Keywords Mental health Treatment utilization Epidemiology France ORIGINAL PAPER

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1 ORIGINAL PAPER Prevalence and predictors of no lifetime utilization of mental health treatment among people with mental disorders in France: findings from the Mental Health in General Population (MHGP) survey Hélène Font 1 Jean Luc Roelandt 1 Hélène Behal 2 Pierre Alexis Geoffroy 3,4 Baptiste Pignon 5,6,7,8 Ali Amad 9,11 Nicolas Simioni 12 Guillaume Vaiva 9,11 Pierre Thomas 9,11 Alain Duhamel 2 Imane Benradia 1 Benjamin Rolland 9,10,13,14 Received: 16 November 2017 / Accepted: 28 March 2018 Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract Purpose No lifetime utilization of mental health treatment (NUMT) is an indicator of the treatment gap among people in need of treatment. Until now, the overall prevalence and predictors of NUMT have never been explored in France. Methods In a 39,617-respondent survey, participants were assessed for NUMT, i.e., no lifetime psychotherapy, psychopharmacotherapy, or psychiatric hospitalization. Mental disorders were investigated using the Mini International Neuropsychiatric Interview (MINI 5.0.0). MINI diagnoses were grouped into five categories: mood disorders (MDs); anxiety disorders (ADs); alcohol use disorders (AUDs); substance use disorders (SUDs); and psychotic disorders (PDs). Using multivariable logistic regression models, we explored the factors associated with NUMT among the MINI-positive respondents. The odds ratio and 95% confidence interval were calculated for each factor. Results In total, 12,818 (32.4%) respondents were MINI-positive, 46.5% of them reported NUMT (35.6% for MDs, 39.7% for PDs, 42.8% for ADs, 56.0% for AUDs, and 56.7% for SUDs). NUMT was positively associated with being male [OR 1.75 ( )] and practising religion [OR 1.13 ( )] and negatively associated with ageing [per 10-year increase: OR 0.88 ( )], being single [OR 0.74 ( )], being a French native [OR 0.67 ( )], and experiencing MDs [OR 0.39 ( )], ADs [OR 0.47 ( )], AUDs [OR 0.83 ( )], SUDs [OR 0.77 ( )], or PDs [OR 0.50 ( )]. Conclusions In France, NUMT rates were the highest for AUDs and SUDs. Additionally, suffering from MDs or ADs increased the lifetime treatment utilization for people having any other mental disorder. This finding emphasizes the need to better screen AUDs and SUDs among people treated for MDs or ADs. Keywords Mental health Treatment utilization Epidemiology France * Hélène Font helene.font63@gmail.com 1 Centre Collaborateur de l Organisation Mondiale de la Santé, 211 rue Roger Salengro, Hellemmes, France 2 Département de Biostatistiques, Univ. Lille, CHU Lille, EA 2694, Santé publique: épidémiologie et qualité des soins, Lille, France 3 AP-HP, GH Saint-Louis, Lariboisière, Fernand Widal, Pôle Neurosciences, Paris, France Université Paris Diderot, UMR-S 1144, Paris, France AP-HP, DHU PePSY, Hôpitaux Universitaires Henri Mondor, Pôle Psychiatrie Addictologie, Créteil, France INSERM, U955, équipe 15, Créteil, France 7 Fondation FondaMental, Créteil, France 8 UPEC, Université Paris-Est, Faculté de médecine, Créteil, France 9 Pôle de Psychiatrie et Addictologie, CHRU de Lille, Lille, France 10 INSERM U1171, Univ Lille, Lille, France 11 UMR9193 PsychiC SCALab, Department of Psychiatry, Univ. Lille, CNRS, CHU de Lille, Lille, France 12 Fondation Phénix, Centre Phénix Plainpalais, Geneva, Switzerland Service Universitaire d Addictologie de Lyon (SUAL), CH Le Vinatier, Bron, France Université de Lyon, UCBL, Lyon, France Vol.:( )

