Actionable Predictive Factors of Homelessness in a Psychiatric Population: Results from the REHABase Cohort Using a Machine Learning Approach

Guillaume Lio, Malek Ghazzai, Frédéric Haesebaert, Julien Dubreucq, Hélène Verdoux, Clélia Quiles, Nemat Jaafari, Isabelle Chéreau-Boudet, Emilie Legros-Lafarge, Nathalie Guillard-Bouhet, Catherine Massoubre, Benjamin Gouache, Julien Plasse, Guillaume Barbalat, Nicolas Franck and Caroline Demily ()
Additional contact information
Guillaume Lio: Centre d’Excellence Autisme iMIND, pôle HU-ADIS, Hôpital le Vinatier, 69678 Bron, France
Malek Ghazzai: Centre d’Excellence Autisme iMIND, pôle HU-ADIS, Hôpital le Vinatier, 69678 Bron, France
Frédéric Haesebaert: Pôle Centre Rive Gauche, Hôpital Le Vinatier, 69678 Bron, France
Julien Dubreucq: Centre Hospitalier Universitaire de Saint-Etienne, 42270 Saint-Priest-en-Jarez, France
Hélène Verdoux: Hôpital Charles Perrens, Université de Bordeaux, 33405 Talence, France
Clélia Quiles: Hôpital Charles Perrens, Université de Bordeaux, 33405 Talence, France
Nemat Jaafari: CREATIV & URC Pierre Deniker, Centre Hospitalier Laborit, Université de Poitiers, 86000 Poitiers, France
Isabelle Chéreau-Boudet: Centre Référent Conjoint de Réhabilitation (CRCR), Centre Hospitalier Universitaire de Clermont-Ferrand, 63000 Clermont-Ferrand, France
Emilie Legros-Lafarge: Centre Référent de Réhabilitation Psychosociale de Limoges (C2RL), 87000 Limoges, France
Nathalie Guillard-Bouhet: Centre Hospitalier Laborit, 86000 Poitiers, France
Catherine Massoubre: Centre Hospitalier Universitaire de Saint-Etienne, 42270 Saint-Priest-en-Jarez, France
Benjamin Gouache: Centre Hospitalier Alpes-Isère, 38120 Saint Egrève, France
Julien Plasse: Pôle Centre Rive Gauche, Hôpital Le Vinatier, 69678 Bron, France
Guillaume Barbalat: Pôle Centre Rive Gauche, Hôpital Le Vinatier, 69678 Bron, France
Nicolas Franck: Pôle Centre Rive Gauche, Hôpital Le Vinatier, 69678 Bron, France
Caroline Demily: Centre d’Excellence Autisme iMIND, pôle HU-ADIS, Hôpital le Vinatier, 69678 Bron, France

IJERPH, 2022, vol. 19, issue 19, 1-12

Abstract: Background: There is a lack of knowledge regarding the actionable key predictive factors of homelessness in psychiatric populations. Therefore, we used a machine learning model to explore the REHABase database (for rehabilitation database— n = 3416), which is a cohort of users referred to French psychosocial rehabilitation centers in France. Methods: First, we analyzed whether the different risk factors previously associated with homelessness in mental health were also significant risk factors in the REHABase. In the second step, we used unbiased classification and regression trees to determine the key predictors of homelessness. Post hoc analyses were performed to examine the importance of the predictors and to explore the impact of cognitive factors among the participants. Results: First, risk factors that were previously found to be associated with homelessness were also significant risk factors in the REHABase. Among all the variables studied with a machine learning approach, the most robust variable in terms of predictive value was the nature of the psychotropic medication (sex/sex relative mean predictor importance: 22.8, σ = 3.4). Post hoc analyses revealed that first-generation antipsychotics (15.61%; p < 0.05 FDR corrected), loxapine (16.57%; p < 0.05 FWER corrected) and hypnotics (17.56%; p < 0.05 FWER corrected) were significantly associated with homelessness. Antidepressant medication was associated with a protective effect against housing deprivation (9.21%; p < 0.05 FWER corrected). Conclusions: Psychotropic medication was found to be an important predictor of homelessness in our REHABase cohort, particularly loxapine and hypnotics. On the other hand, the putative protective effect of antidepressants confirms the need for systematic screening of depression and anxiety in the homeless population.

Keywords: homelessness; antipsychotics; REHABase; psychotropic medication; classification and regression tree model (CART); machine learning; depression (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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