Citation: Cuenca-Martínez, F.;
Sempere-Rubio, N.; Varangot-Reille,
C.; Fernández-Carnero, J.; Suso-Martí,
L.; Alba-Quesada, P.; Touche, R.L.
Effects of High-Intensity Interval
Training (HIIT) on Patients with
Musculoskeletal Disorders:
A Systematic Review and Meta-
Analysis with a Meta-Regression and
Mapping Report. Diagnostics 2022, 12,
2532. https://doi.org/10.3390/
diagnostics12102532
Academic Editor: Koichi Nishimura
Received: 26 September 2022
Accepted: 13 October 2022
Published: 19 October 2022
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diagnostics
Systematic Review
Effects of High-Intensity Interval Training (HIIT) on Patients
with Musculoskeletal Disorders: A Systematic Review and
Meta-Analysis with a Meta-Regression and Mapping Report
Ferran Cuenca-Martínez 1,†
, Núria Sempere-Rubio 2,†
, Clovis Varangot-Reille 1
,
Josué Fernández-Carnero 3,4,*
, Luis Suso-Martí 1,*
, Patricio Alba-Quesada 1 and Roy La Touche 4,5,6
1
Exercise Intervention for Health Research Group (EXINH-RG), Department of Physiotherapy,
University of Valencia, 46022 Valencia, Spain
2
UBIC, Department of Physiotherapy, Faculty of Physiotherapy, Universitat de València, 46010 Valencia, Spain
3
Department of Physical Therapy, Occupational Therapy, Rehabilitation and Physical Medicine,
Rey Juan Carlos University, 28933 Madrid, Spain
4
Motion in Brains Research Group, Institute of Neuroscience and Sciences of the Movement (INCIMOV),
Centro Superior de Estudios Universitarios La Salle, Universidad Autónoma de Madrid, 28049 Madrid, Spain
5
Departamento de Fisioterapia, Centro Superior de Estudios Universitarios La Salle, Universidad Autónoma
de Madrid, 28049 Madrid, Spain
6
Instituto de Neurociencia y Dolor Craneofacial (INDCRAN), 28003 Madrid, Spain
*
Correspondence: josue.fernandez@urjc.es (J.F.-C.); luis.suso@uv.es (L.S.-M.);
Tel.: +34-914-88-88-00 (J.F.-C.); +34-963-98-38-55 (L.S.-M.)
†
These authors contributed equally to this work.
Abstract: The aim was to assess the impact of high-intensity interval training (HIIT) on patients
with musculoskeletal disorders. We conducted a search of Medline, Embase, PEDro, and Google
Scholar. We conducted a meta-analysis to determine the effectiveness of HIIT on pain intensity,
maximal oxygen consumption (VO2 max), disability, and quality of life (QoL). We employed the
GRADE and PEDro scales to rate the quality, certainty, and applicability of the evidence. Results
showed signiﬁcant differences in pain intensity, with a moderate clinical-effect (SMD = −0.73; 95%
CI: −1.40–−0.06), and in VO2 max, with a moderate clinical-effect (SMD = 0.69; 95% CI: 0.42–0.97).
However, the meta-analysis showed no statistically signiﬁcant results for disability (SMD = −0.34;
95% CI: −0.92–0.24) and QoL (SMD = 0.40; 95% CI: −0.80–1.60). We compared HIIT against other
exercise models for reducing pain intensity and increasing VO2 max. The meta-analysis showed no
signiﬁcant differences in favour of HIIT. Meta-regression analysis revealed that pain intensity scores
were negatively associated with VO2 max (R2 = 82.99%, p = 0.003). There is low-moderate evidence
that the HIIT intervention for patients with musculoskeletal disorders can reduce pain intensity and
increase VO2 max but has no effect on disability and QoL. Results also showed that HIIT was not
superior to other exercise models in reducing pain intensity and increasing VO2 max.
Keywords: high-intensity interval training; musculoskeletal pain; pain intensity; VO2 max; disability;
quality of life
1. Introduction
Musculoskeletal pain is an important public health issue because of its impact on
quality of life (QoL) and the disability it can represent [1]. More than 20% of the world’s
population is affected by painful conditions, contributing to the high consumption of health-
care resources [2]. Pain management can be approached from several perspectives, both
pharmacological and non-pharmacological, the latter of which includes physical agents,
manual therapy, psychosocial interventions, patient education, and exercise training [3,4].
Exercise therapy has been reported to be highly effective in managing patients with
musculoskeletal pain [5] and has been shown to produce hypoalgesia by releasing beta-
endorphins or endocannabinoids [6–8]. Exercise therapy also interacts with the autonomic,
Diagnostics 2022, 12, 2532. https://doi.org/10.3390/diagnostics12102532
https://www.mdpi.com/journal/diagnostics
Diagnostics 2022, 12, 2532
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cognitive, and affective aspects of pain [9,10]. For example, a recent meta-analysis found
that aerobic exercise led to reduced pain intensity, duration, and frequency as well as
improved QoL for patients with migraines [11].
The effects of high-intensity interval training (HIIT) on pain tolerance and threshold
have sparked interest among the scientiﬁc community concerned with pain [12,13]. As
described by Andreato, HIIT is a form of training that alternates high-intensity exercises
at 90% or more of the maximal oxygen consumption (VO2 max) (or ≥80% VO2 max for
the clinical population) with recovery periods, repeating the exercise several times [14].
A number of articles have recently shown that HIIT could improve pain-related clinical
variables in patients with musculoskeletal disorders [15–17]. To date, systematic reviews
on HIIT have mainly focused on patients with cardiovascular diseases, cancer, or obesity,
where HIIT has shown great effectiveness in modifying cardiorespiratory variables [18–20].
Picavet et al. found that disability and quality of life are commonly affected in patients
with musculoskeletal disorders [1]. This work prompted us to include these two variables
in our study, with the objective of evaluating the role of this therapeutic exercise model on
this clinical population of patients with musculoskeletal disorders. In addition to this, we
wanted to include the pain intensity variable because almost 1/5 of the world’s population
lives with clinical conditions that involve pain [2]. Finally, we also wanted to include
the variable VO2 max because it is an objective variable and, in addition, it is the gold
standard for assessing cardiorespiratory ﬁtness, which seems to be affected in patients
with musculoskeletal disorders with associated pain [21]. As far as we know, no published
review has assessed the effects of HIIT on clinical and cardiorespiratory variables in patients
with musculoskeletal disorders and pain.
Therefore, the main aim of the present study was to develop a systematic review and
meta-analysis to assess the effectiveness of HIIT on pain intensity, maximal oxygen con-
sumption, disability, and health-related QoL for patients with musculoskeletal disorders.
2. Materials and Methods
This systematic review and the meta-analysis were performed according to the Pre-
ferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines
described by Moher [22]. The protocol of this systematic review and meta-analysis was reg-
istered in an international registry prior to starting the review (Prospero: CRD42020216298
(5 November 2020)).
2.1. Inclusion Criteria
The selection criteria used in this systematic review and meta-analysis were based
on methodological and clinical factors, such as the Population, Intervention, Control,
Outcomes, and Study Design (PICOS) described by Stone [23].
2.1.1. Population
The participants selected for the studies were patients older than 18 years with any
kind of musculoskeletal disorder. The participants’ gender was irrelevant.
2.1.2. Intervention and Control
The intervention was the HIIT exercise modality, which could be given as an indepen-
dent treatment, added to an existing intervention, or embedded in an existing intervention
(e.g., usual care and treatment). For the control group, the comparators were minimal
intervention, no intervention, and usual care (e.g., maintenance of the habitual daily physi-
cal activity proﬁle, standard physical activity recommendations, physical exercise habits,
and exercise intervention [excluding HIIT modality]) in combination or not with placebo
interventions. In addition, we performed a sub-analysis to evaluate the effectiveness of
HIIT compared with other therapeutic exercise models (e.g., moderate-intensity exercise,
high-intensity continuous training, and home exercises) in those articles that, in addition
Diagnostics 2022, 12, 2532
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to a control or comparator with no intervention or minimal intervention, presented an
additional group that performed an exercise model.
2.1.3. Outcomes
The measures used to assess the results and effects were pain intensity, VO2 max,
disability, and health-related QoL.
2.1.4. Study Design
We selected randomised controlled trials (RCTs), randomised parallel-design con-
trolled trials, randomised cross-over trials, and prospective controlled clinical trials.
2.2. Search Strategy
The search for studies was performed using Medline (PubMed) (1950–2020), Embase
(1950–2020), PEDro (1950–2020), and Google Scholar. The ﬁrst search was run on the
8 November 2020 (however, the search was updated on 31 January 2022). We used a
validated search ﬁlter for retrieving studies on measurement properties in PubMed; the
same ﬁlter was adapted for all other databases [24]. In addition, the search was adapted
and performed in Google Scholar due to its capacity to search for relevant articles and grey
literature [25,26]. No restrictions were applied to any speciﬁc language as recommended
by the international criteria [27]. The search strategy combined medical subject headings
(MeSH) and non-MeSH terms, adding a Boolean operator (OR and/or AND) to combine
them. The terms were as follows: “Hig- Intensity Interval Training”, “High-Intensity Inter-
val Trainings”, “Interval Training, High-Intensity”, “Interval Trainings, High Intensity”,
“Training, High-Intensity Interval”, “Trainings, High-Intensity Interval”, “High-Intensity
Intermittent Exercise”, “Exercise, High-Intensity Intermittent”, “Exercises, High-Intensity
Intermittent”, “High-Intensity Intermittent Exercises”, “Sprint Interval Training”, “Sprint
Interval Trainings”, “Pain”, “Chronic Pain”, “Musculoskeletal Pain”, “Pain intensity”, “Dis-
ability”, “Quality of Life”, “VO2 max”, “Maximal Oxygen Consumption”, and “Maximal
Oxygen Uptake”.
Two independent reviewers (F.C.-M. and J.F.-C.) conducted the search using the same
methodology, and the differences were resolved by consensus. Additionally, meticulous
manual searches were performed, including journals that have published articles related
to the topic of this review as well as reference lists of the included studies. The reference
sections of the original studies were screened manually. To remove duplicates, we employed
the citation management software Mendeley (Mendeley desktop v1.17.4, Elsevier, New
York, NY, USA) and hand-checked the citations [28].
