Understanding the psychosocial experiences of adults with mild-moderate hearing loss: An application of Leventhal’s self-regulatory model
Bibliographic record
Abstract
OBJECTIVE: This study explored the psychosocial experiences of adults with hearing loss using the self-regulatory model as a theoretical framework. The primary components of the model, namely cognitive representations, emotional representations, and coping responses, were examined. DESIGN: Individual semi-structured interviews were conducted. The data were analysed using an established thematic analysis procedure. STUDY SAMPLE: Twenty-five adults with mild-moderate hearing loss from the UK and nine hearing healthcare professionals from the UK, USA, and Canada were recruited via maximum variation sampling. RESULTS: Cognitive representations: Most participants described their hearing loss as having negative connotations and consequences, although they were not particularly concerned about the progression or controllability/curability of the condition. Opinions differed regarding the benefits of understanding the causes of one's hearing loss in detail. Emotional representations: negative emotions dominated, although some experienced positive emotions or muted emotions. Coping responses: engaged coping (e.g. hearing aids, communication tactics) and disengaged coping (e.g. withdrawal from situations, withdrawal within situations): both had perceived advantages and disadvantages. CONCLUSIONS: This novel application of the self-regulatory model demonstrates that it can be used to capture the key psychosocial experiences (i.e. perceptions, emotions, and coping responses) of adults with mild-moderate hearing loss within a single, unifying framework.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".