Patient-reported outcomes of lifestyle interventions in patients with severe mental illness: a systematic review and meta-analysis
BMC Psychiatry volume 22, Article number: 261 (2022)
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.
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 . 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 , few show significant effects . 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 . 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’ . They are mostly self-report questionnaires but can also be acquired through interviews, diaries, or other tools . 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 . 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  and it followed a beforehand published study protocol (PROSPERO registration number: CRD42020212135) . 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 ,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 . 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.
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’ , captured by self-report questionnaires, diaries, or other data collection tools .
Data collection and analysis
In the first round of selection, titles and abstracts were screened for eligibility using the Rayyan screening tool . 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).
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 . 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 . 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.
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 .
The outcomes of interest were PROs . The conceptual model of Wilson & Cleary was used to provide the theoretical framework . 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 . 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 (www.meta-analysis.com). 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 .
Heterogeneity was assessed using the I2-statistic, with scores of < 25%, 25-50 and > 50%, indicating low, moderate, and high heterogeneity, respectively . 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 .
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 . Details on the study selection process can be found in Fig. 1.
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).
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 . 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  (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).
Results of the meta-analyses
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).
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).
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 , short-term increase of fruit and vegetable consumption , and adherence to the Mediterranean diet . 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 . 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 . 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 . Self-efficacy was measured and found significantly improved in three studies [55, 60, 65]. Sleep quality was found significantly improved in one study . 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 . 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 . Our finding on depression severity is in line with a systematic review by Bruins et al. . 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 . 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. . 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 . 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 . This method was shown to provide flexible, efficient, and precise measurements of depression in Dutch patients . 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 measure
Preferred Reporting Items for Systematic Reviews and Meta-Analyses
Randomised controlled trial
Grading of Recommendations Assessment, Development, and Evaluation
Standardized mean difference
Correll CU, Solmi M, Veronese N, Bortolato B, Rosson S, Santonastaso P, et al. Prevalence, incidence and mortality from cardiovascular disease in patients with pooled and specific severe mental illness: a large-scale meta-analysis of 3,211,768 patients and 113,383,368 controls. World Psychiatry. 2017;16(2):163–80.
Laursen TM. Life expectancy among persons with schizophrenia or bipolar affective disorder. Schizophr Res. 2011;131(1-3):101–4.
Walker ER, McGee RE, Druss BG. Mortality in mental disorders and global disease burden implications. JAMA Psychiatry. 2015;72(4):334.
De Hert M, Correll CU, Bobes J, Cetkovich-Bakmas M, Cohen D, Asai I, et al. Physical illness in patients with severe mental disorders. I. Prevalence, impact of medications and disparities in health care. World Psychiatry. 2011;10(1):52–77.
Vancampfort D, Stubbs B, Mitchell AJ, De Hert M, Wampers M, Ward PB, et al. Risk of metabolic syndrome and its components in people with schizophrenia and related psychotic disorders, bipolar disorder and major depressive disorder: a systematic review and meta-analysis. World Psychiatry. 2015;14(3):339–47.
Firth J, Siddiqi N, Koyanagi A, Siskind D, Rosenbaum S, Galletly C, et al. The lancet psychiatry commission: a blueprint for protecting physical health in people with mental illness. Lancet Psychiatry. 2019;6(8):675–712.
Olfson M, Gerhard T, Huang C, Crystal S, Stroup TS. Premature mortality among adults with schizophrenia in the United States. JAMA Psychiatry. 2015;72(12):1172–81.
Vancampfort D, Firth J, Schuch FB, Rosenbaum S, Mugisha J, Hallgren M, et al. Sedentary behavior and physical activity levels in people with schizophrenia, bipolar disorder and major depressive disorder: a global systematic review and meta-analysis. World Psychiatry. 2017;16(3):308–15.
Liu NH, Daumit GL, Dua T, Aquila R, Charlson F, Cuijpers P, et al. Excess mortality in persons with severe mental disorders: a multilevel intervention framework and priorities for clinical practice, policy and research agendas. World Psychiatry. 2017;16(1):30–40.
Teasdale SB, Ward PB, Samaras K, Firth J, Stubbs B, Tripodi E, et al. Dietary intake of people with severe mental illness: systematic review and meta-analysis. Br J Psychiatry. 2019;214(5):251–9.
Richardson S, McNeill A, Brose LS. Smoking and quitting behaviours by mental health conditions in Great Britain (1993-2014). Addict Behav. 2019;90:14–9.