2 Introduction The gap between experiencing a mental health disorder and using treatment for this disorder has been called the treatment gap [1]. The treatment gap in mental health varies widely depending on country and category of disorder. According to international estimates published in 2004 in the Bulletin of the World Health Organization [1], the treatment gap rates in the Americas ranged between 48.6% for dysthymia and 82.0% for obsessive compulsive disorders. The treatment gap rates in Europe appeared even more heterogeneous, ranging from 17.8% for schizophrenia to 92.4% for alcohol use disorders (AUDs). Consequently, reducing the mental health treatment gap has recently been identified as one of the top priorities for contemporary mental health policy in Europe [2]. However, the mental health treatment gap is a complex issue, as there are many contributing factors. On the one hand, some psychiatric symptoms and their subsequent cognitive impairments can limit individuals with mental health disorders from spontaneously seeking treatment. On the other hand, some social and cultural factors, including stigma, health policies, and mental health insurance coverage [3], might also play a crucial role in determining treatment utilization for mental health disorders. The lifetime utilization of mental health treatment among people with mental health disorders is a limited but useful indicator of the treatment gap, whether in the general population [4, 5] or in certain subgroups [6]. In particular, people with no lifetime utilization of mental health treatment (NUMT) can be defined as those who have neither used any service nor received any treatment for a mental disorder. Among people with a mental disorder, NUMT individuals constitute an extreme section of the population affected by the mental health treatment gap, namely, those who have never received any treatment. Better understanding of these persons and identifying individual or cultural factors that may have prevented them from obtaining treatment are major challenges in increasing the use of mental health services and thereby potentially reducing the treatment gap. Previous investigations of NUMT have primarily focused on specific categories of mental health disorders, essentially mood disorders [4] and substance use disorders [5, 7]. Consequently, it is still unclear whether the factors that affect NUMT rates are similar among the different types of mental health disorders. Moreover, it is unknown whether people with multiple mental health disorders exhibit increased or, on the contrary, decreased NUMT rates compared to people with only one mental disorder. In a 39,607-respondent survey conducted in the French general population, we determined the NUMT rates for different mental disorders (defined by the 10th International Classification of Diseases ICD-10) and explored the factors associated with global and specific NUMT rates among the main sociodemographic features and comorbid disorders. Overall, this was the first study to explore NUMT in the French population. Materials and methods Type of study We analyzed data from a cross-sectional multi-site French survey called Santé Mentale en Population Générale, i.e., Mental Health in General Population (MHGP). This survey was conducted by the World Health Organization Collaborating Centre (WHO-CC). Its complete methodology has been described elsewhere [8 11]. Sample Between 1999 and 2003, 39,617 persons were interviewed at 47 French sites. The inclusion criteria were as follows: (1) providing informed consent to participate in the survey; (2) being aged 18 years and over; (3) speaking French; and (4) being neither institutionalized nor homeless. At each site, approximately 900 participants were recruited by quota sampling stratified by age, sex, occupational status, and educational level based on the profile of the general population at each site according to the French national census. Variables and diagnostic categories Trained nurses conducted face-to-face interviews comprising two main parts. The first part assessed aspects of previous mental health treatment utilization. More specifically, participants were asked the following questions: (1) have you ever attended a consultation with a psychiatrist or a psychologist? ; (2) have you ever been prescribed a psychotropic drug, that is, a drug for a psychiatric disorder or a drug for nerves? ; and (3) have you ever been hospitalized in a psychiatric or mental health setting?. We considered that a respondent never had previously used mental health treatment or services and then we categorized him/her as a NUMT person if he/she answered no to these three questions. The second part of the interview corresponded to the Mini International Neuropsychiatric Interview (MINI, French version 5.0.0), which is a standardized and validated tool for investigating ICD-10 psychiatric disorders in the general population [12]. Each of the following ICD-10 mental disorders was investigated: (1) current (i.e., past 2 weeks) major depressive disorder; (2) lifetime manic

