Question · asked by 1 review

Disability (developmental, intellectual, or sensory) vs Persons without disabilities: Oral health-related quality of life

Persons with disabilities in Saudi Arabia report poorer overall oral health-related quality of life and greater oral-health impact than those without disabilities, synthesized narratively without a pooled estimate (ungraded).

What each review found

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FindingEffectStudiesGRADE certainty
Disability (developmental, intellectual, or sensory) vs Persons without disabilities
Overall oral health-related quality of life (OHRQoL) impact (self- and proxy/caregiver-reported) · Persons with disabilities (children and adults with autism, Down syndrome, cerebral palsy, hearing impairment, or… · Cross-sectional, Autism centres, dental hospital, disability centres, hospital, and public schools across Saudi Arabia (Riyadh, Jeddah, Qassim, Abha)
Persons with disabilities in Saudi Arabia report poorer overall oral health-related quality of life and greater oral-health impact than those without disabilities, synthesized narratively without a pooled estimate (ungraded).
Disabilities and Disparities in Oral Health-Related Quality of Life: A Systematic Review and Meta-Analysis… (2024) All outcomes
Narrative synthesis (no pooled estimate). PWDs reported reduced functional, emotional, and social well-being and greater oral-health impact on quality of life. AlJameel 2021 (Down syndrome): 34.9% of children and 46%…Not reportedGRADE not reported

Findings are shown side by side, never pooled across reviews.

The reviews

ReviewSearched up toIncluded studiesAMSTAR 2
Disabilities and Disparities in Oral Health-Related Quality of Life: A Systematic Review and Meta-Analysis in Saudi Arabia.
2024 All outcomes
1 July 2024 (initial search); 25 September 2024 (last update)10Not applicable

Studies behind the findings

The primary studies the full-text reviews tie to this outcome. Reviews with headline outcomes only do not list them here.

How reviews are matched to this question

Reviews word the same question differently. Four decision models (TypeSafe's Jev, Liquid AI's d1-ultra, SubQ Snap and Baseten's Elephant) judged each wording of the population, intervention, comparator and outcome against the others; two wordings count as the same when at least three of them agree and none clearly disagrees, and findings count as this question only when all four elements match. Timing, setting and subgroup never split a question: they are shown on each finding.