Psychosocial Challenges Faced by Mothers of Children with Speech and Swallowing Difficulties in Non-Progressive Neurological Disorders: A Phenomenological Analysis
Bibliographic record
Abstract
Non-progressive neurological conditions such as cerebral palsy, childhood stroke, brain tumors, and traumatic brain injury commonly impair movement, balance, posture, speech, and swallowing, with speech and swallowing difficulties affecting up to 80% of children with developmental delay. These complex clinical conditions place a significant burden on children and their caregivers, leading to long-term physical, psychological, social, and economic challenges that markedly reduce quality of life. This qualitative study aimed to explore the psychosocial experiences of mothers caring for children with speech and swallowing difficulties associated with non-progressive neurological disorders in Pakistan. Face-to-face semi-structured interviews were conducted with 25 purposively selected mothers enrolled in the Person with Disability Program at the Helping Hand Institute of Rehabilitation Sciences, Mansehra. Interviews lasted approximately 45 minutes, were audio-recorded with informed consent, and analyzed using interpretative phenomenological analysis. The findings highlight that mothers experience extensive psychosocial difficulties, often compounded by inadequate family and societal support. The study concludes that caregivers of children with speech and swallowing difficulties in a developing country context face multidimensional challenges, underscoring the need for comprehensive, family-centered rehabilitation and psychosocial support programs to enhance caregiver well-being and improve child care outcomes.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 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) | 0.001 | 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".