Implementation of stop smoking support by mental healthcare professionals: cross-sectional analysis of why nothing much happens

Abstract

Smoking is highly prevalent and persistent among people with mental illness, but implementation of smoking cessation care by mental healthcare professionals (MHCPs) is lagging behind. This study took a broad approach to understanding implementation of stop smoking support (SSS) by MHCPs (N = 220 for main analyses), incorporating background characteristics, psychosocial factors, client factors, and organizational/environmental factors. Variable selection was based on previous work and the Consolidated Framework for Implementation Research. Cross-sectional survey data were collected online in the Netherlands from 2021 to 2022, and analyzed using logistic regression and regression tree analyses. Participants were 81 nurses, 74 psychologists, 40 psychiatrists, 12 child psychologists and 13 other MHCPs; aged 42 on average, 24% male, 14% currently smoked and 32% quit smoking. Results show that most MHCPs do not ask about smoking, do not advise or motivate clients to quit smoking, and do not refer clients motivated to quit to SSS. In order to improve this situation, proactive efforts should be undertaken to target MHCPs’ perceptions of clients’ responsibility and quit success, preferably through strategies that reach MHCPs regardless of their affinity with SSS, taking MHCPs’ profession and own smoking status into account.

Supplementary Information

The online version contains supplementary material available at 10.1007/s44192-025-00135-3.

Introduction

Professionals working in mental healthcare encounter many clients who smoke, as smoking is two to three times more common among people with mental disorders [1–4]. Smoking rates are alarmingly high in people diagnosed with schizophrenia, bipolar disorder, post-traumatic stress disorder, and substance use disorders [1]. However, the mental healthcare system is still hesitant to support clients who smoke to quit, let alone to prioritize smoking cessation as a treatment goal [5, 6].

People with mental disorders typically smoke more heavily and have more difficulty to quit smoking, compared to those without mental disorders [7, 8]. This leads to more smoking-related diseases such as cancer, respiratory illness and cardiovascular disease, as well as reduced life expectancy, in this population [9–11]. Furthermore, smoking is reciprocally related with anxiety and depressive symptoms, smoking is a risk factor for schizophrenia and depressive disorder, and heavy smoking is related to cognitive impairment and decline in middle age [12–15]. Quitting smoking decreases anxiety and depressive mood and improves positive mood and quality of life, also among people diagnosed with mental disorders [16, 17]. People with mental illness who smoke are equally or even more motivated to quit compared to the general population [18], but quitting self-efficacy is often low and heavier smoking complicates quitting [1, 7, 18–20]. Importantly, people with mental disorders are capable of quitting smoking successfully, provided that they receive adequate support to quit smoking [21–25].

Mental healthcare professionals (MHCPs) can potentially play an important role in helping people with mental illness to quit smoking. However, a mixed-method review showed that almost half of mental healthcare professionals (MHCPs) have negative attitudes toward smoking cessation and permissive attitudes toward smoking [26]. Many MHCPs believed that clients were uninterested in quitting and that quitting would be too stressful for clients, and they perceived themselves to have insufficient time, training and confidence to address smoking [26]. As a result, many people with mental disorders who smoke report that MHCPs had never advised or motivated them to quit, or had even advised them to continue smoking [19, 27]. A qualitative study showed that, even though most clients would like support to quit, both clients and MHCPs waited for the other party to address smoking, such that the issue remains unaddressed [19]. MHCPs believed that clients should indicate the focus of treatment, and that discussing smoking cessation might harm the therapeutic relationship [19]. Taken together, the suboptimal implementation of SSS in mental healthcare is a missed opportunity to effectively help a large group of people and improve health.

The consolidated framework for implementation research (CFIR) states that the successful implementation of interventions depends on factors related to interventions or treatments themselves, the ‘inner setting’ (e.g. organization, or unit) and ‘outer setting’ (e.g. healthcare system) in which interventions are implemented, the healthcare professional, and the implementation process [28]. Much of the research on SSS within healthcare focuses on aspects of the healthcare professional, e.g. their attitudes and self-efficacy regarding providing SSS. Although these are clearly important, it is key to examine the potential role of factors from other CFIR-domains (e.g. aspects of the inner or outer setting) in implementation of SSS as well.

Current study

Guided by the CFIR, the current study took a broad approach to understanding MHCPs’ actions in relation to smoking behavior in their clients. The study focused on several key tasks within SSS [29]: asking clients whether they smoke (Ask), advising clients who smoke, in a clear and personalized way, to quit smoking (Advise), providing a brief motivational intervention to clients who smoke (Motivate), and referring clients who smoke and are motivated to quit to SSS (Refer). The study aimed to examine (1) whether the extent to which MHCPs ask clients about substance use differs between substances, including tobacco (2) to what extent MHCPs implement SSS tasks, (3) which professional (e.g. background characteristics), psychosocial (e.g. attitudes towards SSS), client (e.g. diagnosis), and organizational/environmental factors (e.g. organizational smokefree policies) explain implementation of key SSS tasks by MHCPs (i.e. Ask, Advise, Motivate, Refer), and 4) whether factors interact in explaining implementation of these key SSS tasks by MHCPs. Data was collected through a cross-sectional survey among MHCPs working in the Netherlands.

Methods

Design

This was an observational cross-sectional survey study. Qualitative findings from complementary interviews with  MHCPs  and people with a DSM 5 diagnosis who smoke are reported elsewhere [19].

Participants and procedure

Data were collected in The Netherlands from January 2021 through April 2022. The online survey was distributed via Qualtrics (www.qualtrics.com). Participants were informed that the study focused on supporting smoking cessation in people with mental health problems, and MHCPs’ views on this. Risk of bias was reduced by explicitly stating that MHCPs could also participate if they did not have experience with this. Participants were recruited mostly through their professional associations, social media and via colleagues. Psychologists, psychiatrists, nurses, child psychologists (‘orthopedagoog' in Dutch1) and other MHCPs were eligible if they were involved in the diagnostic process and/or treatment of people with mental health problems. No exclusion criteria were applied. In total 379 people started with the survey, of whom 308 (81.3%) met inclusion criteria and had completed enough questions to be included in the analyses for RQ1 and RQ2, and 220 (58.0%) for RQ3 and RQ4 (see Table 2 for descriptive statistics for all predictor variables, including participant characteristics). The median time needed to complete the survey was 19 min (IQR 15–27).

Table 2.

