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Record W4414089803 · doi:10.1177/02646196251369668

Realizing life goals: Lived experience of young and middle-age adults with adult-onset vision impairment in Nigeria

2025· article· en· W4414089803 on OpenAlexaff
Kelechukwu Ahaiwe, Emmanuel Bassey, Moses Chukwuemeka Ohamaeme, Caroline Ellison

Bibliographic record

VenueBritish Journal of Visual Impairment · 2025
Typearticle
Languageen
FieldHealth Professions
TopicOlder Adults Driving Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsFeelingPsychological interventionIntervention (counseling)Visual impairmentLived experienceQualitative researchRehabilitationEveryday lifeActivities of daily living

Abstract

fetched live from OpenAlex

This study explored the life goals implications of adult-onset vision impairment among young and middle-aged adults living in Nigeria. Using a qualitative descriptive design approach, Eight young and middle-aged adults with adult-onset vision impairment were recruited for the study. Data were gathered using semi-structured individual interviews which focused on discussing life goals (i.e., educational, employment, and social goals) and barriers to goals achievement. Three overlapping themes that reflect participants’ accounts were identified, namely, (1) relationship-related challenges, (2) crumbled education and employment pursuits, and (3) strategies to achieve goals and feeling hopeful. Findings indicate that adult-onset vision impairment can interfere with educational, employment, and relationship goals of young and middle-aged adults living in Nigeria. This study suggests that vision rehabilitation intervention can be optimized by incorporating targeted supports and interventions around achieving an individual’s life goals in the rehabilitative management plan.

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)0.002
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0040.002
Scholarly communication0.0020.002
Open science0.0000.003
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 head0.030
GPT teacher head0.391
Teacher spread0.361 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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