Speyer H, Jakobsen AS, Westergaard C, Nørgaard HCB, Jørgensen KB, Pisinger C, et al. Lifestyle interventions for weight Management in People with serious mental illness: a systematic review with Meta-analysis, trial sequential analysis, and Meta-regression analysis exploring the mediators and moderators of treatment effects. Psychother Psychosom. 2019;88(6):350–62.
Vancampfort D, Firth J, Correll CU, Solmi M, Siskind D, De Hert M, et al. The impact of pharmacological and non-pharmacological interventions to improve physical health outcomes in people with schizophrenia: a meta-review of meta-analyses of randomized controlled trials. World Psychiatry. 2019;18(1):53–66.
Naslund JA, Whiteman KL, McHugo GJ, Aschbrenner KA, Marsch LA, Bartels SJ. Lifestyle interventions for weight loss among overweight and obese adults with serious mental illness: a systematic review and meta-analysis. Gen Hosp Psychiatry. 2017;47:83–102.
(FDA) USFaDA. Guidance for industry. Patient-reported outcome measures: use in medical product development to support labeling claim. Silver Spring: US Food and Drug Administration; 2009.
Johnston BC, Patrick DL, Busse JW, Schünemann HJ, Agarwal A, Guyatt GH. Patient-reported outcomes in meta-analyses – part 1: assessing risk of bias and combining outcomes. Health Qual Life Outcomes. 2013;11(1):109.
Mercieca-Bebber R, King MT, Calvert MJ, Stockler MR, Friedlander M. The importance of patient-reported outcomes in clinical trials and strategies for future optimization. Patient Relat Outcome Meas. 2018;9:353–67.
McCabe R, Saidi M, Priebe S. Patient-reported outcomes in schizophrenia. Br J Psychiatry. 2007;191(S50):s21–s8.
Calvert M, Kyte D, Mercieca-Bebber R, Slade A, Chan A-W, King MT, et al. Guidelines for inclusion of patient-reported outcomes in clinical trial protocols: The SPIRIT-PRO extension. JAMA. 2018;319(5):483–94.
Rivera SC, Kyte DG, Aiyegbusi OL, Slade AL, McMullan C, Calvert MJ. The impact of patient-reported outcome (PRO) data from clinical trials: a systematic review and critical analysis. Health Qual Life Outcomes. 2019;17(1):156.
Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372:n71.
Pape LM, Adriaanse MC, Van Meijel B. Patient-reported outcomes among lifestyle interventions in patients with serious mental illness: a systematic review. PROSPERO 2020 CRD42020212135 Available from: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020212135.
Delespaul PH. Consensus over de definitie van mensen met een ernstige psychische aandoening (EPA) en Hun aantal in Nederland. [consensus on the definition of people with severe mental illness (EPA) and their number in the Netherlands.]. Tijdschr Psychiatr. 2013;55(6):427–38.
Ouzzani M, Hammady H, Fedorowicz Z, Elmagarmid A. Rayyan—a web and mobile app for systematic reviews. Syst Rev. 2016;5(1):210.
Higgins JPT, Savović J, Page MJ, Elbers RG, Sterne JAC. Chapter 8: assessing risk of bias in a randomized trial. In: Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA, editors. Cochrane Handbook for Systematic Reviews of Interventions version 6.1 (updated September 2020). Cochrane; 2020. Available from www.training.cochrane.org/handbook.
Guyatt GH, Oxman AD, Vist GE, Kunz R, Falck-Ytter Y, Alonso-Coello P, et al. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ. 2008;336(7650):924–6.
Wilson I, Cleary P. Linking clinical variables with health-related quality of life: a conceptual model of patient outcomes. JAMA. 1995;273:59–65.
Cohen J. Statistical power analysis for the behavioral sciences. Hillsdale: L. Erlbaum Associates; 1988.
Cuijpers P. Meta-analyses in mental health research: A practical guide; 2016.
Mauri M, Simoncini M, Castrogiovanni S, Iovieno N, Cecconi D, Dell'Agnello G, et al. A psychoeducational program for weight loss in patients who have experienced weight gain during antipsychotic treatment with olanzapine. Pharmacopsychiatry. 2008;41(1):17–23.
Attux C, Martini LC, Elkis H, Tamai S, Freirias A, Camargo M, et al. A 6-month randomized controlled trial to test the efficacy of a lifestyle intervention for weight gain management in schizophrenia. BMC Psychiatry. 2013;13:60.
