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Record W2233081715 · doi:10.1155/2008/247027

Asthma Counselling Targeted to Removal of Domestic Animals

2008· article· en· W2233081715 on OpenAlexaff
Louise Hagan, Pierre Valois, Hélène Patenaude, Hélène Boutin, Louis‐Philippe Boulet, France Lafrenière

Bibliographic record

VenueCanadian Respiratory Journal · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMedicineAsthmaFamily medicineInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: To create and evaluate the efficacy of a short individualized educational intervention program, based on Prochaska's transtheoretical model, for a six-month period in a population of adult asthma patients living with domestic animals but sensitized to these pets. METHODS: A randomized, controlled study using a pretested questionnaire was conducted at three different times (pretest, and at three and six months postintervention). RESULTS: Eleven members (29%) of the intervention group and eight members (21%) of the control group removed their pets within six months (X(2)=3.23; P>0.35). The two groups showed similar improvements in their perception of the benefits of pet removal and in their level of belief that they could do it. The experimental group showed a greater improvement in knowledge acquisition about asthma and allergies than the control group (P<0.05). Both experimental and standard educational interventions were effective in facilitating progression through the stages of behavioural change. CONCLUSION: Overall, the results do not support the utility of behavioural change educational intervention, tailored to the transtheoretical model stage of the individual, in the context of convincing patients to remove their pets from their homes. However, the decision-making aid appears to be helpful in raising awareness of the problem of asthma and allergy in the patient, and in developing appropriate knowledge.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.909
Threshold uncertainty score0.530

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 head0.030
GPT teacher head0.315
Teacher spread0.286 · 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 designNot applicable
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

Citations4
Published2008
Admission routes1
Has abstractyes

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