Barriers and facilitators of inpatients and healthcare professionals prior to the implementation of a Multidisciplinary Lifestyle-Focused Approach in the Treatment of Inpatients With Mental Illness (MULTI+): The MULTI+ Study II

Abstract

Background

Despite the efficacy of lifestyle interventions for the physical and mental health of people with mental illness, there is little change in clinical care. Understanding barriers and facilitators of implementation can help interpret intervention effectiveness and aid implementation. This cross-sectional study identifies barriers and facilitators before implementing a multidisciplinary lifestyle approach in the treatment of inpatients with mental illness (MULTI+). Additionally, we analyze associations between barriers and facilitators, and recipients’ health and demographic characteristics.

Method

This study used baseline data from an open cohort stepped wedge cluster randomized trial. The Measurement Instrument for Determinants of Innovations was used to investigate barriers and facilitators associated with the innovation (MULTI+), user (recipients and deliverers), and organization. Data was collected through semi-structured interviews for recipients and an online survey for deliverers. We explored associations between barriers and facilitators, and recipients’ health and demographic characteristics through multiple regression models.

Results

We included 134 recipients and 125 deliverers. Perceived barriers to implementing MULTI+ included complexity, incomplete information, and incompatibility with current treatment. Recipients and deliverers reported personal barriers, including a lack of personal benefits, potential drawbacks, and insufficient knowledge. Facilitators such as the recognized importance of lifestyle-focused care, social support, and organizational commitment could enhance implementation. Being hospitalized for more than a year was negatively associated with determinants such as compatibility, patient relevance, and satisfaction (range between β = −.25 and β = −.45). Regression models indicated few other associations. Suggestions to address barriers were made.

Conclusions

This study is one of the first to analyze barriers and facilitators before the large-scale implementation of a multicomponent lifestyle-focused approach in mental healthcare. Recipients and deliverers experience barriers and facilitators across all domains. Addressing these factors through patient-level tailoring, structured training, the use of champions, and sustained organizational support may enhance implementation and sustainability.

Trial Registration

ClinicalTrials.gov registration. Identifier: NCT04922749. Retrospectively registered 3rd of June 2021.

Plain Language Summary

Obstacles and Supportive Factors for People With Mental Illness and Their Healthcare Professionals Before Introducing a Lifestyle Program in Inpatient Treatment. While we know that lifestyle programs can help improve the health of people with mental illness (MI), integrating these programs can be challenging. This study looks at what makes it easier or harder to use lifestyle programs, so they can be improved. This study is part of a larger study that looks at the impact of a lifestyle program (multidisciplinary lifestyle-focused approach in the treatment of inpatients with mental illness). We used data collected before the program started to understand barriers and facilitators. People with MI were interviewed, and healthcare professionals completed an online survey. We then analyzed factors that may influence the experience of people with MI, such as diagnosis or gender. There were 134 people with MI and 125 healthcare professionals that answered our questions. Things that made it harder for people with MI to use the program included finding the program complex, seeing few personal benefits and feeling that the program might not fit well with their current treatment. However, they believed lifestyle programs are important and should be part of their care. People hospitalized for longer thought it would be harder to engage than those hospitalized for a shorter time. Healthcare professionals reported that they did not know enough about the program and expected personal drawbacks. However, they felt supported by their team and believed the organization would be committed to the program. To improve integration, we suggest that the program be tailored to people's interests and goals, and healthcare professionals should receive clear roles, responsibilities, and training. It is also important that everyone participates. Following these recommendations may help the program work better and support long-term success.

Introduction

Lifestyle interventions, such as those focused on physical activity, diet, smoking cessation, and sleep, have increasingly been shown to effectively improve the physical and mental health of people with mental illness (MI; Firth et al., 2019, 2020). However, an implementation gap remains between this research and real-world practice (Aschbrenner et al., 2021; Deenik et al., 2020). People with MI, including those with mood, anxiety, and psychotic disorders, exhibit higher rates of unhealthy modifiable lifestyle behaviors—such as poor diet, low levels of physical activity, and high tobacco use—compared to the general population (Dickerson et al., 2018; Stubbs et al., 2016; Teasdale et al., 2019). These behaviors contribute to the development of physical diseases, leading to a reduced life expectancy of up to 20 years (Hjorthøj et al., 2017; Plana-Ripoll et al., 2019). Despite evidence showing the positive effects of lifestyle interventions, few innovations are sustainably integrated into routine clinical care (Firth et al., 2020; Jacobs et al., 2015; Shelton et al., 2018).

