High Intensity Interval training (HIIT) for people with severe mental illness: A systematic review & meta-analysis of intervention studies– considering diverse approaches for mental and physical recovery

HIIT & Severe Mental Illness Meta-analysis

Journal Pre-proof

High Intensity Interval Training (HIIT) for people with Severe Mental Illness: A systematic review & meta-analysis of intervention studies– considering diverse approaches for mental and physical recovery Nicole Korman , Michael Armour , Justin Chapman , Simon Rosenbaum , Steve Kisely , Shuichi Suetani , Joseph Firth , Dan Siskind PII: DOI: Reference:

S0165-1781(19)31771-8 https://doi.org/10.1016/j.psychres.2019.112601 PSY 112601

To appear in:

Psychiatry Research

Received date: Revised date: Accepted date:

17 August 2019 3 October 2019 3 October 2019

Please cite this article as: Nicole Korman , Michael Armour , Justin Chapman , Simon Rosenbaum , Steve Kisely , Shuichi Suetani , Joseph Firth , Dan Siskind , High Intensity Interval Training (HIIT) for people with Severe Mental Illness: A systematic review & meta-analysis of intervention studies– considering diverse approaches for mental and physical recovery, Psychiatry Research (2019), doi: https://doi.org/10.1016/j.psychres.2019.112601

This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier B.V.

Highlights   

High intensity interval training (HIIT) appears as feasible as moderate intensity continuous training (MCT) for people with severe mental illness (SMI) People with SMI may experience promising improvements in cardiorespiratory fitness (CRF) and depression following HIIT interventions HIIT resulted in comparable improvements in CRF as MCT, but a moderate benefit in depression over MCT

High Intensity Interval Training (HIIT) for people with Severe Mental Illness: A systematic review & meta-analysis of intervention studies– considering diverse approaches for mental and physical recovery

Short running title: HIIT & Severe Mental Illness Meta-analysis *Nicole Kormana,b Michael Armourc Justin Chapmana,f Simon Rosenbaumd Steve Kiselya,b Shuichi Suetania,f **Joseph Firthd,e **Dan Siskinda,b Affiliations a

Addiction and Mental Health Services, Metro South Health Services, Australia

b

School of Medicine, University of Queensland, Brisbane, Australia

c

NICM Health Research Institute, Western Sydney University, Westmead, NSW,

Australia d

School of Psychiatry, University of New South Wales, Australia

e

Division of Psychology and Mental Health, Faculty of Biology, Medicine and Health,

University of Manchester, Manchester, UK. f

Queensland Institute of Medical Research, Brisbane, Australia

** Co-senior author *Corresponding Author Coorparoo Community Care Unit, Metro South Addiction and Mental Health Services 6 Baragoola St Coorparoo Qld 4005 Australia P +61 7 37277200 F +61 7 37277250 E [email protected] Word count: 4990 References: 61 Tables: 2 Figures: 5 Supplementary Material: 5 Short Running Title: HIIT SMI Meta-analysis

Abstract There is a mortality gap of 15 to 20 years for people with severe mental illness (SMI psychotic spectrum, bipolar, major depressive disorders). Modifiable risk factors include inactivity and low cardiorespiratory fitness (CRF). Exercise can improve mental and physical outcomes; optimal type and intensity of exercise for people with SMI has yet to be determined. High Intensity Interval training (HIIT) is an exercise with distinct cardio-metabolic advantages in other disease populations compared to traditional moderate intensity continuous training (MCT). We investigated the feasibility and efficacy of HIIT for people with SMI.

Major electronic databases were searched, identifying HIIT studies for adults experiencing SMI. Data on feasibility, safety, study design, sample characteristics, and physical and psychological outcomes were extracted and systematically reviewed. Meta-analyses were conducted within group, pre and post HIIT interventions, and between group, to compare HIIT with control conditions.

Nine articles were identified including three pre/post studies, one non randomised and five randomised trials, (366 participants, 45.1% female). HIIT appears as feasible as MCT, with few safety concerns. Following HIIT, there was a moderate improvement in CRF and depression. There was no difference between HIIT and MCT for adherence or CRF. HIIT improved depression more than MCT.

1 Introduction The mortality gap for people with severe mental illness (SMI) is approximately 15-20 years compared to the general population and the gap is thought to be widening (Laursen et al., 2019; Tanskanen et al., 2018). The vast majority of this research is derived from higher income countries; the mortality gap is thought to be even larger in low income settings (Hjorthøj et al., 2017). Modifiable risk factors such as inactivity, smoking, poor nutrition and obesity play a significant role, with cardiovascular and metabolic disease risk in people with SMI estimated as 1.4-2 times the general population (Correll et al., 2017; Osborn et al., 2008). Cardiorespiratory fitness (CRF) refers to the ability of the circulatory and respiratory systems to supply oxygen to skeletal muscles during sustained activity (Ross et al., 2016). Higher CRF levels are associated with improved mortality independent of obesity, smoking, and substance abuse in the general population (Lee et al., 2010). People with SMI have low cardiorespiratory fitness (CRF), (Scheewe et al., 2019; Vancampfort et al., 2017a; Vancampfort et al., 2017b). Exercise interventions are feasible, can increase CRF in people with SMI (Stubbs et al., 2016; Vancampfort et al., 2015) and have demonstrated benefits in various mental health outcomes including cognition, negative and positive symptoms of schizophrenia, depressed mood (Czosnek et al., 2019; Firth et al., 2019; Stubbs et al., 2018a).

The vast majority of past research into exercise interventions for people with SMI has investigated continuous aerobic exercise, typically of moderate or moderate to vigorous intensity in comparison with no activity, (Firth et al., 2015; Vancampfort et

al., 2016a). Additionally, the optimal prescription of exercise with respect to exercise intensity for people with SMI has yet to be established (Vancampfort et al., 2016a). High Intensity Interval training (HIIT) is a potent, time efficient type of exercise training involving repetitive intervals of short bursts of high intensity exercise (durations between six seconds to four minutes) alternating with periods of rest or recovery (ten seconds to five minutes), (Batacan et al., 2017). In athletes and the general population, HIIT is increasingly recognized as an efficacious exercise modality (Gibala et al., 2012) with demonstrated improvements in CRF, power and performance, and reductions in fat mass compared to continuous aerobic training (Gibala et al., 2006; Laursen et al., 2005; Matsuo et al., 2014). HIIT has also been found to be efficacious in various chronic disease populations (e.g. heart failure, metabolic syndrome, coronary artery disease) with respect to CRF and various metabolic risk factors in comparison to continuous training (Weston et al., 2014; Wisløff et al., 2007). In a 2017 meta-analysis of exercise interventions for people with SMI, subgroup analysis revealed interventions involving HIIT were more effective at improving CRF than low to moderate intensity protocols, indicating intensity may be a factor in the efficacy of exercise interventions in this population (Vancampfort et al., 2017b). People with SMI have high cardio-metabolic risks and low CRF, hence HIIT may be a promising exercise protocol to impact on modifiable risk factors which contribute to premature mortality.

A 2018 narrative review of exercise interventions in schizophrenia concluded that HIIT has the potential to reduce metabolic risk factors (Schmitt et al., 2018). However, this was based on two pre- post studies, a case report and a study on the

effects of a single episode of HIIT, was not systematic, and did not include recently published randomized controlled trials for people with SMI. In addition, it did not address possible adverse effects, which is important given the potential risks of acute exercise in people with significantly low fitness (Thompson et al., 2007b). Despite the potential benefit, the feasibility and safety of HIIT interventions for people with SMI remains uncertain. In this systematic review, we aimed to critique the available evidence for the feasibility and safety and available physical and psychological outcomes for HITT, for people with SMI.

2 Methods

Protocol and registration

This study was registered with PROSPERO (registration number: CRD42018104708). The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement recommendations was followed in conducting this review (Moher et al., 2009). 2.1 Search Strategy

A systematic search of Embase, Pubmed, Cochrane Central trials registry and PsycINFO was initially conducted from inception to June 2019. The Medical Subject Heading (MeSH) database was employed to establish all related articles on HIIT and SMI and related terms, in conjunction with text words. (Search strategy in Supplementary material 1.)

2.2 Eligibility criteria Studies involving participants over the age of 18 with a diagnosis of SMI (Johnson, 1997); major depressive disorders, psychotic spectrum disorders and bipolar disorder were included in the review. Studies needed to follow a HIIT protocol, defined as intervals of work involving brief high intensity exercise interspersed by intervals of recovery (at lower intensity or complete rest), (Batacan et al., 2017). Included studies needed an identified method of assessing exercise intensity (such as heart rate, rate of perceived exertion or strength). Studies were excluded if HIIT occurred less than once per week, or less than 2 weeks duration.

We included all randomized and non-randomised controlled trials and pre/post studies were considered. Published data in all languages were included and translated into English where necessary.

