The health experience of children, adolescents and their families during the COVID-19 pandemic: an exploratory qualitative study in pediatric homecare
Bibliographic record
Abstract
Introduction: The COVID-19 pandemic has had a significant impact on society. Families with an ill child were more vulnerable to that context. To the best of our knowledge, no study has explored the health experience of the entire family during the COVID-19 pandemic by giving them a voice. Thus, our study aimed to explore the health experiences of children and adolescents aged 11 years and older, as well as their families, who received pediatric home care in the canton of Vaud, Switzerland, during this pandemic for an initial health problem or as part of ongoing care. Methods: A qualitative approach was employed, including 27 semi-structured interviews (but for quality reasons only 25 were coded) with children and adolescents aged ≥ 11 years and their family members who received pediatric home nursing care in the canton of Vaud. The interview guide was based on the Calgary Family Assessment and Intervention Model. Data were collected from February to April 2023 and analyzed using an inductive and deductive approach based on the theoretical framework. The total duration of the interviews is 958 minutes, and they lasted between 15 and 80 minutes. Results: The findings highlight that families with an ill child face numerous challenges at individual, familial, and community levels. They were perceived heterogeneously between the participants. For instance, government measures were sometimes perceived as precious resources and sometimes not. While some challenges are exacerbated by the pandemic, others are unrelated. However, it is important to emphasize that these families also possess a variety of resources that stem from the same systems levels. Practical needs as prioritized access to food delivery were highlight by parents, specially mothers who seemed to support the majority of the burden. Conclusions and implications: Despite their remarkable resilience, families experienced difficulties during the COVID-19 pandemic. This underscores the need to learn from this experience to prepare for the future better. some measures must also be quickly implemented to counter the long-term deleterious effects of the pandemic, especially regarding the health of children and adolescents particularly in terms of psychosocial support for families. A better focus should be made on siblings to take care of them as they are to often the great forgotten ones.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".