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Record W2153390961 · doi:10.1093/ptj/83.2.123

A Quantitative Analysis of Research Publications in Physical Therapy Journals

2003· article· en· W2153390961 on OpenAlexaffabout
Patricia A. Miller, K Ann McKibbon, R. Brian Haynes

Bibliographic record

VenuePhysical Therapy · 2003
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsMcMaster UniversityHamilton Health Sciences
Fundersnot available
KeywordsPsychologyMedicineMedical physics

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: Many physical therapists depend on their professional journals for high-quality evidence. The purpose of this study was to evaluate the rigor of research and review articles in 4 national physical therapy journals. SUBJECTS AND METHODS: All articles in 6 consecutive issues of the Australian Journal of Physiotherapy, Physical Therapy, Physiotherapy, and Physiotherapy Canada, published between January 2000 and June 2001 (N=179), were reviewed. One trained reviewer identified the type and purpose of each article and assessed the rigor of treatment and review articles according to explicit criteria. RESULTS: The majority of articles reviewed were original studies (56%). The majority of the research articles that dealt with human health care (66%) addressed topics that were not directly applicable to the provision of patient care such as measurement topics and studies on subjects without identified pathologies or impairments. Of the 179 journal articles, 19 met the standards for rigor (11%). The majority of these articles dealt with treatment. The pass rate per journal was as follows: Australian Journal of Physiotherapy, 10% (4/42); Physical Therapy, 15% (7/47); Physiotherapy, 12% (4/34); and Physiotherapy Canada, 7% (4/56). DISCUSSION AND CONCLUSION: Because such a small percentage of articles in these professional journals were identified as having direct application to patient care, physical therapists should attempt to access other sources of information to find additional high-quality evidence. A larger sample with a greater number of issues per journal may have yielded different results and indicated different trends, and further research appears to be warranted.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.078
metaresearch head score (Gemma)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.214
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0780.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0020.022
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.932
GPT teacher head0.694
Teacher spread0.238 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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

Citations51
Published2003
Admission routes2
Has abstractyes

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