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Record 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 on OpenAlexvenueno aff
John W. Loy

Bibliographic record

VenueEvidence Based Library and Information Practice · 2006
Typearticle
Languageen
FieldHealth Professions
TopicHealth Literacy and Information Accessibility
Canadian institutionsnot available
Fundersnot available
KeywordsCINAHLInformation needsMEDLINECancerInclusion (mineral)MedicineInformation seekingEnglish languageComputer scienceFamily medicineInformation retrievalPsychologyPsychological interventionLibrary scienceInternal medicineNursing

Abstract

fetched live from 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.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.173
Threshold uncertainty score0.853

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.159
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 head0.018
GPT teacher head0.357
Teacher spread0.339 · 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.

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

Citations1
Published2006
Admission routes1
Has abstractyes

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