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Patient-reported outcomes of lifestyle interventions in patients with severe mental illness: a systematic review and meta-analysis



Lifestyle interventions for severe mental illness (SMI) are known to have small to modest effect on physical health outcomes. Little attention has been given to patient-reported outcomes (PROs).


To systematically review the use of PROs and their measures, and quantify the effects of lifestyle interventions in patients with SMI on these PROs.


Five electronic databases were searched (PubMed/Medline, Embase, PsycINFO, CINAHL, and Web of Science) from inception until 12 November 2020 (PROSPERO: CRD42020212135). Randomised controlled trials (RCTs) evaluating the efficacy of lifestyle interventions focusing on healthy diet, physical activity, or both for patients with SMI were included. Outcomes of interest were PROs.


A total of 11.267 unique records were identified from the database search, 66 full-text articles were assessed, and 36 RCTs were included, of which 21 were suitable for meta-analyses. In total, 5.907 participants were included across studies. Lifestyle interventions had no significant effect on quality of life (g = 0.13; 95% CI = − 0.02 to 0.27), with high heterogeneity (I2 = 68.7%). We found a small effect on depression severity (g = 0.30, 95% CI = 0.00 to 0.58, I2 = 65.2%) and a moderate effect on anxiety severity (g = 0.56, 95% CI = 0.16 to 0.95, I2 = 0%).


This meta-analysis quantifies the effects of lifestyle interventions on PROs. Lifestyle interventions have no significant effect on quality of life, yet they could improve mental health outcomes such as depression and anxiety symptoms. Further use of patient-reported outcome measures in lifestyle research is recommended to fully capture the impact of lifestyle interventions.

Peer Review reports


People with severe mental illness (SMI) have an increased risk of poor physical health and premature mortality. This can be attributed to the high prevalence of chronic somatic diseases in this patient group, including cardiometabolic diseases, respiratory diseases, and cancer [1,2,3,4,5,6,7]. Evidence suggests that people with SMI more often engage in risky health behaviours than the general population, including sedentary behaviour, low physical activity, unhealthy eating habits, smoking and substance abuse [8,9,10,11]. Given the severe health disparities, large efforts have been made to increase physical health among patients with SMI through behavioural interventions [6]. During the past decades, numerous studies on the efficacy of lifestyle interventions for patients with SMI have been executed [6, 12, 13].

Lifestyle interventions typically focus on weight management and aim to reduce overweight and obesity by stimulating dietary changes, decreasing sedentary behaviour, and increasing physical activity. However, recent systematic reviews and meta-analyses suggest that the effects of lifestyle interventions on physical health parameters, such as weight, body mass index (BMI), waist circumference, and blood pressure, are limited in this group [12], few show significant effects [13]. Especially interventions executed under real life conditions usually result in small to moderate effects that are oftentimes clinically insignificant [6, 12, 14]. Furthermore, to date there is limited information in long-term efficacy due to a lack of long-term follow-up studies [14]. This can lead researchers to be sceptical about the implementation of these interventions in clinical practice.

Little attention has been given to other possible benefits of lifestyle interventions such as improvements in quality of life (QoL), daily functioning, social functioning and participation, health-related well-being, or other patient-reported outcomes (PROs). PROs can be defined as ‘any report of the status of a patient’s health condition that comes directly from the patient, without interpretation of the patient’s response by a clinician or anyone else’ [15]. They are mostly self-report questionnaires but can also be acquired through interviews, diaries, or other tools [16]. PROs are valuable outcomes as they represent topics that are meaningful to patients and provide insight on the impact of interventions from the patient’s perspective [17, 18]. They often correlate poorly with objective physical outcomes or biomarkers, which emphasizes that a broad range of outcomes is needed to comprehensively capture the impact of lifestyle interventions [16]. Patients, health policy makers, and the scientific community have recognised the relevance of PROs, and their use in studies and clinical practice has increased in recent years [18,19,20]. However, the use of PROs in evaluation of lifestyle interventions has not been systematically evaluated and quantified yet.

The aim of this study is to systematically review the use of PROs and their patients-reported outcome measures (PROMs) in the evaluation of lifestyle interventions aiming at the promotion of healthy diet and physical activity for patients with SMI. We will furthermore quantify the effects of lifestyle interventions for SMI on three important PROs, which are quality of life, depression and anxiety.


