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Record W3132128201 · doi:10.1177/0340035221991563

The information needs and behaviour of the Egyptian elderly living in care homes: An exploratory study

2021· article· en· W3132128201 on OpenAlexaboutno aff
Essam Mansour

Bibliographic record

VenueIFLA Journal · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsnot available
Fundersnot available
KeywordsLonelinessQuarter (Canadian coin)RecreationGerontologyElderly peopleInformation needsExploratory researchHealth informationPsychologyMedical informationHealth careMedicineSociologyFamily medicineSocial psychologyGeographySocial scienceLibrary science

Abstract

fetched live from OpenAlex

The purpose of this study is to investigate the information-seeking behaviour of the Egyptian elderly, including their information needs. A sample of 63 elderly people living in care homes was taken. It was divided into five focus groups. Of the 63 elderly people, 40 were men (63.5%) and 23 women (36.5%). Almost half (47.6%) ranged in aged from 61 to 70. About a quarter (23%) of them held a high school diploma. The highest percentage (28.6%) was labelled as average-income people. The highest percentage (60.3%) was also found to be widows or widowers. The types of information used most by the Egyptian elderly related to physical, medical/health, social, rational and recreational needs. Their information sources varied between formal and informal sources. Nearly two-thirds (63.5%) of them showed that limited knowledge, lack of interest, poor information awareness, aging, loneliness and health problems were the most significant obstacles they faced when seeking information.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.274
Teacher spread0.262 · 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 designQualitative
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

Citations6
Published2021
Admission routes1
Has abstractyes

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