Baker AL, Richmond R, Kay-Lambkin FJ, Filia SL, Castle D, Williams JM, et al. Randomized controlled trial of a healthy lifestyle intervention among smokers with psychotic disorders. Nicotine Tob Res. 2015;17(8):946–54.
Bartels SJ, Pratt SI, Aschbrenner KA, Barre LK, Jue K, Wolfe RS, et al. Clinically significant improved fitness and weight loss among overweight persons with serious mental illness. Psychiatr Serv. 2013;64(8):729–36.
Bartels SJ, Pratt SI, Aschbrenner KA, Barre LK, Naslund JA, Wolfe R, et al. Pragmatic replication trial of health promotion coaching for obesity in serious mental illness and maintenance of outcomes. Am J Psychiatry. 2015;172(4):344–52.
Battaglia G, Alesi M, Inguglia M, Roccella M, Caramazza G, Bellafiore M, et al. Soccer practice as an add-on treatment in the management of individuals with a diagnosis of schizophrenia. Neuropsychiatr Dis Treat. 2013;9:595–603.
Bersani FS, Biondi M, Coviello M, Fagiolini A, Majorana M, Minichino A, et al. Psychoeducational intervention focused on healthy living improves psychopathological severity and lifestyle quality in psychiatric patients: preliminary findings from a controlled study. J Ment Health. 2017;26(3):271–5.
Bonfioli E, Mazzi MA, Berti L, Burti L. Physical health promotion in patients with functional psychoses receiving community psychiatric services: results of the PHYSICO-DSM-VR study. Schizophr Res. 2018;193:406–11.
Brar JS, Ganguli R, Pandina G, Turkoz I, Berry S, Mahmoud R. Effects of behavioral therapy on weight loss in overweight and obese patients with schizophrenia or schizoaffective disorder. J Clin Psychiatry. 2005;66(2):205–12.
Brown S, Chan K. A randomized controlled trial of a brief health promotion intervention in a population with serious mental illness. J Ment Health. 2006;15(5):543–9.
Erickson ZD, Mena SJ, Pierre JM, Blum LH, Martin E, Hellemann GS, et al. Behavioral interventions for antipsychotic medication-associated obesity: a randomized, controlled clinical trial. J Clin Psychiatry. 2016;77(2):e183–9.
Evans S, Newton R, Higgins S. Nutritional intervention to prevent weight gain in patients commenced on olanzapine: a randomized controlled trial. Aust N Z J Psychiatry. 2005;39(6):479–86.
Fernandez Guijarro S, Pomarol-Clotet E, Rubio Munoz MC, Miguel Garcia C, Egea Lopez E, Fernandez Guijarro R, et al. Effectiveness of a community-based nurse-led lifestyle-modification intervention for people with serious mental illness and metabolic syndrome. Int J Ment Health Nurs. 2019;28(6):1328–37.
Forsberg KA, Bjorkman T, man PO, lund M. Influence of a lifestyle intervention among persons with a psychiatric disability: a cluster randomised controlled trail on symptoms, quality of life and sense of coherence. J Clin Nurs. 2010;19(11):1519–28.
Gaughran F, Stahl D, Ismail K, Greenwood K, Atakan Z, Gardner-Sood P, et al. Randomised control trial of the effectiveness of an integrated psychosocial health promotion intervention aimed at improving health and reducing substance use in established psychosis (IMPaCT). BMC Psychiatry. 2017;17(1):413.
Goldberg RW, Reeves G, Tapscott S, Medoff D, Dickerson F, Goldberg AP, et al. "MOVE!" outcomes of a weight loss program modified for veterans with serious mental illness. Psychiatr Serv. 2013;64(8):737–44.
Ho RT, Fong TC, Wan AH, Au-Yeung FS, Wong CP, Ng WY, et al. A randomized controlled trial on the psychophysiological effects of physical exercise and tai-chi in patients with chronic schizophrenia. Schizophr Res. 2016;171(1):42–9.
Holt RIG, Gossage-Worrall R, Hind D, Bradburn MJ, McCrone P, Morris T, et al. Structured lifestyle education for people with schizophrenia, schizoaffective disorder and first-episode psychosis (STEPWISE): randomised controlled trial. Br J Psychiatry. 2019;214(2):63–73.
Jakobsen AS, Speyer H, Nørgaard HCB, Karlsen M, Birk M, Hjorthøj C, et al. Effect of lifestyle coaching versus care coordination versus treatment as usual in people with severe mental illness and overweight: two-years follow-up of the randomized CHANGE trial. PLoS One. 2017;12(10):e0185881.