2.3 Study Selection After removal of duplicates, studies meeting inclusion criteria from the search strategy were identified at title and abstract stage (NK). Studies that met inclusion criteria at title and abstract stage or that could not be excluded on the basis of information in the abstract were reviewed at full text level by two independent authors and assessed according to inclusion criteria (NK and MA). Relevant journals were hand searched. Snowball searches of key papers and reference lists were conducted. (Figure 1 for identification of included studies).

2.4 Data Items and Collection process

Data extraction was conducted by NK and MA. Any discrepancies during all stages of study selection, data extraction and quality assessment were resolved through discussion with senior authors, DS and JF, and through re-checking original source papers.

A systematic tool was developed, and quantitative data from each study was extracted on feasibility (exercise adherence, recruitment, participation), and adverse events. Secondary data on study design, sample characteristics, exercise protocol details including details of HIIT intervals and intensity, and physical and psychological data was collected. Studies were classified based on whether HIIT was compared with active (exercise) control, inactive (non-exercise) control or no control group.

Physical and psychological data was categorized into domains: A) PHYSICAL = physical fitness (VO2max/peak - a measure of an individual’s ability to absorb and consume oxygen during exercise, resting heart rate, power and strength) B) METABOLIC= metabolic health items (Body Mass Index, BMI, body weight, waist circumference, fasting glucose and lipids, blood pressure, body composition) C) PSYCHIATRIC = psychiatric symptoms (positive, negative symptoms, depressed mood) D) FUNCTION= quality of life, functioning

Extracted data were validated by MA. Data analysis was conducted by NK, DS and MA. In cases where data was missing, attempts were made to contact corresponding authors to obtain this information.

2.5 Study Quality

Two authors (NK and MA) independently assessed all studies using the modified Physiotherapy Evidence Database (PEDRo) scale, which consists of a checklist of 10 scored yes-or-no items pertaining to the internal validity of studies (Maher et al., 2003). High quality studies achieved a rating of 7-10; fair; 4-7; poor; 1-3. The PEDRo scale is included in supplementary material 2.

In addition, two authors (NK and MA) independently assessed RCT’s using the Cochrane Risk of Bias tool (Higgins et al., 2011), which assesses six domains of study characteristics that may introduce bias including: random sequence generation, allocation concealment, blinding of participants, personnel and outcome assessors, incomplete data, selective reporting or other sources of bias. In both instances any disagreement in quality assessment rating was resolved by discussion or if necessary, resolved by a third senior author (DS).

We conducted two types of meta-analyses, 1) within group analyses of pre/post data following HIIT for all included studies (pre post trials, non-randomised and RCT’s), and 2) between group analyses for RCT’s utilising endpoint data comparing HIIT with control conditions, i.e. moderate intensity continuous training (MCT) for all available physical and psychological outcomes.

All studies provided pre and post means with standard deviation (SD). Two studies provided means +/- Standard Error (SE) allowing SD to be calculated.

Due to the small size of studies, and variation in exercise conditions and participants, we used random-effects model for all analyses. Hedges’ g and the 95 % confidence interval (CI) was calculated as estimates of the effect size. Effect sizes were categorized as small (0.2–0.4), medium (0.4–0.8), or large (greater than 0.8), (Cohen, 1988). Where possible, intention-to-treat analyses were sought and included in the meta-analyses.

Where there were sufficient studies, we conducted a sensitivity analysis to remove low quality studies (PEDRo ≤ 3). Heterogeneity (I2) was calculated to assess the risk of bias across studies which was assessed using the I2 statistic. An I2 of more than 75% was considered to indicate high level heterogeneity, I2 of 50–75% as indicative of substantial heterogeneity, and an I2 of less than 40% as low heterogeneity. If there were ten or more studies, we assessed for publication bias using the Cochrane test for funnel plot asymmetry (Higgins et al., 2011).

3 Results The search identified 659 results, providing 525 unique citations after duplicates were removed (Figure 1). In total, 501 studies were excluded at the title-abstract stage and 24 records screened. In two cases, authors were contacted regarding protocols registered as a clinical trial, but no data were available. At the final stage,

21 full text articles were reviewed in full, and nine unique articles met eligibility criteria and were included in the systematic review and meta-analysis (Abdel-Baki et al., 2013; Chapman et al., 2017; Gerber et al., 2018; Hanssen et al., 2018; Heggelund et al., 2011; Minghetti et al., 2018; Romain et al., 2018; Strassnig et al., 2015; Wu et al., 2015). Additional data were requested for one study (Chapman et al., 2017). There were insufficient number of studies to perform subgroup analysis or metaregression to evaluate the potential moderating influence of participant and exercise protocol characteristics.

Publication bias using the Cochrane test for funnel plot asymmetry could not be evaluated, as fewer than 10 studies were included in each analysis.

3.1 Feasibility and Safety: (Table 1) Only four out of the nine included studies reported participation, mean 74%, which ranged between 64 and 85%, (Table 1). Two studies that did not report participation also excluded participants if they did not attend a minimum number of sessions (Gerber et al., 2018; Hanssen et al., 2018). A total of 366/967 participants were recruited into HIIT studies (38%). Approximately one third (105/366) of HIIT participants (29%) dropped out with no difference between the HIIT and MCT groups (odds ratio 0.86 (95% CI 0.46 – 1.62); I2 = 0%).

Only one study formally assessed acceptability of HIIT and found similar enjoyment for both HIIT and MCT groups, although small sample size (n=16), (Chapman et al., 2017). One study used a formal adverse events protocol to report adverse events; 4 studies did not address adverse outcomes. 11 out of 225 participants involved in any HIIT programs experienced an injury (4.8%) and a further two participants dropped out due to “physical discomfort”. One HIIT versus MCT study reported adverse events; the proportion of adverse events was equal in each condition - 2/8 (25%), (Chapman et al., 2017).

(Insert Table 1)

3.2 Study characteristics: (Table 1) Of the nine studies meeting criteria, three were pre/post studies involving a single arm HIIT intervention, two studies compared HIIT against inactive or wait list control, four studies compared HIIT against a moderate intensity exercise control. Selected studies included a total of 366 participants, of whom 45% (n = 165) were females. Of these, 225 participants were in a HIIT program. The mean age was 35.5 years and BMI 28.2kg/m2 (SD 3.7). Three studies included participants with major depressive disorders, five of schizophrenia and/or bipolar disorders, and one study included participants with a range of SMI’s (Table 1). All the included studies employed a training frequency of either 2 or 3 times per week. Study duration ranged from 4 weeks to 26 weeks but the majority (n=7) were of short duration, (i.e. 12 weeks or less). An aerobic HIIT exercise protocol (n=8) was

the most commonly employed with one study using a high velocity resistance protocol. Mean exercise session duration for HIIT (including rest/recovery), (8 studies) was 31 mins, and MCT (4 studies) was 32.5 minutes; whereas mean exercise minutes per session (active exercise minus rest) was 17 minutes for HIIT and 22.5 minutes for MCT. Over half of the HIIT studies (n=6) utilised an interval schedule involving short (≤ 30 seconds) of exercise “work”; two studies utilised longer work and recovery periods – (4 minutes work; 3 mins recovery/rest), (Table 1). Only one study specifically addressed motivation to exercise in the intervention (Abdel-Baki et al., 2013). The majority (6/9) of studies involved direct supervision of participants (i.e. personal trainer, kinesiology or medical students, trained exercise coach), however three studies did not specifically report on this. Only one study asked participants to exercise alone without supervision in the last third of the study but did not report specific adherence to this (Chapman et al., 2017).

Primary outcomes included CRF, (n=3), effects of HIIT on depression (n =3), feasibility, (n=2), metabolic outcomes, (n=2), effect of HIIT on sports and exercise motivation (n=1), specific outcome measures are included in Table 2.

(Insert Table 2)

3.3 Quality Median PEDRo score of 9 included studies was 4. In terms of the PEDRo scale, three studies were small pre-post studies of low quality and only two studies rated high quality (Minghetti et al., 2018; Romain et al., 2018), (Supplementary Table 1). Due to the limited number of randomised trials, all RCT’s were included in our metaanalysis irrespective of quality, (Supplementary Table 2).

3.4 Physical health

Seven studies measured CRF via VO2max or VO2peak. The majority of studies (5/7) obtained CRF via direct maximal testing (2 via submaximal tests), (Table1). Pre/post data was analysed for the seven studies assessing CRF, (two pre/post studies, one non randomised trial, four RCT’s) and revealed a significant increase in CRF following HIIT, moderate effect size, high heterogeneity, I2= 75% (Figure 2). Sensitivity analysis to remove low quality studies revealed a smaller but significant effect, (hedges g 0.27 (0.123, 0.418, p<0.00), I2=68).

Four of the studies assessing CRF found improvements that were of a magnitude to be considered clinically significant (Abdel-Baki et al., 2013; Heggelund et al., 2011; Minghetti et al., 2018; Romain et al., 2018), that is, VO2max or VO2peak increases of greater than 3.5ml/L/kg), (Kodama et al., 2009). Individual studies reported small improvements in other physical fitness outcomes that included net mechanical efficiency of walking (Heggelund et al., 2011), power

and strength (Strassnig et al., 2015) resting heart rate and pulse pressure (Wu et al., 2015), (Table 2).