3 episode; (3) current (i.e., past 2 years) dysthymia; (4) current (i.e., past-month) panic disorder; (5) current (i.e., past-month) agoraphobia; (6) current (i.e., past-month) social phobia; (7) current (i.e., past-month) post-traumatic stress disorder (PTSD); (8) current (i.e., past-year) AUD; (9) current (i.e., past-year) other substance use disorder (SUD); and (10) any lifetime psychotic disorder. The ICD-10 diagnoses were then grouped into different diagnosis categories: (1) any mood disorder (i.e., major depressive disorder, manic episode, and dysthymia); (2) any anxiety disorder (i.e., panic disorder, agoraphobia, social phobia, and post-traumatic stress disorder); (3) AUDs; (4) SUDs; and (5) any psychotic disorder. This categorization was previously used by the WHO to explore the mental health treatment gap [1]. Statistical analyses Qualitative variables were expressed as frequencies and percentages. Age was expressed as the mean and standard deviation (SD). Six logistic regression models were built to identify the factors associated with NUMT in different populations. One included respondents with at least one positive diagnosis of a mental disorder according to the MINI, and five assessed subgroups of respondents according to the diagnostic mental disorder categories: mood disorders, anxiety disorders, AUDs, other SUDs and psychotic disorders. The objective of these different analyses was to identify the factors associated with NUMT in general, as well as for each of the five predefined categories of mental health disorders. The selection of sociodemographic factors potentially associated with NUMT was based on previous literature on treatment utilization [13 16]: sex, age, marital status, educational level, household income, occupational status, place of birth (French-born or foreign-born), religious practice, and living alone were systematically included in the multivariable models. Additionally, we introduced the diagnostic categories of mental disorders as covariables in the model of MINI-positive people. Similarly, for models applied in a specific mental disorder population, we included the other mental disorder diagnoses as covariables. The strength of the association between each factor and NUMT in the different multivariable logistic regression models was expressed as the odds ratio (OR) and its 95% confidence interval (95% CI). Statistical testing was conducted at a two-tailed α level of The Nagelkerke R 2 is provided for each model, as an indicator of goodness of fit. Data were analyzed using SAS software (version 9.3, SAS Institute Inc., Cary, NC, USA). Ethic procedures The protocol of the MHGP survey was declared to and approved by an ad hoc national ethics committee (#CCTIRS ) prior to conducting the study. All the participants gave their written consent prior to participation in the survey. Results Of the 39,617 participants in the survey, 12,818 (32.4%) exhibited at least one positive diagnosis of a mental disorder according to the MINI. Among them, 6846 (53.5%) reported previous mental health treatment for any reason, whereas 5952 (46.5%) were NUMT. Table 1 and Fig. 1 show the NUMT rates. Moreover, Fig. 1 displays the prevalence rates of NUMT persons based on the different diagnostic categories. In total, 5450 respondents (i.e., 13.8% of the entire sample) had at least one diagnosis of a mood disorder (NUMT: n = 1937; 35.6%); 4425 respondents (11.2%) met the criteria for current major depressive disorder, 1619 (36.6%) of whom reported NUMT; and 925 respondents (2.3%) met the criteria for dysthymia, 245 (26.9%) of whom reported NUMT. Finally, 628 (1.6%) respondents met the criteria for a previous or current manic episode, and 178 of them (28.3%) reported NUMT. Additionally, 8672 respondents (21.9%) met the criteria for at least one diagnosis of an anxiety