− HEALTH Agentic artificial intelligence (AI) is an emerging development in the digital transformation of healthcare.…− HEALTH Artificial intelligence (AI) is expanding the capacity of public health systems to detect infectious disease…+ HEALTH Purpose To estimate diagnostic performance of a deep learning algorithm for extremity fracture detection on r…− HEALTH Objective Hypomimia, or reduced facial expressiveness, is a cardinal motor feature of Parkinson's disease (PD…− SCIENCE Background Generative artificial intelligence (GenAI) chatbots have shown utility in assisting with various r…− HEALTH ObjectiveTo critically review the current pharmacologic treatment landscape for epidermal growth factor recep…− HEALTH Her name was June. June would be the last month she ever knew. I remember the way her bed made her so small,…− LIFESTYLE Precision nutrition on a global scale necessitates an understanding of food not as static collections of so-c…
TruaceTracing the truth around AIWednesday, September 23, 2026
Subscribe
TRV-2026-1174Version 1 · Certified

Written 2026-09-23 06:53:31 UTC · current record

Reason for this version

Certified into the record

Canonical text (the exact bytes fingerprinted)

TRUVACE RECORD VERSION
record: TRV-2026-1174
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-09-23T06:53:31.400838Z
status: published
lens: p_space
sector: science
headline: Attitudes and Perceptions of Generative Artificial Intelligence Chatbots in the Scientific Process of Traditional, Complementary, and Integrative Medicine Research: A Large-Scale, International Cross-Sectional Survey
dek: Background Generative artificial intelligence (GenAI) chatbots have shown utility in assisting with various research tasks. Traditional, complementary, and integrative medicine (TCIM) is a patient-centric approach that emphasizes holistic well-being. The integration of TCIM and GenAI presents numerous key opportunities. However, TCIM researchers' attitudes toward GenAI tools remain less understood. This large-scale, international cross-sectional survey aimed to elucidate the attitudes and perceptions of TCIM res…
gain_title: (none)
problem_title: The most frequently reported challenges involved bias, errors, and limitations. Background Generative artificial intelligence (GenAI) chatbots have shown utility in assisting with various research tasks.
trace_subject: (none)
gain_reading: (none)
gain_evidence: (none)
problem_reading: The most frequently reported challenges involved bias, errors, and limitations. Background Generative artificial intelligence (GenAI) chatbots have shown utility in assisting with various research tasks.
problem_evidence: (none)
quick_read: Background Generative artificial intelligence (GenAI) chatbots have shown utility in assisting with various research tasks. Traditional, complementary, and integrative medicine (TCIM) is a patient-centric approach that emphasizes holistic well-being.

Most respondents reported familiarity with GenAI chatbots (58.08%) and viewed them as very important to the future of scientific research (54.37%). The most acknowledged benefits included workload reduction (74.07%) and increased efficiency in data analysis/experimentation (71.14%).
limitation: 
tag: Evidence-backed problem
key_points: Background Generative artificial intelligence (GenAI) chatbots have shown utility in assisting with various research tasks. | Traditional, complementary, and integrative medicine (TCIM) is a patient-centric approach that emphasizes holistic well-being. | The integration of TCIM and GenAI presents numerous key opportunities.
rundown: Background Generative artificial intelligence (GenAI) chatbots have shown utility in assisting with various research tasks. Traditional, complementary, and integrative medicine (TCIM) is a patient-centric approach that emphasizes holistic well-being.

The integration of TCIM and GenAI presents numerous key opportunities. However, TCIM researchers' attitudes toward GenAI tools remain less understood.
sources:
- peer_reviewed | Journal of Evidence-Based Medicine | https://doi.org/10.1111/jebm.70189 | 2026-09-22
prev: 0000000000000000000000000000000000000000000000000000000000000000
sha256
ea2ea1d4ed4842cbcac2e8f32820075b633d845928b8218acd476ad73ae93087
previous
0000000000000000000000000000000000000000000000000000000000000000
Verify this record
How to verify without trusting this page

Fetch the canonical text of any version from /api/record/TRV-2026-1174 and hash it yourself — for example shasum -a 256 on the saved canonical field. The result must equal content_hash, and each version’s text ends with prev:followed by the prior version’s hash (version 1 chains to 64 zeros). If a single character of any version had been altered since certification, the chain would not reproduce.