Search strategy and selection criteria

This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [21] and it followed a beforehand published study protocol (PROSPERO registration number: CRD42020212135) [22]. Two researchers (LP and MA) developed and executed the search strategy with support of a mental health information specialist. The search was conducted in the databases PubMed/Medline, Embase, PsycINFO, CINAHL, and Web of Science from inception to 12 Nov 2020. We performed the search using search terms such as (“SMI” OR “severe mental illness*” OR “severe mental disorder*” OR “serious mental illness*” OR “serious mental disorder*”) AND (“life style” OR “health promotion” OR “physical fitness” OR “exercise” OR “healthy diet”) AND (“patient reported outcome measures” OR “prom”) AND “randomized controlled trial”). The full search string is shown in the Supplementary Material (Table S1). To identify any additional relevant studies, we systematically screened reference lists of key systematic reviews that were retrieved from the search string that was originally used as an orientation on currently available reviews on the topic.

We included randomised controlled trials (RCTs) only. Studies of all languages and publication dates were considered. We used the following four main domains of inclusion criteria to assess eligibility of the studies.


We included studies that included patients with SMI, using the definition of SMI by Delespaul and the consensus group SMI [23],stating that a psychiatric disorder can be defined as severe when the illness (1) requires coordinated treatment of health professionals; (2) is accompanied by serious limitations in social functioning; (3) is of chronic nature (structural or long-term, at least a few years) and not in symptomatic or functional remission; and (4) where the limitations are cause and consequence of the disorder [23]. Using these criteria, we included studies focusing on schizophrenia spectrum disorders or other psychotic disorders, bipolar disorder, severe personality disorder, or depressive disorder when chronicity was indicated. Studies with anxiety disorders, substance use disorders, eating disorders, or dementia as primary diagnosis were excluded.


The included studies investigated lifestyle interventions focussing primarily on promoting physical activity, dietary changes, or a combination of both. We focussed on non-pharmacological interventions promoting weight loss, weight management, healthy diet, decrease of sedentary behaviour, or increase of physical activity.

Control condition

Studies with nonactive or minimally active control conditions were considered eligible (e.g. treatment as usual or waitlist control group).


We were interested in patient-reported outcomes (PROs), defined as ‘any report of the status of a patient’s health condition that comes directly from the patient without interpretation of the patient’s response by a clinician or anyone else’ [15], captured by self-report questionnaires, diaries, or other data collection tools [16].

Data collection and analysis

Study selection

In the first round of selection, titles and abstracts were screened for eligibility using the Rayyan screening tool [24]. Literature was screened on the basis of our inclusion and exclusion criteria by the first author (LP). At the start, two other researchers (MA and BvM) independently screened a smaller sample of each 5% of all records (n = 1.145). Selection criteria were defined in greater detail which ultimately led to consensus. Additionally, a selection of articles that were cases of doubt (n = 160) and were screened by only one researcher (LP) in the first round. These underwent a second screening by two researchers for a definite decision (LP and MA). Disagreements in inclusion and exclusion were resolved by discussion. Disagreements or uncertainties were discussed with the senior researcher (BvM).

In the second round of screening, each full-text article was screened independently by two researchers (LP and JK). Disagreements were resolved by discussion or decision by a third and fourth researcher (MA and BvM). An overview of the study selection process can be found in the PRISMA flow diagram (Fig. 1).

Fig. 1
figure 1

PRISMA flow diagram of study search and selection

Data extraction

The process of data extraction was carried out by two persons independently (LP and JK). The data was extracted using a standardised data extraction file which was developed beforehand. The following items were extracted for description of study characteristics: first author, year of publication, country, setting and diagnosis, sample size, mean age, intervention (intervention aim, focus, format, components, duration, and delivery), control group, follow-up moments and PROM questionnaires. Additionally, data for quality assessment and meta-analysis was extracted, and risk of bias assessment was done by two independent researchers (JK and LP). Discrepancies were once again resolved by discussion.