2.3. Selection Criteria and Data Extraction
First, two independent reviewers (F.C.M. and L.S.M.), who assessed the relevance
of the RCTs regarding the study questions and aims, performed a data analysis, which
was performed based on information from the title, abstract, and keywords of each study.
If there was no consensus or the abstracts did not contain sufﬁcient information, the full
text was reviewed. In the second phase of the analysis, the full text was used to assess
whether the studies met all the inclusion criteria. Differences between the two independent
reviewers were resolved by a consensus process moderated by a third reviewer [29]. Data
described in the results were extracted by means of a structured protocol that ensured that
the most relevant information was obtained from each study [30].
2.4. Methodological Quality Assessment
We used the Cochrane Handbook for Systematic Reviews of Interventions version
5.1.0 to assess the risk of bias in the included studies [30]. The assessment tool covers a total
of 7 domains: (1) random sequence generation (selection bias), (2) allocation concealment
(selection bias), (3) blinding of participants and personnel (performance bias), (4) blinding
of outcome assessments (detection bias), (5) incomplete outcome data (attrition bias),
Diagnostics 2022, 12, 2532
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(6) selective reporting (reporting bias), and (7) other biases. Bias was assessed as low risk,
high risk, or unclear risk.
The studies’ methodological quality was assessed using the PEDro scale [31], which
assesses the internal and external validity of a study and consists of 11 criteria: (1) spec-
iﬁed study eligibility criteria, (2) random allocation of patients, (3) concealed allocation,
(4) measure of similarity between groups at baseline, (5) patient blinding, (6) therapist
blinding, (7) assessor blinding, (8) fewer than 15% dropouts, (9) intention-to-treat analysis,
10) intergroup statistical comparisons, and 11) point measures and variability data. The
methodological criteria were scored as follows: yes (1 point), no (0 points), or do not
know (0 points). The PEDro score for each selected study provided an indicator of the
methodological quality (9–10 = excellent; 6–8 = good; 4–5 = fair; 3–0 = poor) [32]. We used
the data obtained from the PEDro scale to map the results of the quantitative analyses.
Two independent reviewers (F.C.-M. and L.S.-M.) examined the quality of all the
selected studies using the same methodology. Disagreements between the reviewers were
resolved by consensus with a third reviewer. The concordance between the results (inter-
rater reliability) was measured using Cohen’s kappa coefﬁcient (κ) as follows: (1) κ > 0.7
indicated a high level of agreement between assessors; (2) κ = 0.5–0.7 indicated a moderate
level of agreement; and (3) κ < 0.5 indicated a low level of agreement) [33].
2.5. Evidence Map
We created a visual map of the scientiﬁc evidence for each article to visually display
the information as a bubble plot. The review information is based on 3 dimensions:
1.
Type of outcome measure (bubble colour): The bubble colour represents the variables
(pain intensity, blue; VO2 max, violet; disability, green; QoL, black).
2.
Variable (x-axis): We employed the calculation of effect sizes.
3.
Effect (y-axis): Each of the reviews was classiﬁed according to its methodological
quality using the PEDro scale.
4.
Statistically signiﬁcant differences: Articles with statistically signiﬁcant differences
were marked with white dots.
2.6. Certainty of Evidence
The certainty of evidence analysis was based on classifying the results into levels
of evidence according to the Grading of Recommendations, Assessment, Development,
and Evaluation (GRADE) framework, which is based on ﬁve domains: study design,
imprecision, indirectness, inconsistency, and publication bias [34]. The assessment of the
ﬁve domains was conducted according to GRADE criteria [35,36]. Evidence was categorised
into the following four levels accordingly: (a) High quality. Further research is very unlikely
to change our conﬁdence in the effect estimate. All ﬁve domains are also met; (b) Moderate
quality. Further research is likely to have an important impact on our conﬁdence in the effect
estimate and might change the effect estimate. One of the ﬁve domains is not met; (c) Low
quality. Further research is very likely to have a signiﬁcant impact on our conﬁdence in the
effect estimate and is likely to change the estimate. Two of the ﬁve domains are not met;
and, ﬁnally, (d) Very low quality. Any effect estimates are highly uncertain. Three of the
ﬁve domains are not met [35,36].
For the study design domain, the recommendations were downgraded one level
in the event there was an uncertain or high risk of bias and serious limitations in the
effect estimate (more than 25% of the participants were from studies with fair or poor
methodological quality, as measured by the PEDro scale). In terms of inconsistency, the rec-
ommendations were downgraded one level when the point estimates varied widely among
studies, the conﬁdence intervals showed minimal overlap, or when the I2 was substantial
or large (greater than 50%). At indirectness domain recommendations were downgraded
when severe differences in interventions, study populations or outcomes were found (the
recommendations were downgraded in the absence of direct comparisons between the
interventions of interest or when there are no key outcomes, and the recommendation is
Diagnostics 2022, 12, 2532
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based only on intermediate outcomes or if more than 50% of the participants were outside
the target group). For the imprecision domain, the recommendations were downgraded by
one level if there were fewer than 300 participants for the continuous data [37].
2.7. Data Synthesis and Analysis
The statistical analysis was conducted using MetaXL software (version 5.3 (EpiGear
International, Sunrise Beach, Queensland, Australia) [38]. To compare the outcomes re-
ported by the studies, we calculated the standardised mean difference (SMD) over time
and the corresponding 95% conﬁdence interval (CI) for the continuous variables. The
statistical signiﬁcance of the pooled SMD was examined as Hedges’ g to account for a
possible overestimation of the true population effect size in the small studies [39].
We used the same inclusion criteria for the systematic review and the meta-analysis
and included three additional criteria: (1) In the results, there was detailed information
regarding the comparative statistical data of the exposure factors, therapeutic interventions,
and treatment responses; (2) the intervention was compared with a similar control group;
and (3) data on the analysed variables were represented in at least three studies.
The estimated SMDs were interpreted as described by Hopkins et al. [40], that is,
we considered that an SMD of 4.0 represented an extremely large clinical effect, 2.0–4.0
represented a very large effect, 1.2–2.0 represented a large effect, 0.6–1.2 represented a
moderate effect, 0.2–0.6 represented a small effect, and 0.0–0.2 represented a trivial effect.
We estimated the degree of heterogeneity among the studies using Cochran’s Q statistic
test (a p-value < 0.05 was considered signiﬁcant) and the inconsistency index (I2) [40].
We considered that an I2 > 25% represented small heterogeneity, I2 > 50% represented
medium heterogeneity, and I2 > 75% represented large heterogeneity [41]. The I2 index is a
complement to the Q test, although it has the same problems of power with a small number
of studies [41]. When the Q-test was signiﬁcant (p < 0.1) and/or the result of I2 was >75%,
there was heterogeneity among the studies, and the random-effects model was conducted
in the meta-analysis. To detect publication bias and to test the inﬂuence of each individual
study, we performed a visual evaluation of the Doi plot [42], seeking asymmetry. We also
performed a quantitative measure of the Luis Furuya-Kanamori (LFK) index, which has
been shown to be more sensitive than the Egger test in detecting publication bias in a meta-
analysis of a low number of studies [43]. An LFK index within ±1 represents no asymmetry,
exceeding ±1 but within ±2 represents minor asymmetry, and exceeding ±2 involves
major asymmetry. To test each study’s inﬂuence, we visually examined the forest plot and
performed an exclusion sensitivity analysis. Lastly, we applied a meta-regression analysis
to analyse the relationship between pain intensity and VO2 max variables using a random
effects model employing the effect size statistic (Hedges’ g) of the pain intensity scores to
correlate with the VO2 max scores [44].
3. Results
The study search strategy was presented in the form of a ﬂow diagram (Figure 1).
3.1. Characteristics of the Included Studies
The patients were diagnosed with a persistent musculoskeletal pain condition [2 knee
osteoarthritis studies [45,46], two axial spondylarthritis studies [16,47], three studies on
chronic nonspeciﬁc low back pain [17,48,49], one study on episodic migraineurs [50], one
study on ﬁbromyalgia [15], one study on subacromial pain syndrome [51], one study
on rheumatoid arthritis and adult-juvenile idiopathic arthritis [52], and one study on
general persistent pain condition with previous trauma [53], and all of them evaluated
pain intensity, VO2 max, disability, and health-related QoL. Table 1 lists the descriptive
characteristics of the included studies.
Diagnostics 2022, 12, 2532
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3.2. Interventions
In all groups, HIIT was compared to other types of training or interventions (including
controls and no interventions), with the exception of Bressel et al. [45], which studied a
single HIIT and balance training group, and Sveaas et al. (2014 & 2019) [16,47], which
included an HIIT and moderate-intensity continuous training (MICT) group and another
no exercise group. Of the studies referred to above, three had two groups: one HIIT group
and one MICT group [15,17,46]. Atan and Karavelio˘glu [15] included a third standard
care group. Two other studies had only one HIIT and one standard care group [48,51].
Two studies had an HIIT group and another group that maintained the activities of daily
living [52] and their usual physical activity [54]. Flehr et al. [53] had one HIIT group and
one yoga group, while Verbrugghe et al. [49] studied four groups with different types of
HIIT. The total duration of the intervention ranged from 6 to 12 weeks, with most studies
having a frequency of two to three times per week, except for Keogh et al. [46] and Atan
and Karavelio˘glu [15], which had frequencies of four and ﬁve times per week, respectively.
Table 2 presents extensive details on the intervention characteristics of the included studies.
, 12, x FOR PEER REVIEW 
6 of 32 
 