In general, translating evidence-based interventions (EBIs) into real-world settings can take years, with failure rates estimated between 30% and 90%, depending on factors such as the definition of failure and the complexity of the intervention (Jacobs et al., 2015; Morris et al., 2011; Shelton et al., 2018; Wiltsey Stirman et al., 2012). Implementing EBIs in complex systems can be hindered or facilitated by various factors, which are often interdependent (Bauer & Kirchner, 2020; Flottorp et al., 2013). These barriers and facilitators can manifest at different levels, including patient, provider, and organizational levels (Hébert et al., 2012; Nilsen & Bernhardsson, 2019). Patients are typically considered recipients (i.e., those who benefit from the intervention), while healthcare professionals are regarded as deliverers (i.e., those directly involved in delivering the intervention; Damschroder et al., 2022a, 2022b). Both groups can experience factors that influence how well the intervention is implemented. For recipients, these include motivation, social support, psychiatric symptoms, and medication side effects (Gandhi et al., 2019; McKibbin et al., 2014; Melamed et al., 2019; Pereira et al., 2019; Roberts & Bailey, 2011). Deliverers may be affected by the training and support they receive, competing demands, and their personal lifestyle (Ball et al., 2022; Deenik et al., 2019a; Koomen et al., 2023). Furthermore, organizational factors such as funding and culture, are important for facilitating change (Deenik et al., 2019a; Williams et al., 2015).

Despite growing evidence on barriers and facilitators in real-world settings, little is known about factors that affect the integration of multi-component lifestyle interventions in inpatient psychiatric care. Understanding these factors can help interpret effectiveness results and inform strategies to improve interventions (Powell et al., 2017). Such implementation strategies can improve the implementation and sustainability of interventions (Proctor et al., 2013). Furthermore, while interventions affect both recipients and deliverers, their perspectives are not always considered together.

Deeniket al. previously evaluated a multidisciplinary lifestyle-enhancing treatment for people with severe MI (multidisciplinary lifestyle approach in the treatment of inpatients with mental illness [MULTI]; Deenik, 2019). They found improvements in physical health, psychosocial functioning, and less medication use, with no increase in healthcare costs in a real-world inpatient setting (Deenik et al., 2018, 2019a, 2022b). Organizational factors were identified as the strongest barriers (Deenik et al., 2019b). These insights led to increased organizational support and the expansion to MULTI+ across all inpatient facilities (Deenik et al., 2022a). This study aims to explore determinants (i.e., factors that facilitate or hinder change) that may influence the scaled-up implementation of MULTI+ (Fleuren et al., 2004). First, we identify barriers and facilitators for both recipients and deliverers, and then explore associations between determinants and health and demographic characteristics of recipients.

Method

Study Design and Setting

This study uses data collected before the implementation phase as part of a broader evaluation of an open cohort stepped-wedge cluster randomized trial (den Bleijker et al., 2022). In this trial, three clusters, each consisting of multiple psychiatric wards, gradually implement MULTI+ in semiannual “steps” over 18 months (see Figure 1).

Figure 1.

Open Cohort Stepped Wedge Cluster Randomized Trial in Inpatient Psychiatric Wards in Three Clusters, Demarcated by the Dates of Implementation of MULTI+.

Note. MULTI+ = multidisciplinary lifestyle approach in the treatment of inpatients with mental illness.

Measurements (T0, T1, T2, and T3) are obtained semiannually.

Source. Figure from den Bleijker et al. (2022).

Study Population

This study was conducted at 44 inpatient wards of the mental healthcare organization GGz Centraal in the Netherlands, in which ≈2000 people with MI are treated annually. Recipients were included if they were aged ≥16 years and had received >10 days of treatment. This >10-day criterion was pragmatically selected to ensure that recipients had adequate exposure to treatment and could provide meaningful insights. Recipients were excluded if they had limited understanding of Dutch or if their physical or psychiatric condition hindered informed consent. Deliverers were included if they worked in one of the inpatient wards.

The MULTI+ Intervention

MULTI+ is a multidisciplinary, multi-component approach aimed at improving lifestyle factors (den Bleijker et al., 2022). Lifestyle-focused care is embedded as a priority within the organization, with MULTI+ becoming an integral part of standard treatment. MULTI+ focuses on 10 core components: routine daily structure and sleep, physical activity, attention to nutrition and eating habits, reducing or quitting substance use (including tobacco use), multidisciplinary approach, skills training, psychoeducation, critical review of the obesogenic environment and existing policies, active participation of deliverers, and training of deliverers. Wards have diverse recipient populations and can tailor and codesign components. Wards may prioritize different components in the initial phases, and real-world application of components will vary between wards. All wards should adopt a multicomponent approach and consult qualified professionals from relevant disciplines (e.g., dietitians and physical activity professionals).

Head physicians supervise the implementation of MULTI+, and all deliverers have access to educational resources. Active day-to-day programs are developed in multidisciplinary sessions, incorporating cotailoring with recipients whenever possible. The program includes sports-related activities, work-related activities, psychoeducation, and skills training, with active participation from recipients and deliverers. Recipients are encouraged to participate in at least two activities per day to interrupt sedentary behavior. Continuous attention is given to nutrition, eating habits, circadian rhythm, sleep hygiene, and smoking cessation, supported by interventions when necessary. Compliance is reviewed in multidisciplinary consultations, with additional support offered when needed.

Procedure

The complete procedural methods of the study are described elsewhere (den Bleijker et al., 2022). Barriers and facilitators were identified at the measurement point closest to the start of MULTI+ implementation for each cluster (i.e., T0 for cluster 1, T1 for cluster 2, and T2 for cluster 3) to provide an up-to-date perspective. At the time of measurement, all recipients and deliverers admitted to or working in an inpatient ward were invited to participate.

