Balancing Duty, Stigma, and Caregiving Needs of People With Neurodevelopmental or Neurocognitive Disorders During a Public Health Emergency in South Asia: A Qualitative Study of Carer Experiences
Bibliographic record
Abstract
OBJECTIVE: Individuals with neurodevelopmental and/or neurocognitive disorders (NNDs) have complex, long-term care needs. In Bangladesh, India, and Pakistan, informal carers shoulder the responsibility and strain of providing care for people with NNDs. Intense care demand, societal and cultural care expectations, and lack of support infrastructure often lead to psychosocial strain in this inadequately researched community, particularly during crises such as the COVID-19 pandemic. This study explored and identified specific features of the coping styles exhibited by informal carers of people with NNDs from Bangladesh, India, and Pakistan during the COVID-19 pandemic. MATERIAL AND METHODS: Between June and November 2020, 245 carers in India, Pakistan, and Bangladesh responded to open-ended questions in the CLIC (Coping with Loneliness, Isolation, and COVID-19) survey. A reflexive thematic analysis was conducted to uncover the underlying themes and identify coping strategies and stressors. A frequency analysis was performed to examine the associations between these themes and carer nationality. Significant tests identified coping styles. RESULTS: We identified three coping styles: religiosity (Pakistan), caregiving as a natural life path (Bangladesh), and self-care (India). The religiosity and natural life path styles reside on the fatalism/acceptance continuum and suggest an insight-oriented therapeutic approach. Self-care is a problem-solving strategy that calls for a behaviorally oriented approach. Family overreliance on the carer was a concern across all three groups. CONCLUSIONS: The findings underscore the need for accessible support pathways to sustain care standards, ensuring the well-being of carers and care recipients.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.004 |
| 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".