Differences Between Patients with Alcohol Use Disorder Referred to Outpatient or Residential Treatment: An Observational Study

Abstract

Aims

Identifying the proper treatment setting and treatment level for alcohol use disorder (AUD) is of vital importance for securing favorable treatment outcomes. Clear evidence is lacking, but available research suggests that residential treatment works best for patients with high AUD severity, comorbid mental health disorders, and other social and functional problems. However, it is not evident that patients are referred to this costly treatment option based on these characteristics. We therefore examined whether patients in outpatient and residential AUD treatment differed on key characteristics.

Methods

Tests of bivariate associations were used to assess group differences between outpatients and patients in residential treatment in severity of alcohol use, other drug use, mental health, cognitive functioning, personality functioning, physical health, and social functioning.

Results

Severity of alcohol use, as measured by the Alcohol Use Disorders Identification Test (AUDIT), differed between the outpatient and residential groups. The residential group had a higher severity of alcohol use. Patients in the residential group were also somewhat older and much less likely to be employed.

Conclusions

Patients in outpatient and residential treatment mainly differed in the severity of alcohol use. Potential reasons for referrals to different treatment settings and their implications for clinical practice are discussed.

Keywords

alcohol use disorder alcohol treatment treatment setting residential treatment outpatient treatment

Introduction

Inpatient, or residential, treatment is a common treatment modality for alcohol use disorder (AUD) (Mutschler et al., 2022). Residential treatment programs provide intensive support that typically cannot be delivered in outpatient settings (Fischer et al., 2019) and often involve a package of different interventions (Drake et al., 2008). Because it is more expensive and resource-intensive, residential treatment is often considered an option reserved for patients with the most severe and complex AUD (de Andrade et al., 2019; Mutter et al., 2015; Reif et al., 2014; Staiger et al., 2014). Outpatient treatment, on the other hand, is often assumed to target milder to moderate manifestations (Becker et al., 2023). Generally, treatment rates for individuals with AUD are low, and, globally, only one in six receives treatment (Mekonen et al., 2021). Conversely, discontinuation rates are high (Brorson et al., 2013; Ling et al., 2022; Mutter et al., 2015), with approximately one in four patients not completing treatment (Lappan et al., 2020).

Despite decades of research, a superior effect of residential treatment for AUD compared with other treatments has not been demonstrated (de Andrade et al., 2019; Miller, 2000; Reif et al., 2014). However, reviews focusing on residential treatment across broader substance use disorder (SUD) populations have suggested moderate effects of treatment on substance use, mental health, social functioning, crime, and mortality (AshaRani et al., 2020; Cleary et al., 2008, 2009; Drake et al., 2008). Nonetheless, the field still lacks consensus-based best-practice guidelines for residential treatment and clear evidence on whether this high-cost treatment format has a superior effect compared to outpatient options (de Andrade et al., 2019). Solid evidence is also lacking as to whether residential treatment is reserved for the most severe and complex cases.

Adherence and treatment completion may be related to favorable outcomes (Mutter et al., 2015; Pfund et al., 2021), but the mechanisms remain unclear. For example, one study found that treatment completion was related to outcomes, whereas time in treatment was not (Gossop et al., 2002). This study also found no effects of residential treatment specifically on alcohol outcomes (Gossop et al., 2003), although it did not specifically target patients with AUD. Recent research has indicated that longer treatments are associated with higher rates of discontinuation (Lappan et al., 2020), and it has been recommended to keep the duration of residential treatment as short as possible (Baker et al., 2020). This is also the case for outpatient treatment, where treatment duration is not associated with outcomes (Kramer Schmidt et al., 2018). However, it is still an open question if matching the right patient to the right treatment strategy (i.e., referral to the most appropriate treatment and correct dosage) will enhance the likelihood of treatment retention and completion, and thus yield more favorable outcomes.