Risk of bias assessment

The Cochrane Risk of Bias Tool 2.0 was used to assess the methodological limitations of the included studies [25]. Risk of bias assessment was performed independently by two researchers (LP and JK). The following domains were assessed: (1a) the randomisation process; (1b) identification or recruitment of participants into clusters; (2) deviations from intended interventions; (3) missing outcome data; (4) measurement of the outcome; and (5) selection of the reported result [25]. The risk of bias for each domain was scored as either low, high, or with some concern, and an overall judgement for each study was made. In addition, we made a distinction between high-risk studies and ‘lower-risk’ studies. The fourth domain was removed for this purpose, as it was expected to score as ‘high risk’ in any case because of the inability of blinding in lifestyle intervention trials. Studies were labelled ‘lower risk of bias’ when at least three of the remaining domains scored low risk and none of the domains scored high risk.

Quality assessment

The general quality of the evidence was assessed (LP) using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE). Five GRADE domains were assessed: (1) risk of bias, (2) imprecision, (3) indirectness, (4) heterogeneity, and (5) publication bias. Possible ratings for each meta-analysis were either high, moderate, low, or very low, representing the strength of the evidence [26].

Outcome measures

The outcomes of interest were PROs [15]. The conceptual model of Wilson & Cleary was used to provide the theoretical framework [27]. The model divides outcomes into five categories: biological and physiological variables, symptom status, functional status, general health perceptions, and overall QoL. We considered the model while analysing the concepts of the different PROs and in deciding which ones should be pooled in the meta-analysis. For the meta-analysis, we chose the most frequently used PROMs that measured the health status of a patient rather than health behaviour, as we considered those as most relevant and meaningful for patients. Based on these criteria, quality of life, depression severity, and anxiety severity were considered the most important outcomes.

Data synthesis and statistical analysis

For the meta-analyses, we used widely accepted PROMs. The decisions on which PROMs were similar enough to be pooled in meta-analysis was made based on the underlying construct and items of each PROM [16]. We used the means, standard deviations, and sample size of each intervention and control group, or alternatively the p-values and sample sizes to calculate the effect size. When more than one outcome of the same construct was reported in one study, we performed a sensitivity analysis, pooling an effect size for the lowest effect sizes, the highest effect sizes, and all effects combined. Studies were considered outliers if their 95% confidence interval (CI) lied outside of the 95% CI of the pooled effect. Meta-analysis was conducted for the outcomes quality of life, depression, and anxiety. The Comprehensive Meta-analysis software (Version 3.3.070) was used to calculate the Hedges’ g statistic with 95% confidence intervals (CI) using the random effects model ( In this context, a Hedges’ g of 0.2 would be considered as minor, 0.5 as moderate, and 0.8 as a major effect [28].

Heterogeneity was assessed using the I2-statistic, with scores of < 25%, 25-­50 and > 50%, indicating low, moderate, and high heterogeneity, respectively [29]. We examined the heterogeneity and differences in effect sizes of specific groups by executing subgroup analyses and exploratory analyses using the mixed-effects analysis. Publication bias was assessed graphically by inspecting funnel plots and statistically by utilizing Egger’s regression tests [29].


Study selection

After removal of duplicates, a total of 11.267 records were obtained from the databases. By applying the predefined eligibility criteria, we selected 66 records for full-text screening. Thirty articles failed to meet the inclusion criteria and were subsequently excluded. We included 36 studies meeting the inclusion criteria. Twenty-one studies were included in the meta-analyses. Fourteen studies could not be pooled, as they included PROMs that were not reported frequently enough (e.g. self-esteem or loneliness), or only included PROMs focussing on health behaviour (e.g. registration of dietary behaviour or physical activity). One study did not provide sufficient data for the analysis of quality of life in terms of missing sample size per condition and effect size data [30]. Details on the study selection process can be found in Fig. 1.