Kaltsatou A, Kouidi E, Fountoulakis K, Sipka C, Theochari V, Kandylis D, et al. Effects of exercise training with traditional dancing on functional capacity and quality of life in patients with schizophrenia: a randomized controlled study. Clin Rehabil. 2015;29(9):882–91.
Kwon JS, Choi JS, Bahk WM, Yoon Kim C, Hyung Kim C, Chul Shin Y, et al. Weight management program for treatment-emergent weight gain in olanzapine-treated patients with schizophrenia or schizoaffective disorder: a 12-week randomized controlled clinical trial. J Clin Psychiatry. 2006;67(4):547–53.
Looijmans A, Jörg F, Bruggeman R, Schoevers RA, Corpeleijn E. Multimodal lifestyle intervention using a web-based tool to improve cardiometabolic health in patients with serious mental illness: results of a cluster randomized controlled trial (LION). BMC Psychiatry. 2019;19(1):339.
Marzolini S, Jensen B, Melville P. Feasibility and effects of a group-based resistance and aerobic exercise program for individuals with severe schizophrenia: a multidisciplinary approach. Ment Health Phys Act. 2009;2(1):29–36.
Masa-Font R, Fernández-San-Martín MI, Martín López LM, Alba Muñoz AM, Oller Canet S, Martín Royo J, et al. The effectiveness of a program of physical activity and diet to modify cardiovascular risk factors in patients with severe mental illness after 3-month follow-up: CAPiCOR randomized clinical trial. Eur Psychiatry. 2015;30(8):1028–36.
McCreadie Robin GR. Dietary improvement in people with schizophrenia: randomised controlled trial. Br J Psychiatry. 2005;187:346–51.
McKibbin CL, Patterson TL, Norman G, Patrick K, Jin H, Roesch S, et al. A lifestyle intervention for older schizophrenia patients with diabetes mellitus: a randomized controlled trial. Schizophr Res. 2006;86(1-3):36–44.
Mota-Pereira J, Silverio J, Carvalho S, Ribeiro JC, Fonte D, Ramos J. Moderate exercise improves depression parameters in treatment-resistant patients with major depressive disorder. J Psychiatr Res. 2011;45(8):1005–11.
Muralidharan A, Brown CH, Zhang Y, Niv N, Cohen AN, Kreyenbuhl J, et al. Quality of life outcomes of web-based and in-person weight management for adults with serious mental illness. J Behav Med. 2020;43(5):865–72.
Ryu J, Jung JH, Kim J, Kim CH, Lee HB, Kim DH, et al. Outdoor cycling improves clinical symptoms, cognition and objectively measured physical activity in patients with schizophrenia: a randomized controlled trial. J Psychiatr Res. 2020;120:144–53.
Silva BA, Cassilhas RC, Attux C, Cordeiro Q, Gadelha AL, Telles BA, et al. A 20-week program of resistance or concurrent exercise improves symptoms of schizophrenia: results of a blind, randomized controlled trial. Braz J Psychiatry. 2015;37(4):271–9.
Skrinar GS, Huxley NA, Hutchinson DS, Menninger E, Glew P. The role of a fitness intervention on people with serious psychiatric disabilities. Psychiatr Rehabil J. 2005;29(2):122–7.
Speyer H, Christian Brix Nørgaard H, Birk M, Karlsen M, Storch Jakobsen A, Pedersen K, et al. The CHANGE trial: no superiority of lifestyle coaching plus care coordination plus treatment as usual compared to treatment as usual alone in reducing risk of cardiovascular disease in adults with schizophrenia spectrum disorders and abdominal obesity. World Psychiatry. 2016;15(2):155–65.
Stiekema APM, Looijmans A, van der Meer L, Bruggeman R, Schoevers RA, Corpeleijn E, et al. Effects of a lifestyle intervention on psychosocial well-being of severe mentally ill residential patients: ELIPS, a cluster randomized controlled pragmatic trial. Schizophr Res. 2018;199:407–13.
Sylvia LG, Pegg SL, Dufour SC, Janos JA, Bernstein EE, Chang WC, et al. Pilot study of a lifestyle intervention for bipolar disorder: nutrition exercise wellness treatment (NEW Tx). J Affect Disord. 2019;250:278–83.