Most studies of residential treatment have been observational or non-randomized, and a lack of high-quality randomized controlled trials (RCTs) has long been noted (Cleary et al., 2009). As a result, many systematic reviews of residential treatment outcomes have relied on a mix of study designs, rendering their conclusions unreliable. Furthermore, residential treatment is poorly defined, with no agreed-upon treatment duration or standard (Cleary et al., 2008; Reif et al., 2014). We still do not know whether 1, 3 or 6 months of treatment will lead to different outcomes, or whether longer treatments are superior to shorter ones (de Andrade et al., 2019). In conclusion, research on residential treatment to date has been hindered by methodological issues, including the use of unspecified treatments and interventions, the lack of uniform outcome measures across studies, varied comparison groups, and high rates of discontinuation (Cutcliffe et al., 2016; de Andrade et al., 2019). This may result in published studies examining only individuals who completed treatment, and it is to be expected that these individuals were probably more satisfied than those who discontinued treatment.

More severe AUD and SUD, low psychosocial and everyday functioning, comorbid mental health disorders, homelessness or lack of stable housing, and low levels of social support are often criteria used for evaluating suitability for residential treatment (Becker et al., 2023; de Andrade et al., 2019; Reif et al., 2014). Reif et al. (2014) also suggest that residential treatment may be most effective for this group.

However, referral practices may be influenced by factors beyond severity and functioning. The general population's knowledge about treatments for AUD is sparse (Venegas et al., 2021; Wallhed Finn et al., 2014) and folk concepts of alcohol problems (i.e., “alcoholism”) still prevail (Morris et al., 2023). In the general population, it is still common to believe that SUD and AUD require residential treatment to obtain favorable outcomes. On the other hand, recent findings indicate that most individuals with AUD prefer other and more easily available interventions (Wallhed Finn et al., 2023). In addition to objective criteria, patient preferences, beliefs, and those of family members and other close individuals may influence whether the patient is referred to residential or outpatient treatment. Nonetheless, residential treatment remains a widely used treatment format in many countries. This includes Norway, as evidenced by the diverse range of treatment facilities with varying therapeutic rationales and interventions (Nasjonal kompetansetjeneste TSB, 2023).

In routine practice, if objective criteria for referrals are used, patients referred to residential treatment should differ in severity from patients referred to outpatient treatment. We therefore aimed to examine and describe differences between the outpatient and residential groups on the following key characteristics: (a) severity of AUD; (b) comorbid drug use; (c) psychological distress; (d) cognitive function; (e) self-control; (f) physical health; and (g) social network and support.

Methods

Procedures and Participants

Data from a multicenter study on patient factors as predictors of outcome in alcohol use disorder treatment in Norway were applied for the analysis. The study was designed as a prospective longitudinal study. Data from treatment entry (baseline) are used in the current study.

Patients were recruited at baseline primarily through consecutive enrollment from two outpatient clinics and two residential treatment centers in Eastern Norway, both dedicated to the treatment of SUD, including AUD. The clinics differed in level and intensity of treatment, but they largely served comparable patient populations. Referrals among the clinics were not uncommon.

The two outpatient clinics were part of a public hospital trust. The residential treatment services were owned by a non-profit private institution, but part of the specialist health services through operating agreements with the regional health authorities. All services offered standard treatment for AUD and other SUDs. Standard outpatient treatments were individual therapy, group treatment or pharmacological treatment. The residential treatments were more comprehensive and included individual and group treatment, milieu-based therapy, psychoeducation, physical activity, and follow-up of somatic issues if needed. AUD treatment in Norway is almost free of charge, except for a minor fee for outpatient treatment. As a consequence, cost is usually not a barrier to receiving treatment, which implies that our clinical sample should be representative of the treatment-seeking population.

In total, 136 participants were included in the study. All had AUD as their primary diagnosis, and all participants met the criteria for a diagnosis of harmful use of alcohol (F10.1) or alcohol dependence (F10.2) (World Health Organization, 1994). The Regional Committee for Medical and Health Research Ethics Southeast Norway (REK) approved the study. All participants provided their written informed consent.

