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Record W3005024870 · doi:10.2196/15680

Improving Retention in Care and Promoting Adherence to HIV Treatment: Protocol for a Multisite Randomized Controlled Trial of Mobile Phone Text Messaging

2020· article· en· W3005024870 on OpenAlexvenueno aff
Elvis Asangbeng Tanue, Dickson Shey Nsagha, Nana Njamen Théophile, Jules Clément Nguedia Assob

Bibliographic record

VenueJMIR Research Protocols · 2020
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsnot available
Fundersnot available
KeywordsShort Message ServiceRandomized controlled trialMedicineMobile phonemHealthIntervention (counseling)Health careDiscontinuationPhoneProtocol (science)Psychological interventionFamily medicineNursingAlternative medicineComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: The World Health Organization has prioritized the use of new technologies to assist in health care delivery in resource-limited settings. Findings suggest that the use of SMS on mobile phones is an advantageous application in health care delivery, especially in communities with an increasing use of this device. OBJECTIVE: The main aim of this trial is to assess whether sending weekly motivational text messages (SMS) through mobile phones versus no text messaging will improve retention in care and promote adherence to treatment and health outcomes among patients receiving HIV treatment in Fako Division of Cameroon. METHODS: This is a multisite randomized controlled single-blinded trial. Computer-generated random block sizes shall be used to produce a randomization list. Participants shall be randomly allocated into the intervention and control groups determined by serially numbered sealed opaque envelopes. The 156 participants will either receive the mobile phone text message or usual standard of care. We hypothesize that sending weekly motivational SMS reminders will produce a change in behavior to enhance retention; treatment adherence; and, hence, health outcomes. Participants shall be evaluated and data collected at baseline and then at 2, 4, and 6 months after the launch of the intervention. Text messages shall be sent out, and the delivery will be recorded. Primary outcome measures are retention in care and adherence to treatment. Secondary outcomes are clinical (weight, body mass index), biological (virologic suppression, tuberculosis coinfection), quality of life, treatment discontinuation, and mortality. The analysis shall be by intention-to-treat. Analysis of covariates shall be performed to determine factors influencing outcomes. RESULTS: Recruitment and random allocation are complete; 160 participants were allocated into 3 groups (52 in the single SMS, 55 in the double SMS, and 53 in the control). Data collection and analysis are ongoing, and statistical results will be available by the end of August 2019. CONCLUSIONS: The interventions will contribute to an improved understanding of which intervention types can be feasible in improving retention in care and promoting adherence to antiretroviral therapy. TRIAL REGISTRATION: Pan African Clinical Trial Registry in South Africa PACTR201802003035922; https://pactr.samrc.ac.za/TrialDisplay.aspx?TrialID=3035. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/15680.

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)0.046
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.081
Threshold uncertainty score0.272

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0460.034
Meta-epidemiology (narrow)0.0070.004
Meta-epidemiology (broad)0.0130.006
Bibliometrics0.0030.004
Science and technology studies0.0050.005
Scholarly communication0.0040.004
Open science0.0040.003
Research integrity0.0100.012
Insufficient payload (model declined to judge)0.0810.014

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 head0.233
GPT teacher head0.600
Teacher spread0.368 · 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 designRandomized trial
Domainnot available
GenreProtocol

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

Citations11
Published2020
Admission routes1
Has abstractyes

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