Exploring Caregivers’ Perspectives and Perceived Acceptability of a Mobile-Based Telemonitoring Program to Support Pregnant Women at High-Risk for Preeclampsia in Karachi, Pakistan: A Qualitative Descriptive Study
Bibliographic record
Abstract
Very little is known about the perspectives of the caregivers on the use of telemonitoring (TM) interventions in low-middle-income countries. Understanding caregivers' perspectives on TM interventions is crucial, given that caregiving activities are correlated with the social, emotional, and clinical outcomes among pregnant women. This study aims to explore caregivers' perspectives and perceived acceptability of a mobile phone-based TM program to support pregnant women at high-risk for preeclampsia. A qualitative description design was used to conduct and analyze 28 semi-structured interviews with a diverse group of caregivers. The study was conducted at the Jinnah Post Graduate Medical Center, Karachi, Pakistan. The caregivers were identified through purposive sampling and additional caregivers were interviewed until the point of data saturation. The conventional content analysis technique was used to analyze digital audio recordings of the caregiver interviews. All caregivers embraced the proposed mobile phone-based TM program because they perceived many benefits, including a reduction in caregivers' anxiety and workload, increased convenience, and cost-effectiveness. However, the caregivers cited several caveats to the future implementation of the TM program including the inability of some women and caregivers to use the TM program and the poor acceptance of the TM system among less educated and non-tech savvy families. Our study recommends developing a TM program to reduce the caregiver stress and workload, designing a context-specific TM program using a user-centric approach, training caregivers on the use of the TM program, sensitizing caregivers on the benefits of the TM program, and developing a low-cost TM program to maximize access.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".