Questionnaire data were collected through semi-structured interviews for recipients in a suitable location as determined by researchers, deliverers, and recipients. These interviews were guided by an adapted version of the measurement instrument for determinants of innovations (MIDI). While the MIDI items informed the interview content, the semi-structured format allowed researchers to ask probing questions, tailor questions to recipients and wards, and take more time as needed. If recipients had difficulty answering all questions, deliverers were asked to assist. Recipients could also choose to conduct interviews across multiple sessions if preferred. After each measurement, 50 gift vouchers worth 10 euros each were raffled among recipients. Data from deliverers were collected through online questionnaires in return for a small gift at ward level, such as a plant or a water jug.

Informed consent from recipients was obtained verbally through visual informed consent (VIC), which visually explains the goals and procedures of the study. The Medical Ethics Committee (METC Isala, Case No. 200333) approved the use of this VIC, and trained researchers delivered the VIC verbally. Recipients were excluded if they could not comprehend the information given. If a recipient stopped answering questions, the interview was stopped. Informed consent for deliverers was obtained online before the survey began. Data were collected using the online survey software program Castor EDC for both recipients and deliverers (Castor, 2019; den Bleijker et al., 2022).

Outcomes

Health and Demographic Characteristics of Recipients

Health and demographic characteristics were obtained from electronic patient records. Diagnosis was categorized based on the DSM-5. Medication use was retrieved from the affiliated pharmacy's electronic system and converted to defined daily dose (DDD) using the Anatomical Therapeutic Chemical Classification System from the World Health Organization (World Health Organization, 2021). The DDD of antipsychotic use (N05A) and antidepressant use (N06A) was included. A combined DDD was calculated by summing the DDDs of both groups.

Barriers and Facilitators

Barriers and facilitators related to the implementation of MULTI+ were assessed using MIDIs (Fleuren et al., 2014). This questionnaire consists of 29 determinants categorized into four domains (the innovation, user, organization, and sociopolitical domain). Each determinant is based on one or more items, most of which use a 1–5 point Likert scale. The MIDI can identify determinants influencing the use of an innovation. The MIDI allows participants to omit items not applicable to their role or experience. Typically, higher scores on a determinant reflect stronger agreement with conditions that are associated with increased use of innovations (as conceptualized in the MIDI framework). We used separate MIDIs for recipients and deliverers to tailor the questionnaires to each end-user. Recipients answered questions about the user (i.e., recipient) and innovation (i.e., MULTI+) domains. Deliverers answered questions about the innovation (i.e., MULTI+), user (i.e., deliverer), and organization domains. The sociopolitical context domain was not assessed, as all deliverers belonged to the same organization and subject to the same legislation and regulations. MIDI questions were adapted to fit MULTI+ (see Additional File 2). Examples of questions for recipients include: “I think the effects of the lifestyle intervention would be clearly visible” and “I believe that working on my lifestyle should be a part of my treatment” (answers from 1 = totally disagree to 5 = totally agree). Examples for deliverers include: “The innovation clearly describes the activities I should perform and in which order” (answers from 1 = totally disagree to 5 = totally agree) and “If the lifestyle treatment were to be implemented in your organization, would you expect management to make formal agreements regarding the use of this treatment?” (answers from 1 = no to 2 = yes). Because questions were posed before implementation, the intervention and its implications were explained beforehand.

Internal consistency of the domains of the MIDI for recipients was poor for the innovation domain (α = .57) and acceptable for the user domain (α = .80). For deliverers, the internal consistency was acceptable for the innovation domain (α = .75) and good for the user domain (α = .82), and the organization domain (α = .87).

Statistical Analysis

We present the quantitative data from this study. Participants were included in the analyses if at least one MIDI determinant could be calculated. This resulted in variable sample sizes per determinant. This approach aligns with the structure of the MIDI instrument, which allows each determinant to be analyzed independently. Missing responses may reflect either intentional skipping (e.g., when items are not applicable) or unintentional factors (e.g., misunderstanding or fatigue). To assess potential health or demographic bias due to missing data, we conducted exploratory comparisons between participants with complete versus partial responses to the determinants. We conducted analyses separately for deliverers and recipients, using independent t-tests for continuous variables and chi-square tests for categorical variables. Included variables were age, gender, highest education level (both groups), diagnosis (recipients), length of hospitalization (recipients), medication use (DDD; recipients), and occupation (deliverers). Descriptive analyses were conducted to assess the barriers, facilitators, and health and demographic characteristics of recipients. For the MIDI evaluation, we used the means and standard deviations for each determinant. For multi-item determinants, an equally weighted average score of the items was calculated. Scores on determinants were calculated if one or more items were answered. Following recent studies (Deenik et al., 2019a; Verberne et al., 2018), items on which 20% of participants scored negatively (score of <3 = disagree/totally disagree) were considered barriers and items on which 80% of participants scored positively (score of >3 = agree/totally agree) were considered facilitators.

Using a forced entry method, multiple regression models were performed to assess the associations between barriers and facilitators, and health and demographic characteristics of recipients. Dependent variables were the scores on the individual determinants of the MIDI. Independent variables were gender, age, diagnosis (four categories: psychotic disorders, mood disorders, substance use disorder, and other disorders), total hospitalization (dichotomous > 1 year yes/no) and DDD. We included all determinants with either ≥15.0% negative or ≥75.0% positive answers to gain more insight into associations.