Measures

Background Characteristics

Background variables related to sociodemographic characteristics were obtained from participant interviews and medical records. Sex assigned at birth was registered from the medical records.

Alcohol Use

Alcohol Use Disorders Identification Test (AUDIT) is a validated screening test (Saunders et al., 1993), and is currently the most widely used instrument to identify hazardous or harmful drinking internationally (Babor & Robaina, 2016). There is evidence that AUDIT is a sensitive instrument in assessing alcohol dependence severity in clinical settings, extending its utility beyond its original use as a brief screening tool (Donovan et al., 2006). The AUDIT comprises 10 questions, with responses from 0–4, yielding a score between 0–40, addressing different areas: consumption, dependence, and alcohol-related problems.

Other Drug Use

Other drug use was measured with the Drug Disorders Identification Test (DUDIT) (Berman et al., 2005). This instrument is an 11-item self-report questionnaire for drug-related problems. Responses are scored on a scale from 0 to 4, and the DUDIT yields a maximum score of 44. The DUDIT has satisfactory reliability and validity for use in both clinical practice and research (Hildebrand, 2015).

Psychological Distress

Psychological distress was measured using the General Symptom Index (GSI) score from the Symptom Checklist-90-Revised (SCL-90-R) (Derogatis, 1994). This is a widely used self-report inventory of 90 questions scored on a 5-point scale (0–4). The GSI constitutes an overall measure of psychological distress. Normative data and mean scores from the general population are available for comparison (Derogatis, 2010; Siqveland et al., 2016). The SCL-90-R has Norwegian norms and has well-documented reliability and adequate construct validity (Siqveland et al., 2016).

Self-Control

Self-control was assessed using the Self-control domain score from the Severity Indices of Personality Functioning (SIPP-118), which assesses core elements of maladaptive personality functioning (Andrea et al., 2007). It contains 118 items across 16 facets and five higher-order domains. The response categories range from 1 to 4 (entirely disagree to fully agree). Higher total scores indicate more adaptive functioning. The SIPP-118 is considered a reliable instrument for assessing personality functioning (Arnevik et al., 2009; Verheul et al., 2008).

Cognitive Function

Cognitive function was evaluated with the Wechsler Adult Intelligence Scale (WAIS-IV) (Wechsler, 2008). The WAIS-IV is a standardized test of general cognitive ability comprising 10 core subtests and five supplemental subtests. WAIS-IV test scores are based on Scandinavian norms (Wechsler, 2008), and scores are corrected for age. The General Ability Index (GAI) was estimated using two verbal comprehension subtests, Similarities and Information, and two perceptual reasoning subtests, Block Design and Visual Puzzles. The GAI is considered a measure of premorbid cognitive functioning and is presented as an IQ score with a mean of 100 and an SD of 15.

Physical Health and Social Functioning

The physical domain score and social domain score from the World Health Organization Quality of Life Scale (WHOQOL-BREF) (Whoqol Group, 1998) were used to examine physical health and social functioning. The WHOQOL-bref measures quality of life across four domains: physical health, mental health, social relationships, and environment. It consists of twenty-six items scored on a 1 to 5-point Likert scale. The domain scores are scaled in a positive direction; higher scores indicate a higher quality of life. The WHOQOL-bref is an appropriate and valid measure for use in AUD, with excellent internal consistency (Kirouac et al., 2017). It has also been shown to be suitable for use in the Norwegian population, and normative data from a Norwegian general population sample are available (Kalfoss et al., 2021).

Statistical Analysis

The analyses were conducted in RStudio, version 2023.03.1 (Posit PBC). Descriptive statistics were used to summarize key sociodemographic data. Differences in sociodemographic characteristics between the outpatient and residential treatment groups were assessed with the chi-squared test for categorical variables and t-tests for unequal variances (Welch’s t-test) for continuous variables.

Bivariate associations between the key variables were assessed using Welch's t-test and a Mann–Whitney U-test for non-normal variables. Additional age- and sex-adjusted analyses were conducted for each key variable using logistic regression models to ensure that observed differences were not driven by demographic composition. Because these analyses did not meaningfully alter the results, they were not included in the paper (see Supplementary material, Appendix 1).