Endpoint data in four RCT’s where HIIT was compared with MCT interventions for CRF, found no significant difference between HIIT and MCT, heterogeneity I 2=0%, (Figure 3).

3.5 Metabolic Outcomes

Of the nine trials, seven assessed at least one metabolic outcome (Table 2). Few studies revealed any significant impact following HIIT. We compared pre post data following HIIT and found no significant effect of HIIT on any anthropometrics measure; waist circumference (two pre/post, two RCT’s), hedges’ g = -0.16, 95% CI -0.32, 0.008 p=0.06, I2=0%, BMI (two pre/post, two RCT’s); hedges’ g = -0.039, 95% CI -0.19, 0.039, p=0.63, I2= 0%, and body weight (two pre/post, two RCT’s and one nonrandomised trial); hedges’ g = -0.035, 95% CI 0.02, 0.13, p= 0.68, I2 = 0%, (Supplementary material 3).

Of note, one 14 week pre/post study found a 4.3cm reduction in waist circumference in an early psychosis population, with greater reductions for participants with high adherence (>64% of sessions), (Abdel-Baki et al., 2013). Another wait list control RCT only found significant (3.17cm) change to waist circumference on post hoc analysis, also in participants with high adherence (>64%) (Romain et al., 2018).

Studies also assessed body composition (n=2), or various components of the metabolic syndrome such as fasting blood sugar (n=3) and lipids (n=3), however insufficient number of comparable outcomes for meta-analytic techniques. One 12 week non-randomised controlled trial found HIIT improved high density lipoprotein (HDL) cholesterol more than control condition involving playing computer games (Heggelund et al., 2011). No other HIIT study revealed significant changes in fasting glucose, fasting lipids, blood pressure or body composition. However, the vast majority of mean baselines values (82%) across all metabolic outcomes were within normal ranges, except two studies with mildly raised baseline triglycerides (AbdelBaki et al., 2013; Romain et al., 2018).

Only one RCT compared HIIT with MCT for metabolic outcomes (weight, waist, body composition), and found no within or between group changes for any measure, however this was a very small study (n=16) with high attrition (43.5%), (Chapman et al., 2017).

3.6 Psychiatric outcomes 3.6.1 Depressed mood

Depression was the most commonly measured mental health outcome (7/9 studies), (Table 2). We assessed pre/post data following HIIT for depressed mood in seven studies (two pre/post studies, one non randomised, four RCT’s) and found a significant improvement in mood, however high heterogeneity, I2=82% (Figure 4). Six of the seven trials found a significant reduction in depression scores (range 18% to

46% reduction in depression scores). Sensitivity analysis to remove low quality studies revealed a larger effect on depressed mood (hedges’ g = -0.87, CI; -1.2, .048, p=0.00, I2=73.5%).

We assessed endpoint data for depressed mood in four RCT’s comparing HIIT with MCT as the control condition. We found a moderate improvement in the HIIT group compared to MCT for depressed mood, heterogeneity I2=0%, (Figure 5).

3.6.2 Positive and negative Symptoms We were cautious in applying meta-analytic techniques in the presence of high heterogeneity to a low number of studies, hence systematically reviewed psychiatric symptoms instead, as there were less studies assessing these outcomes (Seide et al., 2019). We found inconsistent findings for positive and negative symptoms pre and post HIIT studies. Four HIIT studies assessed psychiatric symptoms (via PANSS). There was no impact of HIIT on positive symptoms for any HIIT trial (Table 2). Two small prepost studies revealed significant but small reductions in total psychopathology scores however another 12 week controlled trial did not find any change in total scores. In a HIIT versus wait list control study, Romain et al. (2018) found a significant reduction in negative symptoms (17% reduction from baseline) compared to wait list control (no change) over 26 weeks, using intention to treat analysis. Wu et al. (2015) reported a significant but smaller (11%) reduction in a small 8 week pre post study, both studies found <20% reduction in negative symptoms and hence unlikely to be of

clinical significance (Leucht et al., 2019). Conversely two small pre post studies found no change to negative symptoms (Heggelund et al., 2011; Strassnig et al., 2015).

HIIT versus MCT studies did not investigate positive and negative symptoms.

3.6.3 Quality of life and functioning

A small number of HIIT studies investigated quality of life (n=2) and social (Social and Occupational Functioning scale, SOFAS) and global functioning (Global Assessment of Functioning, GAF), (n=3), Romain et al found a significant increase in global functioning compared to wait list control (mean change 4.6 GAF points); likely to be clinically significant (GAF change >4 points) (Amri et al., 2014; Rickwood et al., 2015). Two studies found statistically significant improvements in social functioning following HIIT although unlikely to be of clinical significance (<10 points on the SOFAS), (Rickwood et al., 2015). Neither of the two HIIT versus inactive control trials revealed changes to the mental or physical component of quality of life scales, (Heggelund et al., 2011; Romain et al., 2018). Two small pre post studies found small increases in clinical global impression of illness severity (CGI), (Abdel-Baki et al., 2013; Strassnig et al., 2015), but the change was unlikely to be clinically significant (< 2 CGI points), (Kelly, 2010).

4 Discussion Based on limited data, HIIT interventions appear to be as feasible as MCT for people with SMI who are willing to engage in exercise programs. In addition, there may be improvements to both cardiorespiratory fitness and mood with relatively brief commitments to active exercise following HIIT.

Participation rates for any HIIT program were high (74%) and comparable with a meta-analysis of exercise interventions in people with SMI (77- 79%), (Firth et al., 2015; Vancampfort et al., 2015). Similarly, drop outs from HIIT programs was 29%, which is comparable with two other recent meta-analysis for other exercise interventions for people with SMI, (24-32.5%), (Firth et al., 2015; Vancampfort et al., 2015). HIIT drop out rates were considerably lower than those seen in antidepressant and antipsychotic medication trials (50%) where side effects of medication can be a significant barrier to adherence (Lieberman et al., 2010; Martin et al., 2006). However drop outs from HIIT programs in other disease populations (ie cardiometabolic) were lower (18%) than our findings (Weston et al., 2014). This difference may be partially explained by the motivational deficits experienced by people with SMI (Rabinowitz et al., 2012). Of note, only one HIIT intervention specifically addressed motivation to exercise (Abdel-Baki et al., 2013). This was surprising as it is well established that people with SMI experience many physical and psychological barriers to exercise, including amotivation (Firth et al., 2016; Soundy et al., 2014) and targeted motivational interventions are a primary recommendation in the provision of exercise interventions for people with SMI

(Stubbs et al., 2018b; Vancampfort et al., 2015). In future, HIIT study adherence and participation may be improved with the inclusion of motivational strategies.

Drop-out rates were comparable between HIIT and MCT protocols which has been similarly reported in HIIT studies in cardiometabolic disease populations (Vella et al., 2017; Weston et al., 2014). These findings contrast somewhat with the previously advanced notion that compared to traditional MCT, HIIT may be too psychologically aversive for people with SMI to adhere to (Biddle et al., 2015; Hardcastle et al., 2014). Some HIIT studies in other disease populations have found HIIT may be more enjoyable than MCT as the short recovery periods may provide relief from the active exercise, contrasting with the experience of continuous exercise (Bartlett et al., 2011; Tjønna et al., 2008). However the preferences and enjoyment of people with SMI should be addressed in larger studies, as this is highly relevant when considering sustainability and effective integration of exercise programs into mental health settings (Krogh et al., 2014).

The majority of studies were of shorter duration (less than 12 weeks), which may have been too short to produce maximum benefit. Support for this observation comes from the finding the longest HIIT study (26 weeks) reported particularly favourable cardiometabolic benefits in those with high adherence (attended >64% sessions). Unfortunately, this study also reported high drop out rates (50%), (Romain et al., 2018). This is reflected in the broader exercise and SMI literature where benefits only occur in those who adhere for some time to the intervention (Scheewe

et al., 2013; Vancampfort et al., 2016b). Longer term adherence is crucial for meaningful impact on outcomes, hence the sustainability of longer HIIT programs requires further research. Additionally, unsupervised HIIT has been successfully reported in other disease populations (Moholdt et al., 2012; Wisløff et al., 2007). As only one HIIT and SMI study offered unsupervised HIIT, more investigation of this is required given the potential impact on resources if supervision is necessary for adherence in this population.

Whilst CRF reduces cardiovascular events in the general population (Thompson et al., 2007a), it has been advocated that high intensity exercise may make susceptible persons at risk of sudden cardiac events. Given people with SMI have low baseline fitness (Vancampfort et al., 2017b), the safety of any HIIT intervention remains a primary concern. Based on available data, we found low overall rates of adverse events in HIIT interventions. Similar findings were reported in a systematic review of HIIT studies in patients with coronary artery disease and heart failure (Wewege et al., 2018). Potential HIIT participants should be screened appropriately for contraindications such as acute or unstable chronic cardiorespiratory conditions or unstable diabetes (Weston et al., 2014).

