Use of Peplau's Interpersonal Relations Model to Counsel People With AIDS
Bibliographic record
Abstract
BACKGROUND: Although faced with serious concerns that need to be addressed, clients are often left alone as they cope with AIDS. Nurses are sometimes unsure of their ability to help persons who have termi nal illnesses. OBJECTIVES: The purposes of this research were to provide an example of the development of a nursing approach by the use of Peplau's interpersonal relations model and to gain a greater understanding of life-and-death issues raised by men and women with HIV and AIDS. STUDY DESIGN: A qualitative analysis of a man with AIDS was completed by use of Peplau's model. RESULTS: A question, such as "What are your concerns regarding your situation or your disease?" can greatly encourage clients facing a terminal illness to discuss their concerns. Nurses can assist clients in discussing their concerns regarding death. Nurses can create trusting relationships with clients and understand various issues facing the clients and the interaction process involved. Greater knowledge and understanding of these issues are gained when looking at three categories of concern: care and dis ease, life and death, and stereotypes and prejudices. CONCLUSION: Nurses can make a qualitative difference in the lives of clients with AIDS when they accom pany these persons on their journey. Nurses can minimize loneliness and provide professional support to clients dealing with HIV and AIDS. (J Am Psycbiatr Nurses Assoc [2000]. 6 119-125.)
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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".