disorder (NUMT: n = 3705; 42.8%). Specifically, 819 respondents (2.1%) were diagnosed with agoraphobia (NUMT: n = 302; 37.4%), 1693 (4.3%) with panic disorder (NUMT: n = 457; 27.0%), 1737 (4.4%) with social phobia (NUMT: n = 762; 43.9%), 5070 (12.8%) with generalized anxiety disorder (NUMT: n = 2274; 45.6%), and 285 (0.7%) with PTSD (NUMT: n = 126; 44.2%). A total of 1721 respondents (4.3%) were diagnosed with AUDs (NUMT: n = 963; 56.0%). Furthermore, 1095 respondents (2.8%) met the criteria for other SUDs (NUMT: n = 621; 56.7%). Finally, 1110 respondents (2.8%) exhibited a diagnosis of psychotic disorder (NUMT: n = 439; 39.7%). The results of the multivariable logistic regressions are presented in Table 2 (unadjusted results are presented in Table 3). Overall, the analyses found that being male was significantly and positively associated with NUMT for all disorders combined [OR 1.75; 95% CI ( )], as well as for mood disorders [OR 1.70; 95% CI ( )], anxiety disorders [OR 1.73; 95% CI ( )], AUDs [OR 1.60; 95% CI ( )]; SUDs [OR 1.66; 95% CI ( )]; and psychotic disorders [OR 1.93; 95% CI ( )]. Increased age showed significant but negative association with NUMT for all disorders combined [OR 0.88; 95% CI ( )], mood disorders [OR 0.88;

4 Table 1 Descriptive statistics of the sample (MHGP ) Total, n = 39,617 MINI-pos a, n = 12,818 (32.4) MDD, n = 4,425 (11.2) DYSTH, n = 925 (2.3) MANIC EP, n = 628 (1.6) Any MD b, n = 5,450 (13.8) AGO- RAPH, n = 819 (2.1) PANIC DIS, n = 1,693 (4.3) SOC PHOB, n = 1,737 (4.4) GEN ANX, n = 5070 (12.8) PTSD, n = 285 (0.7) Any AD c, n = 8672 (21.9) AUDs, n = (4.3) SUDs, n = 1095 (2.8) PSYCHOT, n = (2.8) Gender (female) 21,337 (53.9) 7303 (57.0) 2771 (62.6) 610 (66.0) 262 (41.7) 3348 (61.4) 552 (67.4) 1124 (66.4) 1129 (65.0) 3076 (60.7) 169 (59.3) 4709 (55.8) 340 (19.8) 290 (26.5) 567 (51.1) Age (years) 44.7 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± 16.0 Marital status Single 11, (33.6) 1474 (33.5) 268 (29.2) 253 (40.6) 1816 (33.6) 227 (28.0) 603 (35.9) 644 (37.4) 1464 (29.1) 93 (32.9) 2711 (31.5) 730 (42.7) 785 (72.0) 483 (43.8) (28.1) 5994 (47.1) 1861 (42.4) 364 (39.6) 236 (37.8) 2280 (42.1) 412 (50.8) 783 (46.6) 830 (48.2) 2545 (50.5) 126 (44.5) 4276 (49.7) 697 (39.7) 246 (22.5) 403 (36.5) Married/living with a partner Divorced/widowed Educational level Uncompleted primary Uncompleted secondary Completed secondary Monthly household income < ,392 (54.4) 6877 (17.5) 2461 (19.3) 1059 (24.1) 287 (31.2) 135 (21.6) 1317 (24.3) 172 (21.2) 294 (17.5) 249 (14.4) 1029 (20.4) 64 (22.6) 1621 (18.8) 300 (17.6) 60 (5.5) 271 (19.7) 9441 (23.8) 2941 (22.9) 1201 (27.1) 275 (29.7) 110 (17.5) 1428 (26.2) 241 (29.4) 384 (22.6) 345 (19.9) 1203 (23.7) 79 (27.7) 2016 (23.2) 331 (19.2) 94 (8.6) 214 (19.3) 19,439 (49.1) 10,373 (27.1) 14,772 (38.4) French-born 32,960 (83.8) 6776 (52.9) 2349 (53.1) 460 (49.7) 361 (57.5) 2883 (52.9) 414 (50.6) 895 (52.9) 898 (51.7) 2707 (53.4) 150 (52.6) 4558 (52.6) 1014 (58.9) 679 (62.0) 606 (54.6) 3101 (24.2) 875 (19.8) 190 (20.6) 157 (25.0) 1139 (20.9) 164 (20.0) 414 (24.5) 494 (28.4) 1160 (22.9) 56 (19.7) 2098 (24.2) 376 (21.9) 322 (29.4) 290 (26.1) 5614 (43.0) 2263 (52.9) 469 (51.8) 299 (48.8) 2710 (51.3) 377 (47.7) 788 (48.1) 755 (44.7) 2128 (43.0) 148 (53.4) 3732 (44.2) 822 (48.9) 545 (51.6) 577 (53.7) 10,552 (82.9) 3484 (79.3) 796 (86.3) 528 (84.3) 4365 (80.6) 675 (83.0) 1406 (83.7) 1492 (86.3) 4176 (83.0) 221 (78.1) 7188 (83.5) 1424 (83.4) 907 (83.3) 849 (76.9) Religious practice 9091 (27.7) 2777 (26.0) 1063 (28.7) 199 (26.2) 110 (21.2) 1258 (27.7) 211 (29.5) 358 (25.1) 346 (23.6) 1139 (26.8) 70 (70.1) 1916 (26.3) 220 (15.8) 103 (11.9) 278 (30.1) Living alone 9798 (24.9) 3509 (27.5) 1387 (35.9) 333 (36.1) 217 (34.9) 1724 (31.8) 209 (25.6) 569 (27.3) 428 (24.8) 1265 (25.1) 89 (31.2) 2180 (25.3) 581 (34.0) 345 (31.7) 364 (33.1) In employment 21, (51.3) 1987 (44.9) 428 (46.3) 335 (53.3) 2541 (46.6) 373 (45.5) 826 (48.8) 858 (49.4) 2689 (53.0) 132 (46.3) 4451 (51.3) 1003 (58.3) 528 (48.2) 531 (47.8) (53.2) NUMT 25, (46.5) 1619 (36.6) 245 (26.9) 178 (28.3) 1937 (35.6) 302 (37.4) 457 (27.0) 762 (43.9) 2274 (45.6) 126 (44.2) 3705 (42.8) 963 (56.0) 621 (56.7) 439 (39.7) (64.7) AGORAPH agoraphobia, AUDs alcohol use disorders, DYSTH dysthymia, MANIC EP manic episode, MD mood disorder, MDD major depressive disorder, MINI Mini International Neuropsychiatric Interview 5.0.0, MINI-pos MINI positive, PANIC DIS panic disorder, PSYCHOT psychotic disorders, SOC PHOB social phobia, SUDs substance use disorders (other than AUDs), NUMT no lifetime utilization of any mental health treatment a The MINI-pos column encompasses all MINI-positive subjects, i.e., those who had at least one disorder diagnosed using the MINI b The any MD subgroup encompasses all subjects with positive MINI criteria for MDD, DYSTH, or MANIC EP c The any AD subgroup encompasses all subjects with positive MINI criteria for AGORAPH, PANIC DIS, SOC PHOB, or PTSD

5 significant among people with anxiety disorders, psychotic disorders, or mood disorders. Furthermore, the multivariable analyses performed separately for each disorder revealed that suffering from another mental disorder was globally associated with a reduced NUMT rate (cf. Table 2). However, the degree of decrease differed depending on the type of associated disorder. The reduction in NUMT was large in cases of a comorbid mood or anxiety disorder, whereas it was more modest for comorbid AUDs or SUDs. Discussion Fig. 1 Rates of participants who reported no lifetime use of mental health treatment (i.e., never having met a psychiatrist or psychologist, never having been hospitalized in a mental health unit, and never having been prescribed any psychotropic drug) according to the type of mental disorder (MHGP ) 95% CI ( )], anxiety disorders [OR 0.86; 95% CI ( )], and psychotic disorders [OR 0.79; 95% CI ( )] but not for AUDs and SUDs. Compared with living with a partner, being single was significantly associated with a reduced NUMT risk for all disorders combined [OR 0.74; 95% CI ( )], mood disorders [OR 0.67; 95% CI ( )], anxiety disorders [OR 0.84; 95% CI ( )], and SUDs [OR 0.47; 95% CI ( )]; however, this association was not significant for psychotic disorders. Similarly, compared with living with a partner, being separated, divorced, or widowed was negatively associated with NUMT for all disorders combined [OR 0.65; 95% CI ( )], as well as for mood disorders [OR 0.58; 95% CI ( )], anxiety disorders [OR 0.69; 95% CI ( )], and AUDs [OR 0.53; 95% CI ( )]. Whatever the type of mental disorder, NUMT did not appear to be associated with household income or employment. Being French-born was significantly associated with decreased NUMT for all disorders combined [OR 0.67; 95% CI ( )], as well as for mood disorders [OR % CI ( )], anxiety disorders [OR 0.68; 95% CI ( )], AUDs [OR 0.57; 95% CI ( )], and psychotic disorders [OR 0.52; 95% CI ( )] but not for SUDs. Living alone was globally associated with previous or present treatment utilization among the entire population of people with mental disorders, more particularly with AUDs and SUDs. However, this association was not The main objective of this study was to assess the different rates of NUMT in people with mental disorders in the French general population and to address the main determinants of NUMT based on the type of experienced mental disorder. Overall, we found noticeable discrepancies in NUMT rates according to the underlying type of mental disorder. Mood, psychotic, and anxiety disorders had the lowest NUMT rates. In contrast, AUDs and SUDs were much more associated with NUMT. The differences in NUMT rates among the different types of disorders are fully consistent with the discrepancies in the mental health treatment gap rates in Europe reported by the WHO [1], and data were collected approximatively during the same time frame. The gaps observed in our study may appear smaller than those reported by the WHO. However, the methodologies employed were completely different, and the WHO estimated the immediate treatment gap, namely, the proportion of people who were currently in treatment, whereas we used a lifetime approach. Regarding the determinants of NUMT, we found that NUMT was significantly reduced when there were multiple mental health disorders. This finding indicated