Across variables used in the analyses, missingness ranged from 5.1% to 14.7%. On the AUDIT, 8.2% had missing AUDIT scores, 9.6% had at least one missing item, and 90.4% were complete cases with no missing data. The number of missing participants is reported, as appropriate, showing the bivariate associations.

Results

Sociodemographic Characteristics

Table 1 presents participant characteristics by treatment setting (outpatient or residential).

Table 1.

Sociodemographic Characteristics.

Variable	Outpatient	Residential
Number of patients, N	89	47
Men, n (%)	56 (63)	32 (68)
Women, n (%)	33 (37)	15 (32)
Mean age, M (SD)	46.9 (11.83)	53.7 (9.59)*
Age range (years)	23–69	34–69
Married, n (%)	28 (32)	10 (21)
Higher education, n (%)	37 (42)	13 (28)
Employed, n (%)	53 (60)	9 (19)*

If not otherwise specified, the values are counts of patients in each category. Percentages in parentheses show the distribution within each treatment category.

*Statistically significant at p < .001.

There was no statistically significant difference in the number of men and women across treatment levels. However, the patients in residential treatment were significantly older (t(134) = –3.61, p < .001). The patients in residential treatment were also significantly less likely to be employed, χ²(1, N = 136) = 20.24, p < .001. The median number of children for patients in both outpatient and residential treatment was 0.

Bivariate Analysis

Table 2 shows the bivariate associations between key characteristics of the outpatient and residential groups. Only the AUDIT score at baseline differed significantly between the groups. The total number of participants and the number in each group are shown in the last column. Adjusting for age and sex did not substantially alter the results and is not shown in the table (see Supplementary material, Appendix 1).

Table 2.

Bivariate Associations Between Key Characteristics by Treatment Setting.

Key Variables	Outpatient Group	Residential Group	p-value	Participants Total/Groups
AUDIT, M (SD)	19.57 (9.50)	26.33 (8.30)	<.001	125 (86/39)
DUDIT, median (IQR)	0 (0–9)	0 (0–20)	0.418	124 (85/39)
GSI, M (SD)	0.99 (0.62)	0.94 (0.62)	.637	128 (88/40)
GAI, M (SD)	95.29 (11.78)	90.50 (14.25)	.063	129 (87/42)
Self-control domain, M (SD)	5.16 (1.12)	5.39 (0.93)	.257	116 (77/39)
Physical domain, M (SD)	13.12 (2.54)	13.17 (2.75)	.934	119 (81/38)
Social domain, M (SD)	13.27 (2.83)	13.02 (2.98)	.664	120 (82/38)

AUDIT: Alcohol Use Disorder Identification Test; DUDIT: Drug Use Disorder Identification Test; GAI: General Ability Index, WAIS-IV; GSI: General Symptom Index, SCL-90R; IQR: interquartile range; Self-Control Domain from the SIPP-118, Physical Domain, and Social Domain from the WHOQOL-BREF.

Discussion

In the present study, we investigated differences in key characteristics between patients receiving outpatient and residential treatment. We expected that being in residential treatment would be associated with more severe alcohol use, other drug use, more psychological distress, poorer cognitive functioning, less self-control, more physical health problems, and poorer social function. However, among these variables, only the higher severity of alcohol use in the residential group clearly distinguished the groups. In addition, patients in residential treatment were somewhat older and less employed than those in outpatient treatment. The following discussion will address the potential implications of these findings, including issues related to treatment referrals and the effectiveness of treatment settings.

That patients with more severe alcohol use seek and receive residential treatment aligns with guidelines and prior study findings (Becker et al., 2023; Haber et al., 2021; Mutschler et al., 2022): Patients with very high AUD severity may fare better in a treatment option that is typically considered more intensive. However, it was somewhat surprising that only alcohol problem severity, as measured by the AUDIT, appeared to be the only clear difference between the outpatient and the residential group.

