Experiences of Health Care Workers Regarding Maintenance of Confidentiality Concerning Hearing Challenged People in Selected Public Health Facilities in eThekwini District, South Africa
Bibliographic record
Abstract
Communication between a health care provider and a patient is a pre-requisite for any intervention to occur in the process of health care. Deaf patients depend on interpreters when seeking health care. Confidentiality is an issue since interpreters are involved in the Deaf community. Health care workers (HCWs) are tasked to ensure that the delivery of information to the patient is accurate and kept confidential. A descriptive exploratory qualitative design was used to explore the experiences of HCWs regarding the maintenance of confidentiality for hard of hearing patients. The study population comprised HCWs who worked with hearing challenged patients. Purposive sampling, which is a type of non-probability sampling, was utilized to select the study participants from the population. This research study was conducted at two hospitals in eThekwini District. Structured interviews, using an interview schedule, were used to collect data. The actual sample size was 10 participants. Data was analysed using Tesch’s eight steps of thematic analysis. Six major themes emerged from the data analysis namely training of health care workers, communication preferences for hard of hearing patients, communication challenges, health care worker-patient relationship, involvement of family members as interpreters and measures to maintain confidentiality. Majority of participants experienced communication challenges with patients who are hard of hearing since only few HCWs are trained in sign language. The findings of this study will contribute to addressing issues related to the maintenance of confidentiality of hard of hearing patients. This study does not claim to exhaust the subject but to raise awareness of new investigations in other realities. Further research in the larger representative population of HCWs and hard of hearing patients is necessary to make the health care system more accessible and communication with HCWs more satisfying and effective.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".