Research Priorities for Autonomous Sensory Meridian Response: An Interdisciplinary Delphi Study
Bibliographic record
Abstract
Autonomous Sensory Meridian Response (ASMR) is a multisensory experience most often associated with feelings of relaxation and altered consciousness, elicited by stimuli which include whispering, repetitive movements, and close personal attention. Since 2015, ASMR research has grown rapidly, spanning disciplines from neuroscience to media studies but lacking a collaborative or interdisciplinary approach. To build a cohesive and connected structure for ASMR research moving forwards, a modified Delphi study was conducted with ASMR experts, practitioners, community members, and researchers from various disciplines. Ninety-eight participants provided 451 suggestions for ASMR research priorities which were condensed into 13 key areas: (1) Definition, conceptual clarification, and measurement of ASMR; (2) Origins and development of ASMR; (3) Neurophysiology of ASMR; (4) Understanding ASMR triggers; (5) Factors affecting the likelihood of experiencing/eliciting ASMR; (6) ASMR and individual/cultural differences; (7) ASMR and the senses; (8) ASMR and social intimacy; (9) Positive and negative consequences of ASMR in the general population; (10) Therapeutic applications of ASMR in clinical contexts; (11) Effects of long-term ASMR use; (12) ASMR platforms and technology; (13) ASMR community, culture, and practice. These were voted on by 70% of the initial participant pool using best/worst scaling methods. The resulting agenda provides a clear map for ASMR research to enable new and existing researchers to orient themselves towards important questions for the field and to inspire interdisciplinary collaborations.
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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 | 0.158 | 0.123 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".