The importance of timely identification and treatment of psychosis are increasingly the focus of early interventions, with research targeting the initial high-risk period in the months following first-episode hospitalization. However, ongoing psychiatric treatment and service utilization after the symptoms have been stabilized over the initial years following first-episode has received less research attention.

To model the variables predicting continued service utilization with psychiatrists for adolescents following their first-episode psychosis; examine associated temporal patterns in continued psychiatric service utilization.

This study utilized a cohort design to assess adolescents (age 14.4 ± 2.5 years) discharged following their index hospitalization for first-episode psychosis. Bivariate analyses were conducted on predictor variables associated with psychiatric service utilization. All significant predictor variables were included in a logistic regression model.

Variables that were significantly associated with psychiatric service utilization included: diagnosis with a schizophrenia spectrum disorder rather than major mood disorder with psychotic features (OR = 24.0; P = 0.02), a first degree relative with depression (OR = 0.12; P = 0.05), and months since last psychiatric inpatient discharge (OR = 0.92; P = 0.02). Further examination of time since last hospitalization found that all adolescents continued service utilization up to 18 months post-discharge.

Key findings highlight the importance of early diagnosis, that a first degree relative with depression may negatively influence the adolescent's ongoing service utilization, and that 18 months post-discharge may a critical time to review current treatment strategies and collaborate with youth and families to ensure that services continue to meet their needs.

The authors have not supplied their declaration of competing interest.

Nearly half of care home residents with advanced dementia have clinically significant agitation. Little is known about costs associated with these symptoms toward the end of life. We calculated monetary costs associated with agitation from UK National Health Service, personal social services, and societal perspectives.

Prospective cohort study.

Thirteen nursing homes in London and the southeast of England.

Seventy-nine people with advanced dementia (Functional Assessment Staging Tool grade 6e and above) residing in nursing homes, and thirty-five of their informal carers.

Data collected at study entry and monthly for up to 9 months, extrapolated for expression per annum. Agitation was assessed using the Cohen-Mansfield Agitation Inventory (CMAI). Health and social care costs of residing in care homes, and costs of contacts with health and social care services were calculated from national unit costs; for a societal perspective, costs of providing informal care were estimated using the resource utilization in dementia (RUD)-Lite scale.

After adjustment, health and social care costs, and costs of providing informal care varied significantly by level of agitation as death approached, from £23,000 over a 1-year period with no agitation symptoms (CMAI agitation score 0–10) to £45,000 at the most severe level (CMAI agitation score >100). On average, agitation accounted for 30% of health and social care costs. Informal care costs were substantial, constituting 29% of total costs.

With the increasing prevalence of dementia, costs of care will impact on healthcare and social services systems, as well as informal carers. Agitation is a key driver of these costs in people with advanced dementia presenting complex challenges for symptom management, service planners, and providers.

The contribution of ‘environment’ has been investigated across diverse and multiple domains related to health. However, in the context of large-scale genomic studies the focus has been on obtaining individual-level endophenotypes with environment left for future decomposition. Geo-social research has indicated that environment-level variables can be reduced, and these composites can then be used with other variables as intuitive, precise representations of environment in research.

Using a large community sample (N = 9498) from the Philadelphia area, participant addresses were linked to 2010 census and crime data. These were then factor analyzed (exploratory factor analysis; EFA) to arrive at social and criminal dimensions of participants' environments. These were used to calculate environment-level scores, which were merged with individual-level variables. We estimated an exploratory multilevel structural equation model (MSEM) exploring associations among environment- and individual-level variables in diverse communities.

The EFAs revealed that census data was best represented by two factors, one socioeconomic status and one household/language. Crime data was best represented by a single crime factor. The MSEM variables had good fit (e.g. comparative fit index = 0.98), and revealed that environment had the largest association with neurocognitive performance (β = 0.41, p < 0.0005), followed by parent education (β = 0.23, p < 0.0005).

Environment-level variables can be combined to create factor scores or composites for use in larger statistical models. Our results are consistent with literature indicating that individual-level socio-demographic characteristics (e.g. race and gender) and aspects of familial social capital (e.g. parental education) have statistical relationships with neurocognitive performance.