Study characteristics

Table 1 shows a summary of the key characteristics of all 36 included RCTs. We included studies from 15 different countries of which 47% European (n = 17) [30, 35,36,37, 39, 42,43,44, 47,48,49, 51, 53, 54, 56, 61, 62], 31% North American (n = 11) [33, 34, 38, 40, 45, 52, 55, 57, 60, 63, 65], 8% Asian (n = 3) [46, 50, 58], 8% Australian (n = 3) [32, 41, 64], and 6% South American origin (n = 2) [31, 59]. At baseline, a total of 5.907 participants were enrolled across studies. The studies were published from 2005 until 2020 and 56% (n = 20) were published during the past 5 years. The studies had a sample size ranging from 13 to 814 participants (mean/median = 164/101). The mean age of the participants ranged from 31 to 60 years. The percentage of male participants ranged from 14 to 100% (mean/median = 56/52). The main primary diagnoses were schizophrenia spectrum disorders or psychotic disorders in 86% of the included trials (n = 32). Other primary diagnoses were bipolar disorder (n = 2) and major depressive disorder (n = 2). Participants were recruited from outpatient settings in 86% of all trials (n = 31), in some trials from inpatient clinics (n = 4), or a combination of both (n = 1).

Table 1 List of all included studies – Study characteristics


Of all 36 included studies, 78% (n = 28) focused on lifestyle interventions incorporating both physical activity and eating behaviour [30, 31, 33, 34, 36,37,38,39,40,41,42,43, 47, 48, 50, 51, 53, 55, 57, 60,61,62,63,64,65], some considering additional risk behaviours such as smoking or substance use [32, 44]. Seven trials (19%) focused only on exercise interventions [35, 46, 49, 52, 56, 58, 59] and one trial only on a dietary intervention [54]. The most common intervention goals were weight management or weight loss, cardiometabolic improvements, and general health promotion. The majority of interventions included psychoeducation, motivational interviewing, and cognitive behavioural strategies such as self-monitoring, goal setting, problem solving, cognitive restructuring, and skills training. Twenty interventions (56%) were group-based [30,31,32, 35,36,37,38, 42, 43, 46, 49, 50, 52,53,54,55, 58,59,60, 64], nine (25%) were a combination of both individual and group elements [40, 44, 45, 47, 51, 56, 57, 62, 65], and seven (19%) were individually targeted [33, 34, 39, 41, 48, 61, 63]. Duration of the interventions ranged from 5 weeks to 12 months, with an average of 26 weeks. All control conditions were nonactive or minimally active.

Patient reported outcomes and measures

In the included trials, we found 69 different PROMs. Overall, the most frequently evaluated PROs were (health-related) quality of life, health behaviours, and symptom status. The most frequently used PROMs for QoL were the MOS Short Form Health Surveys SF-36 and the SF-12 [66, 67]. The two most commonly reported health behaviours were physical activity, measured most often with the International Physical Activity Scale (IPAQ) and dietary behaviour measured with food frequency questionnaires, such as the Dietary Instrument for Nutrition Education questionnaire (DINE) [68, 69]. The two most commonly assessed symptoms were depression and anxiety, measured with a variety of PROMs including the Beck Depression Inventory (BDI) and the Symptom Checklist 90 (SCL-90-R) [70, 71]. There was evidence of appropriate psychometric properties of 52% of all PROMs (n = 36). Details can be found in the Supplementary Material (Table S2). However, the validity and reliability of 17% of PROMs remained questionable (n = 12). This was mostly true for self-reported measures of physical activity and dietary behaviour.

Risk of bias

According to the Cochrane risk of bias tool, 35 of the 36 trials were with high risk of bias, and one trial raised some concerns [36] (Fig. 2). Reason for this high risk of bias was the unavoidable lack of blinding of participants and personnel due to the nature of the interventions. When removing that particular domain, 7 of the 36 studies scored a ‘lower risk’ of bias (19%) [32, 34, 44, 47, 48, 53, 62]. The randomisation procedure scored a low risk of bias in 39% of trials (n = 14) [32, 34, 37, 44, 47,48,49, 52, 53, 58, 61, 62, 64, 65]. Few studies (n = 11) described allocation concealment [32, 39, 44, 47,48,49, 52, 58, 62, 64, 65]. Furthermore, 36% of all trials (n = 13) seem to have used an appropriate statistical analysis (intention-to-treat without last observation carried forward method) [33, 34, 38, 40, 43,44,45,46,47,48, 51, 53, 62]. Detailed scores can be found in the Supplementary Material (Fig. S1).

