ArticleQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation2022
Impact and predictors of quality of life in adults diagnosed with a genetic muscle disorder: a nationwide population-based study.
Article in Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- Mediating effect of respiratory symptoms on the association between residential distance and the quality of life among residents living near waste incineration plants in Dongguan, Southern China.BMC public health · 2024Article
- Arrhythmias and cardiac MRI associations in patients with established cardiac dystrophinopathy.Open heart · 2024Article
- A comprehensive qualitative framework for health-related quality of life in Duchenne muscular dystrophy.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 7 institutions in 1 country.
Funding
Abstract
objectivesTo determine the impact of genetic muscle disorders and identify the sociodemographic, illness, and symptom factors influencing quality of life.
methodsAdults (aged 16-90 years) with a confirmed clinical or molecular diagnosis of a genetic muscle disorder identified as part of a nationwide prevalence study were invited to complete an assessment of the impact of their condition. Quality of life was measured using the World Health Organization Quality of Life questionnaire. Impact was measured via the prevalence of symptoms and comparisons of quality of life against New Zealand norms. Multivariate regression models were used to identify the most significant predictors of quality of life domains.
results490/596 participants completed the assessment (82.2% consent rate). Quality of life was lower than the general population on physical (t = 9.37 p < 0.0001, d = 0.54) social (t = 2.27 p = 0.02, d = 0.13) and environmental domains (t = 2.28 p = 0.02, d = 0.13), although effect sizes were small. No difference was found on the psychological domain (t = - 1.17 p = 0.24, d = 0.07). Multivariate regression models (predicting 42%-64% of the variance) revealed personal factors (younger age, being in employment and in a relationship), symptoms (lower pain, fatigue, and sleep difficulties), physical health (no need for ventilation support, fewer activity limitations and no comorbidities), and psychosocial factors (lower depression, anxiety, behavioural dyscontrol and higher self-efficacy, satisfaction with health care and social support) contributed to improved quality of life.
conclusionsA range of factors influence the quality of life in adults diagnosed with a genetic muscle disorder and some may serve as targets for multi-faceted intervention.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.