The assumptions for linearity, normality, and homogeneity were checked by comparing means with medians and analyzing frequency histograms, normality plots, and plots of residuals versus predicted values. The Breusch-Pagan and Shapiro-Wilk tests were used to evaluate heteroskedasticity and normality, respectively. Because we used Likert items as dependent variables, there was a higher risk of nonlinear relationships. To better assess linearity, the rainbow test for linearity from the lmtest package in R was used (Zeileis & Hothorn, 2002). If the normality assumption was violated, we conducted sensitivity analyses through bootstrapping with 5,000 samples and 95% intervals. All statistical tests were performed using IBM SPSS Statistics 28 (IBM Corp, 2021) and R version 4.3.1 (R Core Team, 2023).

Results

We approached 680 recipients for interviews, of which 301 (44.3%) were interviewed. A total of 134 recipients provided data on the MIDI, allowing for the calculation of at least one determinant, of which 83 (61.9%) were men and 51 (38.1%) were women, with a mean age of 53 and a variety of diagnoses (see Table 1). We sent surveys to 1,275 deliverers. Of those, 125 deliverers (9.8%) participated in the survey, providing sufficient data to calculate at least one determinant. Most of the participants were women (76.0%), and the most common occupation was nursing (36%). The mean age was 43 years. We explored whether participants with complete versus partial determinant responses differed in health or demographic characteristics. No statistically significant differences were found in age, gender, or highest education level (both groups); length of hospitalization (recipients) and medication use (DDD; recipients); or occupation (deliverers).

Table 1.

Demographics of Recipients and Deliverers

	User groups
Variables	Recipients (N = 134)	Deliverers (N = 125)
Gender, N (%) man	83 (61.9)	29 (23.2)
Age in years, M (SD)	53 (16.2)	43 (13.4)
Recipient diagnoses N (%)
Psychotic disorders	43 (32.1)
Mood disorders (bipolar and depressive)	31 (23.1)
Substance-related disorders	24 (17.9)
Other diagnoses	34 (25.4)
Unknown	2 (1.5)
DDD, antipsychotic and antidepressant (SD)	1.3 (1.4)
DDD, range	0.0–9.8
Days admitted, longer than a year*, N (SD)	64 (47.8)
Main source of income (%)
Paid job	16 (11.9)
Pension	19 (14.2)
Benefits	74 (55.2)
Prefer not to say/else	19 (14.2)
Missing	6 (4.5)
Country of birth, N (%) The Netherlands	116 (86.6)	122 (97.6)
Marital status N (%)
Married	14 (10.4)	77 (61.6)
Widowed	3 (2.2)	0 (.0)
Divorced	21 (15.7)	9 (7.2)
Unmarried	81 (60.4)	20 (16.0)
Living together	9 (6.7)	19 (15.2)
Missing	6 (4.5)	0 (.0)
Highest education, N (%)
Elementary school	8 (6.0)	0 (.0)
Secondary school	34 (25.4)	4 (3.2)
Secondary vocational education and training	41 (30.6)	43 (34.4)
Higher education	37 (27.6)	77 (61.6)
Other education	8 (6.0)	1 (.8)
Unknown	6 (4.5)	0 (.0)
Occupation deliverers, N (%)
Team leader/department manager		8 (6.4)
Practitioner		15 (12.0)
Nurse		41 (32.8)
Nursing specialist		4 (3.2)
Student/intern nurse		11 (8.8)
Else		46 (36.8)

Note. * more than 365 days admitted to an inpatient psychiatric ward. Other recipient diagnoses were neurobiological developmental disorders (n = 13), personality disorders (n = 6), neurocognitive disorders (n = 4), somatic symptom disorders (n = 3), anxiety disorders (n = 2), trauma and stress-related disorders (n = 2), other issues that could be reason for care (n = 2), disruptive, impulse control, and conduct disorders (n = 1) and obsessive-compulsive disorders (n = 1). Other occupations for deliverers were, for example, activity leader (n = 7), movement therapist (n = 3), or caregiver (n = 3).

Barriers and Facilitators

Table 2 shows the barriers and facilitators identified among recipients and deliverers before the implementation of MULTI+, according to the cutoff scores used in this study. All results are reported at the determinant level.

Table 2.

