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Record W3119271654 · doi:10.1093/ofid/ofaa439.1231

1045. Treatment-Related Physical, Emotional, and Psychosocial Challenges and their Impact on Indicators of Quality of Life

2020· article· en· W3119271654 on OpenAlexaboutno aff
Patricia Rios, Brent Allan, Chinyere Okoli, Benjamin Young, Erika Castellanos, Garry Brough, Anton Eremin, Giulio Maria Corbelli, Marvelous Muchenje, Marta Mc Britton, Nicolas Van de Velde

Bibliographic record

VenueOpen Forum Infectious Diseases · 2020
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePsychosocialPillQuality of life (healthcare)OddsAdverse effectOdds ratioFamily medicineDemographyGerontologyLogistic regressionPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background Despite effectiveness of antiretroviral therapy (ART), some people living with HIV (PLHIV) still face barriers to daily oral ART adherence, including inconvenient scheduling, food requirements, adverse effects, and privacy concerns. We characterized treatment-related physical, emotional, and psychosocial challenges among PLHIV from 25 countries. Methods 2389 PLHIV adults on ART were surveyed in the 2019 Positive Perspectives Study, a standardized, self-reported survey of HIV patients aged 18-84 years on treatment. Data were collected on ART-related perceptions and behaviors. Descriptive and multivariable analyses were performed. Results Most participants were male (67.9%), aged < 50 years (70.7%), and reported viral suppression (74.1%). ART-related challenges included cueing of bad memories (58.4%), disguising HIV pills (57.9%), stress (33.3%), and difficulty swallowing pills (33.1%). Privacy and emotional challenges were generally similar between the USA and Canada (Figure 1). In the pooled sample, those who felt limited by their ART had higher odds of reporting suboptimal overall health (AOR 1.90, 95%CI:1.57-2.29), treatment dissatisfaction (AOR 2.21, 95%CI:1.82-2.69), and suboptimal adherence (AOR 1.90, 95%CI:1.57-2.29). Difficulty swallowing, any side effects, and privacy concerns were associated with increased odds of suboptimal overall health (AOR 2.10, 1.88, and 1.43, respectively) and suboptimal adherence (AOR 2.51, 1.50, and 1.87, respectively; all P< 0.05); results for other outcomes are in Figure 2. Overall, 12.6% (302/2389) had shared their HIV status solely with their primary HIV provider, whereas 6.8% (163/2389) “always” shared their HIV status. Only 52.0% were comfortable discussing ART-related privacy concerns with providers, although 29.0% overall missed ≥1 ART dose in the past month from privacy concerns. Overall, 54.7% preferred a nondaily regimen if their HIV stays suppressed, while 72.3% were open to ART with fewer therapies. Figure 1 Figure 2 Conclusion This study identified several challenges with ART among PLHIV, underscoring the need for increased flexibility of ART delivery to meet diverse patient needs. Addressing these needs may improve overall health outcomes for more PLHIV on therapy. Disclosures Patricia De Los Rios, MSc, GlaxoSmithKline (Shareholder)ViiV Healthcare (Employee) Chinyere Okoli, PharmD, MSc, DIP, ViiV Healthcare (Employee) Benjamin Young, MD, PhD, ViiV Healthcare (Employee) Garry Brough, BA Joint Hons in French/Italian, ViiV Healthcare (Employee, Independent Contractor, Other Financial or Material Support, Speakers Fees and Honoraria) Anton Eremin, MD, ViiV Healthcare (Advisor or Review Panel member) Marvelous Muchenje, BSW, MSc. in Global Health, ViiV Healthcare Canada (Employee) Nicolas Van de Velde, PhD, GlaxoSmithKline (Shareholder)ViiV Healthcare (Employee)

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.043
GPT teacher head0.385
Teacher spread0.342 · 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 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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