We found a moderate overall improvement in CRF following HIIT interventions of a level shown to reduce mortality in the general population (Kodama et al., 2009), confirming the efficacy of HIIT found in athletes, sedentary adults, metabolic populations and people with substance abuse disorders (Batacan et al., 2017; Flemmen et al., 2014; Weston et al., 2014). This is promising as this occurred with small time commitments and volumes of active exercise per week. As such, HIIT

may be an attractive prospect for some people with SMI, particularly where the experience of short bursts of activity is preferable to continuous exercise.

We found that HIIT was comparable to MCT with respect to CRF. Based on available evidence, adults with SMI may achieve similar improvements in CRF following either HIIT or MCT protocols and hence choose an exercise protocol that suits both preference and capabilities – these are important constructs underpinning autonomous motivation to exercise for people with SMI (Vancampfort et al., 2015). However, some non-mental health studies in both clinical and non- clinical populations have found HIIT to be more efficacious than MCT with respect to CRF (Helgerud et al., 2007; Weston et al., 2014). In a previous meta-analysis of sedentary adults, improved CRF was associated with a longer duration of study, more HIIT repetitions, longer active work intervals and longer recovery periods, with the 4*4 minute interval type being associated with the highest CRF improvements (Milanović et al., 2015). The majority of our included studies were of shorter duration (<12 weeks) and employed both shorter work (<60 second) and shorter recovery intervals, which may offer some explanation for our findings. In this review, there were insufficient studies to investigate specific properties of the HIIT intervals, however this should be a focus of future research in people with SMI.

There were insufficient studies to draw conclusions regarding comparison between HIIT and MCT studies for metabolic outcomes. For other HIIT studies investigating metabolic outcomes, we found no significant effect of HIIT on metabolic markers such as fasting glucose, lipids, and blood pressure. The majority of HIIT participants had normal baseline values for these

outcomes, hence detecting significant change was unlikely. HIIT participants were overweight (average BMI 28); however, we found no overall effect of HIIT on any anthropometrics (ie BMI, waist circumference or weight). Previous research in people with SMI has shown that exercise alone has little impact on anthropometrics, particularly when dietary interventions are not included (Firth et al., 2015; Pearsall et al., 2014). However, HIIT studies in cardiometabolic populations have demonstrated reductions in fat mass, waist circumference, metabolic makers and insulin sensitivity (Batacan et al., 2017; Weston et al., 2014; Whyte et al., 2010). None of our included HIIT studies controlled for the dietary intake of participants, which may be a potential confounding factor. Additionally, people with SMI face unique challenges with their metabolic health; contributing factors include the obesogenic nature of psychiatric medications stimulating hunger, cognitive deficits and impaired reward pathways, which may also explain the lack of impact on metabolic outcomes we found (AlvarezJiménez et al., 2008; Firth et al., 2019; Igor et al., 2006).

We found a significant improvement in depressed mood following any HIIT intervention, with a sensitivity analysis showing a larger effect size when low quality studies were removed. These results are in keeping with a substantial body of evidence regarding the antidepressant effect of exercise (Schuch et al., 2016a). We also found HIIT interventions for people with SMI had a modest advantage over MCT for depressed mood. In particular, previous meta-analyses have found that it is higher level intensity exercise interventions (at least moderate to vigorous) that resulted in the greatest improvements in mood in both people with schizophrenia and depression (Firth et al., 2015; Schuch et al., 2016b).

By contrast, HIIT had limited effect on other psychiatric symptoms, quality of life or functional outcomes. The most promising was seen in negative symptoms in a 26 week RCT with wait list controls although the changes did not reach clinical significance (Romain et al., 2018). Conversely, two studies showed no impact of HIIT on negative symptoms at all, although of much shorter study duration (8 weeks), which may explain the differences found, (Heggelund et al., 2011; Strassnig et al., 2015). Whilst exercise has shown potential to improve negative symptoms (Firth et al., 2015), the duration and or volume of HIIT employed in included studies may have been insufficient to produce change or clinically meaningful improvement.

A major limitation to this systematic review was associated with both the limited number and quality of available studies, (average PEDRo rating was fair, only two high quality studies), which limits conclusions that can be drawn at this time. Whilst it is difficult to blind participants in exercise trials, well designed HIIT RCT’s with adequate concealment and assessor blinding and are required in future. In addition, HIIT should be compared with control groups that include other types of exercise protocols and non-exercise interventions. Whilst participation and adherence rates were high, recruitment was low (38%) and there may be a selection bias involving only those interested in exercise agreeing to engage in HIIT. In addition, the majority of analyses were conducted on people who completed exercise programs, rather than intention to treat, further limiting generalisability. Similarly, HIIT protocols were diverse and more research is needed in order to develop any specific recommendations regarding optimal HIIT prescriptions for people with SMI. The vast majority of our heterogeneity was low other than for

depression and CRF pre and post HIIT, accordingly those results should be interpreted with caution. Further limitations of pre/post meta-analyses were that results were subject to regression to the mean, non-independence of rating of scores and the placebo effect given that none of the participants could be blind to intervention group. Finally, lack of control for dietary intake in HIIT studies could have influenced metabolic outcomes and should be addressed in future studies.

Based on available evidence, HIIT appears to be feasible and safe for people with SMI willing to engage in exercise– however more information is needed on the acceptability of HIIT and whether HIIT protocols can be sustained for longer durations and without supervision. HIIT appears to be comparable to MCT for CRF outcomes and may have a moderate advantage over MCT for depression. Current evidence suggests HIIT may produce promising improvements in CRF and depression, but little impact on metabolic outcomes. Exercise interventions play an important role in improving physical and mental health outcomes and should be incorporated into the multidisciplinary management offered to people with SMI. People with SMI should be encouraged to choose an exercise protocol that suits their preference and capacities; HIIT is a feasible type of exercise protocol that may be beneficial for those willing to engage in it.

Conflict of Interest Statement The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References Abdel-Baki, A., Brazzini-Poisson, V., Marois, F., Letendre, E., & Karelis, A. D., 2013. Effects of aerobic interval training on metabolic complications and cardiorespiratory fitness in young adults with psychotic disorders: a pilot study. Schizophr Res, 149(1-3), 112115. doi:10.1016/j.schres.2013.06.040 Alvarez-Jiménez, M., González-Blanch, C., Crespo-Facorro, B., Hetrick, S., Rodríguez-Sánchez, J., Pérez-Iglesias, R., & Vázquez-Barquero, J., 2008. Antipsychotic-induced weight gain in chronic and first-episode psychotic disorders: a systematic critical reappraisal. CNS drugs, 22(7), 547-562. doi:10.2165/00023210-200822070-00002 Amri, I., Millier, A., & Toumi, M., 2014. PMH2 - Minimum Clinically Important Difference in the Global Assessment Functioning in Patients with Schizophrenia. Value in Health, 17(7), A765-A766. doi:10.1016/j.jval.2014.08.285 Bartlett, J. D., Close, G. L., Maclaren, D. P. M., Gregson, W., Drust, B., & Morton, J. P., 2011. High-intensity interval running is perceived to be more enjoyable than moderateintensity continuous exercise: Implications for exercise adherence. Journal of Sports Sciences, 29(6), 547-553. doi:10.1080/02640414.2010.545427 Batacan, R. B., Duncan, M. J., Dalbo, V. J., Tucker, P. S., & Fenning, A. S., 2017. Effects of high-intensity interval training on cardiometabolic health: a systematic review and meta-analysis of intervention studies. British Journal of Sports Medicine, 51(6), 494. doi:10.1136/bjsports-2015-095841 Biddle, S., & Batterham, A., 2015. High-intensity interval exercise training for public health: a big HIT or shall we HIT it on the head? International Journal of Behavioral Nutrition and Physical Activity, 12(1), n/a. doi:10.1186/s12966-015-0254-9 Chapman, J. J., Coombes, J. S., Brown, W. J., Khan, A., Chamoli, S., Pachana, N. A., & Burton, N. W., 2017. The feasibility and acceptability of high-intensity interval training for adults with mental illness: A pilot study. Mental Health and Physical Activity, 13, 4048. doi:10.1016/j.mhpa.2017.09.007 Cohen, J., 1988. Statistical power analysis for the behavioral sciences (2nd ed.. ed.). Hillsdale, N.J.: L. Erlbaum Associates. Correll, C., Solmi, M., Veronese, N., Bortolato, B., Rosson, S., Santonastaso, P., Thapa‐ Chhetri, N., Fornaro, M., Gallicchio, D., Collantoni, E., Pigato, G., Favaro, A., Monaco, F., Kohler, C., Vancampfort, D., Ward, P., Gaughran, F., Carvalho, A., & Stubbs, B., 2017. 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, 16(2), 163-180. doi:10.1002/wps.20420

