The Impact of Sex Upon Needs and Quality of Life Within a Population on XXXX Treatment.

@entity1 @entity284
BACKGROUND: Best practice models are calling for a holistic, needs-led, and sex-informed treatment approach to substance misuse treatment. To date, research into the impact of sex on needs and quality of life within @entity284 -treatment populations using validated research tools is limited. OBJECTIVES: The aim of the study was to evaluate the impact of sex upon self-rated unmet need and quality of life among @entity1 on @entity284 treatment. METHODS: Cross-sectional survey of adults attending a specialist @entity284 treatment clinic, in Dublin, Ireland. @entity1 completed the Camberwell Assessment of Need Short Appraisal Schedule, @entity1 Version and the WHO Quality of Life-Brief Version. Ongoing drug use was determined using the Maudsley Addiction Profile and weekly supervised urine toxicology screens. A linear regression analysis was conducted. RESULTS: One hundred eight of 190 eligible service-users (57%) participated. No significant differences existed between the @entity1 and the nonparticipants on demographic variables or measures of drug use. Among them, 33% were @entity1 . @entity1 demonstrated lower levels of ongoing opiate use. Linear regression analysis indicated that @entity1 had a greater number of unmet needs (P=0.02) and lower quality of life in the domains of physical health (P=0.003), psychological well being (P<0.001), environmental well being (P=0.03), and social relationships (P=0.007). When the Bonferroni adjustment was applied to account for multiple testing, the relationship between psychological well being and female sex remained statistically significant. CONCLUSIONS: Our study suggests that female sex may be associated with greater self-rated needs and poorer quality of life within a @entity284 -treated population, in particular, in the domain of psychological well being. Further research in this area is warranted to discover if these findings can be replicated and confirmed in larger samples.
