In Norway, as in most other European countries , there are distinct specialized mental health and SUD treatment departments. Specialized mental health services are owned on behalf of the state by four regional health authorities (RHAs), which are responsible for the provision of health services for the population in their area.Specialized mental health services are organized together with general hospital services in 19 health trusts. The services are mostly public, and the private health service providers have an operating agreement with the RHA . General practitioners or other specialist health services make referrals of patients to mental health services. As in most Western countries, the services for people with mental disorders have gone through major changes in recent decades. There has been a reduction in the number of patients staying in psychiatric institutions with most people with mental problems being provided with outpatient mental health services. According to National guidelines for treatment and rehabilitation of substance use problems and dependency , patients with severe mental illness such as psychosis, bipolar disorders and severe anxiety and depression and co-occurring SUD should receive treatment for their substance use problems within mental health care. Whereas patients with severe SUD and co-occurring less severe mental health disorders should receive treatment within specialized SUD treatment services.
A comprehensive national census of patients in mental health treatment, commissioned and financed by the Norwegian Directorate of Health, was carried out by the SINTEF Research Foundation. The census was conducted in all psychiatric wards and departments (including acute wards) providing inpatient treatment on a specific date, and in all clinics and departments (including community mental health centres), providing outpatient treatment during a specific 14-day period. Each patient’s clinician was responsible for completing the form. Because the study had a national cross-sectional design with high coverage of institutions in specialized mental health services, it was possible to estimate the point prevalence for the entire patient population. The Regional Committee for Medical and Health Research Ethics (reg. no. 2012/848) approved the current study.
All inpatients on a given day (20 November 2012) and all outpatients who had one or more consultations during a 14-day period (15–28 April 2013) were the targeted study participants. All mental health services in public and private sectors were invited to participate in the census. Several months prior to the census, the service managers and clinicians received information describing the project and the data collection procedures. The clinicians completed one form per patient. The registration forms included a wide range of topics, including main and secondary diagnoses (International Classification of Diseases, ICD–10), demographics and socio-demographic characteristics. The completed forms were returned by registered mail to a firm that performed scanning and coarse quality control of the data. The project team performed further quality control of the data files.
In total, 94 of the 104 psychiatric inpatient departments and 107 of the 110 psychiatric outpatient clinics in the health trusts participated in the census. Most of the units that did not participate were small, and they cited a lack of time as their reason for not participating. Non-participating clinics comprised 1% of all outpatient consultations, and non-participating institutions comprised 4% of all inpatient days during 2012. Data were returned for 2,358 inpatients and 23,167 outpatients. Based on data from the National Patient Register on the number of patients attending the mental health services during the inclusion periods, the response rates were estimated to be 65% of 3,618 inpatients and 60% of 38,904 outpatients.
Data from main psychiatric diagnosis was collected and the following diagnostic categories were used: Schizophrenia (F20), Other psychoses (F22–25, F28-F29), Bipolar disorder (F31), Depression (F32-F34), Anxiety (F40, F41), PTSD (F43.1), Eating disorders (F50), Personality disorders (F60, F61), Other psychiatric diagnoses or unspecified (all other F-diagnoses).
Substance use was measured based on the recorded ICD–10 diagnoses of SUD as secondary diagnosis (F10-F19), or reported substance use in the last four weeks preceding treatment, and included the following response options: (1) Less than once a week; (2) almost weekly; (3) 2–4 times a week; (4) almost daily. For individuals with psychiatric disorders, regular alcohol use and occasional use of illicit drugs may pose a risk of worsening psychiatric symptoms [23,24] and development of problematic substance use . Based on a recorded SUD diagnosis and reported substance use, we constructed a dichotomized variable, with a value of 1 for the presence of a SUD diagnosis or reported regular alcohol use (2–4 times a week or more/occasional illicit drug use), and 0 for no SUD diagnosis and non-regular alcohol use and no illicit drug use. Type of drug used was categorized according to ICD–10 in the following categories: alcohol (F10), opioids (F11), cannabis (F12), sedatives (F13, benzodiazepines and other addictive drug), stimulants (F14 and F15, cocaine, amphetamines and other stimulants) or multiple substance use (F19, combinations of type of drugs used).
Demographic and socio-demographic characteristics
In addition to gender and age, we included education (where low education corresponds to only primary school, medium education to secondary school and high education to university or other higher education), income (with the categories income from labour, health-related benefits, other economic support) and marital status (grouped in the three categories married/cohabitant/partner, separated/divorced/widow(er) and single/unmarried).
The binary nature of the substance use variable as the dependent variable implies a logit model. The STATA software package was used for all analyses (Stata/SE 14.2 for Windows; StataCorp LP, College Station, TX). We estimated 3 models; the first model included only diagnoses (Model 1), gender and age were added in the second model (Model 2), and the third model also included the socio-demographic variables level of education, main source of income and marital status (Model 3).