Barriers and Facilitators of Recipients and Deliverers Prior to the Implementation of MULTI+

Determinants	Recipients						Deliverers
	N	Gem	SD	% negative	% neutral	% positive	N	Gem	SD	% negative	% neutral	% positive
Determinants associated with MULTI+
Procedural clarity	122	3.8	.9	11.5	10.7	77.9	124	3.2	.8	14.5	47.6	37.9
Correctness	103	4.0	1.0	9.7	5.8	84.5**	122	3.8	.7	4.1	18.9	77.0
Completeness	127	3.5	.9	20.5*	13.4	66.1	118	3.4	.7	8.5	44.9	46.6
Complexity	113	3.5	1.3	31.0*	9.7	59.3	116	3.5	.9	10.3	33.6	56.0
Compatibility	109	3.4	1.1	25.7*	18.3	56.0	116	3.4	.8	12.9	32.8	54.3
Observability	109	3.8	.9	10.1	11.9	78.0	116	3.4	.8	12.1	38.8	49.1
Relevance for client	120	3.9	1.1	15.0	10.8	74.2	115	3.7	.9	9.6	26.1	64.3
Determinants associated with the user
Personal benefits	122	3.6	.9	26.2	.8	73	112	3.3	.6	21.4*	9.8	68.8
Personal drawbacks	118	3.4	.9	30.5	5.9	63.6	109	3.3	.6	21.1*	19.3	59.6
Outcome expectations—Importance	116	3.9	.6	8.6	2.6	88.8**	108	3.8	.6	7.4	2.8	89.8**
Outcome expectations—expectations	117	3.5	.8	23.1*	6.8	70.1	105	3.4	.4	11.4	15.2	73.3
Professional obligation	106	4.2	.8	7.5	4.7	87.7**	104	3.9	.8	4.8	17.3	77.9
Client/patient satisfaction	97	3.9	.9	9.3	15.5	75.3	103	3.4	.7	8.7	45.6	45.6
Client/patient cooperation	108	3.9	1.1	13.9	9.3	76.9	103	3.1	.9	17.5	47.6	35.0
Social support	109	3.7	.8	12.8	4.6	82.6**	96	3.8	.5	6.3	2.1	91.7**
Descriptive norm (1–7)	109	4.0	2.2	22.8*	17.4	59.8	99	4.6	1.1	16.2	23.2	60.6
Subjective norm (normative beliefs)	102	3.8	.7	7.8	8.8	83.3**	92	4.0	.6	4.3	1.1	94.6**
Self-efficacy	113	3.6	.8	15.0	13.3	71.7	97	3.6	.5	9.3	4.1	86.6**
Knowledge	110	3.8	1.0	14.5	11.8	73.6	98	3.3	1.0	19.4	33.7	46.9
Awareness of content of innovation (1–4)							98	2.6	.7	44.9*		55.1
Determinants associated with the organization
Formal ratification by management (no/yes)							98	1.9	.4	14.3		85.7**
Replacement when staff leave							97	3.5	1.0	17.5	18.6	63.9
Staff capacity							97	3.8	1.0	12.4	17.5	70.1
Financial resources							95	3.7	1.1	16.8	13.7	69.5
Time available							97	3.8	1.1	16.5	13.4	70.1
Material resources and facilities							97	3.8	1.0	14.4	12.4	73.2
Coordinator (no/yes)							97	1.9	.3	10.3		89.7**
Unsettled organization (no/yes)							97	1.7	.5	30.9*		69.1
Information accessible about use of the innovation							96	3.9	.7	6.3	8.3	85.4**
Performance feedback							95	3.8	.8	8.4	16.8	74.7

Note. MULTI+ = MUltidisciplinary Lifestyle approach in the Treatment of Inpatients with mental illness; MIDI = Measurement Instrument for Determinants of Innovations.

Determinants associated with the user refers to both recipients and deliverers, depending on the group in which the MIDI was assessed. Scores on determinants were calculated if one or more items were answered on that determinant. Scores on Likert scales range from 1-5 unless specified otherwise.

^*Barrier (>20% negative responses).

^**Facilitator (>80% positive responses).

Recipients

Perceived barriers for recipients regarding MULTI+ were completeness (whether all information and materials needed to work with MULTI+ are provided; 20.5%), complexity (perceived complexity to use MULTI+; 31.0%) and compatibility with current treatment (whether MULTI+ fits the way recipients work within the group; 25.7%). Barriers perceived by recipients were limited expected personal benefits (degree to which MULTI+ has advantages for the recipient; 26.2%, e.g., feeling physically healthier), foreseen drawbacks (degree to which MULTI+ has disadvantages for the recipient; 30.5%, e.g., the intervention taking up a lot of time), low outcome expectations (23.1%, e.g., whether recipients would be more physically active) and low descriptive norm (expected degree to which deliverers would use MULTI+; 22.8%).

A perceived facilitator regarding MULTI+ was correctness (degree to which MULTI+ was based on factual knowledge; 84.5%). Facilitators perceived by recipients were importance (importance of reaching lifestyle-related goals; 88.8%, e.g., being more physically active), professional obligation (whether lifestyle-focused care should be part of treatment; 87.7%), social support (expected support from important social referents around recipients; 82.6%, e.g., nurses or group members) and subjective norm (influence of important others on the use of the innovation; 83.3%, e.g., nurses or group members).

Deliverers

Deliverers did not point to any intervention-specific barriers or facilitators for MULTI+, based on the defined cut-off scores in this study. However, deliverers identified user-related determinants, including (lack of) personal benefits (degree to which MULTI+ has advantages for the deliverer; 21.4%, e.g., spending less time on [somatic] care) and foreseen drawbacks (degree to which MULTI+ has disadvantages for the deliverer; 21.1%, e.g., not having enough time for other tasks) as barriers, as well as awareness of the content of MULTI+ (degree to which deliverers were already familiar with content; 44.9%). The only barrier associated with the organizational domain was an unsettled organization (whether ongoing changes pose obstacles to the implementation process; 30.9%).

