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Enregistrement W2601736198

Health literacy, language, and understanding of colon cancer prevention information among English-as-a-second-language older Chinese immigrant women to Canada

2010· dissertation· en· W2601736198 sur OpenAlexaboutno aff
Laura Todd

Notice bibliographique

RevueUWSpace (University of Waterloo) · 2010
Typedissertation
Langueen
DomaineMedicine
ThématiqueGlobal Cancer Incidence and Screening
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésImmigrationLiteracyHealth literacyMedicineLanguage barrierEnglish languageGerontologyLinguisticsPsychologyPolitical scienceHealth carePedagogyMathematics education
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Introduction: Colon cancer incidence and mortality rates in Canada are among the highest worldwide. If detected early colon cancer is highly curable and regular screening can significantly decrease risk of colon cancer mortality. Despite this, screening rates in Canada are consistently low and immigrant and senior populations are particularly vulnerable due to low health literacy and language barriers. This research consists of three studies that were designed to explore the cancer prevention experiences of older English-as-a-Second Language (ESL) Chinese immigrant women in Canada. This includes an investigation of colon and breast cancer screening utilization, health literacy skills and comprehension of colon cancer prevention information, and experiences and preferences when seeking cancer information by these immigrant women. \nMethods: A convenience sample of 110 Mandarin and Cantonese-speaking ESL immigrant women were recruited from two Southern Ontario communities. For study inclusion participants were required to: (1) be 50 years of age or older, (2) have immigrated to Canada, (3) have Cantonese or Mandarin as their first language and English as their second language, and (4) be able to read in English. Participants were excluded if they or their spouse had been previously diagnosed with any type of cancer. Participants completed a battery of questionnaires assessing demographic characteristics, use of breast and colon cancer screening, acculturation, self-efficacy, health beliefs and health literacy. Health literacy was assessed using the Short Test of Functional Health Literacy in Adults (S-TOFHLA) and comprehension of a colon cancer prevention information sheet from Cancer Care Ontario was assessed using the cloze procedure. Participants participated in a semi-structured interview to explore cancer information seeking preferences and experiences, and their understanding of cancer prevention information. Multivariate logistic regression was used to identify predictors of colon and breast cancer screening. To identify variables significantly associated with performance on the S-TOFHLA and cloze test regression analyses were performed. Directed content analysis was used to identify themes associated with barriers to cancer information seeking and understanding that emerged from the interviews. \nResults: Study #1: There was high self-reported screening for breast and colon cancer. Eighty-five percent of the women were current mammography screeners and 75% were current colon cancer screeners. Recommendation from a physician (OR=.140; 95% CI= .044, -.448), having a female physician (OR=.141; 95% CI= .033, .591), and high or moderate proficiency in English (OR=.283; 95% CI= .089, .902) significantly predicted mammography screening. Physician recommendation (OR=.103; 95% CI= .031, .349), first language (OR= 1.85; 95% CI= .055, .628) and higher self-efficacy (OR= 3.613; 95% CI= 1.179, 11.070) predicted use of colon cancer screening. Other important predictors included greater health literacy and longer residency in Canada. Study #2: Only 38.7% of the women had adequate health literacy on S-TOFHLA and 54.3% had adequate comprehension of the colon cancer information. Comprehension of the colon cancer information was significantly lower among women who received the information in English, compared to those who received the information in Chinese (p<0.01). Age, acculturation, self-reported proficiency reading English, and education were significant predictors of health literacy but varied depending on the measure (S-TOFHLA, cloze) and language of information (English, Chinese). Study #3: There were unique health information seeking preferences among the older Chinese immigrant women including a strong preference for interpersonal and interactive cancer information from their physician and trusted others, such as friends and family. Barriers to cancer information seeking included language difficulties and limited time with physicians. Differences in health literacy did not distinguish the women on any of the major themes. \nConclusion: Language, culture, health literacy and the role of the physician emerged across all three studies examining the cancer prevention experiences of older Chinese immigrant women. While language concordant educational materials may improve understanding of cancer information, the results from this study suggest that it is important to consider factors other than language alone and to address important cultural issues that play a role in the access, use, and understanding of cancer information.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,002
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,150
Score d'incertitude au seuil0,302

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0020,001
Communication savante0,0010,000
Science ouverte0,0000,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,009
Tête enseignante GPT0,266
Écart entre enseignants0,257 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2010
Routes d'admission1
Résumé présentoui

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