Bibliographic record
Abstract
TV listening plays a large role in the lives of hearing-impaired (HI) individuals. Yet, few studies have examined TV listening in this group. In this paper, we report the findings of an online survey on TV listening conducted among HI individuals with and without hearing aids (HAs) in the United States in 2015. The research investigated if and in what form TV listening experiences of unaided and aided HI individuals might differ with regard to their viewing habits, difficulties they experience, and compensation strategies they employ. 515 HI people of ages 50+ years participated, 260 of whom owned HAs. HA users reported that they watched TV or video on average for 6 hours 10 min per day, 57 minutes longer than the duration reported by non-HA owners. Furthermore, HA users indicated fewer difficulties when watching TV than non-HA owners, suggesting that HA usage alleviated difficulties with TV listening. Nevertheless, the most frequent problems were still encountered by more than 39% of the HA users. Difficulties increased with greater self-reported unaided hearing disability, and female participants indicated more problems than male participants. Finally, those with carpeted floors reported fewer difficulties than those without carpets. The most frequently used compensation strategies were changing TV or HA volumes and using closed captioning. Only few HA users used audio streaming accessories. Given the exploratory nature of this study, further research is needed to inform interventions and improve the TV listening experiences of HI viewers.
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 | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".