Czosnek, L., Lederman, O., Cormie, P., Zopf, E., Stubbs, B., & Rosenbaum, S., 2019. Health benefits, safety and cost of physical activity interventions for mental health conditions: A meta-review to inform translation efforts. Mental Health and Physical Activity, 16, 140-151. doi:10.1016/j.mhpa.2018.11.001 Firth, J., Cotter, J., Elliott, R., French, P., & Yung, A. R., 2015. A systematic review and metaanalysis of exercise interventions in schizophrenia patients. 45(7), 1343-1361. doi:10.1017/S0033291714003110 Firth, J., Rosenbaum, S., Stubbs, B., Gorczynski, P., Yung, A. R., & Vancampfort, D., 2016. Motivating factors and barriers towards exercise in severe mental illness: a systematic review and meta-analysis. 46(14), 2869-2881. doi:10.1017/S0033291716001732 Firth, J., Siddiqi, N., Koyanagi, A., Siskind, D., Rosenbaum, S., Galletly, C., Allan, S., Caneo, C., Carney, R., Carvalho, A. F., Chatterton, M. L., Correll, C. U., Curtis, J., Gaughran, F., Heald, A., Hoare, E., Jackson, S. E., Kisely, S., Lovell, K., Maj, M., McGorry, P. D., Mihalopoulos, C., Myles, H., O'Donoghue, B., Pillinger, T., Sarris, J., Schuch, F. B., Shiers, D., Smith, L., Solmi, M., Suetani, S., Taylor, J., Teasdale, S. B., Thornicroft, G., Torous, J., Usherwood, T., Vancampfort, D., Veronese, N., Ward, P. B., Yung, A. R., Killackey, E., & Stubbs, B., 2019. The Lancet Psychiatry Commission: a blueprint for protecting physical health in people with mental illness. The Lancet Psychiatry, 6(8), 675-712. doi:10.1016/S2215-0366(19)30132-4 Flemmen, G., Unhjem, R., & Wang, E., 2014. High-intensity interval training in patients with substance use disorder. BioMed research international, 2014, 616935-616935. doi:10.1155/2014/616935 Gerber, M., Minghetti, A., Beck, J., Zahner, L., & Donath, L., 2018. Sprint Interval Training and Continuous Aerobic Exercise Training Have Similar Effects on Exercise Motivation and Affective Responses to Exercise in Patients With Major Depressive Disorders: A Randomized Controlled Trial.(Report). Frontiers in Psychiatry, 9. doi:10.3389/fpsyt.2018.00694 Gibala, M. J., Little, J. P., Macdonald, M. J., & Hawley, J. A., 2012. Physiological adaptations to low‐volume, high‐intensity interval training in health and disease. Journal of Physiology, 590(5), 1077-1084. doi:10.1113/jphysiol.2011.224725 Gibala, M. J., Little, J. P., Van Essen, M., Wilkin, G. P., Burgomaster, K. A., Safdar, A., Raha, S., & Tarnopolsky, M. A., 2006. Short‐term sprint interval versus traditional endurance training: similar initial adaptations in human skeletal muscle and exercise performance. Journal of Physiology, 575(3), 901-911. doi:10.1113/jphysiol.2006.112094 Hanssen, H., Minghetti, A., Faude, O., Schmidt-Trucksäss, A., Zahner, L., Beck, J., & Donath, L., 2018. Effects of endurance exercise modalities on arterial stiffness in patients

suffering from unipolar depression: A randomized controlled trial. Frontiers in Psychiatry, 8(JAN). doi:10.3389/fpsyt.2017.00311 Hardcastle, S. J., Ray, H., Beale, L., & Hagger, M. S., 2014. Why sprint interval training is inappropriate for a largely sedentary population. Frontiers in Psychology, 5(1). doi:10.3389/fpsyg.2014.01505 Heggelund, J., Nilsberg, G. E., Hoff, J., Morken, G., & Helgerud, J., 2011. Effects of high aerobic intensity training in patients with schizophrenia - A controlled trial. Nordic Journal of Psychiatry, 65(4), 269-275. doi:10.3109/08039488.2011.560278 Helgerud, J., Høydal, K., Wang, E., Karlsen, T., Berg, P., Bjerkaas, M., Simonsen, T., Helgesen, C., Hjorth, N., Bach, R., & Hoff, J., 2007. Aerobic High-Intensity Intervals Improve V˙O2max More Than Moderate Training. Medicine & Science in Sports & Exercise, 39(4), 665-671. doi:10.1249/mss.0b013e3180304570 Higgins, J. P. T., Altman, D. G., Gøtzsche, P. C., Jüni, P., Moher, D., Oxman, A. D., Savovid, J., Schulz, K. F., Weeks, L., & Sterne, J. A. C., 2011. The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials. BMJ, 343(7829). doi:10.1136/bmj.d5928 Hjorthøj, C., Stürup, A. E., McGrath, J., & Nordentoft, M.,2017. Life Expectancy and Years of Potential Life Lost in Schizophrenia: A Systematic Review and Meta-Analysis. In (Vol. 43, pp. S133-S134). Igor, E., David, B., & Scott, E. L., 2006. Food Intake and Reward Mechanisms in Patients with Schizophrenia: Implications for Metabolic Disturbances and Treatment with SecondGeneration Antipsychotic Agents. Neuropsychopharmacology, 31(10), 2091. doi:10.1038/sj.npp.1301051 Johnson, D. L., 1997. Overview of severe mental illness. Clinical Psychology Review, 17(3), 247-257. doi:10.1016/S0272-7358(97)00017-2 Kelly, P. J., 2010. Calculating clinically significant change: Applications of the Clinical Global Impressions (CGI) Scale to evaluate client outcomes in private practice. Clinical Psychologist, 14(3), 107-111. doi:10.1080/13284207.2010.512015 Kodama, S., Saito, K., Tanaka, S., Maki, M., Yachi, Y., Asumi, M., Sugawara, A., Totsuka, K., Shimano, H., Ohashi, Y., Yamada, N., & Sone, H., 2009. Cardiorespiratory Fitness as a Quantitative Predictor of All-Cause Mortality and Cardiovascular Events in Healthy Men and Women: A Meta-analysis. JAMA, 301(19), 2024-2035. doi:10.1001/jama.2009.681 Krogh, J., Lorentzen, A., Subhi, Y., & Nordentoft, M., 2014. Predictors of adherence to exercise interventions in patients with clinical depression – A pooled analysis from two clinical trials. Mental Health and Physical Activity, 7(1), 50-54. doi:10.1016/j.mhpa.2014.01.003

Laursen, B. P., Shing, M. C., Peake, M. J., Coombes, S. J., & Jenkins, G. D., 2005. INFLUENCE OF HIGH-INTENSITY INTERVAL TRAINING ON ADAPTATIONS IN WELL-TRAINED CYCLISTS. Journal of Strength and Conditioning Research, 19(3), 527-533. doi:10.1519/15964.1 Laursen, T., Plana-Ripoll, O., Andersen, P., McGrath, J., Toender, A., Nordentoft, M., Canudas-Romo, V., & Erlangsen, A., 2019. Cause-specific life years lost among persons diagnosed with schizophrenia: Is it getting better or worse? Schizophrenia research, 206, 284-290. doi:10.1016/j.schres.2018.11.003 Lee, D.-C., Artero, E., Sui, X., & Blair, S., 2010. Review: Mortality trends in the general population: the importance of cardiorespiratory fitness. Journal of Psychopharmacology, 24, 27. Leucht, S., Barabássy, Á., Laszlovszky, I., Szatmári, B., Acsai, K., Szalai, E., Harsányi, J., Earley, W., & Németh, G., 2019. Linking PANSS negative symptom scores with the Clinical Global Impressions Scale: understanding negative symptom scores in schizophrenia. Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology. doi:10.1038/s41386-019-0363-2 Lieberman, J., Stroup, T., McEvoy, J., Swartz, M., Rosenheck, R., & Perkinds, D., 2010. Effectiveness of Antipsychotic Drugs in Patients with Chronic Schizophrenia. New England Journal of Medicine, 363(11), 1092-1093. doi:10.1056/NEJMx100054 Maher, C. G., Sheerington, C., Herbert, R. D., Moseley, A. M., & Elkins, M., 2003. Reliability of the PEDro scale for rating quality of randomized controlled trials. (Research Report).(Physiotherapy Evidence Database). Physical Therapy, 83(8), 713. Martin, J., Perez, V., Sacristan, M., Rodriguez-Artalejo, F., Martinez, C., & Alvarez, E.,2006. Meta-analysis of drop-out rates in randomised clinical trials, comparing typical and atypical antipsychotics in the treatment of schizophrenia. In Eur. Psychiat. (Vol. 21, pp. 11-20). Matsuo, T., Saotome, K., Seino, S., Shimojo, N., Matsushita, A., Iemitsu, M., Ohshima, H., Tanaka, K., & Mukai, C., 2014. Effects of a Low-Volume Aerobic-Type Interval Exercise on V˙O2max and Cardiac Mass. Medicine & Science in Sports & Exercise, 46(1), 42-50. doi:10.1249/MSS.0b013e3182a38da8 Milanovid, Z., Sporiš, G., & Weston, M., 2015. Effectiveness of High-Intensity Interval Training (HIT) and Continuous Endurance Training for VO 2max Improvements: A Systematic Review and Meta-Analysis of Controlled Trials. Sports Medicine, 45(10), 1469-1481. doi:10.1007/s40279-015-0365-0 Minghetti, A., Faude, O., Hanssen, H., Zahner, L., Gerber, M., & Donath, L., 2018. Sprint interval training (SIT) substantially reduces depressive symptoms in major depressive disorder (MDD): A randomized controlled trial. Psychiatry Res, 265, 292-297. doi:10.1016/j.psychres.2018.04.053

Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G., 2009. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ, 339(7716). doi:10.1136/bmj.b2535 Moholdt, T., Grimsmo, J., Slørdahl, S., & Wisløff, U., 2012. Home-Based Aerobic Interval Training Improves Peak Oxygen Uptake Equal to Residential Cardiac Rehabilitation: A Randomized, Controlled Trial. PLOS ONE, 7(7), e41199. doi:10.1371/journal.pone.0041199 Osborn, D., Wright, C., Levy, G., King, M., Deo, R., & Nazareth, I., 2008. Relative risk of diabetes, dyslipidaemia, hypertension and the metabolic syndrome in people with severe mental illnesses: systematic review and metaanalysis. BMC psychiatry, 8, 8484. doi:10.1186/1471-244X-8-84 Pearsall, R., Smith, D. J., Pelosi, A., & Geddes, J., 2014. Exercise therapy in adults with serious mental illness: a systematic review and meta-analysis. BMC psychiatry, 14(1), 117-117. doi:10.1186/1471-244X-14-117 Rabinowitz, J., Levine, S. Z., Garibaldi, G., Bugarski-Kirola, D., Berardo, C. G., & Kapur, S., 2012. Negative symptoms have greater impact on functioning than positive symptoms in schizophrenia: analysis of CATIE data. Schizophrenia research, 137(1-3), 147. doi:10.1016/j.schres.2012.01.015 Rickwood, D. J., Mazzer, K. R., Telford, N. R., Parker, A. G., Tanti, C. J., & McGorry, P. D., 2015. Changes in psychological distress and psychosocial functioning in young people visiting headspace centres for mental health problems. Medical Journal of Australia, 202(10), 537-542. doi:10.5694/mja14.01696 Romain, A. J., Fankam, C., Karelis, A., Letendre, E., Mikolajacks, G., Stip, E., & Abdel-Baki, A., 2018. Effect of interval training on metabolic risk factors in overweight individuals with psychosis: A randomized controlled trial. Schizophrenia Bulletin, 44, S17. doi:10.1093/schbul/sby014.039 Ross, N. R., Blair, S. S., Arena, A. R., Church, L. T., Després, A. J.-P., Franklin, D. B., Haskell, J. W., Kaminsky, S. L., Levine, S. B., Lavie, S. C., Myers, S. J., Niebauer, S. J., Sallis, S. R., Sawada, S. S., Sui, S. X., & Wisløff, S. U., 2016. Importance of Assessing Cardiorespiratory Fitness in Clinical Practice: A Case for Fitness as a Clinical Vital Sign: A Scientific Statement From the American Heart Association. Circulation, 134(24), e653-e699. doi:10.1161/CIR.0000000000000461 Scheewe, T. W., Backx, F. J. G., Takken, T., Jörg, F., Strater, A. C. P., Kroes, A. G., Kahn, R. S., & Cahn, W., 2013. Exercise therapy improves mental and physical health in schizophrenia: a randomised controlled trial. Acta Psychiatrica Scandinavica, 127(6), 464-473. doi:10.1111/acps.12029

Scheewe, T. W., Jorg, F., Takken, T., Deenik, J., Vancampfort, D., Backx, F. J. G., & Cahn, W., 2019. Low Physical Activity and Cardiorespiratory Fitness in People With Schizophrenia: A Comparison With Matched Healthy Controls and Associations With Mental and Physical Health. Frontiers in Psychiatry, 10. doi:10.3389/fpsyt.2019.00087 Schmitt, A., Maurus, I., Rossner, M. J., Röh, A., Lembeck, M., Von Wilmsdorff, M., Takahashi, S., Rauchmann, B., Keeser, D., Hasan, A., Malchow, B., & Falkai, P., 2018. Effects of Aerobic Exercise on Metabolic Syndrome, Cardiorespiratory Fitness, and Symptoms in Schizophrenia Include Decreased Mortality. Frontiers in Psychiatry, 9, 690-690. doi:10.3389/fpsyt.2018.00690 Schuch, F., Vancampfort, D., Richards, J., Rosenbaum, S., Ward, P., & Stubbs, B., 2016a. Exercise as a treatment for depression: A meta-analysis adjusting for publication bias. Journal of Psychiatric Research, 77, 42-51. doi:10.1016/j.jpsychires.2016.02.023 Schuch, F. B., Vancampfort, D., Richards, J., Rosenbaum, S., Ward, P. B., & Stubbs, B., 2016b. Exercise as a treatment for depression: A meta-analysis adjusting for publication bias. Journal of Psychiatric Research, 77, 42-51. doi:10.1016/j.jpsychires.2016.02.023 Seide, S. E., Röver, C., & Friede, T., 2019. Likelihood-based random-effects meta-analysis with few studies: empirical and simulation studies. BMC medical research methodology, 19(1), 16. doi:10.1186/s12874-018-0618-3 Soundy, A., Stubbs, B., Probst, M., Hemmings, L., & Vancampfort, D., 2014. Barriers to and Facilitators of Physical Activity Among Persons With Schizophrenia: A Survey of Physical Therapists. Psychiatric Services, 65(5), 693-696. doi:10.1176/appi.ps.201300276 Strassnig, M. T., Signorile, J. F., Potiaumpai, M., Romero, M. A., Gonzalez, C., Czaja, S., & Harvey, P. D., 2015. High velocity circuit resistance training improves cognition, psychiatric symptoms and neuromuscular performance in overweight outpatients with severe mental illness. Psychiatry Res, 229(1-2), 295-301. doi:10.1016/j.psychres.2015.07.007 Stubbs, B., Rosenbaum, S., Vancampfort, D., Ward, P. B., & Schuch, F. B., 2016. Exercise improves cardiorespiratory fitness in people with depression: A meta-analysis of randomized control trials. Journal of Affective Disorders, 190, 249-253. doi:10.1016/j.jad.2015.10.010 Stubbs, B., Vancampfort, D., Hallgren, M., Firth, J., Veronese, N., Solmi, M., Brand, S., Cordes, J., Malchow, B., Gerber, M., Schmitt, A., Correll, C., De Hert, M., Gaughran, F., Schneider, F., Kinnafick, F., Falkai, P., MöLler, H., & Kahl, K., 2018a. EPA guidance on physical activity as a treatment for severe mental illness: a meta-review of the evidence and Position Statement from the European Psychiatric Association (EPA), supported by the International Organization of Physical Therapists in Mental Health (IOPTMH). European Psychiatry, 54, 124-144. doi:10.1016/j.eurpsy.2018.07.004

