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Record W4297186570 · doi:10.2196/42216

Incentives and Reminders to Improve Long-term Medication Adherence (INMIND): Protocol for a Pilot Randomized Controlled Trial

2022· article· en· W4297186570 on OpenAlexvenueno aff
Chad Stecher, Ishita Ghai, Lillian Lunkuse, Peter Wabukala, Mary Odiit, Agnes Nakanwagi, Sebastian Linnemayr

Bibliographic record

VenueJMIR Research Protocols · 2022
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
FundersNational Institute of Mental Health
KeywordsRandomized controlled trialIncentiveProtocol (science)Medication adherenceMedicineTerm (time)Physical therapyPsychologyAlternative medicineInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Nonadherence to antiretroviral therapy (ART) among people living with HIV is a crucial barrier to attaining viral suppression globally. Existing behavioral interventions have successfully increased ART adherence, but typically show only short-term impact that dissipates after the interventions are withdrawn. OBJECTIVE: This study aims to test the feasibility, acceptability, and preliminary efficacy of a novel intervention that uses SMS text messages and conditional incentives to support ART initiators in establishing pill-taking habits. METHODS: A sample of 150 participants aged ≥18 years who have initiated ART in the preceding 3 months will be recruited from Mildmay Uganda in Kampala, Uganda. All (150/150, 100%) participants will be educated on the anchoring strategy and will choose an existing routine to pair with their daily ART adherence from a set of 3 suggested routines: getting dressed in the morning, eating breakfast, or eating dinner. Then, participants will be randomized to receive either usual care (control group: 50/150, 33.3%) or 1 of the 2 interventions delivered over 3 months: daily SMS text message reminders to follow their chosen anchoring plan (messages group; treatment group 1: 50/150, 33.3%) or daily SMS text messages and incentives conditional on taking their ART medication around the time of their chosen anchor (incentives group; treatment group 2: 50/150, 33.3%). Long-term ART adherence will be evaluated for 6 months after the intervention, and survey assessments will be conducted at baseline, 3 months, and 9 months. Outcomes include feasibility and acceptability measures and intervention efficacy outcomes defined by electronically measured mean medication adherence during the intervention and during the 6 months after the intervention, along with a measure of routine ART adherence based on taking medications around the time of participants' anchor during the intervention and during the 6 months after intervention. RESULTS: As of February 18, 2022, recruitment was completed. A total of 150 participants were recruited, and data collection is expected to end in December of 2022. Final results are expected to be submitted for publication by April 2023. CONCLUSIONS: This study is the first to use behavioral economics-based interventions in combination with the anchoring strategy to improve long-term ART adherence among treatment initiators. We hypothesize that the combination of SMS text message reminders and incentives will increase participants' use of their anchoring strategy, and thus medication adherence will be better maintained after the intervention ends in our intervention groups relative to the control group that uses only the anchoring strategy. Results of this pilot study will help to refine this combined intervention approach for testing at scale and broaden our understanding of the habit formation process. TRIAL REGISTRATION: ClinicalTrials.gov NCT05131165; https://clinicaltrials.gov/ct2/show/NCT05131165. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/42216.

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)0.030
metaresearch head score (Gemma)0.023
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 score0.094
Threshold uncertainty score0.313

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.023
Meta-epidemiology (narrow)0.0060.003
Meta-epidemiology (broad)0.0090.005
Bibliometrics0.0020.003
Science and technology studies0.0040.003
Scholarly communication0.0040.003
Open science0.0040.002
Research integrity0.0060.009
Insufficient payload (model declined to judge)0.0940.014

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 head0.183
GPT teacher head0.562
Teacher spread0.379 · 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

Citations3
Published2022
Admission routes1
Has abstractyes

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