Psychosocial adjustment in children and adolescents with a parent with multiple sclerosis: a systematic review
Bibliographic record
Abstract
OBJECTIVE: This systematic review explored the potential impact of parental multiple sclerosis on their offspring. It considered adjustment to parental multiple sclerosis at different developmental stages and the factors associated with good versus poor adjustment. DATA SOURCES: MEDLINE, EMBASE, PsycINFO, CINAHL and Web of Science were searched for studies on children with a parent with multiple sclerosis. Inclusion and exclusion criteria were formulated. Hand-searching journals and reference lists, contacting authors and multiple sclerosis societies for additional unpublished papers complemented the searches. REVIEW METHODS: Twenty studies that satisfied the inclusion criteria were included. The research articles were ranked according to a quality assessment checklist and were categorized as good, medium or poor quality. RESULTS: The review found good evidence to suggest that parental multiple sclerosis has a negative impact on children's social and family relationships and their psychological well-being. The review also identified potential factors associated with poor adjustment. These factors included parental negative emotions, increased illness severity, family dysfunction, children's lack of knowledge about the illness and lack of social support. Adolescent children also seemed to be more at risk for psychosocial problems than school-age children. CONCLUSIONS: There is good evidence that parental multiple sclerosis has a negative psychosocial impact on children, especially on adolescents.
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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".