Predictive typology of subjective quality of life among participants with severe mental disorders after a five-year follow-up: a longitudinal two-step cluster analysis

Fleury, Marie‐Josée; Grenier, Guy; Bamvita, Jean‐Marie

doi:10.1186/s12955-015-0346-x

Cited by 17 publications

(14 citation statements)

References 81 publications

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“…Greater need for care is usually associated with worse outcomes for individuals with mental disorders, in terms of QoL 17 and recovery. 18 Needs may also have a detrimental effect on service performance: greater problem severity in relation to mental health correlated with lower continuity of care on both patient- and observer-rated scales.…”

Section: Methodsmentioning

confidence: 99%

Mediation analysis of severity of needs, service performance and outcomes for patients with mental disorders

2016

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Section: Methodsmentioning

confidence: 99%

Mediation analysis of severity of needs, service performance and outcomes for patients with mental disorders

2016

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“…Objective QOL includes aspects of the physical environment and social functioning (2), whereas subjective QOL (SQOL) relates more to individual preferences, opinions, and life satisfaction (3). Research on QOL has been conducted with patients affected by mental health disorders (MHDs) (4–7); while studies on QOL and homelessness have focused on veterans (8–10), newly housed individuals who were previously homeless (11, 12), or homeless individuals with MHDs or substance use disorders (SUDs) (13, 14). However, few studies have focused on QOL in homeless populations.…”

Section: Introductionmentioning

confidence: 99%

Profiles of Quality of Life in a Homeless Population

et al. 2019

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Quality of life (QOL) is a key indicator in mental health planning, program evaluation, and evaluation of patient outcomes. Yet few studies have focused on QOL in homeless populations. More specifically, research has yet to identify profiles of homeless individuals based on their QOL using cluster analysis. This study developed a typology of QOL for a sample of 455 homeless individuals recruited from 27 community and public organizations in Quebec (Canada). The typology was developed based on QOL scores, as well as sociodemographic, clinical, and service use variables. Study participants had to be at least 18 years old, with current or previous experience of homelessness. A questionnaire including socio-demographics, residential history, service utilization, and health-related variables was administered. Four clusters were identified using a two-step cluster analysis. QOL was highest in the cluster consisting of older women with low functional disability, and relatively few episodes of homelessness. The second cluster with high QOL scores included individuals living in temporary housing with relatively few mental health or substance use disorders (SUDs). The third cluster with low QOL included middle-aged women living in temporary housing, with criminal records, personality disorders, and SUDs. QOL was also lower in the fourth cluster composed of individuals with multiple homeless episodes and complex health problems as well as high overall service use. Findings reinforced the importance of disseminating specific programs adapted to the diverse profiles of homeless individuals, with a view toward increasing their QOL.

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“…Among non‐UIFSM, a two‐step cluster analysis revealed three clusters of responses in relation to the reasons for their decision. Cohesion was poor (0.2) using the silhouette measure of cohesion and separation , although the ratio of the larger to smaller cluster was 2.19 (good) . Four reasons were of importance amongst these parents (Table ), ‘I don't like the current menu’ and ‘I like to know how much food my child eats’, ‘I like to know what food my child eats’ and ‘I think school meals are of poor quality’.…”

Section: Resultsmentioning

confidence: 99%

“…Degrees of association between clusters of 0.5 or greater were considered important, similar to the analysis undertaken by Fleury et al . Cluster analyses were followed by an analysis of variance ( anova ) to test for any differences in demographic characteristics of resultant clusters.…”

Section: Methodsmentioning

confidence: 99%

“…Two-step cluster analyses were used to identify natural groupings of respondents (UIFSM or non-UIFSM) on the basis of their endorsement of all/selected statements relating to the decision about taking USIFM. Participants were first preclustered into small subclasses, and then clustered into an appropriate number of larger classes, based on respondents with similar profiles (27) . Degrees of association between clusters of 0.5 or greater were considered important, similar to the analysis undertaken by Fleury et al (27) Cluster analyses were followed by an analysis of variance (ANOVA) to test for any differences in demographic characteristics of resultant clusters.…”

Section: Methodsmentioning

confidence: 99%

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Factors associated with universal infant free school meal take up and refusal in a multicultural urban community

Goodchild

Faulks

Swift

et al. 2017

J Human Nutrition Diet

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Background: Universal infant free school meals (UIFSM) were introduced in September 2014 and are available to all key stage 1 (4-7 years) children attending state-maintained infant and primary schools in England. This paper aimed to investigate the school-based factors, child and family socio-demographic characteristics, and parental beliefs associated with UIFSM take up in an urban community.Methodology: A cross-sectional questionnaire survey was completed in October-November 2015, amongst parents whose children attended eligible schools in Leicester, England. A questionnaire about school meals was also completed by each school.Results: Parents reported their child did not take (non-UIFSM, n=159) or took (UIFSM, n=517) a UIFSM on most days. The non-UIFSM group were more likely to be White-British, have a higher socio-economic status, have English as a first language and involve their child in the decision over whether or not to take UIFSM, compared to the UIFSM group. Cluster analysis revealed non-UIFSM parents were either; concerned over quality of meals and what/how much their child ate, concerned only by what/how much their child ate or their child did not like the food provided. Two subsets of parents in the UIFSM group were either; very positive about UIFSM or appeared to take meals because they were free. Schools used a variety of measures to increase and maintain UIFSM take up.Conclusions; Parents like to have control over what their child eats at school and children need to enjoy their school meals. Using a range of interventions to target sub-sets of parents may help local authorities, schools and caterers to increase UIFSM take up.

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Predictive typology of subjective quality of life among participants with severe mental disorders after a five-year follow-up: a longitudinal two-step cluster analysis

Cited by 17 publications

References 81 publications

Mediation analysis of severity of needs, service performance and outcomes for patients with mental disorders

Mediation analysis of severity of needs, service performance and outcomes for patients with mental disorders

Profiles of Quality of Life in a Homeless Population

Factors associated with universal infant free school meal take up and refusal in a multicultural urban community

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