Figure 1. PRISMA Flowchart for selecting studies. 
3.1. Characteristics of the Included Studies 
The patients were diagnosed with a persistent musculoskeletal pain condition [2 
knee osteoarthritis studies [45,46], two axial spondylarthritis studies [16,47], three studies 
on chronic nonspecific low back pain [17,48,49], one study on episodic migraineurs [50],
Figure 1. PRISMA Flowchart for selecting studies.
Diagnostics 2022, 12, 2532
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Table 1. Characteristics of the included studies.
Author, Year
Country
Population
Disease
(n)
Age (Years)
Sex (%)
Diagnostic Criteria
Disease Duration (Years)
Study Design—Duration
Intervention(s) and Control Group
(n)
Outcome Measured
(Instrument)
Results
Atan et al., 2020 [15]
Turkey
Fibromyalgia
(n = 55)
Age, 48.7 ± 9.1 y
100% F
American College of Rheumatology 2016
diagnostic criteria
Duration, 2.5 ± 1.6 y
Pilot ROT—6 weeks
Intervention
- HIIT (n = 19)
- MICT (n = 19)
Control
Usual care (n = 17)
- Pain Intensity (VAS)
- HRQoL (SF-36 PF, PRL, Pain, GH, V, SF,
ER, MH, EWB, E/F, HC)
- VO2 max (mL/kg/min)
HIIT showed signiﬁcant differences
compared with a control group on pain
intensity, VO2 max, and SF-36 PF, PRL, ER,
E/F, EWB, GH, and HC (p < 0.05) but no
signiﬁcant difference compared with MCT.
Berg et al., 2020 [50]
Norway
Chronic SAPS
(n = 21)
Age, 48.1 ± 12.5 y
48% F/52% M
Clinical criteria
Duration, 3.5 ± 4.8 y
RCT—8 weeks
Intervention
HIIT + Home-exercise (n = 13)
Control
Home-exercise (n = 8)
- Pain intensity (NPA)
- Disability (SPADI)
HIIT showed signiﬁcant intragroup (p < 0.05)
and intergroup differences (p < 0.05)
compared with a control group in terms of
disability but no signiﬁcant difference in
pain intensity.
Bressel et al., 2014 [44]
United States
Knee OA
(n = 18)
Age, 64.5 ± 10.2 y
89% F/11% M
Clinical and radiological criteria
Duration, 6.8 ± 7.4 y
Pre-post study—6 weeks
Intervention
- HIIT + Balance training (n = 18)
Control
No intervention (n = 18)
Pain Intensity (VAS)
HIIT showed a signiﬁcant improvement in
pain intensity (p < 0.05).
Flehr et al., 2019 [52]
Australia
Persistent pain condition
(n = 32)
Age, 30.2 ± 8 y
100% F
N/R
Duration, More than 12 months
RCT—8 weeks
Intervention
HIIT (n = 15)
Control
Bikram Yoga (n = 17)
- Pain Intensity (BPI)
- HRQoL (SF-36 PF, PRL, Pain, GH, V, SF,
ER, MH)
No signiﬁcant difference between HIIT and
Bikram Yoga in pain intensity. There was a
signiﬁcant intergroup difference on quality
of life (SF-36 PF: p = 0.019; SF-36 MH:
p = 0.005), with yoga showing higher
improvement (SF-36 PF: M = 80.91; SF-36
MH: M= 63.94).
Hanssen et al., 2018 [49]
Switzerland
Episodic migraine without aura
(n= 36)
Age, 36.8 ± 10.3 y
81% F/19% M
International classiﬁcation of headache disorders,
3rd ed.
Duration, N/R
RCT—12 weeks
Intervention
- HIIT (n = 13)
- MICT (n = 11)
Control Group
No intervention (n = 12)
VO2 max
(mL/kg/min)
No group × time interaction between the
three groups (p = 0.14).
Diagnostics 2022, 12, 2532
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Table 1. Cont.
Author, Year
Country
Population
Disease
(n)
Age (Years)
Sex (%)
Diagnostic Criteria
Disease Duration (Years)
Study Design—Duration
Intervention(s) and Control Group
(n)
Outcome Measured
(Instrument)
Results
Keogh et al., 2018 [45]
Australia
Knee OA
(n = 17)
Age, 62.4 ± 8.3 y
76% F/24% M
Diagnosis by an orthopaedic surgeon
Duration, 4.7 ± 4.6 y
Pilot RCT—8 weeks
Intervention
HIIT (n = 9)
Control
MICT (n = 8)
- Disability (WOMAC, Lequesne Index)
Both interventions demonstrated signiﬁcant
beneﬁts on the WOMAC (HIIT: p = 0.05;
MICT: p = 0.006) but without intergroup
differences. No patient had signiﬁcant
improvement in the Lequesne index.
Sandstad et al., 2015 [51]
Norway
RA and JIA
(n = 27)
Age, 33.0 ± 8.1 y
100% F
Diagnosis by a rheumatologist
Duration, N/R
Cross-over trial—10 weeks
Intervention
HIIT (n = 12)
Control
No intervention (n = 15)
- Pain Intensity (VAS)
- Disability (MHAQ)
- VO2 max (mL/kg/min)
HIIT had a signiﬁcant improvement in
VO2 max (p < 0.001) but no difference in pain
intensity and disability.
Sveaas et al., 2014 [49]
Norway
axSpA
(n = 24)
Age, 48.5 ± 12.0 y
50% F/50% M
Spondyloarthritis International Society criteria
Duration, 24.9 ± 15.8 y
Pilot RCT—12 weeks
Intervention
HIIT (n = 10)
Control
Usual care (n = 14)
VO2 max (mL/kg/min)
HIIT had a signiﬁcantly higher VO2 max at
12 weeks than the control group (p < 0.001)
Sveaas et al., 2019 [16]
Norway
axSpA
(n = 97)
Age, 46.2 ± N/R y
53% F/47% M
Spondyloarthritis International Society criteria
Duration, N/R
RCT—12 weeks
Intervention
HIIT (n = 48)
Control
No intervention (n = 49)
- Pain intensity (BASDAI neck/back/hip
and peripheral pain)
- VO2 max (mL/kg/min)
HIIT signiﬁcantly improves the
neck/back/hips, and peripheral pain
intensity, and the VO2 max more than the
control group (p < 0.001; p = 0.016; p < 0.001).
Thomsen et al., 2019 [53]
Norway
PsA
(n = 67)
Age, 48.0 ± 11.5 y
64% F/36% M
Classiﬁcation of psoriatic arthritis
Study group criteria
Duration, N/R
RCT—11 weeks
Intervention
HIIT (n = 32)
Control
No intervention (n = 35)
- Pain Intensity (VAS)
HIIT showed no clear effect on pain intensity
at the end of the intervention and at
9 months of follow-up.
Diagnostics 2022, 12, 2532
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Table 1. Cont.
Author, Year
Country
Population
Disease
(n)
Age (Years)
Sex (%)
Diagnostic Criteria
Disease Duration (Years)
Study Design—Duration
Intervention(s) and Control Group
(n)
Outcome Measured
(Instrument)
Results
Verbrugghe et al., 2018
[47]
Belgium
Nonspeciﬁc Chronic LBP
(n = 20)
Age, N/R
55% F/45% M
Clinical criteria
Duration, N/R
CCT—6 weeks
Intervention
HIIT (n = 10)
Control
Usual care (n = 10)
- Pain Intensity (NPRS)
- Disability (RMDQ)
- HRQoL (SF-36 PF, PRL, ER, E/F, EWB,
SF, Pain, GH)
- VO2 max (mL/kg/min)
Both groups had a reduction in disability
(p < 0.05) with no intergroup difference. HIIT
improved signiﬁcantly HRQoL (SF-36 PRL,
ER, SF, and Pain) (p < 0.05) but with no
intergroup differences.
Verbrugghe et al., 2019
[17]
Belgium
Nonspeciﬁc Chronic LBP
(n = 36)
Age, 44.2 ± 9.8 y
68% F/32% M
Clinical criteria
Duration, 11.1 ± 7.7 y
RCT—12 weeks
Intervention
HIIT (n = 18)
Control
MIT (n = 18)
- Pain Intensity (NPRS)
- Disability (MODI)
- VO2 max (mL/kg/min)
HIIT signiﬁcantly improved disability and
VO2 max more than MIT (p < 0.05). HIIT
signiﬁcantly reduced pain intensity (p < 0.05)
but with no signiﬁcant differences with MIT.
Verbrugghe et al., 2020
[48]
Belgium
Nonspeciﬁc chronic LBP
(n = 80)
Age, 44.1 ± 9.7 y
58% F/42% M
Clinical criteria
Duration, 13.4 ± 9.1 y
RCT—12 weeks
Intervention
- HITCOM (n = 19)
- HITSTRE (n = 21)
- HITSTAB (n = 20)
- HITMOB (n = 20)
- Pain Intensity (NPRS)
- Disability (MODI)
- VO2 max (mL/kg/min)
All four HIIT groups signiﬁcantly reduced
pain intensity and disability and increased
VO2 max (p < 0.05), with no intergroup
differences.
axSpA, axial spondyloarthritis; BPI, Brief Pain Inventory; CCT, Controlled clinical trial; E/F, energy/fatigue; ER, emotional role limitation; EWB, emotional well-being; GH, general
health; HC, health change; HIIT, high-intensity interval training; HITCOM, high-intensity general resistance training, and high-intensity core strength training; HITMOB, trunk mobility
exercises; HITSTAB, high-intensity core strength training; HITSTRE, high-intensity general resistance training; HRQoL, health-related quality of life; JIA, juvenile idiopathic arthritis;
LBP, low back pain; MCT, moderate continuous training; MH, mental health; MHAQ, Modiﬁed Health Assessment Questionnaire; MICT, moderate-intensity continuous training;
MIT, moderate-intensity training; MODI, Modiﬁed Oswestry Index; MPQ, McGill Pain Questionnaire; N/R, not reported; NPRS, Numeric Pain Rating Scale; OA, osteoarthritis; ODI,
Oswestry Disability Index; PF, physical functioning; PRL, physical role limitation; PsA, psoriatic arthritis; RA, rheumatoid arthritis; RCT, randomised control trial; RMDQ, Roland-Morris
Disability Questionnaire; SF-36, Short Form-36 Health Survey; SAPS, subacromial pain syndrome; SF, social functioning; SPADI, Shoulder Pain and Disability Index; V, vitality; VAS,
visual analogue scale; WOMAC, Western Ontario and McMaster Universities Osteoarthritis Index.
Diagnostics 2022, 12, 2532
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Table 2. Prescription parameters extracted from each included study.
Trial
Group
Exercise Protocol
(Distribution and Exercise Type)
Intensity
(Pain Control during Training)
Frequency
and Duration
Exercise Testing
Atan et al.,
2020 [15]
HIIT (AerT) + StrT +
Stretching
Total exercise duration: 35 min
Warmup and cooldown: 5 min stationary cycling.
HIIT protocol: 4 × 4 min of high-intensity stationary cycling interval alternating
with 3 min cycling recovery periods.
Work/rest ratio: [1:0.75]
Followed by 10 min full body (shoulder, arm, leg, and hip) StrT, using 1–3-kg
weights (1 × 8–10 rep) and 5 min stretching (4–5 × 20–30 s for each muscle group).
Measurement: HRmax (Monitorisation:
N/R)
Warmup and cooldown: 50% HRmax
HIIT:
Interval: 80–95% HRmax
Active Rest: 70% HRmax
StrT: N/R
Pain: N/R
5×/week
6 weeks
Maximal
cardiopulmonary test on
a cycloergometer at
baseline and follow-up.
HRmax, VO2 max, BP,
workload, MET and
duration-of-test were
recorded.
MICT (AerT) + StrT
+ Stretching
Total exercise duration: 55 min.
Warmup and cooldown: 5 min stationary cycling.
MICT protocol: 45 min continuous stationary cycling
Followed by 10 min full body (shoulder, arm, leg, and hip) StrT, using 1–3-kg
weights (1 × 8–10 rep) and 5 min stretching (4–5 × 20–30 s for each muscle group).
Measurement: HRmax (Monitorisation:
N/R)
Warmup and cooldown: 50% HRmax
MICT: 65–70% HRmax
StrT: N/R
Pain: N/R
Usual Care
Recommendations regarding exercise for ﬁbromyalgia.
N/A
Berg et al.,
2020 [50]
HIIT (StrT) + Usual
Care
HIIT protocol: 4 × 4 min shoulder abduction-adduction at 2 Hz intervals alternating
with 3 min walking rest periods
Work/Rest Ratio: [1:0.75]
If the patient was able to continue the ﬁnal interval for one additional minute, the
workload was increased by 250 g in the following session.
Home-based exercises: Scapular stabilising, rotator cuff, and pain-free ROM exercises.
Measurement: WRmax
Interval: 80% WRmax
Rest: N/R
Pain: When pain exceeds 5/10, session
was ended.
3×/week
8 weeks
Time to exhaustion test
during shoulder
abduction-adduction.
WRmax was recorded.
Usual Care
Home-based exercises: Scapular stabilising, rotator cuff, and pain-free ROM exercises.
N/R
Bressel et al.,
2014 [44]
BalanceT +
HIIT (AerT)
Balance training: Perturbations with water jets.
Followed by: HIIT protocol: (Progressive increase from 1st to 6th week) 3 to 6 × 0.5
to 2.5 min walking (1.3 to 2.1 m/s) on an underwater treadmill interval alternating
with 1 to 2.5 min walking (1.3 to 1.8 m/s) rest periods. (depth: xiphoid process)
Work/rest ratio: [1:2; 1:1.3; 1:1; 1:1; 1:1; 1:1]
Measurement: RPE (Borg Scale/20)
BalanceT:
Progressive increase (from 1st to 6th
week) from 11 to 18/20.
HIIT:
Interval: Progressive increase (from 1st
to 6th week) from 13 to 19/20.
Rest: 10/20.
Pain: N/R
3×/week
6 weeks
N/A
Diagnostics 2022, 12, 2532
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Table 2. Cont.
Trial
Group
Exercise Protocol
(Distribution and Exercise Type)
Intensity
(Pain Control during Training)
Frequency
and Duration
Exercise Testing
Flehr et al.,
2019 [52]
HIIT (StrT + AerT)
45 min functional training incorporating running, throwing, standing from a seated
position, placing items overhead, and picking items up.
Warmup and demonstration: 15 min.
Movement learning: 15 min
HIIT protocol: 15 min reproduction of the movement at high intensity. Four formats
possible: As fast as possible, 8-exercises Tabata intervallic training followed by
AerT, Maximum reps or load in a set time, or as many rounds as possible in 12 min
followed by AerT
N/R
Interval: N/R
Rest: N/R
Pain: N/R
3×/week
8 weeks
N/R
Yoga
90 min Bikram Yoga class (Room at 40 ◦C and 40% humidity): Deep breathing, 45 to
50 min standing, stretching, and relaxation postures.
Light to moderate (according to ACSM)
and sometimes vigorous.
Pain: N/R
Hanssen et al.,
2018 [49]
HIIT (AerT)
