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Using latent class analysis to identify the complex needs of youth on probation.

ABSTRACT: Youth involved with the juvenile justice system have higher rates of unmet social and psychological service needs than the general population. Yet, scant research has addressed the potentially complex needs of youth on probation. This study is thus a first step in improving our ability to promote positive youth development and improved outcomes from youth on probation. It uses administrative data on probation youth from FY2011-2013 in a mid-Atlantic state. We estimated latent class models based on the ordinal scoring (high, moderate, none/low) of the 25 subscales from a standardized assessment administered at intake. In order to test whether groups were distinct, we examined a range of variables, including the official risk classification and recidivism rates measured by officieal rearrests and reconvictions. We report the demographic differences between the estimated groups, as well as adverse childhood experiences, school and employment status, previous legal history, and substance use history. Ultimately, the seven-class model produced four groups that others have noted: a relatively low needs (lowest need), relatively high needs (complex needs), substance use service needs, and mental health service needs. The other three groups that emerged include two gender specific groups (one for male and one for female high-need groups) and a group with skills needs that lacks supportive and protective skills. The analyses will facilitate a better appreciation for the service needs of moderate risk youth. Youth on probation are not a uniform population; they reflect tremendous heterogeneity, and probation systems should embrace systemic responsivity to provide appropriate services to improve youth outcomes. Advancing efforts to provide a broader spectrum of services that address multi-morbid conditions can ensure that youth have opportunities to improve their quality of life during the period of supervision.

SUBMITTER: Lee JS

PROVIDER: S-EPMC7236694 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Using latent class analysis to identify the complex needs of youth on probation.

Lee JoAnn S JS Taxman Faye S FS

Children and youth services review 20200519

Youth involved with the juvenile justice system have higher rates of unmet social and psychological service needs than the general population. Yet, scant research has addressed the potentially complex needs of youth on probation. This study is thus a first step in improving our ability to promote positive youth development and improved outcomes from youth on probation. It uses administrative data on probation youth from FY2011-2013 in a mid-Atlantic state. We estimated latent class models based ...[more]

PMID: 32501317

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Project description:ImportanceMedically complex patients are a heterogeneous group that contribute to a substantial proportion of health care costs. Coordinated efforts to improve care and reduce costs for this patient population have had limited success to date.ObjectiveTo define distinct patient clinical profiles among the most medically complex patients through clinical interpretation of analytically derived patient clusters.Design, setting, and participantsThis cohort study analyzed the most medically complex patients within Kaiser Permanente Northern California, a large integrated health care delivery system, based on comorbidity score, prior emergency department admissions, and predicted likelihood of hospitalization, from July 18, 2018, to July 15, 2019. From a starting point of over 5000 clinical variables, we used both clinical judgment and analytic methods to reduce to the 97 most informative covariates. Patients were then grouped using 2 methods (latent class analysis, generalized low-rank models, with k-means clustering). Results were interpreted by a panel of clinical stakeholders to define clinically meaningful patient profiles.Main outcomes and measuresComplex patient profiles, 1-year health care utilization, and mortality outcomes by profile.ResultsThe analysis included 104 869 individuals representing 3.3% of the adult population (mean [SD] age, 70.7 [14.5] years; 52.4% women; 39% non-White race/ethnicity). Latent class analysis resulted in a 7-class solution. Stakeholders defined the following complex patient profiles (prevalence): high acuity (9.4%), older patients with cardiovascular complications (15.9%), frail elderly (12.5%), pain management (12.3%), psychiatric illness (12.0%), cancer treatment (7.6%), and less engaged (27%). Patients in these groups had significantly different 1-year mortality rates (ranging from 3.0% for psychiatric illness profile to 23.4% for frail elderly profile; risk ratio, 7.9 [95% CI, 7.1-8.8], P < .001). Repeating the analysis using k-means clustering resulted in qualitatively similar groupings. Each clinical profile suggested a distinct collaborative care strategy to optimize management.Conclusions and relevanceThe findings suggest that highly medically complex patient populations may be categorized into distinct patient profiles that are amenable to varying strategies for resource allocation and coordinated care interventions.

Project description:Background: Current evidence suggests that the information needs of people with diabetes mellitus differ across patient groups. With a view to being able to provide individualized information, this study aims to identify (i) the diabetes-related information needs of people with diabetes mellitus; (ii) different subgroups of people with specific information needs; and (iii) associated characteristics of the identified subgroups, such as sociodemographic characteristics, diabetes-related comorbidities, and well-being.Methods: This cross-sectional study was based on data from 837 respondents with diabetes mellitus who participated in the population-based KORA (Cooperative Health Research in the Augsburg Region) Health Survey 2016 in Southern Germany (KORA GEFU 4 study) (45.6% female, mean age 71.1?years, 92.8% Type 2 diabetes). Diabetes-related information needs were assessed with a questionnaire asking about patients' information needs concerning 11 diabetes-related topics, e.g. 'long-term complications' and 'treatment/therapy'. Subgroups of people with different information needs and associated characteristics were identified using latent class analysis.Results: We identified the following four classes of people with different information needs: 'high needs on all topics', 'low needs on all topics', 'moderate needs with a focus on complications and diabetes in everyday life', and 'advanced needs with a focus on social and legal aspects and diabetes research'. The classes differed significantly in age, years of education, type of diabetes, diabetes duration, diabetes-related comorbidities, smoking behaviour, diabetes education, current level of information, and time preference.Conclusions: Knowledge about different patient subgroups can be useful for tailored information campaigns or physician-patient interactions. Further research is needed to analyse health care needs in these groups, changes in information needs over the course of the disease, and prospective health outcomes.

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Using latent class analysis to identify the complex needs of youth on probation.

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Using latent class analysis to identify the complex needs of youth on probation.

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