details. Better understanding of factors driving decision making for infection prophylaxis will help facilitate future implementation of prophylactic regiments.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.369

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.170
GPT teacher head0.376
Teacher spread0.206 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2012
Admission routes2
Has abstractyes

Explore more

Same venuePLoS ONESame topicNeutropenia and Cancer InfectionsFrench-language works237,207