Warmup: 400 m of light running on a treadmill and 2 skipping exercises
HIIT protocol: 4 × 4 min high-intensity running on a treadmill, interval alternating
with 3 min running recovery periods.
Work/rest ratio: [1:0.75]
Cooldown: 400 m of light running and stretching
Measurement: HRmax (HR checked
using HR monitor)
Interval: 90% to 95% HRmax (±5 bpm)
Rest: 70% of HRmax
Pain: N/R
2×/week
12 weeks
Maximal
Cardiopulmonary test on
a treadmill. Anaerobic
lactate-threshold, HRmax,
RPE, and VO2 max were
recorded.
MICT (AerT)
Warmup: 400 m of light running on a treadmill and 2 skipping exercises
MICT protocol: 45 min continuous running on a treadmill.
Cooldown: 400 m of light running and stretching
Measurement: HRmax (HR checked
using HR monitor)
MICT: 70% HRmax (± 5 bpm)
Pain: N/R
Maintain their
habitual daily
physical activity
N/A
N/A
Keogh et al.,
2018 [45]
HIIT (AerT)
Warmup: 7 min stationary cycling, with progressively increasing intensity
HIIT protocol: 5 × 45 s high-cadence stationary cycling interval alternating with 90 s
low-intensity recovery cycling.
Work/Rest Ratio: [1:2]
Cooldown: 6–7 min of light to moderate cycling.
HIIT:
Interval: 110 rpm with a resistance
similar or slightly higher than the rest.
Intensity was deﬁned as “an intensity
at which you felt it was quite difﬁcult to
complete sentences during the
exercise”.
Rest: ∼70 rpm
To avoid pain, progressive increase in
initial sessions.
4×/week
8 weeks
N/R
MICT (AerT)
Warmup and cooldown: Light intensity cycling for 3 min and 2 min, respectively.
MICT protocol: 20 min continuous cycling.
MICT: 60–80 rpm. Intensity was
deﬁned as “An intensity at which you
are able to speak in complete sentences
during the exercise”.
To avoid pain, progressive increase in
initial sessions
Diagnostics 2022, 12, 2532
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Table 2. Cont.
Trial
Group
Exercise Protocol
(Distribution and Exercise Type)
Intensity
(Pain Control during Training)
Frequency
and Duration
Exercise Testing
Sandstad et al.,
2015 [51]
HIIT (AerT)
Warmup: 10 min stationary cycling at moderate intensity
HIIT protocol: 4 × 4 min high-intensity stationary cycling interval alternating with
3 min cycling recovery periods.
The speed and workload were adjusted continuously.
Measurement: HRmax (HR checked
using HR monitor)
Warmup: ~70%
Interval: 85–95% of HRmax
Rest: ~70% of HRmax
Pain: N/R
2×/week
10 weeks
Maximal
cardiopulmonary test on
a bike.
VO2 max and HRmax
(deﬁned as the highest
HR during the test plus
5 bpm).
Maintain daily life
activities
N/A
N/A
Sveaas et al.,
2014 and 2019
[16,49]
HIIT (AerT) + StrT +
MICT (AerT)
Twice a week, supervised HIIT and StrT:
- HIIT protocol: 4 × 4 min walking/running on a treadmill interval alternating with
3 min of active resting.
- StrT protocol: 20 min with external load (2–3 × 8–10 rep): Bench press or chest
press machine, weighted squat or leg press machine, rowing with weights, triceps
and biceps machine, and abdominal bridge.
Once a week, individual interval training or MICT: 40 min of either interval
training or MICT.
Measurement: HRmax (HR checked
using HR monitor)
HIIT:
Interval: 90–95% HRmax
Rest: 70% HRmax
MICT intensity:
>70% HRmax
Pain: Exercises were adapted if pain
was ≥ 5/10
3×/week
12 weeks
Cardiopulmonary test on
a walking treadmill
(modiﬁed Balke
protocol).
VO2 max and HRmax
were recorded.
Asked to not start
exercise
N/A
N/A
Thomsen et al.,
2019 [53]
HIIT (AerT)
Warmup: 10 min.
HIIT protocol: 4 × 4 min high-intensity stationary cycling interval alternating with a
3 min cycling recovery period.
Work/rest ratio: [1:0.75]
Supervised twice a week and individually once a week. Participants were
instructed in using the HIIT concept by, for example, running, bicycling, or walking
uphill.
Measurement: HRmax (HR checked
using HR monitor)
Interval: 85–95% HRmax
Rest: 70% HRmax
Pain: N/R
3×/week
11 weeks
Maximal
cardiopulmonary test on
a bike.
VO2 max and HRmax
(deﬁned as the highest
HR during the test more
5 bpm).
Maintain daily
physical activity
N/A
N/A
Diagnostics 2022, 12, 2532
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Table 2. Cont.
Trial
Group
Exercise Protocol
(Distribution and Exercise Type)
Intensity
(Pain Control during Training)
Frequency
and Duration
Exercise Testing
Verbrugghe
et al., 2018 [47]
HIIT (AerT) + High
Intensity StrT
HIIT protocol:
-Warmup: 5 min
-Followed by HIIT training: 5 × 1 min high-intensity stationary cycling interval
alternating with 1 min of rest. Weekly increase of interval duration by 10 s until
week 6.
Work/rest ratio: [1:1; 1.2:1; 1.3:1; 1.5:1; 1.7:1; 1.8:1]
High load whole body StrT training protocol:
3 upper body (pulley biceps curl, pulley chest press, and pulley vertical traction
behind the neck) and 3 lower body exercises (leg press, leg extension, and leg curl)
with external load: 1 to 2 × 8–12 rep.
Measurement: VO2 max and 1RM
(Monitorisation: N/R)
Interval: VO2 max workload
Rest: N/R
StrT: 80% 1RM
Pain: N/R
2×/week
6 weeks
Maximal
cardiopulmonary testing
(Graded exercise test) on
a bike. VO2 max,
expiratory volume,
respiratory exchange
ratio, and HR were
recorded
A 1RM test was
performed for every
exercise.
Usual Physiotherapy
Care
MICT protocol: 50 min continuous cycling, cross-training, and/or treadmill walking.
Control motor exercise: Addressing lumbopelvic motor control impairments.
Trunk StrT: Unstable posture corrections, plank, and bridge variations
Measurement: HRmax (Monitorisation:
N/R)
MICT: 60–65% HRmax
Pain: N/R
Verbrugghe
et al., 2019 [17]
HIIT (AerT) +
High-intensity
Global and Core StrT
HIIT protocol:
-Warmup: 5 min cycling
-HIIT Training: 5 × 1 min high-intensity cycling interval alternating with a 1 min
cycling recovery period. Weekly increase of interval duration of 10 s until week 6.
Work/rest ratio: [1:1; 1.2:1; 1.3:1; 1.5:1; 1.7:1; 1.8:1]
High-intensity StrT: 3 upper body (vertical
traction, chest press, arm curl) and 3 lower body exercises (leg curl, leg press, leg
extension) executed with external load on machines: 1 × maximum 12 rep
Core muscle training: 6 static core exercises
[glute bridge, resistance band glute clam, lying diagonal back extension, adapted
knee plank, adapted knee side plank, elastic band shoulder retraction with hip
hinge): 1 × 10 rep of a 10 s static hold.
Measurement: % VO2 max, %1RM and
%MVC (Monitorisation: N/R)
HIIT:
Interval: 110 rpm at 100% VO2 max
workload
Rest: 75 rpm at 50% VO2 max workload
StrT: 80% 1RM
5% workload increase when the
participant was able to perform more
than 10 reps on 2 consecutive sessions.
Core: Between 17% and 100% MVC of
m. transversus abdominis, m.
multiﬁdus, m. gluteus. Progressive
increase of time and load (body weight
bearing, elastic or weights).
Pain: N/R
2×/week
12 weeks
Maximal
cardiopulmonary
test on a bicycle.
VO2 max, Maximal
workload, LA, and HR
were recorded.
Workload was updated,
with a complementary
cardiopulmonary test,
for the last 6 weeks.
1RM testing was
performed for every
exercise.
MICT (AerT) +
Moderate intensity
Global and Core
STrT
MICT protocol: Cycling on a cycle ergometer.
- Warmup: 5 min.
- MICT: Continuous 14 min cycling at moderate intensity. Duration increased by
100 s every 2 sessions up to 22 min 40 s.
Moderate intensity Global StrT: Same exercises as above, but at moderate intensity:
1 × 15 rep.
Moderate intensity core training: Same exercises as above but at moderate intensity:
1 × 10 repetitions of a 10 s static hold.
Measurement: % VO2 max, %1RM and
%MVC (Monitorisation: N/R)
MICT: 90 rpm at 60% VO2 max
workload
StrT: 60% of 1RM
Core training:
N/R
Pain: N/R
Diagnostics 2022, 12, 2532
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Table 2. Cont.
Trial
Group
Exercise Protocol
(Distribution and Exercise Type)
Intensity
(Pain Control during Training)
Frequency
and Duration
Exercise Testing
Verbrugghe
et al., 2020 [48]
HIIT (AerT) + Global
StrT
HIIT protocol:
- Warmup: 5 min cycling
- HIIT Training: 5 × 1 min high-intensity cycling interval alternating with a 1 min
cycling recovery period. Weekly increase of interval duration, of 10 s, until week 6.
Work/rest ratio: [1:1; 1.2:1; 1.3:1; 1.5:1; 1.7:1; 1.8:1]
High-intensity StrT: 3 upper body (vertical traction, chest press, arm curl) and 3
lower body exercises (leg curl, leg press, leg extension) executed with external load
on machines: 2 × maximum 12 rep
Measurement: % VO2 max and %1RM
(Monitorisation: N/R)
HIIT:
Interval: 110 rpm at 100% VO2 max
workload
Rest: 75 rpm at 50% VO2 max workload
StrT: 80% 1 RM
Weight was increased when the
participant was able to perform more
than 10 reps on 2 consecutive sessions.
Pain: N/R
2×/week
12 weeks
Maximal
cardiopulmonary test on
a bicycle. VO2 max,
expiratory volume,
respiratory exchange
ratio, and HR were
recorded. Parameters
were adapted at 6 weeks
with another
cardiopulmonary test.
1RM testing was
performed for every
exercise.
HIIT (AerT) + Core
StrT
HIIT protocol: Same HIIT protocol as above.
Core muscle training: 6 static core exercises
[glute bridge, resistance band glute clam, lying diagonal back extension, adapted
knee plank, adapted knee side plank, elastic band shoulder retraction with hip
hinge): 2 × 10 rep of a 10 s static hold.
Measurement: % VO2 max and %MVC
(Monitorisation: N/R)
HIIT:
Interval: 110 rpm at 100% VO2 max
workload
Rest: 75 rpm at 50% VO2 max workload
Core: 40–60% of the MVC of m.
transversus abdominis, m. multiﬁdus,
m. gluteus. Progressive increase of time
and load.
Pain: N/R
HIIT (AerT)+ Global
and Core StrT
HIIT protocol: Same HIIT protocol as above.
High intensity StrT: Same exercise as above: 1 × maximum 12 rep
Core muscle training: Same exercise as above: 1 × 10 rep of a 10 s static hold.
Measurement: % VO2 max, %1RM and
%MVC (Monitorisation: N/R)
HIIT:
Interval: 110 rpm at 100% VO2 max
workload
Rest: 75 rpm at 50% VO2 max workload
StrT: 80% 1 RM
Weight was increased when the
participant was able to perform more
than 10 reps on 2 consecutive sessions.
Core: 40–60% of the MVC of m.
transversus abdominis, m. multiﬁdus,
m. gluteus. Progressive increase in time
and load
Pain: N/R
Diagnostics 2022, 12, 2532
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Table 2. Cont.
Trial
Group
Exercise Protocol
(Distribution and Exercise Type)
Intensity
(Pain Control during Training)
Frequency
and Duration
Exercise Testing
HIIT (AerT)+
Mobility
HIIT protocol: Same HIIT protocol as above.
Mobility Training: 6 mobility exercises (hamstrings stretch, gluteus medius stretch,
lower back rotation mobilisation, back extension stretch, hip ﬂexor stretch, and
mid-back extension mobilisation): Stretches were held on each side 2 × 30 s, and
mobilisations were performed 2 × 10 rep.
HIIT:
Interval: 110 rpm at 100% VO2 max
workload
Rest: 75 rpm at 50% VO2 max workload
Mobility:
N/R
Pain: N/R
1RM, one-repetition maximum; ACSM, American College of Sports Medicine; AerT, aerobic training; BalanceT, balance training; bpm, beats per min; HIIT, high-intensity interval
training; HR, heart rate; HRmax, maximal heart rate; HRR, heart rate reserve; LA, lactate level; MICT, moderate-intensity continuous training; MVC, maximal voluntary contraction; N/A,
not applicable; N/R, not reported; RPE, rating of perceived exertion; rpm, revolutions per minute; StrT, strength training; VO2 max, maximal oxygen uptake; WRmax, highest work rate.
Diagnostics 2022, 12, 2532
16 of 31
3.3. Methodological Quality Results
We evaluated the studies’ quality with the Cochrane assessment tool. Most of the
studies had a low risk of selective reporting bias. The domain with the highest percentage of
studies with a high risk of bias was the blinding of participants and personnel (performance
bias). Figure 2 shows the risk of bias summary and risk of bias graph. The inter-rater
reliability of the methodological quality assessment was high (κ = 0.787). All of the studies
had an excellent or good methodological quality, except the one by Bressel et al. [45] Due to
the nature of the interventions, none of the studies performed blinding of the patients or
evaluators. Table 3 lists the PEDro scores for each study. The inter-rater reliability of the
methodological quality assessment between assessors was high (κ = 0.815).
Diagnostics 2022, 12, x FOR PEER REVIEW 
17 of 32 
 