that respondents with multiple mental disorders were more likely to report previous mental health treatment than those with a single mental disorder. This finding is consistent with a large body of previous literature [17 22]. This may be the result of greater severity of comorbid mental disorders. Indeed, associated mental health disorders have been previously found to be more severe than non-associated disorders, insofar as severity consists of poorer longitudinal outcomes and higher global burden of disease [23 28]. Moreover, it has recently been highlighted that non-comorbid, that is, less severe, forms of mental disorders were associated with reduced treatment rates [28]. Our findings could thus reflect the overall association between severity and treatment utilization, in line with previous results for AUDs [28]. However, the impact on NUMT rates also differed depending on the type of associated disorder. Mood and

6 Table 2 Results of the multivariable logistic regression analyses modeling the factors associated with no lifetime utilization of mental health treatment (NUMT) in six subsamples corresponding to different disorders MINI positive (n = 12,818) Mood dis. (n = 5450) Anxiety dis. (n = 8672) AUDs (n = 1721) Other SUDs (n = 1095) Psychotic dis. (n = 1110) OR (95% CI) p OR (95% CI) p OR (95% CI) p OR (95% CI) p OR (95% CI) p OR (95% CI) p Gender (male vs. female) 1.75 ( ) < ( ) < ( ) < ( ) ( ) ( ) < Age (per 10-year 0.88 ( ) < ( ) < ( ) < ( ) ( ) ( ) < increase) Situation Single (vs. living with 0.74 ( ) < ( ) < ( ) ( ) ( ) < ( ) 0.18 a partner) Separated/widowed 0.65 ( ) < ( ) < ( ) < ( ) ( ) ( ) 0.87 (vs. living with a partner) Educational level CPE (vs. UPE) 0.88 ( ) ( ) ( ) ( ) ( ) ( ) CSE (vs. UPE) 0.92 ( ) ( ) ( ) ( ) ( ) ( ) 0.10 Household income 1.03 ( ) ( ) ( ) ( ) ( ) ( ) 0.47 ( 1300 vs. <1300 ) In employment (yes vs ( ) ( ) ( ) ( ) ( ) ( ) 0.32 French native (yes vs ( ) < ( ) < ( ) < ( ) ( ) ( ) < Religion practitioner 1.13 ( ) ( ) ( ) ( ) ( ) ( ) 0.77 (yes Living alone (yes 0.81 ( ) < ( ) ( ) ( ) ( ) ( ) 0.96 Mood disorder (yes vs ( ) < ( ) < ( ) < ( ) < ( ) < Anxious disorder (yes 0.47 ( ) < ( ) < ( ) < ( ) < ( ) < AUDs (yes 0.83 ( ) ( ) < ( ) ( ) ( ) 0.30 Other SUDs (yes 0.77 ( ) ( ) ( ) ( ) ( ) 0.13 Psychotic disorder (yes 0.50 ( ) < ( ) < ( ) < ( ) ( ) Nagelkerke R 2 of each model MINI-positive at least one diagnosis using the Mini International Neuropsychiatric Interview (MINI 5.0.0), mood dis. mood disorders, i.e., current major depressive disorder, current dysthymia, or lifelong manic or hypomanic episode, anxiety dis. anxiety disorders, i.e., generalized anxiety disorder, panic disorder, agoraphobia, or post-traumatic stress disorder, AUDs alcohol use disorders during the past year, SUDs substance use disorders during the past year, psychotic dis. psychotic disorders

7 Table 3 Results of the univariate logistic regression analyses modeling the factors associated with no lifetime utilization of mental health treatment (NUMT) in six subsamples corresponding to different disorders MINI positive (n = 12,818) Mood dis. (n = 5450) Anxiety dis. (n = 8672) AUDs (n = 1721) Other SUDs (n = 1095) Psychotic dis. (n = 1110) OR (95% CI) p OR (95% CI) p OR (95% CI) p OR (95% CI) p OR (95% CI) p OR (95% CI) p Gender (male vs ( ) < ( ) < ( ) < ( < ( ) < ( ) < female) Age (per 10-year 1.20 ( ) < ( ) < ( ) < ( ) ( ) ( ) < increase) Situation Single (vs. living with 1.46 ( ) < ( ) < ( ) < ( ) ( ) ( ) 0.38 a partner) Separated/widowed 2.51 ( ) < ( ) < ( ) < ( ) < ( ) ( ) < (vs. living with a partner) Educational level CPE (vs. UPE) 0.75 ( ) < ( ) < ( ) < ( ) ( ) ( ) 0.24 CSE (vs. UPE) 0.66 ( ) < ( ) < ( ) < ( ) ( ) ( ) 0.19 Household income 0.83 ( ) < ( ) ( ) < ( ) < ( ) < ( ) ( 1300 vs. < 1300 ) In employment (yes 0.82 ( ) < ( ) ( ) < ( ) < ( ) ( ) French native (yes vs ( ) < ( ) < ( ) < ( ) ( ) ( ) < Religion practitioner 1.00 ( ) ( ) ( ) ( ) ( ) ( ) 0.63 (yes Living alone (yes vs ( ) < ( ) < ( ) < ( ) < ( ) ( ) Mood disorder (yes 0.46 ( ) < < ( ) < ( ) < ( ) < ( ) < Anxious disorder (yes 0.63 ( ) < ( ) < ( ) < ( ) < ( ) < AUDs (yes 1.55 ( ) < ( ) ( ) < ( ) ( ) 0.26 Other SUDs (yes vs ( ) < ( ) ( ) ( ) ( ) 0.18 Psychotic disorder (yes 0.74 ( ) < ( ) < ( ) < ( ) < ( ) < MINI-positive at least one diagnosis using the Mini International Neuropsychiatric Interview (MINI 5.0.0), mood dis. mood disorders, i.e., current major depressive disorder, current dysthymia, or lifelong manic or hypomanic episode, anxiety dis. anxiety disorders, i.e., generalized anxiety disorder, panic disorder, agoraphobia, or post-traumatic stress disorder, AUDs alcohol use disorders during the past year, SUDs substance use disorders during the past year, psychotic dis. psychotic disorders

