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Record W2051302634 · doi:10.1044/nnsld17.1.11

Finding Time, Finding Evidence and Making Decisions: The Challenges of Evidence-Based Practice

2007· article· en· W2051302634 on OpenAlexaffabout
Tammy Hopper

Bibliographic record

VenuePerspectives on Neurophysiology and Neurogenic Speech and Language Disorders · 2007
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsEvidence-based practiceMillerEvidence-based medicineClinical PracticeMedicinePsychologyMedical educationAlternative medicineLibrary scienceFamily medicineComputer science

Abstract

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No AccessPerspectives on Neurophysiology and Neurogenic Speech and Language DisordersArticle1 Apr 2007Finding Time, Finding Evidence and Making Decisions: The Challenges of Evidence-Based Practice Tammy Hopper Tammy Hopper University of AlbertaEdmonton, Alberta Canada Google Scholar More articles by this author https://doi.org/10.1044/nnsld17.1.11 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationTrack Citations ShareFacebookTwitterLinked In References Dickerson, S. S., Sackett, K., Jones, J. M., & Brewer, C. (2001). Guidelines for evaluating tools for clinical decision making.Nurse Educator, 26, 215–220. Google Scholar Finn, P. (2006, June 13). Bias and blinding: Self-fulfilling prophecies and intentional ignorance.The ASHA Leader, 11(8), 16–17, 22. Google Scholar Greenhalgh, T. (1997). How to read a paper: The basics of evidence-based medicine. London: British Medical Journal Press. Google Scholar G. Guyatt, & D. Rennie (Eds.). (2002). Users’ guide to the medical literature: A manual for evidence-based clinical practice. Chicago: American Medical Association Press. Google Scholar Law, M. (2002). Introduction to evidence-based practice.In M. Law (Ed.), Evidence-based rehabilitation: A guide to practice (pp. 1–12). Thoro-fare, NJ: SLACK. Google Scholar McKibbon, A. (1999). Evidence-based principles and practice. Hamilton, ON: B.C. Decker. Google Scholar Miller, R. G., Rosenberg, J. A., Gelinas, D. F., Mitsumoto, H., Newman, D., Sufit, R., et al. (1999). Practice parameter: The care of the patient with amyotrophic lateral sclerosis (an evidence-based review) [Report of the Quality Standards Subcommittee of the American Academy of Neurology]. Neurology, 52, 1311–1323. Google Scholar Nelson, P., & Goffman, L. (2006, May 2). Primer on research: Developing a research question.The ASHA Leader, 11(6), 15, 26. Google Scholar Oller, D. K. (2006, Nov. 7). Primer on research: Interpretation of correlation. The ASHA Leader, 11(15), 24–26. Google Scholar Pollock, N., & Rochon, S. (2002). Becoming an evidence-based practitioner.In M. Law (Ed.), Evidence-based rehabilitation: A guide to practice (pp. 31–46). Thorofare, NJ: SLACK. Google Scholar Porzsolt, F., Ohletz, A., Gardner, D., Ruatti, H., Meier, H., Scholtz-Gorton, N., & Schrott, L. (2003). Evidence-based decision making— The 6-step approach..British Medical Journal, November/December, A-11-A-12. Google Scholar Rappolt, S., & Tassone, M. (2002). How rehabilitation therapists gather, evaluate, and implement new knowledge..The Journal of Continuing Education in the Health Professions, 22, 170–180. Google Scholar Rycroft-Malone, J., Seers, K., Titchen, A., Harvey, G., Kitson, A., & McCormack, B. (2004). What counts as evidence in evidence-based practice?.Journal of Advanced Nursing, 47(1), 81–90. Google Scholar Sackett, D. L, Rosenberg, W. M. C.Gray, J. A., Haynes, R. B., & Richardson, W. S. (1996). Evidence based medicine: What it is and what it isn’t..British Medical Journal, 312(13), 71–72. Google Scholar Sackett, D. L., Straus, S. E., Richardson, W. S., Rosenberg, W., & Haynes, R. B. (2000). Evidence-based medicine: How to practice and teach EBM. London, UK: Churchill Livingstone. Google Scholar Schuele, C. M., & Justice, L. M. (2006, Aug. 15). The importance of effect sizes in the interpretation of research. The ASHA Leader, 11(10), 14–15, 26–27. Google Scholar Scott-Findlay, S., & Pollock, C. (2004). Evidence, research, knowledge: A call for conceptual clarity..World Views on Evidence-Based Nursing, 1(2), 92–97. Google Scholar Thompson, C., McCaughan, D., Cullum, N., Sheldon,T. A., Mulhall, A., & Thompson, D. R. (2001). Research information in nurses’ clinical decision-making: what is useful?.Journal of Advanced Nursing, 36(3), 376–388. Google Scholar World Health Organization. (2001). International Classification of Functioning, Disability and Health (ICF). Geneva, Switzerland: Author. Google Scholar Zipoli, R. P., & Kennedy, M. (2005). Evidence-based practice among speech-language pathologists: Attitudes, utilization, and barriers..American Journal of Speech-Language Pathology, 14(3), 208–220. LinkGoogle Scholar Additional Resources FiguresReferencesRelatedDetailsCited ByAmerican Journal of Speech-Language Pathology29:2 (688-704)8 May 2020What Does Evidence-Based Practice Mean to You? A Follow-Up Study Examining School-Based Speech-Language Pathologists' Perspectives on Evidence-Based PracticeKatrina Fulcher-Rood, Anny Castilla-Earls and Jeff Higginbotham Volume 17Issue 1April 2007Pages: 11-14 Get Permissions Add to your Mendeley library History Published in issue: Apr 1, 2007 Metrics Downloaded 32 times Topicsasha-topicsasha-article-typesasha-sigsCopyright & Permissions© 2007 American Speech-Language-Hearing AssociationPDF DownloadLoading ...

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)0.002
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.641
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.175
GPT teacher head0.483
Teacher spread0.308 · 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 teacher head, not a consensus.

Study designObservational
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

Citations1
Published2007
Admission routes2
Has abstractyes

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