Facilitators perceived by deliverers were importance (importance of reaching lifestyle-related goals for recipients; 89.8%, e.g., adopting healthier eating habits), social support (expected support from important social referents around deliverers; 91.7%, e.g., nurses or team leaders), subjective norm (influence of important others on the use of MULTI+; 94.6%) and self-efficacy (degree to which deliverers believe they are able to carry out activities within MULTI+; 86.6%, e.g., activating recipients). In the organizational domain, facilitators were formal ratification by management (whether formal agreements would be established; 85.7%), coordinator (presence of one or more persons responsible for coordinating the implementation of MULTI+; 89.7%), and accessible information (whether deliverers would have accessible information; 85.4%).

Associations Between Health and Demographic Characteristics of Recipients and Determinants

While normality assumptions were violated across multiple determinants, the results obtained through bootstrapping exhibited minimal divergence. Consequently, we present the results without bootstrapping. Tables 1 and 2 in Additional File 1 show the results of the multiple regression analyses for the determinants of the innovation and recipient domains, respectively.

In the innovation domain, gender was a significant predictor of completeness, with men perceiving higher completeness than women (β = .25). Compared with people with a psychotic disorder diagnosis, people with a mood disorder perceived less completeness (β = −.27), and recipients not diagnosed with substance use, mood disorder, or psychotic disorder (i.e., “other” diagnosis category) perceived less correctness of MULTI+ (β = −.24). Extended hospitalization (>1 year) was negatively associated with compatibility (β = −.45), observability (β = −.27) and relevance for patients (β = −.31).

In the recipient-related domain, age was negatively associated with self-efficacy (β = −.21). Extended hospitalization was negatively associated with personal benefits (β = −.27), drawbacks (β = −.34), probability of outcome expectations (β = −.34), patient satisfaction (β = −.28) and patient cooperation (β = −.25). Recipients who were not diagnosed with substance use, mood, or psychotic disorders (i.e., “other” diagnosis category) perceived higher patient cooperation compared to those with psychotic disorders (β = .26). The adjusted explained variance of the regression models was between zero and 15%.

Discussion

This study contributes to the growing body of research on barriers and facilitators of implementing lifestyle approaches in the treatment of people with MI. Previous studies have investigated these determinants retrospectively (e.g., Deenik et al., 2019a), employed different designs or settings, or focused on specific components (e.g., Ball et al., 2022; Carpiniello et al., 2013; Cowie et al., 2020; Pereira et al., 2019). However, the current study offers a unique perspective by examining preimplementation data from both recipients and deliverers in an inpatient setting. This approach enabled us to establish a baseline, understand the context in which the approach was implemented, and contextualize the outcomes of MULTI+. It also informs future research and implementation efforts (Fernandez et al., 2022). In this discussion, we explore the barriers and facilitators—related to MULTI+, recipients, deliverers, and the organization—that may influence the implementation of MULTI+, propose strategies to address these, and consider our findings in relation to previous studies.

Recipients

Determinants Associated With MULTI+

Recipients found that MULTI+ was based on accurate knowledge (correctness), but they found the information and materials to be incomplete (completeness) and the intervention to be difficult to use (complexity). The perceived complexity of a multi-component approach has been previously noted as a barrier (Deenik et al., 2019a). Additionally, this sense of incompleteness suggests that recipients may require more tailored support and clearer guidance to participate effectively in MULTI+ while previous research has assessed barriers and facilitators postimplementation (Deenik et al., 2019a), our findings show that such needs are already present before implementation begins. These findings underscore the importance and feasibility of tailoring interventions to recipients’ needs from the outset. They also align with previous research emphasizing the necessity of tailored approaches for effective integration (Fernández-Abascal et al., 2021; Firth et al., 2019; Kok et al., 2016; Vancampfort et al., 2015). Such approaches should include meaningful, age-appropriate, and accessible activities with achievable goals. For example, walking can serve as a manageable first step toward increased physical activity, which may help encourage further lifestyle changes (Vancampfort et al., 2015). However, multicomponent approaches like MULTI+ require ongoing support to promote holistic behavior change, which is considered the gold standard (Firth et al., 2019).

The importance of tailoring is further supported by lower compatibility scores among recipients with longer hospitalizations (>1 year; see Table 1 in Additional File 1). Individuals who are hospitalized for longer periods may face more disease-related challenges and reduced social functioning, which necessitates a more tailored approach (McCleery & Nuechterlein, 2019; Ward et al., 2015). Integrating activities into ward routines can improve alignment with care protocols, while tailoring and structured support enhance integration (Marx et al., 2021).

Determinants Associated With Recipients

A perceived lack of personal benefits and potential drawbacks were identified barriers. If recipients do not recognize clear personal advantages or anticipate disadvantages, motivation may diminish (Firth et al., 2016; Richardson et al., 2024). Emphasizing potential benefits, such as improved health outcomes and daily functioning, could help motivate recipients. Research suggests that interventions focusing on providing activities and motivation may be more successful (Firth et al., 2017; Vancampfort et al., 2015). To increase participation in MULTI+, it is therefore important to communicate benefits clearly, while addressing individual concerns (Firth et al., 2016).