8 anxiety disorders were the types of comorbid disorders that showed the most reduced rates of NUMT, whereas the impact of comorbid AUDs or SUDs on NUMT rates was less marked. This result exactly confirms recent similar findings on lifetime mental health treatment utilization based on the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) [29]. Such findings may reflect differences in social stigma with regard to these different types of disorders [30, 31]. Although the utilization of mental health services for mood or anxiety disorders is now more easily accepted in society and general population, AUDs and SUDs remain associated with high social stigma, which might prevent some individuals from seeking treatment. Another possible explanation is that less severe forms of AUDs are associated with reduced treatment-seeking attitudes and with better outcomes [28]. This explanation could possibly also be applied to SUDs. Another important finding is that being male was consistently associated with increased NUMT rates. Generally, in our results, males with mental disorders had an approximately twofold-increased risk of never having any previous lifetime use of mental health treatment compared to females. This important result has been previously, though inconsistently, reported, particularly on the basis of NESARC data [20, 21, 32]. Although this important sex difference cannot be explained by our data, we assume that it could reflect certain social representations according to which males feel more uncomfortable than women seeking treatment for a mental health disorder. Similarly, younger age was also associated with higher NUMT rates, which seems relatively logical. However, this association was not statistically significant for AUDs and SUDs. This association was also previously found in NESARC [32] and other epidemiological studies on treatment utilization [33, 34], even if stratified analyses have also found that this association was not perfectly linear and that people with mental disorders aged more than 65 years usually exhibit reduced concurrent treatment utilization [33, 35]. Furthermore, in our study, both single and separated marital statuses were associated with a reduced NUMT rate for all disorders, except psychotic disorders. Single persons with psychotic disorders even showed a trend toward an increased NUMT rate compared to persons living with a partner. This finding is in line with several previous studies on treatment utilization [7, 34]. While it may seem logical that isolated persons with mental disorders are more likely to seek assistance and treatment, this relationship may also reflect an aspect of severity. However, it is notable that a trend toward a positive association with NUMT was found among single persons with psychotic disorders. More so than cultural factors, this finding could emphasize social isolation as an idiosyncratic feature of the severity of psychotic disorders that hinders people from seeking treatment [36]. Several limitations should be acknowledged. First, MHGP survey was completed between 1999 and The data are thus somewhat old, and the current determinants of NUMT may differ. A second important limitation is that the NUMT parameter included any previous mental health treatment, not specific treatments for the different disorders assessed in the study. This inclusion may have generated a frequency bias, i.e., that more frequent disorders would be associated with lower NUMT rates. This potential bias could therefore partially explain why comorbid mood or anxiety disorders