Facilitating the Informed Consent Process Using Teleconsent: Protocol for a Feasibility and Efficacy Study
Bibliographic record
Abstract
BACKGROUND: Informed consent is among the biggest challenges in recruiting participants for clinical research studies. Researchers face many challenges in conducting clinical trials, some of which include budgetary restrictions, lack of trained personnel, and difficulty recruiting study participants-particularly minorities and participants from rural communities. OBJECTIVE: The objective of this study is to utilize telemedicine to improve the informed consent process for clinical trials and studies. We aim to assess the feasibility and efficacy of the teleconsent intervention among residents in urban and rural settings. METHODS: This study will be conducted separately yet concurrently at two institutions, the Medical University of South Carolina and the University of North Carolina at Chapel Hill, to compare results within and across institutions. RESULTS: Enrollment for Phase 1 began in March of 2018 and concluded in May 2018. Data transcription and analysis will be conducted through June and September of 2018. CONCLUSIONS: In this paper, we present a novel approach for conducting informed consent using a new telemedicine modality, namely, teleconsent. Teleconsent presents the ability to conduct a live interaction among clinical research coordinators and potential participants while synchronously presenting the consent form on the screen and obtaining participant's signature through doxy.me, the teleconsent system. Teleconsent provides potential to improve obtaining informed consent from potential clinical trial participants. REGISTERED REPORT IDENTIFIER: RR1-10.2196/11239.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Research integrity Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Non-randomized trial | high |
| gpt | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Other design | high |
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 | 0.176 | 0.165 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.078 | 0.019 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".