Fig. 2
figure 2

Cochrane risk of bias assessment 2.0

Results of the meta-analyses

We included a total of 21 studies for meta-analysis, some of which included outcomes of more than one analysis. Outcomes of all meta-analyses can be found in Table 2 and forest plots in Fig. 3.

Table 2 Meta-analysis and subgroup analysis of the effects of lifestyle interventions for SMI on quality of life, severity of depression and severity of anxiety compared to the control condition
Fig. 3
figure 3

Forest plots of quality of life, depression severity and anxiety severity

Effects on quality of life

This meta-analysis is based on 19 studies (n = 3.129 participants) that evaluated the effect of lifestyle interventions on QoL in patients with SMI. We performed the main analysis calculating combined effect sizes for studies that used more than one outcome measure for QoL. The pooled effect size for quality of life is Hedges’ g = 0.13 (95% CI = − 0.02 to 0.27), with a corresponding p-value of 0.09, showing no significant increase in QoL in in the intervention groups.

We analysed how the effects would change based on the selection of outcomes with the lower or higher effect size for studies using more than one PROM for QoL. The analysis combining the lowest effect sizes indicated no effect (g = 0.1; 95% CI = − 0.05 to 0.24). In contrast, the analysis combining the highest effect sizes indicated a small and statistically significant effect (g = 0.18; 95% CI = 0.02 to 0.33; p = 0.03).

There was high heterogeneity among QoL studies (Q = 57.6, df = 18, p = 0.00). The null hypothesis of all studies sharing the same common effect size, can be rejected. The I2-statistic is 68.7% (95% CI = 46 to 79), meaning that more than half of the variance in the observed effect reflects the variance of true effects.

Effects on depression severity

For the severity of depression, the meta-analysis was based on nine studies (n = 790 participants). We found a small significant effect on depression severity with a pooled effect size of g = 0.29 (95% CI = 0.00 to 0.58, p = 0.047). Heterogeneity appeared to be high among studies evaluating depression severity (Q = 23.0, df = 8, p = 0.003), with an I2 of 65.2% (95% CI = 8 to 81). We did not perform any subgroup analyses on this outcome as the number of studies was too low, yielding a low power of those analyses.

Effects on anxiety severity

The meta-analysis on the effects of lifestyle interventions on the severity of anxiety summarized four studies (n = 121 participants). We calculated a pooled effect size of g = 0.56 (95% CI = 0.16 to 0.95), indicating a moderate and statistically significant effect (p = 0.006). The I2-statistic was 0% (95% CI = 0 to 68).

Subgroup analysis

For the outcome QoL, five subgroup analyses were performed on the following variables: study region, duration of the intervention, type of intervention, attendance and risk of bias. For the variable attendance, we defined a cut-off value of above 60% for high attendance. For risk of bias, we used the same four domains as for identifying the ‘lower risk’ studies. Risk of bias was significantly associated with the effect size (p = 0.01). Studies with a higher risk of bias seemed to show larger effect sizes than those with a lower risk of bias (g = 0.27 compared to − 0.06). Furthermore, higher attendance was significantly associated with higher effect sizes (p = 0.01), showing an effect size of g = 0.46 in the high attendance group compared to − 0.02 in the low attendance group. Studies from the Asian/ Pacific area tended to have a higher effect size compared to other regions (g = 0.23; compared to Europe g = 0.12, North America g = 0.07, and South America g = 0.1). Asian studies overlapped to some extend with the ‘higher risk’ of bias studies. Interventions with longer duration (9-12 months) tended to have a lower pooled effect size (g = − 0.05, compared to 1-3 months, g = 0.2, and 4-8 months g = 0.37). In the exploratory analysis we found that interventions including mainly structured high intensity physical activity had a large pooled effect size (g = 0.92).

Publication bias

The funnel plot of quality of life indicated some of publication bias and Egger’s test of publication bias was significant (p = 0.0004). Smaller studies showed more positive results. When imputing missing studies with the trim and fill procedure of Duval and Tweedie, the adjusted effect size was g = − 0.05 (95% CI = − 0.12 to 0.017). Funnel plots for depression and anxiety showed no indication for publication bias (Supplementary Material, Fig. S2).


The GRADE assessment shows an overall very low quality of the evidence, caused by the high risk of bias, unexplained heterogeneity, and indirectness due to time differences in outcomes (Supplementary Material, Table S3).