From the perspective of referral practices and level-of-care decisions, severity of alcohol problems is not recommended as the sole criterion. There are several reasons for this. First, severity of alcohol use is not a constant state because it likely fluctuates for many individuals. Second, although baseline alcohol consumption and dependence severity have been reported to predict unfavorable treatment outcomes and relapse (Adamson et al., 2009; Sliedrecht et al., 2019), this is not a consistent finding. Others have found that AUD severity at baseline was not associated with whether a patient benefited more from abstinence-based or controlled drinking interventions (Henssler et al., 2021), indicating that even patients with high AUD severity may benefit from a range of interventions. Third, many have highlighted that AUD recovery needs to be assessed in multiple domains, including mental health, quality of life, and somatic health, among others, not solely alcohol-related measures (Witkiewitz et al., 2020).

We also found that patients in residential treatment were somewhat older and, to a lesser degree, employed than patients in outpatient treatment. The finding that patients in residential treatment are, on average, 7 years older than those in outpatient treatment may indicate that individuals who did not benefit from prior outpatient episodes are later referred to more intensive residential care. It could also be that older age indicates a longer duration of AUD and thus a more severe AUD. Unfortunately, the present study data did not include information on the duration of AUD, and data on previous treatment episodes were incomplete for a subset of the patients.

The observation that individuals in residential treatment, to a lesser degree, are employed may also suggest that this group is more vulnerable than patients in outpatient treatment. However, employment may lead individuals to choose treatments that fit their work schedules, thereby causing them to decline residential treatments. Alternatively, currently employed individuals could have similar AUD severity as unemployed peers, but be unable to commit to residential treatment as a result of work obligations.

Surprisingly, none of the other variables were associated with treatment level. Psychological distress, cognitive functioning, physical health problems, and poorer social functioning were expected to be more pronounced in the residential treatment group than in the one being in outpatient treatment, based on previous research. Although we cannot determine the specific reasons for patients’ referrals to treatment settings, it is of interest to consider why clinicians and patients choose among these options. Robust evidence on who benefits most from residential treatment remains limited, but there is expert consensus that not only severity of AUD, but also the aforementioned factors may indicate a need for residential treatment (e.g., Becker et al., 2023; Haber et al., 2021; Mutschler et al., 2022).

Our results suggest that patients in outpatient and residential treatment do not differ in the severity of psychological distress, cognitive functioning, and physical health problems. These findings may therefore appear to run counter to recommendations regarding levels of care, as one would expect patients with problem severity to be in residential treatment.

However, referrals may be made for reasons other than clinical need, such as patients’ or staff preferences, ideology, family concerns or other factors. Patients could be referred to residential treatment not because of the severity or complexity of their condition, but because they prefer it. Taking patients’ preferences into account when making treatment referrals may lead to choices that differ from those suggested by guidelines. Nonetheless, including patient preferences in decision-making is considered highly important and integral to effective treatment (Hell & Nielsen, 2020). Moreover, the confinement and safety of being in a treatment institution, separated from ordinary life, may appeal to many (Dillon et al., 2020). Other reasons cited include the experience of being with others who share similar problems, a sense of belonging, and reduced isolation (Wilkinson et al., 2008). Families may also feel more assured when a family member is in residential care rather than in outpatient treatment. The possibility for the individual to drink alcohol is also reduced when in residential treatment, thus contributing to harm reduction. Other formal reasons could be a lack of explicit guidelines for referrals. Clinicians may lack knowledge of the differences between residential and outpatient treatment, which is not surprising given inconsistent and conflicting research findings (de Andrade et al., 2019; Malivert et al., 2011; Reif et al., 2014).