Explaining dosage delivered of key SSS tasks: Univariable logistic regression analyses, N = 220

Predictor variables			n (%)/M(SD)	Odds ratio (95% confidence interval)
				Ask	Advise	Motivate	Refer
Participant characteristics
Age			42.38 (12.18)	1.01 (0.98; 1.03)	1.00 (0.98; 1.03)	0.99 (0.97; 1.02)	1.00 (0.98; 1.02)
Gender (male)			53 (24.1)	0.91 (0.49; 1.68)	0.77 (0.41; 1.42)	1.00 (0.53; 1.91)	0.83 (0.44; 1.59)
Profession
Nurse (ref.)			81 (36.8)	1	1	1	1
Child psychologist			12 (5.5)	0.70 (0.20; 2.38)	0.42 (0.12; 1.44)	0.19 (0.05; 0.68)*	0.28 (0.09; 0.98)*
Psychiatrist			40 (18.2)	1.08 (0.51; 2.30)	1.22 (0.55; 2.72)	0.77 (0.34; 1.76)	0.93 (0.40; 2.12)
Psychologist			74 (33.6)	1.15 (0.61; 2.16)	0.36 (0.19; 0.69)**	0.44 (0.23; 0.86)*	0.73 (0.37; 1.44)
Other			13 (5.9)	0.61 (0.18; 2.02)	0.94 (0.28; 3.14)	2.05 (0.42; 10.00)	0.89 (0.25; 3.19)
Years worked			14.44 (11.01)	1.01 (0.98; 1.03)	1.00 (0.98; 1.02)	1.00 (0.97; 1.02)	1.01 (0.98; 1.03)
SSS training (yes)			35 (15.9)	1.03 (0.50; 2.11)	8.54 (2.90; 25.17)***	7.44 (2.20; 25.17)**	2.17 (0.90; 5.23)
Smoking status
Never (ref.)			120 (54.5)	1	1	1	1
Quit smoking			70 (31.8)	0.90 (0.50; 1.62)	1.02 (0.56; 1.85)	1.35 (0.72; 2.54)	0.68 (0.37; 1.27)
Currently smokes			30 (13.6)	0.49 (0.22; 1.12)+	0.44 (0.19; 1.01)+	0.66 (0.30; 1.48)	1.00 (0.42; 2.39)
Psychosocial factors
Attitude			4.24 (0.86)	0.93 (0.68; 1.27)	1.33 (0.97; 1.83)+	1.20 (0.88; 1.65)	1.01 (0.73; 1.40)
Intention			3.61 (1.00)	1.35 (1.03; 1.77)*	2.28 (1.66; 3.14)***	2.25 (1.63; 3.11)***	1.40 (1.05; 1.86)*
Knowledge			2.73 (1.08)	1.15 (0.90; 1.48)	2.31 (1.69; 3.14)***	2.21 (1.60; 3.07)***	1.27 (0.96; 1.66)+
Skills			2.95 (1.11)	1.03 (0.81; 1.31)	1.46 (1.14; 1.88)**	1.70 (1.29; 2.23)***	1.15 (0.89; 1.48)
Self-efficacy			2.90 (1.11)	1.00 (0.79; 1.28)	1.85 (1.41; 2.43)***	2.12 (1.58; 2.85)***	1.25 (0.96; 1.62)+
Role identity			3.40 (1.18)	1.12 (0.90; 1.40)	1.52 (1.20; 1.93)**	1.43 (1.13; 1.82)**	1.31 (1.03; 1.67)*
Social support			2.67 (1.03)	1.00 (0.78; 1.30)	1.77 (1.33; 2.37)***	1.69 (1.25; 2.27)***	1.52 (1.13; 2.04)
Outcome expectations			3.44 (0.96)	1.28 (0.96; 1.70)+	1.25 (0.94; 1.66)	1.18 (0.88; 1.57)	1.11 (0.82; 1.48)
Insufficient training#			3.55 (1.06)	0.83 (0.65; 1.07)	0.51 (0.38; 0.69)***	0.51 (0.37; 0.71)***	0.93 (0.71; 1.21)
Perceptions of responsibility
Start choice			2.26 (0.98)	1.08 (0.82; 1.42)	0.97 (0.74; 1.27)	0.97 (0.74; 1.27)	0.74 (0.55; 0.98)*
Continue addiction			3.95 (0.85)	1.04 (0.76; 1.42)	1.32 (0.96; 1.82)+	1.32 (0.96; 1.82)+	1.59 (1.14; 2.22)**
Start child			3.41 (0.86)	0.85 (0.62; 1.15)	1.37 (0.99; 1.87)+	1.36 (0.99; 1.87)+	1.42 (1.02; 1.98)*
Continue willpower			2.04 (0.85)	0.93 (0.68; 1.26)	1.16 (0.84; 1.59)	1.16 (0.84; 1.59)	0.81 (0.58; 1.13)
Client knowledge			2.82 (1.09)	0.88 (0.69; 1.12)	0.76 (0.60; 0.98)*	0.76 (0.60; 0.98)*	1.00 (0.77; 1.29)
Child risk			1.42 (0.72)	0.86 (0.59; 1.24)	1.33 (0.90; 1.97)	1.33 (0.90; 1.97)	0.87 (0.60; 1.28)
Own choice to smoke			2.99 (1.05)	1.06 (0.82; 1.37)	0.91 (0.71; 1.18)	0.91 (0.71; 1.18)	0.96 (0.74; 1.26)
Tobacco industry			4.19 (0.74)	1.19 (0.83; 1.70)	1.30 (0.91; 1.86)	1.30 (0.91; 1.86)	1.37 (0.94; 1.99)
Own responsibility to quit			3.33 (0.93)	1.43 (1.06; 1.92)*	0.84 (0.63; 1.13)	0.84 (0.63; 1.13)	0.90 (0.66; 1.22)
Netherlands sufficient			2.27 (1.01)	1.17 (0.90; 1.53)	1.02 (0.78; 1.33)	1.02 (0.78; 1.33)	1.12 (0.84; 1.48)
Client factors
Primary DSM 5 diagnoses
Anxiety			157 (71.4)	1.57 (0.87; 2.84)	1.00 (0.56; 1.81)	0.85 (0.46; 1.58)	0.85 (0.45; 1.59)
Bipolar			99 (45.0)	0.84 (0.49; 1.43)	2.57 (1.48; 4.45)***	2.19 (1.23; 3.89)**	1.33 (0.75; 2.36)
Depression			180 (81.8)	1.95 (0.96; 3.94)+	0.85 (0.42; 1.69)	0.83 (0.40; 1.72)	0.86 (0.41; 1.80)
Dissociative			45 (20.5)	1.42 (0.73; 2.74)	2.19 (1.09; 4.40)*	2.67 (1.21; 5.88)*	0.76 (0.38; 1.49)
Behavioural			90 (40.9)	0.70 (0.41; 1.19)	1.39 (0.81; 2.39)	1.03 (0.59; 1.80)	0.53 (0.30; 0.93)*
Neurodevelopmental			38 (17.3)	1.24 (0.61; 2.49)	0.49 (0.24; 1.00)*	0.49 (0.24; 1.00)*	0.92 (0.44; 1.93)
Neurodegenerative			24 (10.9)	0.66 (0.28; 1.55)	1.00 (0.43; 2.35)	0.63 (0.27; 1.48)	0.97 (0.39; 2.38)
Obsessive compulsive			71 (32.3)	1.63 (0.92; 2.90)+	1.14 (0.65; 2.02)	1.38 (0.76; 2.52)	1.02 (0.56; 1.87)
Personality (cluster A)			61 (27.7)	0.76 (0.42; 1.37)	1.32 (0.73; 2.40)	1.21 (0.65; 2.26)	0.67 (0.36; 1.23)
Personality (cluster B)			144 (65.5)	1.15 (0.66; 2.00)	1.39 (0.80; 2.44)	1.26 (0.71; 2.25)	0.92 (0.51; 1.67)