Impact on other patient-reported outcomes

Results for all remaining assessed PRO’s not included in meta-analysis due to the varying outcome concepts and measures showed varying results, overall in favour of lifestyle interventions. An overview of the PRO’s and findings can be found in the descriptive Table 1 and in the Supplementary Material (S2).

Sixteen studies investigated the effects on physical activity [31,32,33,34, 36, 37, 39, 41, 42, 44, 45, 48, 53, 55, 58, 61, 63]. Eight of these studies reported improvements in physical activity in the intervention groups in terms of increased minutes of weekly exercise, higher vigorous activity score, and decreased time spent sitting [33, 34, 37, 39, 41, 42, 53, 55].

Sixteen studies evaluated dietary behaviour [31,32,33,34, 36, 37, 39, 44, 45, 47, 48, 50, 53,54,55, 61]. Three studies found significant improvements in the reduction of fat consumption [55], short-term increase of fruit and vegetable consumption [54], and adherence to the Mediterranean diet [36]. Three other studies found significant changes in readiness to change dietary behaviour in favour of the intervention [33, 34, 51].

Eight studies examined smoking behaviour [31, 32, 39, 42, 44, 47, 48, 61] and three studies used PROMs for substance use and alcohol abuse [32, 39, 44]. Neither smoking, alcohol, or substance use were significantly improved by the interventions, except one study in which both groups reduced cigarette consumption [32]. Readiness and motivation to quit smoking or to change health behaviour was assessed by some studies [32, 40, 51], with no significant improvements.

Several studies examined different aspects of perceived mental health [46, 52, 57, 61]. Illness perception and self-appraisal toward illness was assessed and not found improved by two studies [40, 47]. Perceived general health status was assessed by four studies [39, 41, 48, 61], one study showing improvement [41]. Body image and self-esteem were evaluated in four studies [31, 41, 58, 65]. Body image was significantly improved in two of these studies [41, 65]. Weight-related self-esteem was improved in another study [57]. Self-efficacy was measured and found significantly improved in three studies [55, 60, 65]. Sleep quality was found significantly improved in one study [36]. Several studies assessed different aspects of functioning, such as emotional functioning, daily functioning, and independent living skills [31, 43, 46]. One study showed improvements in daily functioning in favour of the intervention group and another in sense of coherence [43, 46].


In this systematic review and meta-analysis, we examined the use of PROs and PROMs in lifestyle intervention trials for people with SMI. We analysed the effect of three PROs that were used in lifestyle intervention trials for people with SMI, namely quality of life, depression and anxiety. We identified 36 studies of which 21 were used for meta-analysis. The most commonly evaluated PROs were quality of life, health behaviours, and symptom status, often reported as secondary or exploratory outcomes. The included studies showed a large variety of different PROMs. The quality the studies was overall low, only seven of the 36 studies had a lower risk of bias.

The meta-analysis showed a very small effect of lifestyle interventions on QoL with an effect size of 0.13, which was not statistically significant (95% CI = − 0.02 to 0.27, p = 0.09). The prediction interval for QoL was − 0.41 to 0.66, meaning that the true effect of lifestyle interventions on QoL could be beneficial in some populations and unfavourable in others. In our subgroup analysis were not able to distinguish which patients benefit most from lifestyle interventions, as patient characteristics were too homogeneous. In this respect, also the nature of the lifestyle intervention should be taken into consideration, with the central question which requirements these interventions must meet. The rewarding element for the patient seems to be of great importance. We identified two outlier studies in the meta-analysis of QoL outcomes [35, 49]. Those studies had very large effect sizes, with a Hedges’ g = 2.32 (95% CI = 1.15 to 3.49), and g = 1.38 (95% CI = 0.61 to 2.51), respectively. Interestingly, those studies used highly social exercise interventions, i.e. soccer practice and Greek traditional dancing. Attendance in these studies was very high. Including these kinds of interactive and social activities in lifestyle interventions could help patients to stay motivated and could increase compliance with, and thus the success of lifestyle interventions. Exploratory analysis revealed high effects for interventions mainly consisting of structured high intensity PA. Although the two outlier studies contributed to this high effect size, the remaining studies likewise showed large effects.