Recipients perceived descriptive norm (i.e., expected degree of MULTI+ usage by deliverers) as a barrier. When recipients observe that key figures around them are actively engaged, they may be more likely to participate (Deenik et al., 2019a). Conversely, if they expect inconsistent use by deliverers, they may be less likely to participate. Clear organizational endorsement, combined with visible integration of MULTI+ into daily clinical care, can strengthen its effectiveness (Cowie et al., 2020; Marx et al., 2021).

Recipients acknowledged the importance of lifestyle-related outcomes (outcome expectations—Importance) and recognized that lifestyle-focused care should be part of their treatment (professional obligation). Social support and the influence of important others on the use of MULTI+ (subjective norm) were also identified as facilitators, indicating supportive factors for the use of MULTI+. However, recipients had low expectations regarding the actual lifestyle-related outcomes (outcome expectations—expectations). This hesitancy likely reflects broader challenges in engaging people with MI in lifestyle interventions, including medication side effects (e.g., drug-induced movement disorders) and negative symptoms (Pieters et al., 2021). Paradoxically, the potential benefits of lifestyle interventions—such as increased energy, stress reduction, and mood improvement—can be difficult to achieve in people with MI for whom low energy levels and stress are common issues, hindering their participation in these interventions (Firth et al., 2016; Glowacki et al., 2017). These interconnected barriers emphasize the need for a personalized, holistic approach with ongoing support to accommodate the challenges faced by people with MI.

Deliverers

Determinants Associated With MULTI+

No specific barriers or facilitators were identified based on the cut-off scores, but a high percentage of neutral responses (18.9% to 47.6%) suggests uncertainty or ambivalence about MULTI+. This ambiguity may itself act as a barrier to implementation, indicating a need for clear expectations, structured guidance, and reinforcement strategies (Cowie et al., 2020; Lewis et al., 2018; Powell et al., 2015). Additionally, fostering a supportive organizational context with adequate resources and strong leadership can further facilitate the uptake of EBIs (Li et al., 2018). By addressing these factors, the likelihood of successful implementation and sustained use of MULTI+ can be increased.

Determinants Associated With Deliverers

Deliverers reported lack of personal benefits, potential drawbacks, and insufficient knowledge of MULTI+ as barriers. These findings differ from those of an earlier post-implementation study within the same organization, in which personal benefits and knowledge were not reported as barriers (Deenik et al., 2019a). One possible explanation is that the current group of deliverers had not engaged with MULTI+ in practice, and therefore had limited opportunity to become familiar with its potential benefits. Implementing a new way of working initially requires time and effort from deliverers, so it is essential to communicate the benefits of MULTI+. For example, the same previous research showed that a multidisciplinary, lifestyle-focused approach made work more enjoyable and efficient, improved relationships with recipients, and reduced turmoil on site (Deenik et al., 2019a). To further address these challenges, deliverers need continuous support and training (Marx et al., 2021). Providing practical training, such as in motivational interviewing, could further strengthen deliverers's ability to engage recipients (Almansour et al., 2023; Firth et al., 2016). Additionally, assigning ward-level champions (i.e., change agent) with dedicated time and resources could boost motivation and increase the use of MULTI+ (Cowie et al., 2020; Powell et al., 2015).

Active participation by deliverers is central to MULTI+. Previous studies have highlighted the importance of similar determinants, such as attitude and active involvement, in successful implementation (Deenik et al., 2019a; Koomen et al., 2022; Watkins et al., 2020). Research has shown that when deliverers engage in lifestyle-related activities, they not only act as role models but also promote their own health (Deenik et al., 2019a). Encouraging deliverers to adopt healthier behaviors, such as increasing physical activity or making dietary changes, can help foster a broader culture shift (Fibbins et al., 2020; Rosenbaum et al., 2020). This is especially important, as deliverers's own lifestyle and attitude can directly influence recipients’ engagement (Deenik et al., 2022a; Koomen et al., 2023).

Encouragingly, deliverers reported key facilitators, including strong endorsement of lifestyle-related goals for recipients (outcome expectations—importance), self-efficacy, social support, and the influence of important others (subjective norm). These findings are consistent with previous research (Deenik et al., 2019a). Organizations can enhance implementation by leveraging these facilitators, fostering a culture that values lifestyle-focused care, and ensuring ongoing collaboration and support for deliverers.

Determinants Associated With the Organization

Formal ratification by management, the presence of a coordinator, and accessible information were identified as facilitators. However, an unsettled organization posed a potential barrier. Research underscores the importance of strong organizational commitment in sustaining hospital-based interventions (Cowie et al., 2020). Similarly, prior research by Deenik et al. (2019a) emphasizes the necessity of long-term structural support. In recent years, GGz Centraal has prioritized “lifestyle-focused care,” reflecting a shift toward stronger organizational support. This commitment may explain why deliverers identified more facilitators than barriers. Maintaining a supportive organizational structure, with ongoing efforts to normalize MULTI+ as an integral part of care, remains essential.

