Consensus Recommendations to NCCIH from Research Faculty in a Transdisciplinary Academic Consortium for Complementary and Integrative Health and Medicine
Bibliographic record
Abstract
BACKGROUND: This commentary presents the most impactful, shared priorities for research investment across the licensed complementary and integrative health (CIH) disciplines according to the Academic Consortium for Complementary and Alternative Health Care (ACCAHC). These are (1) research on whole disciplines; (2) costs; and (3) building capacity within the disciplines' universities, colleges, and programs. The issue of research capacity is emphasized. DISCUSSION: ACCAHC urges expansion of investment in the development of researchers who are graduates of CIH programs, particularly those with a continued association with accredited CIH schools. To increase capacity of CIH discipline researchers, we recommend National Center for Complementary and Integrative Health (NCCIH) to (1) continue and expand R25 grants for education in evidence-based healthcare and evidence-informed practice at CIH schools; (2) work to limit researcher attrition from CIH institutions by supporting career development grants for clinicians from licensed CIH fields who are affiliated with and dedicated to continuing to work in accredited CIH schools; (3) fund additional stand-alone grants to CIH institutions that already have a strong research foundation, and collaborate with appropriate National Institutes of Health (NIH) institutes and centers to create infrastructure in these institutions; (4) stimulate higher percentages of grants to conventional centers to require or strongly encourage partnership with CIH institutions or CIH researchers based at CIH institutions, or give priority to those that do; (5) fund research conferences, workshops, and symposia developed through accredited CIH schools, including those that explore best methods for studying the impact of whole disciplines; and (6) following the present NIH policy of giving priority to new researchers, we urge NCCIH to give a marginal benefit to grant applications from CIH clinician-researchers at CIH academic/research institutions, to acknowledge that CIH concepts require specialized expertise to translate to conventional perspectives. SUMMARY: We commend NCCIH for its previous efforts to support high-quality research in the CIH disciplines. As NCCIH develops its 2016-2020 strategic plan, these recommendations to prioritize research based on whole disciplines, encourage collection of outcome data related to costs, and further support capacity-building within CIH institutions remain relevant and are a strategic use of funds that can benefit the nation's health.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".