Clinical Research in Practice: A Guide for the Bedside Scientist
Notice bibliographique
Résumé
Clinical Research in Practice is a primer of techniques for the beginning clinical researcher. Written by nursing faculty, it encourages all health care professionals to understand and contribute to the evidence that supports clinical practice. This book uses a straightforward approach to provide clinicians with the basic information required to carry out clinical research studies. The examples and case studies in the book focus on nursing issues, but can be readily applied to physical therapy clinical research. Although the book presents information in an uncomplicated manner, the text includes the major topics that should be present in such a primer. Part 1 contains introductory chapters that deal with the importance of clinical research and an overview of the step-by-step project development process. Part 2 delivers more detail on advancing the background and organizational aspects of the project, such as focusing the question, scanning the literature, soliciting project approval from the institutional review board (IRB), and securing institutional commitment. Part 3 includes the design concepts, including methodology, sampling strategy, and basic statistical analysis. Lastly, part 4 focuses on interpreting the existing evidence and applying it to clinical practice and also reviews validity and reliability concepts. Part 4 also includes chapters specific to survey and qualitative designs, as well as preparing for publication. Special features throughout the text contribute to the book’s practicality. For instance, “From the Mouths of Bedside Scientists” contain interviews of clinical researchers regarding key concepts. “For More Depth and Detail” are text boxes that include key references for further reading. “Another Way to Look at It” are excerpts that help to highlight and simplify real-life illustrations and examples. Appendixes include a glossary, a sample of an informed consent form, a reprinted article on how to review a published article, and a comprehensive checklist for evaluating a research article. The book is written in an easy-to-read, common sense manner. The text is easy to follow, and the special features contribute to the usefulness of the book. Experienced researchers may find it lacking in depth, but novice investigators will find it a refreshing alternative to more exhaustive tomes. The authors are successful at demystifying complicated concepts and encouraging clinicians to attempt clinical research. The reference lists are complete and direct the reader to more in-depth information, if desired. The book may lack the detail for a required text in an entry-level or transitional physical therapist education program. It would, however, make an excellent supplementary text to accompany a more comprehensive volume. In addition, it would prove invaluable to the clinician researcher who is interested in pursuing a clinical research project, but may be apprehensive regarding a commitment to such an endeavor. It provides a quick and supportive refresher course for practitioners who wish to revitalize their skills in evaluating the evidence or to explore a venture into clinical research.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,010 | 0,022 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,002 | 0,004 |
| Communication savante | 0,010 | 0,013 |
| Science ouverte | 0,003 | 0,005 |
| Intégrité de la recherche | 0,007 | 0,015 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,038 | 0,067 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».