 
3.3. Methodological Quality Results 
We evaluated the studies’ quality with the Cochrane assessment tool. Most of the 
studies had a low risk of selective reporting bias. The domain with the highest percentage 
of studies with a high risk of bias was the blinding of participants and personnel (perfor-
mance bias). Figure 2 shows the risk of bias summary and risk of bias graph. The inter-
rater reliability of the methodological quality assessment was high (κ = 0.787). All of the 
studies had an excellent or good methodological quality, except the one by Bressel et al. 
[45] Due to the nature of the interventions, none of the studies performed blinding of the 
patients or evaluators. Table 3 lists the PEDro scores for each study. The inter-rater relia-
bility of the methodological quality assessment between assessors was high (κ = 0.815). 
 
 
Figure 2. Risk of bias summary. Review authors’ judgements about each risk of bias item for each 
included study (Risk of Bias scale) and risk of bias graph. Review authors’ judgements about each 
risk of bias item presented as percentages across all included studies (Risk of Bias scale). 
Table 3. Assessment of the studies’ quality based on the PEDro Scale. 
Items 
 
1 
2 
3 
4 
5 
6 
7 
8 
9 
10 
11 
Total 
Atan et al., 2020 [15] 
1 
1 
1 
1 
0 
0 
1 
1 
1 
1 
1 
8 
Berg et al., 2020 [50] 
1 
1 
1 
0 
0 
0 
0 
1 
1 
1 
1 
6 
Bressel et al., 2014 [44] 
1 
0 
0 
1 
0 
0 
0 
1 
1 
1 
1 
5 
Flehr et al., 2019 [52] 
1 
1 
1 
1 
0 
0 
1 
1 
1 
1 
1 
8 
Hanssen et al., 2018 [49] 
1 
1 
1 
1 
0 
0 
1 
1 
1 
1 
1 
8 
Keogh et al., 2018 [45] 
1 
1 
1 
1 
0 
0 
0 
1 
1 
1 
1 
7 
Sandstad et al., 2015 [51] 
1 
1 
1 
1 
0 
0 
0 
1 
1 
1 
1 
7 
Figure 2. Risk of bias summary. Review authors’ judgements about each risk of bias item for each
included study (Risk of Bias scale) and risk of bias graph. Review authors’ judgements about each
risk of bias item presented as percentages across all included studies (Risk of Bias scale).
Table 3. Assessment of the studies’ quality based on the PEDro Scale.
Items
1
2
3
4
5
6
7
8
9
10
11
Total
Atan et al., 2020 [15]
1
1
1
1
0
0
1
1
1
1
1
8
Berg et al., 2020 [50]
1
1
1
0
0
0
0
1
1
1
1
6
Bressel et al., 2014 [44]
1
0
0
1
0
0
0
1
1
1
1
5
Flehr et al., 2019 [52]
1
1
1
1
0
0
1
1
1
1
1
8
Hanssen et al., 2018 [49]
1
1
1
1
0
0
1
1
1
1
1
8
Keogh et al., 2018 [45]
1
1
1
1
0
0
0
1
1
1
1
7
Sandstad et al., 2015 [51]
1
1
1
1
0
0
0
1
1
1
1
7
Sveas et al., 2014 [16]
1
1
1
1
0
0
1
1
1
1
1
8
Sveas et al., 2019 [49]
1
1
1
1
0
0
1
1
1
1
1
8
Thomsen et al., 2019 [53]
1
1
1
1
0
0
1
1
1
1
1
8
Verbrugghe et al., 2018 [47]
1
0
0
1
0
0
1
1
1
1
1
6
Verbrugghe et al., 2019 [17]
1
1
1
1
0
0
0
1
1
1
1
7
Verbrugghe et al., 2020 [48]
1
1
1
1
0
0
0
1
1
1
1
7
1, patient choice criteria are speciﬁed; 2, random assignment of patients to groups; 3, hidden assignment; 4, groups
were similar at baseline; 5, all patients were blinded; 6, all therapists were blinded; 7, all evaluators were blinded;
8, measures of at least one of the key outcomes were obtained from more than 85% of baseline patients; 9, intention-
to-treat analysis was performed; 10, results from statistical intergroup comparisons were reported for at least one
key outcome; 11, the study provides point and variability measures for at least one key outcome.
Diagnostics 2022, 12, 2532
17 of 31
3.4. Evidence Map
Figure 3 presents the results of the evidence map for the included studies.
 