Personality (cluster C)			107 (48.6)	1.29 (0.76; 2.20)	0.56 (0.33; 0.96)*	0.64 (0.37; 1.12)	0.61 (0.35; 1.07)+
Schizophrenic spectrum/psychosis			91 (41.4)	0.62 (0.36; 1.07)+	1.55 (0.90; 2.67)	1.74 (0.98; 3.10)+	1.17 (0.66; 2.07)
Sexual			17 (7.7)	5.00 (1.39; 17.93)*	2.15 (0.73; 6.34)	2.79 (0.78; 10.03)	1.18 (0.40; 3.49)
Somatic symptom			52 (23.6)	1.17 (0.63; 2.18)	0.89 (0.48; 1.66)	0.78 (0.41; 1.47)	1.27 (0.64; 2.50)
Trauma			141 (64.1)	1.40 (0.80; 2.43)	0.83 (0.48; 1.45)	0.97 (0.55; 1.72)	1.01 (0.56; 1.82)
Addiction			126 (57.3)	1.15 (0.67; 1.60)	2.45 (1.42; 4.24)**	2.11 (1.20; 3.69)**	1.43 (0.81; 2.52)
Eating/food-related			36 (16.4)	0.84 (0.41; 1.71)	0.94 (0.46; 1.92)	0.99 (0.47; 2.08)	0.97 (0.45; 2.07)
Traumatic brain injury			32 (14.5)	1.11 (0.52; 2.35)	0.96 (0.45; 2.03)	1.52 (0.66; 3.46)	0.92 (0.42; 2.02)
Medical			57 (25.9)	1.10 (0.60; 2.01)	0.92 (0.50; 1.69)	0.95 (0.51; 1.77)	0.64 (0.34; 1.19)
Primary age group
5–9 yearsa			7 (3.2)	0.72 (0.16; 3.28)	1.14 (0.25; 5.20)	0.74 (0.16; 3.39)	1.22 (0.23; 6.47)
10–17 years			23 (10.5)	0.30 (0.12; 0.80)*	0.51 (0.21; 1.23)	0.58 (0.24; 1.37)	0.49 (0.20; 1.17)
18–30 years			143 (65.0)	1.94 (1.10; 3.40)*	1.05 (0.60; 1.84)	0.79 (0.44; 1.42)	1.18 (0.65; 2.11)
31–60 years			187 (85.0)	2.44 (1.08; 5.12)*	1.50 (0.72; 3.16)	1.60 (0.76; 3.39)	2.96 (1.39; 6.29)**
> 60 years			80 (36.4)	0.81 (0.47; 1.40)	0.84 (0.48; 1.45)	0.98 (0.55; 1.73)	0.93 (0.52; 1.67)
% of clients who smoke			48.09 (25.84)	1.01 (1.00; 1.02)+	1.02 (1.01; 1.03)***	1.02 (1.01; 1.03)***	1.00 (0.99; 1.02)
Smoking sensitive subject#			3.04 (1.14)	0.97 (0.77; 1.23)	0.95 (0.76; 1.20)	1.30 (1.01; 1.66)*	0.93 (0.73; 1.20)
Negative towards SSS#			3.09 (1.07)	0.93 (0.72; 1.19)	1.12 (0.87; 1.43)	1.37 (1.05; 1.80)*	1.00 (0.77; 1.31)
Unmotivated to quit#			3.53 (1.02)	0.97 (0.75; 1.26)	1.09 (0.84; 1.41)	1.28 (0.98; 1.68)+	1.03 (0.78; 1.35)
Unsuccessful in quitting#			2.69 (1.08)	0.86 (0.67; 1.10)	0.97 (0.76; 1.25)	1.11 (0.86; 1.44)	0.78 (0.60; 1.02)+
Smoking important function#			3.54 (1.16)	0.95 (0.76; 1.20)	1.08 (0.86; 1.36)	1.30 (1.02; 1.65)*	0.95 (0.75; 1.22)
Dishonest about smoking#			2.40 (0.93)	1.00 (0.76; 1.34)	1.03 (0.77; 1.37)	1.09 (0.81; 1.47)	0.86 (0.64; 1.17)
Quitting worsens complaints#			2.61 (1.00)	0.99 (0.76; 1.29)	0.88 (0.67; 1.15)	0.81 (0.61; 1.07)	0.98 (0.74; 1.30)
Impact therapeutic relationship#			2.13 (0.82)	0.89 (0.65; 1.23)	0.80 (0.58; 1.11)	0.84 (0.60; 1.18)	0.66 (0.46; 0.93)*
Organizational/environmental factors
Setting
Outpatient/ambulant			158 (71.8)	1.81 (1.00; 3.29)+	0.66 (0.37; 1.21)	0.65 (0.35; 1.23)	2.13 (1.16; 3.92)*
Day treatment			15 (6.8)	1.49 (0.51; 4.33)	0.73 (0.25; 2.08)	1.59 (0.49; 5.16)	2.03 (0.55; 7.43)
Inpatient			69 (31.4)	0.84 (0.47; 1.48)	1.78 (0.99; 3.20)+	1.57 (0.85; 2.90)	0.50 (0.28; 0.91)*
Smoke-free organization (yes)			116 (52.7)	1.24 (0.73; 2.11)	1.02 (0.60; 1.73)	0.71 (0.41; 1.23)	1.28 (0.73; 2.25)
Collaboration agreements SSS (yes)			36 (16.4)	1.09 (0.54; 2.24)	3.00 (1.34; 6.73)**	3.29 (1.30; 8.29)*	1.87 (0.80; 4.33)
Responsibility organization SSS			2.80 (1.11)	0.91 (0.72; 1.16)	1.78 (1.37; 2.32)***	1.82 (1.38; 2.39)***	1.27 (0.98; 1.65)
Protocol/guideline available
No (ref.)			102 (46.4)	1	1	1	1
Yes			32 (14.5)	1.99 (0.87; 4.54)	6.57 (2.44; 18.43)***	3.94 (1.40; 11.05)**	2.91 (1.10; 7.70)*
Don’t know			86 (39.1)	0.95 (0.53; 1.68)	1.40 (0.79; 2.49)	1.29 (0.72; 2.33)	1.64 (0.89; 3.02)
SSS fits mental healthcare			3.75 (1.04)	0.98 (0.76; 1.26)	1.45 (1.11; 1.89)**	1.33 (1.02; 1.73)*	1.22 (0.93; 1.59)
Task interference#			3.36 (1.03)	1.08 (0.83; 1.40)	0.85 (0.65; 1.10)	0.77 (0.59; 1.02)	0.98 (0.75; 1.30)
Irrelevant to treatment goals#			3.27 (1.15)	0.91 (0.72; 1.14)	0.58 (0.45; 0.75)***	0.66 (0.51; 0.86)**	0.75 (0.58; 0.97)*
Insufficient time#			3.12 (1.11)	1.34 (1.05; 1.72)*	0.92 (0.72; 1.17)	0.93 (0.73; 1.20)	0.93 (0.72; 1.20)
Insufficient materials#			3.09 (1.11)	1.01 (0.80; 1.29)	0.68 (0.53; 0.88)**	0.83 (0.64; 1.06)	0.77 (0.59; 1.00)*
Insufficient client reimbursement#			2.90 (1.15)	0.95 (0.75; 1.19)	0.81 (0.64; 1.02)+	1.00 (0.79; 1.27)	0.87 (0.68; 1.11)
Insufficient referral possibilities#			2.83 (1.05)	0.92 (0.71; 1.18)	0.78 (0.60; 1.01)+	0.86 (0.66; 1.12)	0.74; 0.56; 0.97)*
Insufficient professional rewards#			2.11 (1.08)	0.97 (0.76; 1.23)	1.02 (0.79; 1.30)	0.91 (0.71; 1.18)	0.90 (0.69; 1.16)