Lifestyle interventions might have the potential to improve mental health outcomes. There were indications of reduction of symptoms of depression and anxiety. The overall effects of lifestyle interventions were small for depression (g = 0.29, 95% CI = 0.00 to 0.58, p = 0.047) and moderate for anxiety (g = 0.56, 95% CI = 0.16 to 0.95, p = 0.006). These effect sizes imply a clinically relevant effect [72]. These findings should be confirmed with larger samples. It is also important to note that due to the focus of our review, our findings cannot be generalized to other types of lifestyle interventions, such as smoking cessation or sleep interventions.

Overall, the findings of our meta-analysis are consistent with other systematic reviews. The effect on QoL is similar to the one found in a recent systematic review by Speyer et al., who estimated a nonsignificant SMD of 0.03 (95% CI = − 0.11 to 0.17) in a sample of 15 trials [12]. Our finding on depression severity is in line with a systematic review by Bruins et al. [73]. They found an SMD of − 0.95 (95% CI − 1.90 to − 0.00, p = 0.05) reduction on depressive symptoms, which exceeds the effect size that we found. However, Bruins et al. based their results on less studies (n = 4). Our findings on depression and anxiety are not reflected in the current meta-review of Firth et al. (2020). Although exercise and healthy diet are protective lifestyle factors for developing depression and anxiety, they do not find significant effects of exercise interventions on depression and anxiety symptoms in persons with schizophrenia [74]. This highlights the issue of implementation errors that could be a possible explanation for the lack of effects. For all kinds of reasons, on the level of the patient or care providers, within the patient-caregiver relationship, or due to team factors, preconditions (e.g. financial or personnel), and other factors, implementation may be less successful, which influences the effectiveness of a lifestyle intervention.

There were considerable differences between the studies in terms of study objectives, methodology, intervention duration, intervention format, and content. This increased the heterogeneity between studies and made it challenging to compare them. We tried to find sources of heterogeneity by analysing different subgroups. Of all subgroup analyses, risk of bias and attendance were significantly associated with the effect sizes. High quality studies led to lower effect sizes, which is also seen in the review of Bruins et al. [73]. This implies that low quality studies tend to overestimate the effects. Our subgroup analysis on attendance showed that studies with higher attendance had significantly higher effects on QoL. A positive correlation of adherence and treatment success was also found in another review [75]. This highlights the importance of patient compliance to maximise treatment effects. Interventions with shorter duration tended to have higher efficacy, which was contrary to our expectations. Speyer et al. and Vancampfort et al. found that studies with an individual approach yield higher effects on weight outcomes [12, 13]. In contrast, other reviews state that group interventions would be more effective and highlight the importance of peer support for motivation [73, 76, 77]. Our own analysis showed a tendency of larger benefits of group settings on QoL. We observed a trend of studies from the Asian region showing larger effect sizes, which is consistent with other systematic reviews [12, 73]. This should be interpreted with caution, as these studies tended to have higher risk of bias. Another possible explanation could be the stricter adherence to interventions in the Asian culture.

Strengths and limitations

Our systematic review had several strengths. To the best of our knowledge, this paper is the first systematic review and meta-analysis focussing entirely on the evaluation of PROs among lifestyle interventions in patients with SMI. Secondly, we published a predefined study protocol in the beginning of the study period. Thirdly, we conducted a comprehensive and extensive literature search with the support of an expert information specialist, in which no restrictions in terms of language or publication date were applied. However, our search strategy could have included more diet-related search terms. Fourthly, we included only RCTs as these represent the best quality of evidence. On the other hand, despite the inclusion of RCTs only, almost all trials were of a high risk of bias which together with a range of other factors contributed to an overall very low quality of the evidence. Besides that, the lack of power in the meta-analyses of the severity of depression and anxiety weakened the confidence in these results. Study selection was in large parts performed by a single searcher. We tried to limit the possible bias arising the selection procedure by double-screening a sample of 10% of the articles, and by discussing articles of doubt with two or more researchers. Furthermore, we cannot exclude the possibility of missing studies as we excluded non-randomized trials and included published studies only. Unpublished studies could have contributed to a smaller effect, which we tried to simulate in the adjustment of meta-analysis results for QoL by imputing the missing studies. We furthermore cannot exclude the possibility of missing studies in our search, because PROMs are often reported as secondary outcomes or supplementary material. This complicates tracing down these studies in the first phase of study selection while inspecting titles and abstracts. This error could only have been prevented by retrieving the method sections and supplementary materials of eligible studies during the first screening phase. However, we did not believe that this would have been a workable option due to the large number of studies we retrieved.

