Identifying Inconsistencies and Reporting Deficits in Therapeutic Massage and Bodywork (TMB) Case Reports Authored by TMB Practitioners: a TMB-Adapted CAse REport (CARE) Guidelines Audit Through 2014†
Bibliographic record
Abstract
INTRODUCTION: Case reports are a fundamental tool through which therapeutic massage and bodywork (TMB) practitioners can inform research and impact their field by detailing the presentation, treatment, and follow-up of a single individual encountered in practice. Inconsistencies in case reporting limit their impact as fundamental sources of clinical evidence. Using the TMB-adapted CAse REport (CARE) guidelines, the current study sought to provide a rich description regarding the reporting quality of TMB practitioner authored TMB case reports in the literature. METHODS: 1) Systematic identification of published, peer-reviewed TMB case reports authored by TMB practitioners following PRISMA recommendations; 2) audit development based on TMB-adapted CARE guidelines; 3) audit implementation; and 4) descriptive analysis of audit scores. RESULTS: Our search identified 977 articles and 35 met study inclusion criteria. On average, TMB case reports included approximately 58% of the total items identified as necessary by the TMB-adapted CARE guidelines. Introduction sections of case reports had the best item reporting (80% on average), while Case Presentation (54%) and Results (52%) sections scored moderately overall, with only 20% of necessary Practitioner Description items included on average. Audit scores revealed inconsistent abstract reporting and few audited case reports including client race (20%), perspective (26%), and occupation/activities (40%); practitioner practice setting (12%), training (12%), scope-of-practice (29%), and credentialing (20%); adverse events or lack thereof (17%); and some aspect of informed consent (34%). Treatment descriptor item reporting varied from high to low. Various implications of concern are discussed. CONCLUSION: The current audit and descriptive analysis highlight several reporting inconsistencies in TMB case reports prior to 2015. Reporting guidelines for case reports are important if standards for, and impact of, TMB case reports are desired. Adherence to reporting specifications outlined by the TMB-adapted CARE guidelines could improve the impact and usability of TMB case reports in research, education, and practice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.247 | 0.586 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.022 | 0.016 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".