"It brought hope and peace in my heart:" Caregivers perceptions on kangaroo mother care services in Malawi
Bibliographic record
Abstract
Abstract Background Kangaroo mother care (KMC) is an effective intervention for preterm and low birth weight infants. Effective implementation of KMC relies on a multidisciplinary team centering on the newborn's caregiver, who delivers care with support from health care workers. This study explored the experiences of caregivers on the implementation of KMC. Methods We conducted a descriptive qualitative study in the phenomenological tradition, an interpretative approach to describe the caregivers' lived experience with KMC at four health facilities in Malawi from April and June 2019 through 10 non-participatory observations and 24 face-to-face interviews. We drew a purposive sample of 14 mothers, six fathers, three grandmothers, and one grandfather of infants receiving KMC in three secondary and one tertiary level hospitals. Data were analyzed following a thematic approach. Results Caregivers had limited information on KMC before admission with most of the information learned from peers rather than medical professionals. Stories of positive outcomes following KMC contributed to a shift in perceptions of premature babies and acceptability of KMC as an effective intervention. Unintended consequences resulting from admission due to KMC disrupts responsibilities around the home and disrupts economic activities. Gender division of roles exists with the implementation of KMC and a mother's support networks are crucial. Conclusion Kangaroo mother care is feasible and acceptable among caregivers. KMC babies are described more positively with the potential to grow into strong and healthy children. KMC remains focused on the mother, which undervalues the important roles of her support network. A change in the nomenclature from kangaroo mother care to kangaroo care would include fathers and others delivering care.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 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".