Implications for Practice

Several factors should be prioritized when implementing a multicomponent lifestyle approach like MULTI+. First, interventions must be tailored to recipients’ needs and available resources. This includes designing attainable, personalized activities and goals that integrate into existing care systems. Accessible and meaningful activities, such as walking programs, can encourage gradual lifestyle changes while ensuring compatibility with recipients' preferences and needs (Vancampfort et al., 2015). Second, clear roles and responsibilities for deliverers are necessary (Cowie et al., 2020). Involving them in change efforts fosters shared ownership, while practical support—such as instructional materials and training in motivational interviewing—enhances their ability to engage recipients (Almansour et al., 2023; Firth et al., 2016). Ward-level champions can offer ongoing support and motivation at the team level (Cowie et al., 2020). Lastly, sustained organizational commitment is essential (Deenik et al., 2019a). This includes ensuring adequate resources, visible leadership endorsement, and embedding lifestyle-focused care as a standard practice.

While these strategies provide a foundation, they must be continuously reevaluated as ward dynamics evolve. This is an inherent aspect of the iterative process of organizational change and implementation, where adapting approaches to shifting contexts is essential for ensuring long-term sustainability (Skivington et al., 2021).

Strengths and Limitations

A key strength of this study is its real-world setting, making the findings directly applicable to clinical practice. Real-world research is essential for bridging the gap between research and practice in implementing lifestyle interventions for people with MI and assessing effectiveness across different settings. Additionally, this study considered determinants from both recipient and deliverer perspectives, recognizing that the success of implementation depends on both groups. Despite its importance, few studies take both perspectives into account.

Preimplementation research provides valuable insights for future studies and implementation efforts. While such evaluations ideally inform implementation strategies before an intervention starts, this is not always feasible in dynamic settings. Nonetheless, preimplementation research remains crucial for identifying barriers, shaping future strategies (Fleuren et al., 2014; Powell et al., 2015, 2017), and contextualizing implementation outcomes (Fernandez et al., 2022). Preimplementation determinants can also be used in future studies to explore how they influence the success of the intervention. This process contributes to an iterative learning process, which supports both the interpretation of MULTI+ outcomes and the improvement of similar interventions (Skivington et al., 2021). The MULTI+ approach itself builds on postimplementation insights from the earlier MULTI study (Deenik et al., 2019a), demonstrating how prior research informs large-scale implementation.

This study has several limitations. First, selection and response bias are possible, particularly among deliverers, who had a low response rate of 9.8%. Since participation was voluntary and conducted primarily via email, individuals with a favorable attitude toward lifestyle interventions may have been more likely to respond. Though a broad range of determinants were assessed, covering both positive and negative perceptions, this may explain why more facilitators than barriers were identified. Additionally, conducting research within our own organization may have influenced participants’ willingness to share critical views or led them to give socially desirable answers. We tried to mitigate this risk by explicitly stating that the questionnaire aimed to capture a comprehensive view of daily routine care, including less favorable perspectives. Second, deliverers were occasionally present during recipient interviews to provide support. While this improved feasibility and enabled the inclusion of participants who might otherwise not have been able to participate, it may also have influenced responses due to social desirability or reluctance to share negative experiences. However, interviewers were trained to create a safe and open atmosphere, and recipients were explicitly encouraged to share their honest experiences. Third, limitations related to the study design and data collection include the cross-sectional nature of the study, which prevents causal inference, as well as non-response on determinants. Due to the structure of the MIDI instrument, participants could skip items they deemed irrelevant to their experience. This feature supports content validity of the MIDI, but also means that some skipped items may have stemmed from unintentional factors, such as misunderstanding or interview fatigue. Because these motivations could not be reliably distinguished, we treated all missing items equally in our analysis. To assess potential bias, we performed an exploratory comparison between participants with complete versus partial responses. No significant health or demographic differences were found, suggesting limited risk of bias due to missing data. In addition, multiple regression analyses pose a risk of multiple testing. Although hospitalization showed medium associations (β = −.25 to β = −.45), the adjusted explained variance of the models ranged from zero to 15%, underscoring the need for cautious interpretation. Future studies should further explore these associations and validate findings in different settings. Finally, while MULTI+ addresses multiple lifestyle-related factors, determinants may vary across individual components, warranting further investigation. While linking implementation strategies to determinants would be valuable (Powell et al., 2017), this was beyond the scope of this study. Nonetheless, by drawing on prior research, we provide guidance for implementing lifestyle interventions in healthcare settings.

Conclusion

This study is one of the first to examine barriers and facilitators before the large-scale implementation of a multi-component, lifestyle-focused approach in mental healthcare. The recognized importance of lifestyle-focused care, social support, self-efficacy, and perceived organizational support provides a strong foundation for implementation. However, recipients and deliverers reported barriers such as perceived complexity, limited personal benefits, and insufficient knowledge. Addressing these barriers through patient-level tailoring, structured training, ward-level champions, and sustained organizational commitment can enhance both implementation and sustainability.

These findings offer important insights into the conditions under which MULTI+ is implemented, helping to contextualize its future outcomes. Beyond MULTI+, they also inform the design and implementation of similar interventions in mental healthcare settings. This underscores the value of pre-implementation research as part of an iterative process that strengthens implementation strategies over time.