Ask concerns all vs. none—majority of clients; Advise, Motivate and Refer concern any client (minority—all) vs. none

^aAll MHCPs who worked with children aged 5–9 also saw older clients

^#Barriers to provision of SSS

⁺p < 0.10

^*p < 0.05

^**p < 0.01

^***p < 0.001

Participants were informed that participation was voluntary and that data would be analyzed and stored anonymously and treated confidentially. They provided informed consent before completing the survey. The study was cleared for ethics by the Leiden Den Haag Delft Medical Ethical Committee (N20.165).

Measures

The selection and operationalization of variables was based on previous work on implementation of SSS in medical healthcare [30, 31], which was guided by the CFIR [28], as well as the Measurement Instrument for Determinants of Innovations (MIDI) [32]. In addition, several barriers specific to mental healthcare were added based on the findings of a systematic review of HCPs’ attitudes toward smoking and smoking cessation in people with mental illness [26]. Participants were asked whether they used the term ‘client’ or ‘patient’, in order to adjust the survey to their own terminology. In the survey, SSS was written in full.

Outcome variables

Implementation of Ask: Participants indicated how many clients they asked whether they used each of four substances (i.e. alcohol, cannabis, hard drugs, tobacco), either in a conversation or via a form or questionnaire. Answer categories were [1] ‘all’, [2] ‘the majority’, [3] ‘half’, [4] ‘the minority’, and [5] ‘none’. For RQ3 and RQ4, Ask about tobacco was dichotomized based on the median (all vs. majority-none).

Implementation of Advise, Motivate and Refer: In line with previous work [31], participants indicated how many clients they advised, in a clear and personalized way, to quit smoking (Advise), in how many clients who smoke they applied a brief motivational intervention (Motivate), and how many clients motivated to quit smoking they referred to SSS or treatment for tobacco dependence (Refer). Answer categories were as for Ask. For RQ3 and RQ4, Advise, Motivate, and Refer were dichotomized (all—minority vs. none) based on the median.

Explanatory variables

A comprehensive set of participant characteristics, psychosocial factors, client factors and organizational/environmental factors was assessed. As part of this, sixteen barriers to providing SSS were assessed [31], which are each described under the relevant category below. Participants indicated to what extent each of these factors was a barriers to providing SSS, with answer categories [1] ‘not at all’, [2] ‘not’, [3] ‘slightly’, [4] ‘strongly’, and [5] ‘very strongly’. Participants were instructed that SSS concerns all tasks related to smoking in their clients (“and/or parents/caregivers” added for MHCPs working with children) that are applicable to them.

Participant characteristics: Participants provided their age, gender, profession, number of years worked in their current profession, previous participation in SSS training, and smoking status (never smoked/quit smoking/currently smokes).

Psychosocial factors: Answer categories for psychosocial characteristics were [1] ‘completely disagree’—[5] ‘completely agree’, with [6] ‘do not know/inapplicable’ (recoded into [3] ‘agree nor disagree’), unless indicated otherwise. Participants indicated, with one item each, their attitude (‘I find it important that SSS is provided correctly’), intention (‘I intend to provide SSS correctly’), knowledge and skills (2 items; ‘I have sufficient knowledge/skills to provide SSS correctly’, respectively), self-efficacy (‘I feel capable of providing SSS correctly’), role identity (‘As a [specific professional], I see it as my role to provide SSS correctly’), social support (‘I feel supported in providing SSS’), and outcome expectations (‘If I provide SSS correctly, more clients will successfully quit smoking’). The barrier ‘I have had insufficient training in SSS’ was also assessed ([1] ‘not at all—[5] ‘very strongly’). These items were used before in research on SSS, and based on the MIDI [31, 32].

In addition, perceptions of responsibility were assessed with ten items (answer categories [1] ‘completely disagree’—[5] ‘completely agree’). Eight items were used previously, e.g. ‘People continue to smoke because they lack willpower’ [30]. In addition, ‘It is the client’s own choice to smoke’ and ‘It is the client’s own responsibility to quit smoking’ were added [26].

