Self‐management programmes in temporomandibular disorders: results from an international <scp>D</scp>elphi process
Bibliographic record
Abstract
Self-management (SM) programmes are commonly used for initial treatment of patients with temporomandibular disorders (TMD). The programmes described in the literature, however, vary widely with no consistency in terminology used, components of care or their definitions. The aims of this study were therefore to construct an operationalised definition of self-management appropriate for the treatment of patients with TMD, identify the components of that self-management currently being used and create sufficiently clear and non-overlapping standardised definitions for each of those components. A four-round Delphi process with eleven international experts in the field of TMD was conducted to achieve these aims. In the first round, the participants agreed upon six principal concepts of self-management. In the remaining three rounds, consensus was achieved upon the definition and the six components of self-management. The main components identified and agreed upon by the participants to constitute the core of a SM programme for TMD were as follows: education; jaw exercises; massage; thermal therapy; dietary advice and nutrition; and parafunctional behaviour identification, monitoring and avoidance. This Delphi process has established the principal concepts of self-management, and a standardised definition has been agreed with the following components for use in clinical practice: education; self-exercise; self-massage; thermal therapy; dietary advice and nutrition; and parafunctional behaviour identification, monitoring and avoidance. The consensus-derived concepts, definitions and components of SM offer a starting point for further research to advance the evidence base for, and clinical utility of, TMD SM.
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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 | 0.148 | 0.153 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".