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Record W3137001374 · doi:10.1002/nop2.841

A rapid evidence assessment of recent therapeutic touch research

2021· review· en· W3137001374 on OpenAlexaff
Bernie Garrett, Marliss Riou

Bibliographic record

VenueNursing Open · 2021
Typereview
Languageen
FieldMedicine
TopicComplementary and Alternative Medicine Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCINAHLMEDLINEMedicineRandomized controlled trialAnxietyResearch designAlternative medicinePsychologyPsychological interventionPsychiatryInternal medicinePathology

Abstract

fetched live from OpenAlex

AIM: To synthesize the most recent evidence investigating the effectiveness and safety of therapeutic touch as a complementary therapy in clinical health applications. DESIGN: A rapid evidence assessment (REA) approach was used to review recent TT research adopting PRISMA 2009 guidelines. METHODS: CINAHL, PubMed, MEDLINE, Cochrane databases, Web of Science, PsychINFO and Google Scholar were screened between January 2009-March 2020 for studies exploring TT therapies as an intervention. The main outcome measures were for pain, anxiety, sleep, nausea and functional improvement. RESULTS: Twenty-one studies covering a range of clinical issues were identified, including 15 randomized-controlled trials, four quasi-experimental studies, one chart review study and one mixed methods study including 1,302 patients. Eighteen of the studies reported positive outcomes. Only four exhibited a low risk of bias. All others had serious methodological flaws, bias issues, were statistically underpowered and scored as low-quality studies. No high-quality evidence was found for any of the benefits claimed.

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 imitation

Not 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.

metaresearch head score (Codex)0.168
metaresearch head score (Gemma)0.346
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.168
Threshold uncertainty score0.889

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1680.346
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0130.013
Bibliometrics0.0630.028
Science and technology studies0.0020.003
Scholarly communication0.0170.014
Open science0.0050.009
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0120.002

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.

Opus teacher head0.824
GPT teacher head0.686
Teacher spread0.137 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations31
Published2021
Admission routes1
Has abstractyes

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