Client factors: Participants indicated the primary DSM 5 diagnoses among their clients (based on main DSM 5 categories; multiple answers possible), the age of most clients2 (i.e. 0–4, 5–9, 10–17, 18–30, 31–60, > 60 years; multiple answers possible), and estimated the percentage of people who smoke among clients. In addition, eight client-related barriers were assessed ([1] ‘not at all—[5] ‘very strongly’). Five barriers were used in research into SSS in medical healthcare as well [31], and ‘Clients cannot quit smoking successfully’, ‘Smoking fulfils a too important function for clients, e.g. coping, enjoyment’, and ‘Quitting smoking worsens psychological complaints’ were added.

Organizational/environmental factors: Participants indicated in which settings they worked (i.e. outpatient/ambulant, day treatment, inpatient; multiple answers possible), whether their organization was smoke-free (yes/no/don’t know; recoded into yes vs. no/don’t know), whether they or their organization had collaboration agreements for SSS and, if so, with which type of healthcare provider (recoded into yes vs. no), and availability of guideline/protocol for SSS at their workplace (yes/no/don’t know). In addition, responsibility for organizing SSS was assessed with 1 item (‘I feel responsible for organizing SSS in my direct work environment’, [1] ‘completely disagree’—[5] ‘completely agree’). Perceived fit of SSS in mental healthcare was assessed by having participants indicate, for several settings including mental healthcare, whether they thought that SSS belonged in this specific setting ([1] ‘completely disagree’—[5] ‘completely agree’, with [6] ‘do not know’ (recoded into [3] ‘agree nor disagree’). Finally, seven barriers were assessed, of which six were based on previous work [31], and ‘Quitting smoking is not relevant to the treatment goals or client’s request for help’ was added.

Exploratory variables: other SSS tasks

In order to gain a complete picture of what MHCPs did, and did not, do with regard to SSS, additional SSS tasks were assessed as well. These included Assist and Arrange (5A approach; [33], making a quit plan, or prescribing medication were asked as well, including provision of quit advice and motivational interventions to specific subgroups such as clients with smoking-related complaints or pregnant women (see Supplementary Materials Table 1 for operationalization and results). Furthermore, MHCPs who indicated that they primarily work with clients under 18 completed additional questions about Ask, Advise, Motivate and Refer among parents/caregivers (see Supplementary Materials Table 2).

Statistical analyses

Analyses for RQ1 and RQ2 were performed using all available cases, and analyses for RQ3 and RQ4 were performed among participants with complete data for all included variables. It was ensured that the assumptions of analyses were met. Analyses for RQ1, RQ2 and RQ3 were performed in IBM SPSS Statistics version 25, and analyses for RQ4 were performed in R, using the Rpart and Partykit packages [34, 35].

For RQ1, frequencies and percentages were obtained for Ask for all four substances. Wilcoxon signed rank tests were performed to assess differences in Ask between tobacco and the other substances. For RQ2, additional frequencies and percentages were obtained for Advise, Motivate and Refer.

For RQ3, separate univariable logistic regression analyses for each of the predictor variables were performed first for Ask, Advise, Motivate and Refer. Outcome variables were categorized based on median-split. Univariable analyses were followed by a multivariable analysis for each of the outcome variables, including only significant predictors of the respective outcome variable.

Finally, separate sets of regression tree analyses were performed for RQ4 (i.e. for Ask, Advise, Motivate and Refer), using all explanatory variables. Regression tree analysis examines whether variables interact in explaining a given outcome, and searches for optimal cut-off values in explanatory variables. In contrast to more traditional techniques that require pre-specification of interactions, the procedure searches for potential interactions in a data-driven manner. At the same time, cross-validation is performed to ‘prune’ the tree, and reduce the risk of chance findings. The minimum number of participants per leaf was fixed at 10, and the minimum increase in fit (complexity parameter) was set at 0.0001. Default options were used for the remaining parameters. The selection process of the initial, non-pruned tree was performed 1000 times. Correct classification rate (CCR) was calculated for the final regression tree and compared to the a priori CCR (i.e., all participants assigned to the largest category).

Results

Comparison between substances (RQ1)

A small majority of MHCPs indicated that they asked all clients about alcohol, but only the minority asked all clients about cannabis, hard drugs, or tobacco (see Table 1). Wilcoxon signed rank tests showed that MHCPs asked significantly more clients about use of hard-drugs than tobacco (z = − 3.73, p < 0.001). Similarly, they seemed to ask more clients about alcohol (z = − 1.79, p = 0.08) and cannabis (z = − 1.83, p = 0.07) than tobacco, but these differences were marginally significant.

Table 1.

Implementation of Ask (all substances) and Advise, Motivate and Refer (tobacco): Frequencies (N = 182–308)

		n (%)
		All	Majority	Half	Minority	None
All substances: Ask
Alcohol		162 (52.6)	70 (22.7)	28 (9.1)	41 (13.3)	7 (2.3)
Cannabis		146 (47.4)	61 (19.8)	26 (8.4)	62 (20.1)	13 (4.2)
Hard drugs		141 (45.8)	54 (17.5)	19 (6.2)	70 (22.7)	24 (7.8)
Tobacco*		136 (44.2)	92 (29.9)	28 (9.1)	43 (14.0)	9 (2.9)
Tobacco
Advise*		14 (5.1)	26 (9.4)	22 (7.9)	87 (31.4)	128 (46.2)
Motivate*		20 (7.2)	27 (9.7)	30 (10.8)	99 (35.7)	101 (36.5)
Refer*		38 (14.8)	33 (12.8)	26 (10.1)	69 (26.8)	91 (35.4)

‘Ask’ concerns clients in general; ‘Advise’ and ‘Motivate’ concern clients who smoke; ‘Refer’ concerns clients who are motivated to quit smoking. Numbers printed in bold indicate the most frequent response

^*Included in analyses for RQ2 and R3

Implementation of SSS tasks (RQ2)

Main outcomes: As reported above, a small majority of MHCPs reported to ask all clients about smoking tobacco (see Table 1). However, results also showed that most MHCPs never or rarely advised or motivated clients to quit smoking, nor referred clients motivated to quit to SSS (see Table 1).

Exploratory variables: Other SSS tasks were rarely performed (see Supplementary Materials Table 1). It appeared that MHCPs were more likely to advise or motivate people with smoking-related complaints and pregnant women who smoke. Most MHCPs indicated that they would discuss pros and cons of quitting and smoking, as well as barriers to quitting, with clients motivated to quit. MHCPs working with children sometimes asked parents or caregivers about smoking, but rarely advised, motivated or referred (see Supplementary Materials Table 2).

