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Mitchell, Alex J.; Vancampfort, Davy; De Hert, Marc; Stubbs, Brendon (2015)
Publisher: Elsevier Inc.
Languages: English
Types: Article
Subjects: BF, RA
Background: \ud Prevalence rates of smoking in people with mental illness are high and premature mortality attributed to tobacco related physical comorbidity is a major concern. We conducted a meta-analysis comparing rates of receipt of smoking cessation advice among people with and without mental illness.\ud \ud Method:\ud Major electronic databases were searched from inception till August 2014 for studies comparing rates of receipt of smoking cessation advice of people with and without a mental illness. Two independent authors completed methodological appraisal and extracted data. A random effects meta-analysis was utilized.\ud \ud Results:\ud Seven studies of satisfactory methodological quality (n mental illness = 68,811, n control = 652,847) were included. Overall there was no significant difference in smoking cessation advice rates between those with and without a mental illness (RR = 1.02, 95% CI: 0.94 – 1.11-, n = 721,658, Q = 1421, p < 0.001). Subgroup analyses demonstrated people with severe mental illness (SMI) received comparable rates of smoking cessation advice to those without SMI (RR = 1.09, 95% CI 0.98-1.2, n = 559,122). This remained true for people with schizophrenia (RR = 1.09, 95% CI 0.68-1.70) and bipolar disorder (RR = 1.14, 95% CI 0.85-1.5). People with non-severe mental illnesses were slightly more likely to receive smoking cessation advice (RR = 1.16, 95% CI = 1.04-1.30, Q = 1364, p < 0.001, n = 580,206).\ud \ud Conclusions:\ud People with SMI receive similar smoking cessation advice rates as people without mental illness, whilst those with non-severe mental illness are slightly more likely to receive smoking cessation advice. Whilst progress has been made, offering smoking cessation advice should receive a higher priority in everyday clinical practice for patients with a mental health diagnosis.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

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