<p>South Asians&rsquo; experience of managing hypertension: a grounded theory study</p>
Bibliographic record
Abstract
OBJECTIVE: We examined the process that South Asians undergo when managing their hypertension (HTN). METHOD: Using grounded theory methods, 27 community-dwelling English-, Punjabi-, or Hindi-speaking South Asian participants (12 men and 15 women), who self-identified as having HTN were interviewed. Transcripts were analyzed using constant comparison. RESULTS: The core category was "fitting it in". First, the participants assessed their diagnosis and treatment primarily in the context of their current family/social environment. Participants who paid attention to their diagnosis either fully or partly embraced activities and attitudes associated with successful management of hypertension. However, those who did not attend to their diagnosis, identified other familial/social factors, stress of immigration, and not having symptoms of their disease as barriers. The longer the time since diagnosis of HTN, the more participants came to appropriately manage their HTN. CONCLUSION: Healthcare providers may use this information to enhance their cultural understanding of how and why South Asians manage their HTN.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".