Logistic regression analyses (RQ3)

For asking clients about smoking, univariable analyses showed that MHCPs were significantly more likely to ask any (vs. none) of their clients about smoking if they had stronger intentions to provide SSS, and perceived it as clients’ own responsibility to quit (see Table 2). Also, MHCPs who worked primarily with people with sexual disorders, and with clients aged 18–60 were more likely to ask, whereas those who worked with clients aged 10–17 were less likely to ask. Finally, MHCPs who reported insufficient time as a stronger barrier to providing SSS were more likely to ask. All of these associations, except those for clients’ age, remained significant in the multivariable model (see Table 3).

Table 3.

Explaining dosage delivered of key SSS tasks: multivariable logistic regression analyses, N = 220

Predictor variables			Odds ratio (95% confidence interval)
			Ask	Advise	Motivate	Refer
Participant characteristics
Profession
Nurse (ref.)				1	1	1
Child psychologist				1.44 (0.29; 7.18)	0.57 (0.10; 3.11)	0.32 (0.07; 1.44)
Psychiatrist				1.96 (0.68; 5.70)	1.34 (0.44; 4.13)	0.48 (0.17; 1.33)
Psychologist				0.69 (0.23; 2.09)	1.06 (0.32; 3.47)	0.44 (0.18; 1.10)+
Other				0.49 (0.08; 3.16)	1.40 (0.15; 12.84)	0.50 (0.10; 2.49)
SSS training				3.46 (0.93; 12.86)+	3.71 (0.90; 15.20)+
Psychosocial factors
Intention			1.42 (1.06; 1.92)*	1.85 (1.15; 2.97)*	1.91 (1.18; 3.08)**	1.27 (0.86; 1.89)
Knowledge				2.23 (1.21; 4.12)*	1.35 (0.76; 2.37)
Skills				0.42 (0.22; 0.83)*	0.76 (0.41; 1.42)
Self-efficacy				1.49 (0.78; 2.87)	1.44 (0.77; 2.71)
Role identity				0.87 (0.57; 1.34)	0.77 (0.50; 1.18)	1.05 (0.73; 1.51)
Social support				0.94 (0.58; 1.54)	1.11 (0.70; 1.75)
Insufficient training#				0.89 (0.55; 1.44)	0.74 (0.45; 1.20)
Perceptions of responsibility
Start choice						0.85 (0.60; 1.19)
Continue addiction						1.38 (0.93; 2.06)
Start child						1.36 (0.90; 2.07)
Client knowledge				0.91 (0.65; 1.29)	0.78 (0.55; 1.11)
Own responsibility to quit			1.55 (1.12; 2.13)**
Client factors
Primary DSM 5 diagnoses
Bipolar				1.23 (0.52; 2.94)	1.13 (0.45; 2.81)
Dissociative				1.83 (0.64; 5.19)	1.75 (0.55; 5.59)
Behavioural						0.61 (0.29; 1.28)
Neurodevelopmental				0.37 (0.13; 0.99)*	0.35 (0.13; 0.99)*
Personality (cluster C)				0.77 (0.37; 1.58)
Sexual			5.04 (1.32; 19.32)*
Addiction				0.50 (0.18; 1.38)	0.53 (0.18; 1.57)
Primary age group
10–17 years			0.40 (0.13; 1.27)
18–30 years			1.87 (0.99; 3.55)+
31–60 years			1.18 (0.46; 3.05)			1.66 (0.67; 4.10)
% of clients who smoke					1.01 (0.99; 1.03)
Smoking sensitive subject#					1.20 (0.77; 1.86)
Negative towards SSS#					1.30 (0.82; 2.08)
Smoking important function#					1.20 (0.81; 1.78)
Impact therapeutic relationship#						0.77 (0.51; 1.15)
Organizational/environmental factors
Setting
Outpatient/ambulant						1.34 (0.49; 3.68)
Inpatient						0.57 (0.22; 1.48)
Collaboration agreements SSS (yes)					2.17 (0.68; 6.69)
Responsibility organization SSS					1.39 (0.93; 2.10)
Protocol/guideline available
No (ref.)					1	1
Yes					1.19 (0.29; 4.89)	1.14 (0.37; 3.51)
Don’t know					1.87 (0.83; 4.24)	1.79 (0.89; 3.60)
SSS fits mental healthcare
Irrelevant to treatment goals#					0.84 (0.56; 1.26)	0.88 (0.62; 1.26)
Insufficient time#			1.34 (1.02; 1.75)*
Insufficient materials#						0.93 (0.66; 1.30)
Insufficient referral possibilities#						0.75 (0.53; 1.06)

Ask concerns all vs. none—majority of clients; Advise, Motivate and Refer concern any client (minority—all) vs. none

^#Barriers to provision of SSS

⁺p < 0.10

^*p < 0.05

^**p < 0.01

^***p < 0.001

With regard to advising clients who smoke to quit, univariable analyses showed that psychologists were significantly less likely than nurses to provide quit advice to any (vs. none) of their clients who smoke (see Table 2). MHCPs who were trained in SSS were more likely to provide quit advice, whereas those who reported insufficient training as a stronger barrier to providing SSS were less likely to advise to quit. Furthermore, MHCPs were more likely to advise clients to quit if they had stronger intentions to provide SSS, more self-reported knowledge and skills, stronger self-efficacy and role-identity (i.e. SSS fits with their role), and felt more support for providing SSS. They were less likely to advise if they believed clients to have sufficient knowledge of the consequences of smoking. Several client factors played a role, such that MHCPs were more likely to advise if they worked with people diagnosed with bipolar, dissociative or addiction disorders, but less likely if they worked with people diagnosed with neurodevelopmental or cluster C personality disorders. MHCPs who reported a higher smoking prevalence among their clients were also more likely to advise. Finally, MHCPs were more likely to advise if they or their organization had collaboration agreements with other organizations for SSS, if they felt more responsible for organizing SSS within their organization, if an SSS protocol or guideline was available, and if they believed that SSS fits within mental healthcare. Those who reported that SSS was hindered by the irrelevance of smoking cessation to treatment goals, or by insufficient materials, were less likely to advise to quit. The multivariable model showed that stronger intentions and more self-reported knowledge were independently associated with advising more clients, whereas less self-reported skills, and working with clients with neurodevelopmental disorders were associated with advising fewer clients (see Table 3). The unexpected effect of skills was most likely due to suppression, suggesting that it emerged only in the context of the other variables, as a positive relation was found in the univariable model.

