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Record W4404473521 · doi:10.1177/10497323241292279

Adversity and Resilience: The Stories of People Living With HIV in Ecuador

2024· article· en· W4404473521 on OpenAlexaff
Emilia C. Zamora-Moncayo, Bernarda Herrera-Díaz, Valeria Troya

Bibliographic record

VenueQualitative Health Research · 2024
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsPublic Health OntarioUniversity of Toronto
FundersUniversidad San Francisco de Quito
KeywordsThematic analysisContext (archaeology)Psychological resilienceNarrativePsychologyMental healthHealth careQualitative researchSocial psychologySociologyPublic relationsPolitical sciencePsychiatryGeographySocial science

Abstract

fetched live from OpenAlex

People living with HIV (PLHIV) in Ecuador experience challenges including discrimination, violence, and limited access to healthcare, which impacts their mental health and well-being. However, research shows that PLHIV also rely on social resources to foster resilience. In the Ecuadorian context, there is no literature exploring these narratives, which results in a lack of qualitative data to improve the reality of PLHIV in the country. To gain a deeper understanding of these stories, 15 semi-structured interviews were undertaken (15 verbatim hours) within the context of a peer- and professional-led support group for PLHIV and were analyzed through a thematic approach based on Skovdal and Daniel's conceptual framework on resilience and adversity. Findings suggest that PLHIV face multifaceted challenges across the home, community, and political-economy spheres. Families and communities can elicit pain and fear, leading individuals to avoid discussing their diagnosis due to ongoing rejection. Further, discrimination perpetuated within the public health sector, as well as societal violence, exacerbates adversity. Nevertheless, participants stress the indispensable role of family support, community networks, and accessible healthcare in fostering resilience. Specifically, support, emotional reassurance, and willingness to learn enabled PLHIV to build resilience. These findings emphasize the need for approaches that counter discrimination, enhance well-being, ensure integral and intersectional healthcare access, and promote knowledge around HIV.

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)0.010
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.135
Threshold uncertainty score0.721

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.160
GPT teacher head0.546
Teacher spread0.386 · 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.

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
Published2024
Admission routes1
Has abstractyes

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