Verbrugghe et al., 2020 [48] 1 
1 
1 
1 
0 
0 
0 
1 
1 
1 
1 
7 
1, patient choice criteria are specified; 2, random assignment of patients to groups; 3, hidden assign-
ment; 4, groups were similar at baseline; 5, all patients were blinded; 6, all therapists were blinded; 
7, all evaluators were blinded; 8, measures of at least one of the key outcomes were obtained from 
more than 85% of baseline patients; 9, intention-to-treat analysis was performed; 10, results from 
statistical intergroup comparisons were reported for at least one key outcome; 11, the study pro-
vides point and variability measures for at least one key outcome. 
3.4. Evidence Map 
Figure 3 presents the results of the evidence map for the included studies. 
 
Figure 3. A mapping of included studies based on effect size. Blue, Pain intensity; Violet, VO2 max; 
Green, Disability; Black, Quality of Life. Bubbles marked with white dots indicate statistically sig-
nificant differences (p < 0.05). 
3.5. Meta-Analysis Results 
3.5.1. Pain Intensity 
The meta-analysis showed statistically significant differences for the HIIT interven-
tion, with a moderate clinical effect in seven studies (SMD: −0.73; 95% CI −1.40–−0.06; p < 
0.05) but with evidence of significant heterogeneity (Q = 32.57, p < 0.001, I2 = 82%). The 
shape of the funnel and DOI plot did not present asymmetry, and the LFK index showed 
minor asymmetry (LFK, −1.73) indicating a low risk of publication bias (Figures 4A and 
Figure 3. A mapping of included studies based on effect size. Blue, Pain intensity; Violet, VO2 max;
Green, Disability; Black, Quality of Life. Bubbles marked with white dots indicate statistically
signiﬁcant differences (p < 0.05).
3.5. Meta-Analysis Results
3.5.1. Pain Intensity
The meta-analysis showed statistically signiﬁcant differences for the HIIT intervention,
with a moderate clinical effect in seven studies (SMD: −0.73; 95% CI −1.40–−0.06; p < 0.05)
but with evidence of signiﬁcant heterogeneity (Q = 32.57, p < 0.001, I2 = 82%). The shape
of the funnel and DOI plot did not present asymmetry, and the LFK index showed minor
asymmetry (LFK, −1.73) indicating a low risk of publication bias (Figures 4A and A1). The
certainty of the evidence was low, showing that HIIT likely decreases pain intensity, having
been downgraded due to imprecision (sample size < 300) and inconsistency (I2 = 82%)
(Table 4).
Regarding the sub-analysis comparing HIIT against other therapeutic exercise models,
the meta-analysis showed no signiﬁcant differences for the HIIT intervention in 3 studies
(SMD: −0.35; 95% CI −0.76–0.06, p ≥ 0.05) with no evidence of signiﬁcant heterogeneity
(Q = 1.37, p = 0.5, I2 = 0%). The shape of the funnel and DOI plot did not present asym-
metry, and the LFK index showed no asymmetry (LFK, 0.67) indicating a very low risk of
publication bias (Figures 4B and A2).
Diagnostics 2022, 12, 2532
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Disability (4) 
RCT 
seri-
ous 
Not serious 
ous 
Serious 
35 
33 
- 
(−0.92–
0.24) 
ate (+) 
(+) (+) 
Critical 
Quality of life (4) RCT 
Not 
seri-
ous 
Serious 
Not seri-
ous 
Serious 
53 
44 
- 
0.40  
(−0.80–
1.60) 
Low  
(+) (+) 
Critical 
* CI, confidence interval; RCT, randomised controlled trial. 
 
Figure 4. Synthesis forest plot of pain intensity variable. The forest plot summarises the results of 
the included studies (sample size, standardised mean differences [SMDs], and weight). The small 
boxes with the squares represent the point estimate of the effect size and sample size. The lines on 
either side of the box represent a 95% confidence interval (CI). 
Figure 4. Synthesis forest plot of pain intensity variable. The forest plot summarises the results of the
included studies (sample size, standardised mean differences [SMDs], and weight). The small boxes
with the squares represent the point estimate of the effect size and sample size. The lines on either
side of the box represent a 95% conﬁdence interval (CI).
Table 4. Summary of ﬁndings and quality of evidence (GRADE).
Certainty Assessment
No. of
Participants
Effect
Certainty
Importance
Outcome
(No. of
Studies)
Study
Design
Risk of
Bias
Inconsistency
Indirectness
Imprecision
HIIT
Control
Relative
(95%
CI)
Absolute
(95% CI)
Pain
intensity
(7)
RCT
Not
serious
Serious
Not serious
Serious
119
120
-
−0.73
(1.40–−0.06)
Low
(+) (+)
Critical
VO2 max
(6)
RCT
Not
serious
Not serious
Not serious
Serious
112
118
-
0.69
(0.42–0.97)
Moderate
(+) (+) (+)
Critical
Disability
(4)
RCT
Not
serious
Not serious
Not serious
Serious
35
33
-
−0.34
(−0.92–0.24)
Moderate
(+) (+) (+)
Critical
Quality of
life (4)
RCT
Not
serious
Serious
Not serious
Serious
53
44
-
0.40
(−0.80–1.60)
Low
(+) (+)
Critical
CI, conﬁdence interval; RCT, randomised controlled trial.
3.5.2. VO2 max
The meta-analysis showed signiﬁcant differences for the HIIT intervention, with a
moderate clinical effect in six studies (SMD: 0.69; 95% CI 0.42–0.97, p < 0.05), with no
evidence of signiﬁcant heterogeneity (Q = 4.06, p = 0.54, I2 = 0%). The shape of the funnel
and DOI plot did not present asymmetry, and the LFK index showed minor asymmetry
(LFK, 1.33) indicating a low risk of publication bias (Figures 5A and A2). The certainty of
the evidence was moderate, showing that HIIT probably increases VO2 max, having been
downgraded due to imprecision (sample size < 300) (Table 4).
Diagnostics 2022, 12, 2532
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dence of significant heterogeneity (Q = 4.06, p = 0.54, I2 = 0%). The shape of the funnel a
DOI plot did not present asymmetry, and the LFK index showed minor asymmetry (LF
1.33) indicating a low risk of publication bias (Figures 5A and A2). The certainty of 
evidence was moderate, showing that HIIT probably increases VO2 max, having be
downgraded due to imprecision (sample size < 300) (Table 4). 
 
Figure 5. Synthesis forest plot of VO2 max variable. The forest plot summarises the results of 
included studies (sample size, standardised mean differences [SMDs], and weight). The small bo
with the squares represent the point estimate of the effect size and sample size. The lines on eit
side of the box represent a 95% confidence interval (CI). 
Regarding the subanalysis comparing HIIT against other therapeutic exercise mo
els, the meta-analysis showed no statistically significant differences for the HIIT interv
tion in three studies (SMD: 0.28; 95% CI −0.31–0.87, p ≥ 0.05), with no evidence of sign
cant heterogeneity (Q = 4.16, p = 0.13, I2 = 52%). The shape of the funnel and DOI plot d
not present asymmetry, and the LFK index showed no asymmetry (LFK, −0.31) indicati
a very low risk of publication bias (Figures 5B and A2). 
 
