MétaCan
Menu
← Back to cohort
Record W4389165975 · doi:10.1186/s12913-023-10215-1

Enabling Adherence to Treatment (EAT): a pilot study of a combination intervention to improve HIV treatment outcomes among street-connected individuals in western Kenya

2023· article· en· W4389165975 on OpenAlexafffund
Mia Kibel, Monicah Nyambura, Lonnie Embleton, Reuben Kiptui, Omar Galárraga, Edith Apondi, David Ayuku, Paula Braitstein

Bibliographic record

VenueBMC Health Services Research · 2023
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsMedicineMcNemar's testViral loadDescriptive statisticsIntervention (counseling)Psychological interventionNursing researchFamily medicineHuman immunodeficiency virus (HIV)Physical therapyNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Street-connected individuals (SCI) in Kenya experience barriers to accessing HIV care. This pilot study provides proof-of-concept for Enabling Adherence to Treatment (EAT), a combination intervention providing modified directly observed therapy (mDOT), daily meals, and peer navigation services to SCI living with HIV or requiring therapy for other conditions (e.g. tuberculosis). The goal of the EAT intervention was to improve engagement in HIV care and viral suppression among SCI living with HIV in an urban setting in Kenya. METHODS: This pilot study used a single group, pre/post-test design, and enrolled a convenience sample of self-identified SCI of any age. Participants were able to access free hot meals, peer navigation services, and mDOT 6 days per week. We carried out descriptive statistics to characterize participants' engagement in EAT and HIV treatment outcomes. We used McNemar's chi-square test to calculate unadjusted differences in HIV outcomes pre- and post-intervention among participants enrolled in HIV care prior to EAT. We compared unadjusted time to initiation of antiretroviral therapy (ART) and first episode of viral load (VL) suppression among participants enrolled in HIV care prior to EAT vs. concurrently with EAT using the Wilcoxon rank sum test. Statistical significance was defined as p < 0.05. We calculated total, fixed, and variable costs of the intervention. RESULTS: Between July 2018 and February 2020, EAT enrolled 87 participants: 46 (53%) female and 75 (86%) living with HIV. At baseline, 60 out of 75 participants living with HIV (80%) had previously enrolled in HIV care. Out of 60, 56 (93%) had initiated ART, 44 (73%) were active in care, and 25 (42%) were virally suppressed (VL < 1000 copies/mL) at their last VL measure in the 19 months before EAT. After 19 months of follow-up, all 75 participants living with HIV had enrolled in HIV care and initiated ART, 65 (87%) were active in care, and 44 (59%) were virally suppressed at their last VL measure. Among the participants who were enrolled in HIV care before EAT, there was a significant increase in the proportion who were active in HIV care and virally suppressed at their last VL measure during EAT enrollment compared to before EAT enrollment. Participants who enrolled in HIV care concurrently with EAT had a significantly shorter time to initiation of ART and first episode of viral suppression compared to participants who enrolled in HIV care prior to EAT. The total cost of the intervention over 19 months was USD $57,448.64. Fixed costs were USD $3623.04 and variable costs were USD $63.75/month/participant. CONCLUSIONS: This pilot study provided proof of concept that EAT, a combination intervention providing mDOT, food, and peer navigation services, was feasible to implement and may support engagement in HIV care and achievement of viral suppression among SCI living with HIV in an urban setting in Kenya. Future work should focus on controlled trials of EAT, assessments of feasibility in other contexts, and cost-effectiveness studies.

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)0.003
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: Non-randomized trial · Consensus signal: Non-randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.127
GPT teacher head0.478
Teacher spread0.351 · 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 designNon-randomized trial
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

Citations9
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueBMC Health Services Research→Same topicHIV/AIDS Research and Interventions→French-language works237,207→