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Record W4395110453 · doi:10.5539/ijps.v16n2p40

Cultural Perceptions and Awareness of Dementia Amongst the People of Ibiaku Issiet Community: A Qualitative Study

2024· article· en· W4395110453 on OpenAlexvenueno aff
Imaobong Olsson, Hannah Akpan, Imoh Ekpenyong Akpan, Uwem Ekpenyong Akpan, Ndu Ekpenyong Akpan

Bibliographic record

VenueInternational Journal of Psychological Studies · 2024
Typearticle
Languageen
FieldPsychology
TopicHealth and Well-being Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyPerceptionQualitative researchDementiaSocial psychologySociologySocial science

Abstract

fetched live from OpenAlex

This study investigates the perceptions and interpretations of dementia within the Ibiaku Issiet community, focusing on individuals' understanding of dementia, its symptoms, and its impact on affected individuals and their families. A qualitative approach was employed, utilizing semi-structured interviews with open-ended questions. Fifteen participants, comprising men and women aged 34 to 76, were selected from the community, with inclusion criteria limited to those who have a family member with dementia. Analysis of the data revealed various themes, including spiritual influences, punishment beliefs, limited awareness, stigmatization, spiritual beliefs, lack of accessibility to support services, frustration, helplessness, and a call for educational awareness and support initiatives. These findings highlight the importance of cultural interpretations in understanding dementia and underscore the need for increased awareness and support, particularly in communities lacking awareness. Recommendations include government intervention to provide educational programs and allocate resources for tailored support programs for caregivers within diverse cultural contexts.

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)0.005
metaresearch head score (Gemma)0.005
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0100.006
Scholarly communication0.0030.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.174
GPT teacher head0.551
Teacher spread0.377 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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