Bibliographic record
Abstract
Figure.: M. Kathleen Pichora-Fuller, PhDAt the 17th Annual Canadian Academy of Audiology Conference and Exposition, my co-presenters and I conducted a preconference workshop to explore how models from health psychology and social psychology could inspire a new approach to audiologic rehabilitation. Such a revolution in audiologic practice is long overdue because many people who are hard of hearing do not get the help they need to function well in everyday life and achieve their quality-of-life aspirations. Importantly, health and social psychology approaches have been used effectively for people living with a wide range of chronic health conditions. These methods are designed to increase behaviors that promote health and decrease those that compromise health. By applying similar approaches, audiologists may be able to reduce delays in help seeking, accelerate readiness for action taking, facilitate timely decision making about treatments, support positive behavior changes by the patient and communication partners, and design follow-up to maintain benefits and prevent relapse. In a special series for The Hearing Journal (HJ), my co-presenters and I will explore the themes we presented at the conference. I started the workshop by defining health and health psychology, and describing some of the key features of health promotion and self-management programs for people living with chronic health conditions. Please see page 19 for my article about this topic. Gabrielle Saunders, PhD, and Ariane Laplante-Lévesque, PhD, explained how they are applying two of the dominant health psychology models to understand more about achieving behavior change in audiologic rehabilitation. Their work will be featured in subsequent issues of HJ, as will presentations from the second part of the workshop, which illustrated what the revolution in audiologic rehabilitation might look like if lessons from health and social psychology were used to address the unmet needs of people who are hard of hearing. Arlene Carson, PhD, stressed that people engage in their own self-assessment process as they adjust to living with a hearing loss and that this self-assessment needs to be factored into the clinician's assessment. Gurjit Singh, PhD, emphasized the important role of social support in rehabilitation and the need to involve significant others in interventions. Paul Mick, MD, MPH, provided an overview of epidemiologic research on the links between age-related hearing loss and other health conditions, including recommendations for using these findings in evidence-based practice. Please stay tuned as this special series continues in HJ.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.022 | 0.007 |
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".