Implications for research and clinical practice

Even though lifestyle interventions have modest effects on physical health parameters, there could be other possible benefits that can be captured with PROMs. Despite the value of biomedical outcomes, future trials should involve the patient’s perspective and therefore include PROs to investigate the benefits of lifestyle interventions for SMI in a variety of health concepts. This is particularly critical in mental health research, which often involves outcomes that are difficult or not observable in an objective manner. Researchers should consider PROMs that are matching the aim of their intervention and should choose one measure for every concept that they expect to be influenced by the intervention. The PROM should ideally be valid, reliable, and sensitive to change. Additionally, for the SMI population, the questionnaires should be brief measures that are easy to administer. Self-reported instruments for dietary and exercise tend to be rather inaccurate [78,79,80]. However, they can still be useful to categorise patients into certain groups and to create awareness of the patient’s health behaviour.

For the clinical setting, the use of more flexible instruments would be advantageous. The National Institutes of Health started the Patient-reported Outcomes Measurement Information system (PROMIS) initiative in order to develop an assessment system for PROs and large item bank which can be used for computerized adaptive testing [81]. This method was shown to provide flexible, efficient, and precise measurements of depression in Dutch patients [82]. Given the promising results, the PROMIS system has the potential to facilitate clinical practice and research in the assessment of PROs.


The current systematic review and meta-analysis informs mental health professionals on the use of PROs and PROMs in the evaluation of lifestyle intervention trials, and on the effects of lifestyle interventions in patients with SMI on quality of life, depression and anxiety. Despite small and clinically non-significant effects on physical health parameters, lifestyle interventions can however positively affect PROs such as depression and anxiety symptoms, making them more relevant for clinical practice. Comprehensive knowledge of both the clinical and patient-reported outcomes of these programs is necessary in order to choose appropriate treatment for the SMI patient group.

Availability of data and materials

All data generated or analysed during this study are included in this published article [and its supplementary information files] and the original studies’ publications.



Severe mental illness


Body Mass Index


Quality of life


Patient-reported outcome


Patient-reported outcome measure


Preferred Reporting Items for Systematic Reviews and Meta-Analyses


Randomised controlled trial


Grading of Recommendations Assessment, Development, and Evaluation


Standardized mean difference


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The authors wish to thank Ms. Caroline Planting for her contribution and support in the database search, which was highly appreciated.


This systematic review and meta-analysis was funded by a grant of the Netherlands Organization for Health Research and Development (ZonMw); grant number 80–84300–98-72012. The funder had no control over any methodological aspect of the study nor did they have any input on the conduct, data collection, analysis interpretation or publication of the study results.

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MA, BvM and LP set up the study protocol and performed the study selection. MA and LP collaborated with Caroline Planting to conduct the literature search. LP and JK performed the data extraction and assessed the risk of bias. AvS provided expertise in meta-analysis, LP performed the statistical analysis under support of AvS. The manuscript was written by LP, revised by MA, BvM and AvS, and the final version was approved by all authors.

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Correspondence to Laura M. Pape.

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Supplementary Information

Additional file 1: Supplementary Table S1.

Full search string PubMed/Medline . Supplementary Table S2. List of PROMs in the included studies. Supplementary Figure S1. Cochrane risk of bias assessment (detailed). Supplementary Figure S2. Publication bias. Supplementary Table S3. GRADE summary of evidence.

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Pape, L.M., Adriaanse, M.C., Kol, J. et al. Patient-reported outcomes of lifestyle interventions in patients with severe mental illness: a systematic review and meta-analysis. BMC Psychiatry 22, 261 (2022).

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  • Severe mental illness
  • Lifestyle intervention
  • Patient-reported outcome
  • Systematic review, Meta-analysis