The study could not answer the product question until the participant pipeline was credible.
This was research infrastructure, not a feature test. Before the team could evaluate AI reading support, it needed a credible way to recruit, verify, schedule, and support the participants the study was designed for.
DITAVA Lab was preparing a mixed-methods preference study with DHH adults fluent in ASL to evaluate 18 AI-based text styling designs for skimming support. Prior work had focused on hearing users. This study asked whether those design directions held up for a DHH population.
Prolific could filter for self-reported "hearing impairment," but the study needed more than a broad population flag. It needed evidence of ASL comprehension, a way to route participants by communication preference, and an IRB-compliant path from first contact to session.
No verified DHH/ASL participant pool, no screener, no interpreter routing workflow, and no standardized participant messaging.
Define what evidence was sufficient for study inclusion and what access conditions had to be in place before a session could run.
The risk was not slow recruiting. It was building evidence on the wrong foundation.
If the pool did not match the intended population, the team could not interpret DHH preferences with confidence. If access logistics were handled too late, eligible participants could still be blocked from participating.
Confident interpretation required knowing participants were DHH adults fluent in ASL, not just anyone who self-reported hearing loss. Operationally, this was also a research maturity problem: the lab needed a repeatable system for future DHH studies, not a one-time recruiting push.
I separated recruitment into two gates: eligibility and access.
Finding people, verifying people, and making sessions accessible are different jobs. The two-gate structure emerged from conversations with the PI about what the study actually needed to trust its own participant pool. Treating those jobs separately made the pipeline easier to audit and easier to reuse.
First, Prolific surfaced people who self-identified as DHH or reported hearing loss. That got us to the right broad population segment, but it was not enough for inclusion.
Next, the Qualtrics screener tested receptive ASL comprehension with two short videos and open-ended questions. Submissions then moved into a review tracker with Prolific ID, completion status, correctness rating, and a written note for every decision.
Finally, verified participants were routed into the main study. At scheduling, they selected English or ASL, which determined the Calendly path, interpreter lead time, and participant messaging they received.
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01
Prolific Pre-Filter
Broad targeting based on self-reported DHH identity or hearing loss.
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02
Qualtrics ASL Screener
Behavioral verification using two ASL video comprehension tasks.
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03
Manual Review Tracker
Google Sheets decision log with Prolific ID, completion status, correctness rating, and review notes.
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04
Calendly Scheduling + Routing
Booking flow that routed English and ASL sessions into different lead-time paths.
The evidence standard was behavioral, documented, and respectful of participant burden.
The pipeline worked because each decision had a reason. The goal was to protect study validity while keeping the process low-friction and privacy-conscious.
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01
Test receptive ASL comprehension, not expressive signing.
Expressive verification would have required participants to submit videos of themselves signing. That added privacy concerns and unnecessary friction. Receptive comprehension gave us the eligibility signal without requiring participant video.
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02
Use open-ended ASL comprehension, not another checkbox.
The screener asked participants to interpret signed videos in their own words. That created a stronger signal than self-report alone while avoiding assumptions that every ASL-fluent DHH person has the same relationship to Deaf culture.
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03
Keep human judgment for edge cases.
Some responses were partial, culturally informed, or inconsistent. I used the Notes column as a decision log, flagged uncertain cases for PI review, and kept the reasoning visible instead of forcing every response into an automated pass/fail rule.
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04
Capture access needs before the calendar was locked.
ASL interpretation could not be arranged at the start of a session. The workflow used a 1-day scheduling buffer for English sessions and an 8-day buffer for ASL sessions, building interpreter lead time into the study design.
Treat eligibility and access as protocol, not setup.
The recommendation was a five-stage operating model: screen broadly, verify carefully, document decisions, route by communication preference, then run sessions only when access support was in place.
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01
Prolific outreach.
A screener study was posted on Prolific targeting participants who self-identified as DHH. Those who clicked through were taken to the Qualtrics consent form and screener survey.
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02
ASL comprehension verification.
Participants watched two ASL videos and answered open-ended questions. I reviewed each response, marked it correct or incorrect, and wrote notes explaining the decision.
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03
Pool construction.
Verified participants became a named Prolific pool the lab could contact for future DHH studies.
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04
Study enrollment and scheduling.
The main study was launched to verified participants. At booking, participants selected English or ASL as their session language. That choice routed them to the appropriate Calendly path and triggered interpreter coordination for ASL sessions.
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05
Session delivery.
English-preference participants completed sessions verbally. ASL-preference participants had interpreter coordination built into scheduling. Participant communication used approved templates from first contact through reminder.
Decision Impact
Before: the team had a study concept but no verified path to participants. After: a reusable DHH research workflow with eligibility criteria, an audit trail, and ASL/English session routing.
- Participant pool
- 30+ screener responses reviewed; verified DHH/ASL pool built on Prolific, reusable for future DHH/ASL recruitment
- Session routing
- English and ASL sessions routed at booking; 1-day buffer for English, 8-day buffer for ASL with interpreter coordination confirmed before sessions ran
- Infrastructure
- 5-stage pipeline documented: Prolific outreach, ASL screener, manual review, pool construction, scheduling and delivery
The mixed-methods study could run with verified participants and the right communication path in place before each session. More importantly, the lab no longer had to rebuild the same foundation for the next DHH study. The work turned access logistics into research infrastructure.
The screener held up. The tracking system needed more automation from the start.
Receptive comprehension over expressive signing was the right call.
It gave the team an eligibility signal without increasing privacy risk or making the screener more burdensome.
The tracker needed automation earlier.
Manual review of every submission was accurate. It was also time-intensive across 30+ submissions in the initial screener phase. With more lead time, I’d use conditional logic to surface structurally incomplete responses before they reached the tracker, so human review could focus on substantive judgment calls rather than every submission.
Access logistics are research design decisions.
When to capture communication preference, how to route sessions, and how to write consent language are not administrative details. They determine who can participate and whether the data reflects the population the study intended to reach.