Figure 5. Synthesis forest plot of VO2 max variable. The forest plot summarises the results of the
included studies (sample size, standardised mean differences [SMDs], and weight). The small boxes
with the squares represent the point estimate of the effect size and sample size. The lines on either
side of the box represent a 95% conﬁdence interval (CI).
Regarding the subanalysis comparing HIIT against other therapeutic exercise models,
the meta-analysis showed no statistically signiﬁcant differences for the HIIT intervention
in three studies (SMD: 0.28; 95% CI −0.31–0.87, p ≥ 0.05), with no evidence of signiﬁcant
heterogeneity (Q = 4.16, p = 0.13, I2 = 52%). The shape of the funnel and DOI plot did not
present asymmetry, and the LFK index showed no asymmetry (LFK, −0.31) indicating a
very low risk of publication bias (Figures 5B and A2).
3.5.3. Disability
The meta-analysis showed no statistically signiﬁcant differences for the HIIT inter-
vention in three studies (SMD: −0.34; 95% CI −0.92–0.24, p ≥ 0.05), with no evidence of
signiﬁcant heterogeneity (Q = 4.55, p = 0.21, I2 = 34%). The shape of the funnel and DOI
plot did not present asymmetry, and the LFK index showed minor asymmetry (LFK, −1.68)
indicating a low risk of publication bias (Figures 6A and A3). The certainty of the evidence
was moderate, showing that HIIT probably does not decrease disability, being downgraded
due to imprecision (sample size <300) (Table 4).
Diagnostics 2022, 12, 2532
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significant heterogeneity (Q = 4.55, p = 0.21, I2 = 34%). The shape of the funnel and DOI 
plot did not present asymmetry, and the LFK index showed minor asymmetry (LFK, 
−1.68) indicating a low risk of publication bias (Figures 6A and A3). The certainty of the 
evidence was moderate, showing that HIIT probably does not decrease disability, being 
downgraded due to imprecision (sample size <300) (Table 4). 
 
Figure 6. Synthesis forest plot of disability and quality-of-life variables. The forest plot summarises 
the results of the included studies (sample size, standardised mean differences [SMDs], and weight). 
The small boxes with the squares represent the point estimate of the effect size and sample size. The 
lines on either side of the box represent a 95% confidence interval (CI). 
3.5.4. Quality of Life 
The meta-analysis showed no significant differences for the HIIT intervention in 4 
studies (SMD: 0.40; 95% CI −0.80–1.60, p ≥ 0.05), with evidence of significant heterogeneity 
(Q = 24.01, p < 0.001, I2 = 88%). The shape of the funnel and DOI plot did not present asym-
metry, and the LFK index showed minor asymmetry (LFK, 1.43), indicating a low risk of 
publication bias (Figures 6B and A3). The certainty of the evidence was low, showing that 
HIIT likely does not increase QoL, being downgraded due to imprecision (sample size < 
300) and inconsistency (I2 = 88%) (Table 4). 
3.6. Meta-Regression Analysis 
In the meta-regression analysis, we explored the role of pain intensity scores in im-
proving VO2 max function. The results showed that pain intensity was significantly and 
negatively correlated with VO2 max (β = −0.91; Z = −3.02; p = 0.003 and R2 = 82.99%) (Figure 
7). 
Figure 6. Synthesis forest plot of disability and quality-of-life variables. The forest plot summarises
the results of the included studies (sample size, standardised mean differences [SMDs], and weight).
The small boxes with the squares represent the point estimate of the effect size and sample size. The
lines on either side of the box represent a 95% conﬁdence interval (CI).
3.5.4. Quality of Life
The meta-analysis showed no signiﬁcant differences for the HIIT intervention in 4 stud-
ies (SMD: 0.40; 95% CI −0.80–1.60, p ≥ 0.05), with evidence of signiﬁcant heterogeneity
(Q = 24.01, p < 0.001, I2 = 88%). The shape of the funnel and DOI plot did not present
asymmetry, and the LFK index showed minor asymmetry (LFK, 1.43), indicating a low risk
of publication bias (Figures 6B and A3). The certainty of the evidence was low, showing
that HIIT likely does not increase QoL, being downgraded due to imprecision (sample
size < 300) and inconsistency (I2 = 88%) (Table 4).
3.6. Meta-Regression Analysis
In the meta-regression analysis, we explored the role of pain intensity scores in im-
proving VO2 max function. The results showed that pain intensity was signiﬁcantly and
negatively correlated with VO2 max (β = −0.91; Z = −3.02; p = 0.003 and R2 = 82.99%)
(Figure 7).
Diagnostics 2022, 12, 2532
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Diagnostics 2022, 12, x FOR PEER REVIEW 
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Figure 7. Meta-regression of pain intensity and VO2 max scores. The meta-regression approach uses 
regression analysis to determine the influence of selected variables (the independent variables) on 
the effect size (the dependent variable). The large bubbles, together with the line, indicate the rela-
tionship of our model, and the small bubbles indicate their position, the relationship in the map of 
the effect size on the decrease in pain, on the score in the variable of maximal oxygen consumption. 
4. Discussion 
Our main goal was to analyse the effect of HIIT on the VO2 max, pain intensity, disa-
bility, and QoL of patients with musculoskeletal disorders. Our results suggest that HIIT 
has a significant moderate effect size on VO2 max and pain intensity but does not seem to 
improve the disability and QoL of patients with musculoskeletal disorders. We also found 
that pain intensity was negatively associated with VO2 max. 
We found a moderate certainty of evidence of a moderate effect size of HIIT on VO2 
max when compared with no intervention. Several authors also found that HIIT was supe-
rior to usual care or no intervention in improving VO2 max among patients with cardiovas-
cular disorders or cancer [18,19,55]. We did not find that HIIT was superior to another 
exercise intervention on VO2 max; however, the results across systematic reviews differ 
[19,56,57]. It has been previously reported that HIIT induces muscular adaptations, such 
as mitochondrial biogenesis and increased intramuscular capillarisation [58,59] vascular 
adaptations, such as increased blood cell volume [60], and cardiac adaptations, such as 
increased cardiac output and contractility [59,61]. All of these mechanisms have been 
shown to play a role in VO2 max [62]. 
We found that the patients’ pain intensity scores were negatively associated with VO2 
max, which is an important predictor of all-cause mortality and cardiovascular disease 
[63,64]. It should be noted that patients with chronic pain and musculoskeletal disorders 
have shown an increased risk of cardiovascular and chronic disease and an increased risk 
of mortality due to cardiac disease [65,66]. An improvement in cardiorespiratory capacity 
has been shown to decrease the mortality risk by up to 16% [67,68]. HIIT appears to be an 
effective solution for improving patients’ cardiorespiratory capacity. 
We found a low certainty of evidence of a moderate effect size of HIIT on pain inten-
sity compared with no intervention. Geneen et al. found that physical activity appears to 
Figure 7. Meta-regression of pain intensity and VO2 max scores. The meta-regression approach uses
regression analysis to determine the inﬂuence of selected variables (the independent variables) on the
effect size (the dependent variable). The large bubbles, together with the line, indicate the relationship
of our model, and the small bubbles indicate their position, the relationship in the map of the effect
size on the decrease in pain, on the score in the variable of maximal oxygen consumption.
4. Discussion
Our main goal was to analyse the effect of HIIT on the VO2 max, pain intensity, dis-
ability, and QoL of patients with musculoskeletal disorders. Our results suggest that HIIT
has a signiﬁcant moderate effect size on VO2 max and pain intensity but does not seem to
improve the disability and QoL of patients with musculoskeletal disorders. We also found
that pain intensity was negatively associated with VO2 max.
We found a moderate certainty of evidence of a moderate effect size of HIIT on VO2 max
when compared with no intervention. Several authors also found that HIIT was superior
to usual care or no intervention in improving VO2 max among patients with cardiovascular
disorders or cancer [18,19,55]. We did not ﬁnd that HIIT was superior to another exercise
intervention on VO2 max; however, the results across systematic reviews differ [19,56,57].
It has been previously reported that HIIT induces muscular adaptations, such as mitochon-
drial biogenesis and increased intramuscular capillarisation [58,59] vascular adaptations,
such as increased blood cell volume [60], and cardiac adaptations, such as increased cardiac
output and contractility [59,61]. All of these mechanisms have been shown to play a role in
VO2 max [62].
We found that the patients’ pain intensity scores were negatively associated with
VO2 max, which is an important predictor of all-cause mortality and cardiovascular dis-
ease [63,64]. It should be noted that patients with chronic pain and musculoskeletal
disorders have shown an increased risk of cardiovascular and chronic disease and an
increased risk of mortality due to cardiac disease [65,66]. An improvement in cardiorespi-
ratory capacity has been shown to decrease the mortality risk by up to 16% [67,68]. HIIT
appears to be an effective solution for improving patients’ cardiorespiratory capacity.
We found a low certainty of evidence of a moderate effect size of HIIT on pain intensity
compared with no intervention. Geneen et al. found that physical activity appears to
induce exercise-induced hypoalgesia in patients with chronic pain; however, the results
Diagnostics 2022, 12, 2532
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were inconsistent across the various exercise modalities [69]. When compared with another
exercise intervention, HIIT did not show a greater effect. It has been shown that exercise-
induced hypoalgesia acts through the activation of nociceptive inhibitory pathways that
release endogenous opioids and endocannabinoids [70]; however, populations with chronic
pain often have exercise-induced hypoalgesia dysfunction [70,71]. Nonetheless, we found
that HIIT appeared to be an effective modality for decreasing pain intensity. Patients with
musculoskeletal disorders often present central sensitisation, a facilitation of the nociceptive
signal in the central nervous system [72]. Quantitative sensory testing is employed to
evaluate central nervous system nociceptive modulation [72]. HIIT has shown an intensity-
dependent [12,13] positive effect on pain tolerance [13] and pain thresholds [12,73]. In
certain conditions, the presence of an inﬂammatory state can increase nociceptor activity
and has been associated with pain intensity [71,74–76]. After performing HIIT, a number of
authors have found a decrease in inﬂammatory markers [77–79], such as C-reactive protein,
tumour necrosis factor-alpha and interleukin-6 (IL-6), and a release of anti-inﬂammatory
cytokines, such as IL-10 [79]. In contrast, other authors have found that HIIT induced an
acute increase in IL-6 levels [80,81]; however, Pedersen proposed that this acute liberation
will then induce an anti-inﬂammatory response [82]. Shanaki et al. observed a decrease
in pro-inﬂammatory M1-macrophage markers and an increase in anti-inﬂammatory M2-
macrophage markers in mice after HIIT [83]. However, not all musculoskeletal conditions
show reduced pain intensity in parallel with a decrease in pro-nociceptive or inﬂammatory
serum markers [76,84], and not all musculoskeletal conditions progress with an increased
inﬂammatory state [76].
We found a low level of evidence of no signiﬁcant effect of HIIT on QoL compared
with no intervention or usual care. Mugele et al. systematically reviewed the effect of HIIT
on QoL, compared with usual care, and found unclear results [19]. QoL appears to be
more closely related to interpretation and catastrophising than pain intensity [85], which
might explain why we observed a decrease in pain intensity with no improvement in QoL.
Monticone et al. found that a multidisciplinary treatment involving cognitive-behavioural
therapy and exercise results in a signiﬁcant improvement in QoL, while exercise alone
resulted in little change [86]. We also found moderate certainty evidence of no signiﬁcant
effect of HIIT on disability compared with no intervention or usual care. Kamper et al.
found that a treatment involving a physical and a psychological or social component had a
greater effect on disability than physical therapy alone for patients with chronic low back
pain. HIIT alone might be insufﬁcient for improving disability or QoL in musculoskeletal
disorders [87].
Time constraints and pain are two of the main barriers to physical activity for patients
with musculoskeletal disorders [88–90]. Despite similar effects on VO2 max and pain inten-
sity with other exercise types, HIIT requires less training volume to achieve similar effects
in the included studies that provide the control group’s training duration [15,50]. Wewege
et al. found that the most common adverse effects in patients with cardiovascular disease
were musculoskeletal complaints; however, we observed that HIIT presented similar or
almost no additional major or minor adverse events or pain ﬂare-ups than no intervention
or other exercise modalities [91]. Major cardiac adverse events during HIIT appear at a rate
of 1 per 11,333 HIIT h in patients with cardiovascular disease [91] but with no signiﬁcant
difference in the overall adverse events rate between HIIT and MICT [91]. As recommended
by Weston et al. if health professionals want to implement HIIT, they should evaluate
patients on a case-by-case basis depending on their cardiac history [20]. Heisz et al. found
that participants rated HIIT more enjoyable than MICT and that enjoyment increased with
repeated HIIT when it remained constant with repeated MICT [92]. Health professionals
should include HIIT in the management of musculoskeletal disorders, given that HIIT
is a time-efﬁcient, enjoyable, effective, and safe form of exercise. Finally, it is relevant to
stress that it is important to prescribe exercise speciﬁcally for each patient and for each
clinical condition, although in this work it has been grouped by variables, rather than by
populations.
Diagnostics 2022, 12, 2532
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Limitations
We found low-to-moderate quality evidence for our results. Further studies are needed
on the effects of HIIT on musculoskeletal disorders to conﬁrm our results. The sample sizes
of the included studies were often very small. Future studies should include larger sample
sizes to improve the quality of the evidence. Due to the lack of sufﬁcient data and the
heterogeneity among the interventions (e.g., frequency, intervention duration), we could
not establish the speciﬁc effect on each musculoskeletal disorder and the optimal HIIT
parameters. Due to the small number of trials, we pooled the aerobic and anaerobic HIIT
training studies; future systematic reviews should evaluate them separately. Only a few
studies compared the effect of HIIT against high-intensity continuous training or other
types of exercise; future studies should include this type of high-intensity training.
As recommended by the American Thoracic Society/American College of Chest
Physicians Statement on Cardiopulmonary Exercise Testing, we included VO2 peak and
VO2 max and used them interchangeably [93]. Quantitative sensory testing (e.g., pain
pressure or thermal threshold, conditioned pain modulation, and temporal summation) is
essential in pain research; future studies evaluating the effects of HIIT on musculoskeletal
disorders should include these variables. In addition, no further meta-regression analysis
could be performed due to the small number of articles sharing the outcomes of interest.
Lastly, it is important to stress that there were 3 studies where HIIT was embedded in other
exercise interventions such as balance exercise and continuous exercise. This is a clear
limitation that should be considered when extrapolating the results [16,45,47].
5. Conclusions
There is low to moderate quality evidence that the HIIT intervention for patients with
musculoskeletal disorders can improve pain intensity and VO2 max but not disability and
QoL. The results of the subanalyses showed that HIIT was not superior to other exercise
models in improving pain intensity and VO2 max. Clinically, this tells us that we can
implement high-intensity interval exercise models if our goal is to improve pain intensity
or increase cardiorespiratory ﬁtness through maximal oxygen consumption. However, it is
important to keep in mind two aspects: changes in pain intensity may not be accompanied
by improvements in the subjective perception of quality of life or disability, at least, based
on the data we currently have, and second, that this exercise model was not superior
to other exercise models with respect to eliciting these clinical changes. This should be
considered clinically. Low sample sizes and lack of prescription parameters emphasise the
need for further research on HIIT in musculoskeletal disorders for its implementation in a
clinical context.
Author Contributions: Conceptualization, F.C.-M.; methodology, F.C.-M., N.S.-R., C.V.-R. and R.L.T.;
software, F.C.-M. and R.L.T.; validation, N.S.-R., L.S.-M., P.A.-Q. and J.F.-C.; formal analysis, F.C.-M.
and R.L.T.; investigation, all authors; resources, J.F.-C.; data curation, F.C.-M., C.V.-R. and R.L.T.;
writing—original draft preparation, all authors; writing—review and editing, all authors; visualiza-
tion, all authors; supervision, F.C.-M.; project administration, F.C.-M. and N.S.-R.; funding acquisition,
not applicable. All authors have read and agreed to the published version of the manuscript.
Funding: This research received no external funding.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: Not applicable.
Acknowledgments: The authors would like to thank the CSEU La Salle for its services in editing
this manuscript.
Conﬂicts of Interest: The authors declare no conﬂict of interest.
Diagnostics 2022, 12, 2532
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Appendix A
Diagnostics 2022, 12, x FOR PEER REVIEW 
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Acknowledgments: The authors would like to thank the CSEU La Salle for its services in editing 
this manuscript. 
Conflicts of Interest: The authors declare no conflicts of interest. 
Appendix A 
 