Stubbs, B., Vancampfort, D., Hallgren, M., Firth, J., Veronese, N., Solmi, M., Brand, S., Cordes, J., Malchow, B., Gerber, M., Schmitt, A., Correll, C. U., De Hert, M., Gaughran, F., Schneider, F., Kinnafick, F., Falkai, P., MöLler, H.-J., & Kahl, K. G., 2018b. EPA guidance on physical activity as a treatment for severe mental illness: a meta-review of the evidence and Position Statement from the European Psychiatric Association (EPA), supported by the International Organization of Physical Therapists in Mental Health (IOPTMH). European Psychiatry, 54, 124-144. doi:10.1016/j.eurpsy.2018.07.004 Tanskanen, A., Tiihonen, J., & Taipale, H., 2018. Mortality in schizophrenia: 30‐year nationwide follow‐up study. Acta Psychiatrica Scandinavica, 138(6), 492-499. doi:10.1111/acps.12913 Thompson, D., Franklin, A., Balady, J., Blair, N., Corrado, A., Estes, E., Fulton, F., Gordon, L., Haskell, S., Link, J., Maron, A., Mittleman, K., Pelliccia, N., Wenger, N., Willich, N., & Costa, N., 2007a. Exercise and Acute Cardiovascular Events: Placing the Risks Into Perspective A Scientific Statement From the American Heart Association Council on Nutrition, Physical Activity, and Metabolism and the Council on Clinical Cardiology. Circulation, 115(17), 2358-2368. doi:10.1161/CIRCULATIONAHA.107.181485 Thompson, D. P., Franklin, A. B., Balady, J. G., Blair, N. S., Corrado, A. M. D., Estes, E. N., Fulton, F. J., Gordon, L. N., Haskell, S. W., Link, J. M., Maron, A. B., Mittleman, K. M., Pelliccia, N. A., Wenger, N. N., Willich, N. S., & Costa, N. F., 2007b. Exercise and Acute Cardiovascular Events: Placing the Risks Into Perspective A Scientific Statement From the American Heart Association Council on Nutrition, Physical Activity, and Metabolism and the Council on Clinical Cardiology. Circulation, 115(17), 2358-2368. doi:10.1161/CIRCULATIONAHA.107.181485 Tjønna, E. A., Lee, J. S., Rognmo, O. Ø., Stølen, M. T., Bye, P. A., Haram, Y. P., Loennechen, A. J., Al-Share, J. Q., Skogvoll, M. E., Slørdahl, M. S., Kemi, M. O., Najjar, M. S., & Wisløff, M. U., 2008. Aerobic Interval Training Versus Continuous Moderate Exercise as a Treatment for the Metabolic Syndrome: A Pilot Study. Circulation, 118(4), 346-354. doi:10.1161/CIRCULATIONAHA.108.772822 Vancampfort, D., Firth, J., Schuch, F. B., Rosenbaum, S., Mugisha, J., Hallgren, M., Probst, M., Ward, P. B., Gaughran, F., De Hert, M., Carvalho, A. F., & Stubbs, B., 2017a. 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, 16(3), 308-315. doi:10.1002/wps.20458 Vancampfort, D., Rosenbaum, S., Probst, M., Connaughton, J., Du Plessis, C., Yamamoto, T., & Stubbs, B., 2016a. What are the top 10 physical activity research questions in schizophrenia? Disability and Rehabilitation, 38(22), 2235-2243. doi:10.3109/09638288.2015.1116622

Vancampfort, D., Rosenbaum, S., Probst, M., Soundy, A., Mitchell, A. J., De Hert, M., & Stubbs, B., 2015. Promotion of cardiorespiratory fitness in schizophrenia: a clinical overview and meta‐analysis. Acta Psychiatrica Scandinavica, 132(2), 131-143. doi:10.1111/acps.12407 Vancampfort, D., Rosenbaum, S., Schuch, F., Ward, P., Probst, M., & Stubbs, B., 2016b. Prevalence and predictors of treatment dropout from physical activity interventions in schizophrenia: a meta-analysis. General Hospital Psychiatry, 39, 15-23. doi:10.1016/j.genhosppsych.2015.11.008 Vancampfort, D., Rosenbaum, S., Schuch, F., Ward, P., Richards, J., Mugisha, J., Probst, M., & Stubbs, B., 2017b. Cardiorespiratory Fitness in Severe Mental Illness: A Systematic Review and Meta-analysis. Sports Medicine, 47(2), 343-352. doi:10.1007/s40279016-0574-1 Vella, C. A., Taylor, K., & Drummer, D., 2017. High-intensity interval and moderate-intensity continuous training elicit similar enjoyment and adherence levels in overweight and obese adults. European Journal of Sport Science, 17(9), 1203-1211. doi:10.1080/17461391.2017.1359679 Weston, K. S., Wisløff, U., & Coombes, J. S., 2014. High-intensity interval training in patients with lifestyle-induced cardiometabolic disease: a systematic review and metaanalysis. British Journal of Sports Medicine, 48(16), 1227. doi:10.1136/bjsports-2013092576 Wewege, M. A., Ahn, D., Yu, J., Liou, K., & Keech, A., 2018. High-Intensity Interval Training for Patients With Cardiovascular Disease-Is It Safe? A Systematic Review. Journal of the American Heart Association, 7(21), e009305-e009305. doi:10.1161/JAHA.118.009305 Whyte, L. J., Gill, J. M. R., & Cathcart, A. J., 2010. Effect of 2 weeks of sprint interval training on health-related outcomes in sedentary overweight/obese men. Metabolism, 59(10), 1421-1428. doi:10.1016/j.metabol.2010.01.002 Wisløff, P. U., Støylen, M. A., Loennechen, E. J., Bruvold, A. M., Rognmo, J. Ø., Haram, L. P., Tjønna, M. A., Helgerud, M. J., Slørdahl, M. S., Lee, M. S., Videm, M. V., Bye, M. A., Smith, M. G., Najjar, M. S., Ellingsen, M. Ø., & Skjærpe, M. T., 2007. Superior Cardiovascular Effect of Aerobic Interval Training Versus Moderate Continuous Training in Heart Failure Patients: A Randomized Study. Circulation, 115(24), 30863094. doi:10.1161/CIRCULATIONAHA.106.675041 Wu, M. H., Lee, C. P., Hsu, S. C., Chang, C. M., & Chen, C. Y., 2015. Effectiveness of highintensity interval training on the mental and physical health of people with chronic schizophrenia. Neuropsychiatr Dis Treat, 11, 1255-1263. doi:10.2147/ndt.S81482

Fig. 1. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram.

Fig. 2. Forest plot showing changes in CRF pre and post HIIT. SD, Standard deviation; IV, inverse variance; CI, confidence interval, df, degrees of freedom.

Fig. 3. Changes in Cardiorespiratory fitness in HIIT and MCT conditions

Fig. 4. Changes in depression, pre and post HIIT

Fig. 5. Changes in depression in HIIT and MCT conditions

Table 1, Study Characteristics and feasibility Study

Exercise protocol

Exercise modality Supervisio n

AbdelBaki et al (2013)

HIIT: 10 intervals of 30-second running at 80 to 95% of maximal heart rate with 90second active recovery walks at 50 to 65% of maximal heart rate. CRF via Submax test.

Treadmill, aerobic Supervise d by kinesiologi st or kinesiolog y student

Duration of study Frequency*/w eek Duration of session 14 weeks 2*/ week. 30 mins total

Mins active exercise/ses sion

Drop outs HIIT/dro p outs in control

Average attendance (n/N), % completers

Details of adverse events

Motivatio nal Strategie s Y/N

HIIT: 20 mins

HIIT 9/25(36 %)

(20/28) 68.5%

No injuries stated. Dropped out due to physical discomfort (n=2)

Y

Chapma n et al (2017)

Gerber et al (2018)

HIIT: 3x4min bouts at 85–95% HRpeak, intersperse d with 3min recovery bouts 6070% HRpeak MCT 30min at 65– 75% Hrpeak CRF via maximal test HIIT: Wingatebased interval protocol: 25 repetitions of 30 seconds of active work 80% of VO2max, 30 s complete

Stationary bike/ treadmill, aerobic Supervise d by Personal trainer-1 session of homebased unsupervis ed exercise last 4 weeks

12 weeks duration 3*/week HIIT 25 mins MCT 35mins

HIIT: 21 mins MCT 30 mins

HIIT 4/8 (50%), MCT 3/8 (37.5%)

(total N=36) HIIT 81% MCT 86% of sessions.

Exacerbations of pre-existing conditions: HIIT: hip/back (n=2) MCT: shin/ankle (n=2).

N

Cycle ergometer, aerobic. Supervise d by a trained exercise coach

4 weeks duration 3*/week HIIT 35 mins MCT 30 mins

HIIT: 12.5 mins MCT 20 mins

HIIT 10/35 (28.5%), MCT 12 /37 (32.4%)

N/R

N/R

N

rest. Both groups calorically equivalent. CRF via Maximal test.

Hanssen et al (2018)

HIIT: 25 mins Wingatebased interval protocol of 25 repetitions of 30-s HIIT at 80% VO2max followed by 30 s total rest. (12.5 mins work, 12.5 mins rest). MCT - 20 mins, 60% VO2max. Both groups

Cycle ergometer, aerobic, Supervisio n N/R

4 weeks 3*/week HIIT 35 mins MCT 30 mins

HIIT: 12.5 mins MCT 20 mins

HIIT 6/25, (24%) MCT 7/22, (31.8%)

(total N=12) participation N/R (only included if completed 11/12 sessions)

N/R

N

were calorically equivalent CRF via Maximal test

Heggelu nd et al (2011)

HIIT: 4* 4min 85– 95% HRpeak, 3 min of active resting periods: work load correspond ing to 70% HRpeak. Control: 36 mins computer games CRF via Maximal test.

