Evaluating the Impact of Incentives on Clinical Trial Participation: Protocol for a Mixed Methods, Community-Engaged Study
Bibliographic record
Abstract
BACKGROUND: Monetary incentives in research are frequently used to support participant recruitment and retention. However, there are scant empirical data regarding how researchers decide upon the type and amount of incentives offered. Likewise, there is little guidance to assist study investigators and institutional review boards (IRBs) in their decision-making on incentives. Monetary incentives, in addition to other factors such as the risk of harm or other intangible benefits, guide individuals' decisions to enroll in research studies. These factors emphasize the need for evidence-informed guidance for study investigators and IRBs when determining the type and amount of incentives to provide to research participants. OBJECTIVE: The specific aims of our research project are to (1) characterize key stakeholders' views on and assessments of incentives in biomedical HIV research; (2) reach consensus among stakeholders on the factors that are considered when choosing research incentives, including consensus on the relative importance of such factors; and (3) pilot-test the use of the guidance developed via aims 1 and 2 by presenting stakeholders with vignettes of hypothetical research studies for which they will choose corresponding incentive types. METHODS: Our 2-year study will involve monthly, active engagement with a stakeholder advisory board of people living with HIV, researchers, and IRB members. For aim 1, we will conduct a nationwide survey (N=300) among people living with HIV to understand their views regarding the incentives used in HIV research. For aim 2, we will collect qualitative data by conducting focus groups with people living with HIV (n=60) and key informant interviews with stakeholders involved in HIV research (people living with HIV, IRB members, and biomedical HIV researchers: n=36) to extend and deepen our understanding of how incentives in HIV research are perceived. These participants will also complete a conjoint analysis experiment to gain an understanding of the relative importance of key HIV research study attributes and the impact that these attributes have on study participation. The data from the nationwide survey (aim 1) will be triangulated with the qualitative and conjoint analysis data (aim 2) to create 25 vignettes that describe hypothetical HIV research studies. Finally, individuals from each stakeholder group will select the most appropriate incentive that they feel should be used in each of the 25 vignettes (aim 3). RESULTS: The stakeholder advisory board began monthly meetings in March 2021. All study aims are expected to be completed by December 2022. CONCLUSIONS: By studying the role of incentives in HIV clinical trial participation, we will establish a decision-making paradigm to guide the choice of incentives for HIV research and, eventually, other types of similar research and facilitate the ethical recruitment of clinical research participants. TRIAL REGISTRATION: ClinicalTrials.gov NCT04809636; https://clinicaltrials.gov/ct2/show/NCT04809636. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/33608.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.174 | 0.177 |
| Meta-epidemiology (narrow) | 0.007 | 0.006 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.009 | 0.013 |
| Insufficient payload (model declined to judge) | 0.080 | 0.021 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".