Usher K, Park T, Foster K, Buettner P. A randomized controlled trial undertaken to test a nurse-led weight management and exercise intervention designed for people with serious mental illness who take second generation antipsychotics. J Adv Nurs. 2013;69(7):1539–48.
Yarborough BJ, Leo MC, Yarborough MT, Stumbo S, Janoff SL, Perrin NA, et al. Improvement in body image, perceived health, and health-related self-efficacy among people with serious mental illness: The STRIDE study. Psychiatr Serv. 2016;67(3):296–301.
Ware JE Jr, Sherbourne CD. The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Med Care. 1992;30(6):473–83.
Ware JE, Kosinski M, Keller SD. A 12-item short-form health survey: construction of scales and preliminary tests of reliability and validity. Med Care. 1996;34(3):220–33.
Craig CL, Marshall AL, Sjöström M, Bauman AE, Booth ML, Ainsworth BE, et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003;35(8):1381–95.
Roe L, Strong C, Whiteside C, Neil A, Mant D. Dietary intervention in primary care: validity of the DINE method for diet assessment. Fam Pract. 1994;11(4):375–81.
Beck AT, Steer RA, Carbin MG. Psychometric properties of the Beck depression inventory: twenty-five years of evaluation. Clin Psychol Rev. 1988;8(1):77–100.
Schmitz N, Hartkamp N, Kiuse J, Franke GH, Reister G, Tress W. The symptom check-List-90-R (SCL-90-R): a German validation study. Qual Life Res. 2000;9(2):185–93.
Cuijpers P, Turner EH, Koole SL, Van Dijke A, Smit F. What is the threshold for a clinically relevant effect? The case of major depressive disorders. Depress Anxiety. 2014;31(5):374–8.
Bruins J, Jörg F, Bruggeman R, Slooff C, Corpeleijn E, Pijnenborg M. The effects of lifestyle interventions on (long-term) weight management, cardiometabolic risk and depressive symptoms in people with psychotic disorders: a meta-analysis. PLoS One. 2014;9(12):e112276.
Firth J, Solmi M, Wootton RE, Vancampfort D, Schuch FB, Hoare E, et al. A meta-review of "lifestyle psychiatry": the role of exercise, smoking, diet and sleep in the prevention and treatment of mental disorders. World Psychiatry. 2020;19(3):360–80.
Gurusamy J, Gandhi S, Damodharan D, Ganesan V, Palaniappan M. Exercise, diet and educational interventions for metabolic syndrome in persons with schizophrenia: a systematic review. Asian J Psychiatr. 2018;36:73–85.
Aucoin M, Lachance L, Clouthier SN, Cooley K. Dietary modification in the treatment of schizophrenia spectrum disorders: a systematic review. World J Psychiatry. 2020;10(8):187–201.
Brown C, Geiszler LC, Lewis KJ, Arbesman M. Effectiveness of interventions for weight loss for people with serious mental illness: a systematic review and Meta-analysis. Am J Occup Ther. 2018;72(5):7205190030p1–9.
Firth J, Stubbs B, Vancampfort D, Schuch FB, Rosenbaum S, Ward PB, et al. The validity and value of self-reported physical activity and Accelerometry in people with schizophrenia: a population-scale study of the UK biobank. Schizophr Bull. 2018;44(6):1293–300.
Andorko ND, Rakhshan-Rouhakhtar P, Hinkle C, Mittal VA, McAllister M, Devylder J, et al. Assessing validity of retrospective recall of physical activity in individuals with psychosis-like experiences. Psychiatry Res. 2019;273:211–7.
Ravelli MN, Schoeller DA. Traditional self-reported dietary instruments are prone to inaccuracies and new approaches are needed. Front Nutr. 2020;7:90.
Riley WT, Pilkonis P, Cella D. Application of the National Institutes of Health patient-reported outcome measurement information system (PROMIS) to mental health research. J Ment Health Policy Econ. 2011;14(4):201–8.
Flens G, Smits N, Terwee CB, Dekker J, Huijbrechts I, De Beurs E. Development of a computer adaptive test for depression based on the Dutch-Flemish version of the PROMIS item Bank. Eval Health Prof. 2017;40(1):79–105.
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.
Ethics approval and consent to participate
Consent for publication
The authors declare that they have no competing interests.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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.
About this article
Cite this article
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). https://doi.org/10.1186/s12888-022-03854-x
- Severe mental illness
- Lifestyle intervention
- Patient-reported outcome
- Systematic review, Meta-analysis