 
(a) HIIT vs. control 
Figure A1. Cont.
Diagnostics 2022, 12, 2532
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Diagnostics 2022, 12, x FOR PEER REVIEW 
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(b) HIIT vs. Other therapeutic exercise models 
Figure A1. Synthesis funnel and Doi plot (LFK index) for pain intensity to assess the presence of 
publication bias. 
Appendix B 
 
Figure A1. Synthesis funnel and Doi plot (LFK index) for pain intensity to assess the presence of
publication bias.
Appendix B
Diagnostics 2022, 12, x FOR PEER REVIEW 
26 of 32 
 
 
 
 
(b) HIIT vs. Other therapeutic exercise models 
Figure A1. Synthesis funnel and Doi plot (LFK index) for pain intensity to assess the presence of 
publication bias. 
Appendix B 
Figure A2. Cont.
Diagnostics 2022, 12, 2532
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Diagnostics 2022, 12, x FOR PEER REVIEW 
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(a) HIIT vs. control 
(b) HIIT vs. other therapeutic exercise models 
Figure A2. Synthesis funnel and Doi plot (LFK index) for VO2 max to assess the presence of 
publication bias. 
 
 
Figure A2. Synthesis funnel and Doi plot (LFK index) for VO2 max to assess the presence of
publication bias.
Diagnostics 2022, 12, 2532
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Appendix C
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Appendix C 
 
 
(a) HIIT vs. control (disability) 
 
Figure A3. Cont.
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(b) HIIT vs. control (quality of life) 
Figure A3. Synthesis Funnel and Doi plot (LFK index) for disability and quality-of-life variables to 
assess the presence of publication bias. 
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15. Atan, T.; Karavelioğlu, Y. Effectiveness of High-Intensity Interval Training vs Moderate-Intensity Continuous Training in 
Patients with Fibromyalgia: A Pilot Randomized Controlled Trial. Arch. Phys. Med. Rehabil. 2020, 101, 1865–1876. 
16. Sveaas, S.H.; Bilberg, A.; Berg, I.J.; Provan, S.A.; Rollefstad, S.; Semb, A.G.; Hagen, K.B.; Johansen, M.W.; Pedersen, E.; 
Dagfinrud, H. High intensity exercise for 3 months reduces disease activity in axial spondyloarthritis (axSpA): A multicentre 
randomised trial of 100 patients. Br. J. Sports Med. 2019, 54, 292–297. 
17. Verbrugghe, J.; Agten, A.; Stevens, S.; Hansen, D.; Demoulin, C.; Eijnde, B.O.; Vandenabeele, F.; Timmermans, A. Exercise 
Intensity Matters in Chronic Nonspecific Low Back Pain Rehabilitation. Med. Sci. Sports Exerc. 2019, 51, 2434–2442. 
18. Batacan, R.B.; Duncan, M.J.; Dalbo, V.J.; Tucker, P.S.; Fenning, A.S. Effects of high-intensity interval training on cardiometabolic 
health: A systematic review and meta-analysis of intervention studies. Br. J. Sports Med. 2017, 51, 494–503. 
Figure A3. Synthesis Funnel and Doi plot (LFK index) for disability and quality-of-life variables to
assess the presence of publication bias.
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