Practice-Based Research in Speech-Language Pathology
Bibliographic record
Abstract
Practice-based research is an active and collaborative approach to clinical research that minimizes the research-practice gap. Practice-based research involves collecting data in practice to answer questions that arise from clinical practice. The findings from this research then inform future practices. Though over the past two decades there has been a significant increase in knowledge translation activities, especially the use of collaborative partnerships, the integration of these practices in speech-language pathology is in its infancy. In this thesis, I investigate the role of practice-based research in speech-language pathology. In Chapter 2, I first examine the current role of practice-based research in speech-language pathology through a scoping review. I present a practice-based research Co-Creation Model that characterizes the outcomes of partnerships, and I present the results of the scoping review. The Co-Creation Model outlines capturing practice, changing practice, and creating practice as three potential outcomes of these partnerships. In Chapter 3, I employ two aspects of the model, first capturing practice and then changing practice. In this chapter, I report on a practice-based research partnership between researchers and speech-language pathologists at a school board in Ontario. The clinicians at this school board designed a language and literacy tool and they were interested in determining the effectiveness of the tool. In study 1, we capture the current use of the tool and the results of this study led to a collaborative update of the tool. In study 2, additional data was collected to determine the effectiveness of the updated tool and determine the tool’s validity against standardized measures of language. The results of this study demonstrated that the update of the tool was successful. Chapter 4 aims to understand the experiences of researchers and clinicians engaged in a partnership and draws on qualitative data collected during the practice-based study reported in Chapter 3. Insight from their experiences provided knowledge of barriers and facilitators to partnership, and factors important for partnership initiation and maintenance. Chapter 5 summarizes the findings of these 3 chapters, discusses broader implications of this work, acknowledges limitations of the current work, and outlines considerations for future work in practice-based research.
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 | 0.258 | 0.338 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.012 | 0.014 |
| Science and technology studies | 0.010 | 0.036 |
| Scholarly communication | 0.023 | 0.018 |
| Open science | 0.004 | 0.018 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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.
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".