Treadmill, aerobic Supervise d by Exercise physiologi st

8 weeks 3*/week 36 mins

HIIT: 28 mins

HIIT 4/16 (25%) Control 2/9 (22%)

(N=24) HIIT 85% Control 83%

HIIT- ankle pain (n=1)

N

Romain et al (2018)

Strassni g et al (2015)

HIIT:10 intervals of 2 mins: 30 secs work 80% of theoretical maximum HR, increasing to 90% alternating with 90 secs active recovery (50-65% of max HR). Control: wait list CRF via Submax test HIIT: Maximum power pre tested for each exercise at different loads for 1RM - 3 circuits of 10–12

Treadmill, aerobic. Supervise d by kinesiologi st, kinesiolog y students, medical students

26 weeks duration. 2*/ week 30 mins

HIIT: 20 mins

HIIT 19/38 50% Control 3/28, 11%

HIIT (32/52) 64%

HIIT- back pain (n = 2), knee pain (n = 2), muscle pain (n = 1), cramps (n = 1), minor ankle sprain (n=1)

N

Resistanc e, 11 * upper and lower body computeriz ed Keiser pneumatic exercise machines, Supervisio n N/R

8 weeks 2*/ week Duration of HIIT N/R

N/R

HIIT 11/23 (47%)

N/R

Chest pain (n=1)

N

Wu et al (2015)

repetitions on resistance machines with minimal recovery between reps. 1–2 min rest between circuits HIIT: 95% of max. HR, 5 circuits of 10 seconds work, alternating ↑ amounts of rest (10 50 seconds)

Body weight exercises Supervisio n - N/R

8 weeks 3*/week HIIT 25 mins

HIIT: 9 mins

HIIT 2/20 (10%)

N/R

N/R

N

HIIT – high intensity interval training, MCT – moderate intensity continuous training, N/R – not reported, HRpeak – peak heart rate, VO2max – a measure of an individual’s ability to absorb and consume oxygen during exercise s – seconds, mins – minutes, max HR – maximal heart rate, CRF – cardiorespiratory fitness, Submax – submaximal fitness test, Maximal = maximal fitness test.

Table 2, Participants and Outcomes of Studies Study

Primary Outcomes

Patient group

Mean age, years

Duration illness, years

Study arms

RCT Key findings yes/no

Abdel-Baki et al (2013)

The feasibility of HIIT & effects on metabolic and physical/fitness

FEP

26

About 3.6

HIIT, no control

No

Participants completing the program had: PHYS: HIIT Improved CV fitness (↑ 38% VO2max*) & resting heart rate (↓8.6 bpm*) from baseline. FUNCT: No change in psychosocial (GAF, SOFAS) functioning or illness severity (CGI) MET: waist circumference (↓4.3cm*) from baseline. No other metabolic changes following HIIT

Chapman, et al (2017)

The feasibility & acceptability of HIIT

Any SMI: PSYCHOTIC SPECTRUM D/O’s, MDE

38

N/R

HIIT (n=8) MCT (n=8)

Yes

Intention to treat: PHYS: Compared to MCT: No difference between HIIT and MCT group for CV fitness, no within group improvement in CV fitness for either HIIT or MCT. MET: No impact of HIIT on any metabolic measures; No difference between HIIT & MCT for any metabolic measure. PSYCH: HIIT improved depression (↓35%*DASS21SR) from baseline. No difference between HIIT & MCT for depression.

Gerber et al (2018)

The effects of HIIT on exercise and sports motivation

MDD

33

average 4 in hospital

HIIT (n=`35) MCT (n=37)

Yes

PHYS: HIIT Increased CV fitness (↑2.4%*VO2max). No difference between MCT & HIIT for CV fitness. HIIT increased self-reported moderate intensity exercise mins/week (↑17%IPAQ*) & mod-vig. intensity mins/week (↑38% IPAQ*) from baseline. MCT increased self-reported moderate (16% v 407 %*), & mod-vig. mins/week more than HIIT (38 % v 306 %*) PSYCH: HIIT reduced depression (40% ↓*BDI-IISR) from baseline. No difference between HIIT & MCT for depression. Improvement in intrinsic and internal motivation for HIIT (self-determined motivation*). No difference between HIIT & MCT for self-determined motivation. No difference between HIIT & MCT in affective valence.

Hanssen et al (2008)

Effect of HIIT on depression index severity and arterial stiffness

MDD

38

N/R

HIIT (n=25) MCT (n=22)

Yes

PHYS: Neither HIIT nor MCT had a significant within group impact on CV fitness and no difference between HIIT & MCT. MCT reduced arterial stiffness significantly more than HIIT (↓5% HIIT v ↓ 36% MCT* PWR). MET: No within group or between group changes in systolic or diastolic BP. PSYCH: Compared to MCT, HIIT significantly improved depression (↓46% v 33%*BDI-IISR).

Heggelund et al (2011)

Effects of HIIT on CV risk and walking ability

PSYCHOTIC SPECTRUM D/O’s, DD

34

About 8.7

HIIT (n=16) Computer games control (n=9)

No

PHYS: Compared to computer games; HIIT improved CV fitness (↑12% v ↓1% VO2peak**), & walking efficiency (↑12% v no △ Enet*). PSYCH: HIIT resulted in no significant changes in depression (CDSS), or psychotic sx severity (PANSS). MET: Compared to computer games: HIIT significantly improved HDL (↑4% v ↓ 9%*). No significant difference in body weight or BMI. FUNCT: No significant changes in QoL (SF-36)

Minghetti et al (2018)

The effect of HIIT on depression and physical fitness (maximal and submaximal fitness)

MDD

36

N./R

HIIT (n=35) MCT (n=37)

Yes

PHYS: HIIT Improved CV fitness (↑6.2%*) from baseline. However, no significant difference between HIIT & MCT for CV fitness (6.2% v 6.6% MCT). PSYCH: HIIT reduced depression scores (↓42%*BDISR) for. No difference between HIIT & MCT for depression.

Romain et al (2018)

The effects of HIIT on anthropometrics (waist circumference)

BPAD & PSYCHOTIC SPECTRUM D/O’s

31

About 6.5

HIIT (n= 38) TAU (n= 28)

Yes

Intention to treat analysis. PHYS: HIIT Improved CV fitness (↑40%* estimated VO2max) from baseline. Wait list control did not assess CV fitness. MET: No change in waist circumference, or other metabolic markers. Post hoc analysis on participants with >64% session adherence compared to TAU; 3cm reduction in waist circumference. (↓3% v no △*) from baseline. No within group changes for TG. No changes to BSL, Cholesterol, BP - however all had normal baselines. PSYCH: Compared to TAU: HIIT improved negative symptoms, which worsened in TAU (HIIT↓ 17%* v TAU↑7.9%, PANSS). No changes in HIIT group for general or positive Sx. (PANSS)

Strassnig et al (2015)

The effects of HIIT on power, strength, body composition, physical function

PSYCHOTIC 44 SPECTRUM D/O’s & BPAD

About 12.5

HIIT (n=23)

No

PHYS: Improvement in power & strength*, across 6 tests of upper and lower body movements following HIIT. MET: HIIT had no impact on body weight, BMI, body fat%. PSYCH: HIIT improved total psychiatric Sx (↓7%*PANSS) & reduced depression (↓33%*CDSSCR) from baseline. FUNCT: HIIT Improved global functioning (↑16% *CGI) from baseline. Improvement in cognition: processing speed (↑23%*), & verbal memory (↑14%*) No changes to majority of other functioning tests (SPBB) except dryer loading.

Wu et al (2015)

The effects of HIIT on mental and physical health outcomes

SCZ

39

15.3 HIIT (n=20)

No

PHYS: Reduction in resting heart rate (↓4%*) & reduction in PP (↓20%*) from baseline following HIIT MET: HIIT reduced body weight (↓1kg *) & BMI, (↓ 0.1%*). Increase in diastolic BP (↑9%*) however remained in normal range and increase in MAP (↑3.5%*) from baseline. PSYCH: HIIT reduced negative sx (↓9%*PANSS) & total (↓8%*PANSS) & general psychopathology scores (↓13%*PANSS). Reduction in depressive sx (↓18%* BDISR) & anxiety (↓26.4%*BAI). No changes in positive symptoms.

PSYCHOTIC SPECTRUM D/O’s – psychotic spectrum disorders, BPAD – bipolar disorder, MDD – major depressive disorder, AFF – affective, NON- AFF – non affective psychosis, HIIT – high intensity interval training, MCT – moderate intensity continuous training, N/R – not reported, VO2max , VO2peak– a measure of an individual’s ability to absorb and consume oxygen during exercise s – seconds, mins – minutes, Sx – symptoms, PSYCH – Psychiatric, MET – metabolic, PHYS – physical health, FUNCT – functional, E-net – mechanical efficiency of walking, CV – cardiovascular, PANSS – positive and negative symptoms scale, BAI – Beck Anxiety Inventory, BDI – Beck Depression Inventory, BDI – II – Beck Depression Inventory Version 2, SPBB – moderate-vig. – moderate to vigorous minutes of exercise, MAP – mean arterial pressure, PP – Pulse pressure, CDSS – Calgary Depression Subscale, DASS- 21 – Depression and Anxiety Subscale 21, TAU – Treatment As Usual, PWR – Pulse Wave Reflection, BP – blood pressure, CGI – Clinical Global Impression, BSL – fasting blood sugar level, TG – fasting Triglyceride, QoL – quality of life, bpm – beats per minute, GAF – Global Assessment of Functioning, SOFAS – Social and Occupational Functioning, △ – change, BMI – body mass index, * p< 0.05, ** p< 0.01. SR Self report CRClinician rated