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Enregistrement W1719818235 · doi:10.18438/b8g01g

Information Needs of Cancer Patients are Influenced by Time Since Diagnosis, Stage of Cancer, Patients’ Age, and Preferred Role in Treatment-related Decisions

2006· article· en· W1719818235 sur OpenAlexvenueno aff
John W. Loy

Notice bibliographique

RevueEvidence Based Library and Information Practice · 2006
Typearticle
Langueen
DomaineHealth Professions
ThématiqueHealth Literacy and Information Accessibility
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésCINAHLInformation needsMEDLINECancerInclusion (mineral)MedicineInformation seekingEnglish languageComputer scienceFamily medicineInformation retrievalPsychologyPsychological interventionLibrary scienceInternal medicineNursing

Résumé

récupéré en direct d'OpenAlex

A review of:
 
 Kalyani, Ankem. “Factors Influencing Information Needs Among Cancer Patients: A Meta-Analysis.” Library & Information Science Research; 28.1 (2006) 7-23. 
 
 Objective – The author aims to study the aggregate influence of demographic and situational variables on the information needs of cancer patients, in order to inform the provision of information to those patients.
 
 Design – Meta-analysis.
 
 Setting – Research articles published in the MEDLINE and CINAHL databases.
 
 Subjects – English language studies published between 1993 and 2003. An initial search set of 196 studies from MEDLINE and 283 studies from CINAHL were identified. Following rigorous assessment, 12 studies met the inclusion criteria.
 
 Methods – A comprehensive search of the databases was conducted, initially combining “neoplasm” with “cancer patients” using the Boolean “or”. These results were then combined with five separate searches using the following terms; information need(s), information seeking, information seeking behaviour, information source(s) and information resource(s). This identified in total 479 English language articles. Based on a review of titles and abstracts, 110 articles were found covering information resources or the information needs of cancer patients. These articles were then subjected to the further inclusion criteria and limited to studies which included: analysis of information needs and/or information sources of cancer patients; adults as subjects of the research; and application of quantitative research methods and relevant statistics. 
 
 This eliminated a further 35 papers. Twelve of the remaining 75 studies were selected for meta-analysis based on their use of the same variables measured consistently in comparable units. The final 12 studies included various forms of cancer, and no distinction was made among them. All 12 studies appeared in peer-reviewed journals.
 
 Main results – The meta-analysis found there was consistently no difference between the information needs of men and women. Five subsets were identified within the meta-analysis, and findings for each can be stated as follows:
 
 The younger the age of the patient, the greater their overall need for information was likely to be.
 
 During treatment, the time elapsed from the diagnosis to the information need was not significant. Once identified, the information need remained constant.
 
 During treatment and post-treatment phases, the time elapsed from the diagnosis to the information need made no significant difference, with the information need remaining constant and continuing into the post-treatment phase.
 
 The stage of cancer made no difference to the need for information. Those patients in the advanced stages of cancer required an equal amount of information to those in the early stages of cancer.
 
 The individual patient’s preferred role in treatment-related decisions made a difference to the information need. Patients who took an active role in treatment-related decisions had a greater need for information than those who did not take an active role.
 
 Conclusion – Findings from this meta-analysis can be used to guide information provision to cancer patients, specifically taking patient age and preferred role in treatment decision-making into consideration. Further research into the reasons behind the lower information needs among older patients is called for by the author.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,002
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCommunication savante
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 enseignants0,173
Score d'incertitude au seuil0,853

Scores Codex et Gemma par catégorie

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 technologies0,0000,000
Communication savante0,0000,159
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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 Opus0,018
Tête enseignante GPT0,357
Écart entre enseignants0,339 · 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 tête enseignante, pas un consensus.

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

Citations1
Publié2006
Routes d'admission1
Résumé présentoui

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