Nonetheless, cost and benefit need to be taken into account in treatment selection. Residential treatment is costly and less available than outpatient care. Moreover, the common belief that longer treatments are always better may not be correct because “more” is not necessarily better (Baker et al., 2020). Twenty-five years ago, Miller (2000) noted that clinicians are often surprised when patients respond to lower levels of care than expected to be effective. Relative brief interventions may have significant effects, and increasing treatment intensity does not consistently improve outcomes (Miller, 2000). A large proportion of patients may benefit from easily accessible, brief interventions, delivered both digitally and face-to-face (Saarni et al., 2022). This aligns with more recent research that has not found apparent differences in effect based on treatment length (Andersen et al., 2020; Kramer Schmidt et al., 2018). Similar findings are reported for other mental health disorders, like depression and PTSD (i.e. post-traumatic stress disorder), where the number of sessions or therapist contacts was not associated with therapy effect in a recent meta-analysis (Cigrang et al., 2011; Ciharova et al., 2024).

Consequently, based on the current evidence, it is advisable to follow the recommendation of Baker et al. (2020) and keep treatments as brief as possible at the same time as remaining flexible and sensitive to fluctuations in the patient's condition. Treatment approaches need to be chosen based on cost and benefit. Health care resources are scarce, and residential treatment is costly. With better selection and referral assessments, resources could be allocated more effectively to the group that most needs this comprehensive intervention. The choice of treatment is thus not only a matter of the patient's preferences. Outpatient treatments may be more effective and better tolerated for many patients than previously believed. A structured decision model based on clear criteria and accounting for patients’ preferences could assist clinicians in choosing the most effective treatment (e.g., Delgadillo & Lutz, 2026; Saarni et al., 2022).

Strengths and Limitations

Several limitations apply to the current study. A limitation is that we lacked data on the duration of AUD and had incomplete data on previous treatments. Our use of AUDIT as the sole measure of AUD severity is likewise a limitation.

The generalizability of the results is constrained by the study's naturalistic design: we lacked the stringent control over the treatment setting that a typical RCT would provide. On the other hand, we also consider this a strength. We have reason to believe that the study has captured ordinary patients receiving routine care for AUD, with the comorbidities and variations in functioning that this may entail. As such, the patients may not be representative of all patients with AUD, but we consider them to be representative of patients seeking treatment for AUD in Norway.

The imbalance in group sizes (89 versus 47) could affect statistical power and the robustness of the results. The study is likely to be underpowered, potentially failing to detect smaller differences between the groups. With a larger sample size, this problem could be ameliorated. However, we consider our results from this exploratory analysis informative, given the limited research in this field. Our results may guide future research on treatment levels and formats. More research is clearly needed on treatment selection, predictors of outcome, and residential treatments for AUD and SUD. The study's observational design precludes drawing any conclusions about causal effects.

The strengths of the study are the use of a comprehensive dataset on patients in treatment in clinics representative of specialized treatment in Norway. The study thus benefited from investigating realistic treatment conditions. We have solid data on the variables examined in the study. This is also the first study in Norway to examine whether patient characteristics may predict referral practices and treatment level.

Conclusions

Only higher severity of alcohol use significantly differed between the groups when investigating differences in key characteristics between patients referred to outpatient and residential treatment. Other variables related to mental health, cognitive function, physical health, social relationships, and the patient's overall condition did not differ significantly between the groups. The results may be of importance for assessment, decision-making regarding treatment level, and future research.

Supplemental Material

sj-docx-1-nad-10.1177_14550725261463958 - Supplemental material for Differences Between Patients with Alcohol Use Disorder Referred to Outpatient or Residential Treatment: An Observational Study

Supplemental material, sj-docx-1-nad-10.1177_14550725261463958 for Differences Between Patients with Alcohol Use Disorder Referred to Outpatient or Residential Treatment: An Observational Study by Kristoffer Høiland, Espen Ajo Arnevik, Lien My Diep, Tove Mathisen, Anette Søgaard Nielsen and Jens Egeland in Nordic Studies on Alcohol and Drugs

Footnotes

ORCID iDs

Kristoffer Høiland

Espen Ajo Arnevik

Anette Søgaard Nielsen

Funding

The research was supported by Vestfold Hospital Trust.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Supplemental Material

Supplemental material for this article is available online.

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