Subgroups of Dutch homeless young adults based on risk- and protective factors for quality of life: Results of a latent class analysis

Abstract

It is important to gain more insight into specific subgroups of homeless young adults (HYA) to enable the development of tailored interventions that adequately meet their diverse needs and to improve their quality of life. Within a heterogeneous sample of HYA, we investigated whether subgroups are distinguishable based on risk- and protective factors for quality of life. In addition, differences between subgroups were examined regarding the socio-demographic characteristics, the use of cognitive coping strategies and quality of life. A total of 393 HYA using shelter facilities in the Netherlands were approached to participate, between December 2011 and March 2013. Structured face-to-face interviews were administered approximately 2 weeks after shelter admission by trained research assistants. A latent class analysis was conducted to empirically distinguish 251 HYA in subgroups based on common risk factors (former abuse, victimisation, psychological symptoms and substance use) and protective factors (resilience, family and social support and perceived health status). Additional analysis of variance and chi-square tests were used to compare subgroups on socio-demographic characteristics, the use of cognitive coping strategies and quality of life. The latent class analysis yielded four highly interpretable subgroups: the at-risk subgroup, the high-risk and least protected subgroup, the low-risk subgroup and the higher functioning and protected subgroup. Subgroups of HYA with lower scores in risk factors showed higher scores in protective factors, the adaptive cognitive coping strategies and quality of life. Our findings confirm the need for targeted and tailored interventions for specific subgroups of HYA. Social workers need to be attentive to the pattern of risk- and protective factors in each individual to determine which risk factors are prominent and need to be targeted and which protective factors need to be enhanced to improve the quality of life of HYA.

Associations of resilience with quality of life levels in adults experiencing homelessness and mental illness: a longitudinal study

“…It also found that higher levels of goal-related self-efficacy were positively associated with higher quality of life values [ 55 ]. Another study conducted with youth who experience homelessness used latent class analysis, found that a greater level of resilience acts as a protective factor which is associated with improved quality of life [ 29 ]. The existing evidence and findings from the present study support the positive and instrumental role of resilience in achieving greater quality of life levels among people with experiences of homelessness and mental illness.…”

“…Furthermore, the effects of resilience on well-being outcomes in homeless populations are often assessed using cross-sectional [ 23 , 25 ] or qualitative methodological designs [ 26 , 27 ]. To date, a handful of studies have explored this relationship over a short-term longitudinal period (e.g., ≤ 2 years)[ 24 , 29 ]. The Toronto site of the At Home/Chez Soi (AH/CS) Housing First (HF) randomised trial collected six years of longitudinal data on quality of life and resilience measures among individuals with mental illness who were experiencing homelessness at the time of recruitment.…”

Functioning profiles in a nationally representative cohort of Spanish older adults: A latent class study

“…LCA allows for modelling latent‐variable solutions from a set of observable characteristics. LCA has been successfully applied in numerous contexts (Altena, Beijersbergen, Vermunt, & Wolf, 2018; Essau & de la Torre‐Luque, 2019; Forrester, Leoutsakos, Gallo, Thorpe, & Seeman, 2019). Our latent categorical variable was defined as the functioning profile, whose categories were formed by means of the common responses of participants to the profile factors at baseline (Table 1).…”

Change in Housing Status among Homeless and Formerly Homeless Individuals in Quebec, Canada: A Profile Study

“…Typological research may reveal similar characteristics among subgroups of homeless individuals, facilitating the implementation of housing and other services that address their specific needs. Some studies have attempted to classify homeless individuals within a broad population [ 2 , 11 ] or in subpopulations such as veterans [ 12 , 13 ] and youth [ 14 , 15 , 16 ]. Several typologies have been established based on previous life experience [ 17 , 18 ], physical or mental health problems [ 13 , 19 , 20 ], quality of life [ 21 , 22 ] and patterns of emergency shelter use [ 23 ].…”

“…Cluster analyses with homeless individuals have been conducted using multiple variables: sociodemographic (e.g., age and sex), clinical (e.g., mental health disorders (MHD) and substance use disorders (SUD)) and service use (e.g., frequency of emergency department visits (ED) and hospitalizations) [ 2 , 17 , 20 , 25 ]. Some typologies have included risk factors (e.g., victimization and arrest history) and protective factors (e.g., social support and positive perceived health) as pertinent variables [ 15 , 22 ]. However, several variables have been less studied with respect to housing stability, including suicidal behavior and functional disability, both very prevalent in homelessness [ 26 ]; use of public primary care services, such as having a family doctor [ 27 , 28 ]; or required codes of living/conduct in different housing models [ 29 , 30 ], for example enforcing stringent abstinence policies against substance use as opposed to the harm reduction policies characteristic of Housing First, a PH model with case management [ 31 , 32 ], which offers direct access for homeless individuals with serious MHD and/or SUD to a PH without the obligation to participate in treatment [ 33 ].…”