showed strong associations with reduced NUMT. Moreover, the concept of treatment utilization is not based on consensual and standardized criteria in international studies. In this respect, the questions used to explore NUMT in our study were not similar to those in other studies, which could limit comparisons between publications. The third limitation concerns the biases linked to any cross-sectional study. Indeed, it is difficult to eliminate recall bias and reporting errors from cross-sectional and self-reported data [37]. These biases could lead to an underestimation of true lifetime prevalence of treatment utilization such as it was observed for the lifetime prevalence of mental health disorders [38]. A fourth limitation was that obsessive compulsive disorders were not assessed in the survey. Although we believe that this omission did not substantially change the results, we acknowledge that the MINI psychiatric assessment was not completed in this study. A final important limitation of this study is that some subgroups of the general population were excluded from the recruitment, in particular homeless and/ or hospitalized people, under-18s, and non-french-speaking people. It is likely that the rates of a mental health treatment gap are particularly high among homeless persons [39], and the determinants of NUMT in this population might be very specific. Similar considerations could apply to non-frenchspeakers, although this population is relatively limited in France (a more complete discussion on this point is provided in a recent article on MHGP study [40]). Regardless, including all these types of persons in the study, particularly homeless people, might have significantly changed our findings. However, in practice, including homeless people in largescale general population surveys is difficult for multiple reasons, including the limited access to this population [41]. Similarly, including hospitalized people may have changed our main findings; however, their inclusion would also have skewed the study, as people hospitalized for mental health disorders by definition are not NUMT people. Conclusion Our study provided original findings regarding the prevalence and determinants of NUMT among respondents with mental disorders in France. The results of multivariable

9 regression modeling showed that mood and anxiety disorders were the categories of mental disorders that displayed the lowest NUMT rates, which means that people with anxiety or mood disorders were more likely to have ever received mental health treatment compared to people with other types of mental disorders. As previously acknowledged, it is difficult to ascertain whether this finding was due to lower stigma or to an enhanced need for care. Regardless, it suggests that mood and anxiety disorders are a common entry point for mental health treatment and may thus foster the treatment of associated mental disorders. Our results therefore emphasize the need for systematic and comprehensive mental health screening among people who are treated for psychiatric disorders, especially mood or anxiety disorders [42]. This would require support for raising awareness of and training on such screening among primary care physicians, psychologists, psychiatrists and other caregivers involved in the treatment of mood and anxiety disorders. It has recently been highlighted that in many countries, caregivers involved in treating mental disorders are poorly trained in detecting and treating SUDs [42, 43]. Our findings thus suggest that different types of obstacles, namely, medical, individual or cultural obstacles, may contribute to the treatment gap. Future studies should aim to differentiate these types of factors, as they should be addressed very differently in public health strategies. Acknowledgements The MHGP survey was funded by the French Ministry for Health. The work undertaken in this study was funded by a Grant from the Fondation Actions-Addictions (https :// ns-addic tions.org), which is an independent non-profit foundation promoting evidence-based action against addiction in France. 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