Univariable results for motivating clients to quit resembled those for advising clients to quit. The analyses showed that child psychologists and psychologists were significantly less likely than nurses to motivate any (vs. none) client who smokes to quit smoking (see Table 2). MHCPs were more likely to motivate clients for quitting if they were trained in SSS, did not report insufficient training as a barrier, and had stronger intentions, more self-reported knowledge and skills, stronger self-efficacy and role-identity, and experienced more social support. They were less likely to motivate clients if they believed that clients had sufficient knowledge of the consequences of smoking, and if they worked with people with neurodevelopmental disorders. Those who worked with people with bipolar, dissociative, or addiction disorders were more likely to motivate clients to quit, as were MHCPs who reported a higher prevalence of smoking among their clients. Unexpectedly, those who reported the sensitivity of smoking as a subject, clients being unmotivated to quit, and smoking serving an important function for clients as stronger barriers to SSS were more likely to motivate their clients to quit smoking. The multivariable model showed that MHCPs were significantly more likely to motivate clients to quit smoking if they had stronger intentions to provide SSS, and if neurodevelopmental disorders were not the primary problem among their clients (see Table 3).

The final set of univariable analyses focused on explaining whether MHCPs refer clients to SSS. Results showed that child psychologists were significantly less likely than nurses to refer any (vs. no) client motivated to quit smoking to SSS (see Table 2). Furthermore, MHCPs were more likely to refer if they had stronger intentions and role-identity. MHCPs were also more likely to refer clients if they perceived that people continue to smoke because of addiction, and that most people started smoking as a child, whereas MHCPs who perceived that starting to smoke is a conscious choice were less likely to refer. MHCPs working with people with a behavioral diagnosis were less likely to refer, whereas those working with clients aged 31–60 were more likely to refer. MHCPs who were hindered in providing SSS by the expected negative impact on the therapeutic relationship were less likely to refer. Referrals were also more likely among MHCPs working in outpatient settings, and if a protocol or guideline for SSS was available. In contrast, MHCPs were less likely to refer if they worked in inpatient settings, and if they reported that SSS was hindered by the irrelevance of smoking cessation to treatment goals, insufficient materials and insufficient referral possibilities. None of these associations remained significant in the multivariable model (see Table 3). Only a marginally significant effect of profession was found, such that psychologists appeared less likely than nurses to refer clients.

Regression tree analyses (RQ4)

Regression tree analyses showed that asking about smoking could be explained by the interaction between perceptions of clients’ responsibility for quitting (primary explanatory variable), estimated smoking prevalence among clients, strength of the barrier that clients are unsuccessful in quitting, and the MHCP’s own smoking status and age (CCR = 69%, a priori CCR = 51%), see Fig. 1. Specifically, for MHCPs who did not really perceive clients as responsible for quitting (left side of the figure), those with less than 32.5% of clients smoking were unlikely to ask any client about smoking (probability 0.26). For those with ≥ 32.5% clients smoking, the MHCP’s own smoking status was important such that those who had never smoked were more likely to ask (probability ask 0.66) than both those who currently smoked and had quit smoking (probability 0.40). Furthermore, for MHCPs who more strongly perceived clients as responsible for quitting (right side of the figure), the extent to which they reported it a barrier that clients would be unsuccessful in quitting, as well as the MHCP’s own age, were important. MHCPs who did not strongly endorse the barrier of clients being unsuccessful were quite likely to ask about smoking (probability 0.74). However, among those who did endorse this barrier, an association with age emerged such that MHCPs over 43.5 years of age were relatively likely to ask (probability 0.74) whereas younger MHCPs were less likely to ask (probability 0.33).

Fig. 1.

Regression tree analysis explaining ‘Ask’ (all vs. majority-none) clients about smoking status, N = 220

Analyses for advising clients to quit, motivating clients to quit, and referring clients to SSS did not result in regression trees.

Discussion

This comprehensive cross-sectional study investigated MHCPs’ implementation of key SSS tasks. Both logistic regression analyses and regression tree analyses were used to better understand how implementation can be explained. Results showed that MHCPs estimate that about half of their clients smoke. Despite the high prevalence of smoking and its deleterious effects on both physical and mental health, tobacco use in clients receives relatively little attention. Although a minority of MHCPs indicates that they ask all clients about smoking, the majority does not do so. Furthermore, most MHCPs do not advise or motivate clients to quit, and do not refer clients motivated to quit to adequate SSS. As such, MHCPs who do not ask about smoking, as well as those who ask but fail to undertake further action, implicitly communicate that smoking is irrelevant or even approved of. As a consequence of the low degree of implementation of key SSS tasks, the subsequent analyses explained which MHCPs do anything (vs. nothing) rather than which MHCPs deliver SSS in line with clinical guidelines. The analysis thus shows where to start with efforts to improve SSS in mental healthcare.

SSS starts with asking clients whether or not they smoke. Logistic regression analyses showed that MHCPs are more likely to ask about smoking if they have stronger intentions to provide SSS, as can be expected. Furthermore, results showed that MHCPs are more likely to ask about smoking if they more strongly perceive the client to be responsible for quitting (‘professional’ factors), and if they report insufficient time as a stronger barrier to providing SSS, and if sexual disorders are a common problem among their clients (‘inner setting’ factors). The finding that MHCPs are more likely to ask about smoking if they perceive the client as more responsible is unexpected, and contrasts theory and previous empirical studies. First, in contrast to the current finding, Weiner’s attribution theory of controllability suggests that people are less likely to offer help to stigmatized others whom they perceive to have caused their problems themselves [36]. Second, the current finding for responsibility perceptions appears at odds with previous qualitative findings, which suggested that MHCPs who perceived clients as the ‘problem owners’ are more inclined to wait for clients to bring up smoking, rather than initiate the conversation themselves [19]. Likewise, a study among physicians in medical healthcare showed them to be less likely to support people in quitting if they hold people who smoke more responsible for smoking and quitting [30, 37]. Importantly, the regression tree analysis in the current study showed that the association between perceptions of client responsibility—which emerged as the key explanatory variable—and asking about smoking is not linear. Instead, perceptions of responsibility interacted with the reported smoking prevalence among clients, strength of the barrier that clients are unsuccessful in quitting, and the MHCP’s own smoking status and age. The exact processes taking place here cannot be disentangled in the current study design, and need to be investigated further.

With regard to ‘inner setting’ factors, two notable findings emerged such that time barriers and sexual diagnosis in clients were associated with asking about smoking. It is possible that primarily those MHCPs who do provide SSS experience insufficient time as a barrier, whereas those who do not provide SSS -and, thus, ask fewer clients- do not have this experience. The finding for sexual disorders is more difficult to interpret, but may suggest that MHCPs who are used to discussing intimate topics are less reluctant to discuss smoking. However, this finding was based on a very small number of MHCPs who indicated that sexual disorders are a common problem among their clients, and should first be confirmed in follow-up research.

