Knowledge, attitude and perception towards lower limb amputation amongst persons living with diabetes in rural South Africa: A qualitative study
Bibliographic record
Abstract
BACKGROUND: South Africa has a high prevalence of diabetes mellitus (DM), a leading risk factor for lower limb amputation (LLA). Lower limb amputation is associated with significant morbidity and mortality. Lower limb amputation incidence can be mitigated through prompt identification and treatment of individuals at risk and engagement in self-management practices. Also, when LLA is inevitable, outcomes or prognosis can be improved with timely surgery. AIM: This study explored the knowledge, attitude and perception of persons living with diabetes towards LLA and its prevention. SETTING: Nqamakwe, a rural community in the Eastern Cape province of South Africa. METHOD: This was a descriptive, qualitative study involving persons living with DM, with and without LLA, and community leaders. Fifteen participants were recruited purposively and conveniently from a rural community in the Eastern Cape, South Africa. Data collection took place through semistructured interviews, in English and a local language, Xhosa. Interviews were transcribed and translated, and an inductive approach was used for thematic analysis. RESULTS: A total of 15 individual interviews were conducted. Of those, 13 were persons with DM, five with LLA, including one with bilateral LLA. There was a gap in knowledge on foot self-examination as a measure of preventing LLA amongst persons with DM. The attitude of persons without LLA was mostly fearful and their fears centred around perioperative death, risk for contralateral amputation, loss of limb and independence. Consent to LLA procedure was a last resort and only when pain levels were unbearable. Family support and information on rehabilitation services and assistive devices also fostered consent to LLA surgery. CONCLUSION: There is a need for awareness creation and adequate health education for persons living with DM on LLA and its prevention measures, especially foot care practices. Also, health education programmes for persons living with DM in rural areas should address the various misperceptions of LLA to reduce delays.Contribution: The article revealed gaps in knowledge on LLA and its prevention among individuals living with diabetes as well as areas of concerns that may potentially delay acceptance when LLA is inevitable. Findings from our study may assist primary health care providers to determine important issues to be addressed during routine and pre-operative patient education.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".