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Record W7048350084

L’impact de la migraine sur le rendement et l’engagement occupationnels dans les activités de la vie quotidienne et domestique, et dans les loisirs

2024· other· fr· W7048350084 on OpenAlexfundno aff

Bibliographic record

VenueLe dépôt institutionnel (Université du Québec à Trois-Rivières) · 2024
Typeother
Languagefr
FieldEngineering
TopicAdvanced Electrical Measurement Techniques
Canadian institutionsnot available
FundersUniversité du Québec à Trois-Rivières
KeywordsContext (archaeology)Work (physics)Independence (probability theory)
DOInot available

Abstract

fetched live from OpenAlex

Background: It is estimated that 26% of Canadians living with migraines are limited in their participation in meaningful activities due to this condition (Statistics Canada, 2014).However, beyond the impact on work, little research has explored how migraines affect personal care, leisure activities, and domestic tasks.Moreover, current studies rarely consider the meaning that individuals with migraines attribute to their daily functioning.Finally, while the literature clearly highlights gaps in primary medical care for migraines in Canada, it does not delve into the lived experiences of individuals regarding this care.Research questions: This study aimed to answer the following questions: 1) What is the impact of frequent migraines on occupational performance and engagement in activities of daily living, domestic activities, and leisure activities?2) How do individuals with migraines perceive their management of this condition, and how does this affect their occupational engagement?Conceptual Framework: To guide the exploration of the topic, it was necessary to establish a consensus regarding the definition of migraines.The Canadian Model of Occupational Performance and Engagement (CMOP-E) was selected as the conceptual framework for this project.This model not only introduces the concepts of occupational performance and engagement but also provides relevant occupational categories for structuring the research.Methodology: An exploratory phenomenological study was conducted through semistructured individual interviews and the completion of a socio-demographic questionnaire.Participants were selected using network and snowball sampling.Quantitative data were subjected to simple descriptive analysis, while qualitative data were analyzed using Giorgi's content analysis method (1997).Results: Five individuals with migraines participated in the study.For the personal care activities, participants adjusted certain lifestyle habits to better manage their migraines, though these adjustments did not bring them enjoyment.The productivity activities were often neglected and/or adjusted, with participants expressing mixed levels of satisfaction.While leisure activities promoting well-being were prioritized, occupational engagement in these activities was not entirely satisfactory.Finally, four participants reported satisfaction with the healthcare services they received.However, none currently seek occupational therapy to support their daily functioning.Discussion: The findings align with prior research and underscore the critical role of occupational therapists in this population.This section also emphasizes the need to implement strategies to limit the impact of factors that predispose to or exacerbate migraines.Such strategies could ensure satisfactory occupational engagement for individuals with migraines.Conclusion: This research project demonstrates that migraines have adverse effects on occupational performance and engagement, primarily in leisure and productivity activities, while personal care activities are often used as recovery strategies.Despite this, individuals with migraines do not currently utilize occupational therapy services, even though the symptom management strategies highlighted by participants support the role of occupational therapists as experts in enabling occupation.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.806
Threshold uncertainty score0.390

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0180.002

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 head0.017
GPT teacher head0.254
Teacher spread0.236 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2024
Admission routes1
Has abstractno

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