Although better SSS for people with mental illness starts with MHCPs who more often ask their clients whether they smoke, other findings of this study are relevant as well. Nurses and psychiatrist appear to better implement SSS than psychologists and child psychologists, suggesting that SSS may be better integrated in medical professions. In line with this, comparison with a similar survey in the medical domain suggest that MHCPs are less likely to ask, advise, or refer than most types of medical professionals (e.g., cardiologists, internists, pulmonologists, surgeons, midwives) [31]. This might relate to the fact that adverse physical consequences of smoking are more widely known, and studied, than psychological and cognitive consequences [9]. However, it is important that psychologists and child psychologists become more aware of the relevance of SSS to the problems in their clients. This might be reached through training professionals, which is a common approach to improving quality of care. Although training in SSS facilitates implementation of SSS, only 16% of MHCPs included in the current sample were trained. Relatively low scores on self-efficacy, skills, knowledge and social support suggest that SSS training might help. Despite the suboptimal implementation of SSS tasks, MHCPs overall reported positive attitudes towards SSS and perceived that SSS fits in mental healthcare, suggesting that they might be interested in being trained. For early-career MHCPs, it would greatly help if residency training programs would include the ability to provide stop smoking support as a required competency [6]. On the longer term, this will improve SSS. However, results also show that most MHCPs in the current sample, who have already finalized their residency training, do not feel that providing SSS is part of their role, and do not feel very responsible themselves for improving SSS in mental healthcare. It might therefore still prove difficult to get MHCPs to participate in optimal training programs, but more fruitful to first target MHCPs’ perceptions via other means that do not require active enrolment of MHCPs, such as through campaigns, testimonials, and local implementation champions. Given the findings, such strategies should focus on perceptions of client responsibility as well as misconceptions that clients cannot quit successfully, as research shows that people with mental illness can quit smoking successfully if they receive adequate support [21, 23–25]. Importantly, the therapist’s behavior can also positively affect a client’s outcome expectations in turn [38]. Interestingly, several comments at the end of the questionnaire suggested that merely asking questions made MHCPs reflect on their perceptions and behavior, and resulted in intentions to improve their own implementation of SSS. Of course, this fits with well-established therapeutic approaches such as motivational interviewing and cognitive therapy. Asking questions and having MHCPs arrive at their own answers might be a better fit with their ways of working than just telling them what to do because a guideline says so.

It is also important to take MHCPs’ own smoking status and history into account, as the regression tree model showed that, depending on other factors, those who currently smoked and those who had quit smoking were less likely to ask about smoking than those who had never smoked. The role of professionals’ own smoking behavior has been investigated quite well. For example, meta-analyses showed that physicians’ and nurses’ smoking status was not related to asking about smoking (which is in line with logistic regression analysis results in this study), although those who currently smoked were less likely to advise or counsel their patients who smoke [39, 40]. A survey showed that physicians who quit smoking held patients less personally responsible for smoking than physicians who either currently smoked or had never smoked [30]. A small-scale survey in Dutch addiction care showed that professionals who smoke had narrow perceptions of barriers to quitting smoking compared to non-smoking professionals, focusing mainly on internal factors (e.g. insufficient motivation) and underestimating the role of external factors (e.g. others who smoke) [41]. Like clients, MHCPs who smoke may need to be advised, motivated, and supported to quit smoking. Importantly, MHCPs who smoke and are requested to provide SSS may experience conflict between their professional identity and their identity as a smoker, which could make them resistant to efforts to put SSS on the agenda or to make mental healthcare smoke free. Although this has not yet been studied, research in the general population shows that people who identify with smoking respond more negatively to a antismoking messages or measures [42–44]. Furthermore, the professional identity literature shows that professionals may experience conflict between their professional identity and other important parts of who they are [45].

Limitations and strengths

This study has limitations. First, selection bias might have given a more positive picture of SSS in the current sample compared to the larger group of MHCPs, despite a broad recruitment strategy and informing MHCPs that they could participate regardless of their experience with SSS. Recruitment of child psychologists in particular proved difficult, potentially because child psychologists perceive SSS as less relevant to their profession. Second, social desirability bias can have affected the data, although the survey was anonymous. For both selection bias and social desirability bias, current results might provide a too positive picture, which only underscores the finding that the picture for SSS in mental healthcare is not very positive. Third, the subgroups of MHCPs who either smoked or quit smoking themselves were relatively small in this sample. This may have prevented detection of associations with implementation of SSS in the logistic regression analyses, although regression tree analysis did show the importance of smoking status. Combination of datasets might be more useful to understand the role of professionals’ own smoking status. Fourth, even though most variables had been used before and/or were adapted from a validated instrument [30–32], some items were developed specifically for this study as no existing items were available. Although the CFIR was used to guide variable selection, most factors belong to the ‘professional’, ‘inner setting’ and ‘outer setting’ domains. Including variables to represent all domains would have resulted in a very long survey to complete, but future research may examine the role of factors in the ‘intervention’ and ‘implementation process domains’ in more detail. Finally, the current study was exploratory in nature. Follow-up studies are needed to confirm the importance of the explanatory variables identified in the current study.

This study also has strengths, as it used a diverse and relatively large sample of MHCPs, collected data on a comprehensive set of variables, and used both logistic regression and regression tree analyses. Results showed the added value of regression tree analysis, which showed that the association between perceptions of client responsibility and asking clients about smoking depends on additional factors—which is not easily discovered with more traditional regression models. Importantly, complex problems such as suboptimal implementation of SSS cannot be understood by merely examining main effects of variables, as if they were independent factors, but are typically explained by several factors in interaction.

Conclusion

In sum, this study showed that implementation of SSS in mental healthcare is suboptimal, despite the high prevalence of smoking among people with mental illness, the willingness of many clients to quit smoking, and the large benefits of quitting for both their physical and mental health. In order to improve this situation, proactive efforts should be undertaken to target MHCPs’ perceptions of clients’ responsibility and quit success, preferably through strategies that reach MHCPs regardless of their affinity with SSS, taking MHCPs’ profession and own smoking status into account.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contributions

EM was responsible for conceptualizing, preparing, conducting and reporting the study.

Funding

No funding was received for conducting this study.

Data availability

Pseudonymized data are available from the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participate

The study was cleared for ethics by the Leiden Den Haag Delft Medical Ethical Committee (N20.165). This project was performed in accordance with the Declaration of Helsinki, and relevant guidelines and regulations.

Consent for publication

All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000. Informed consent was obtained from all patients for being included in the study.

Competing interests

The author declares no competing interests.