Objective feedback on physical activity in healthcare interventions
study. The study focused on patients of healthcare
institutions, who were mostly patients with (chronic)
neurological or cardiovascular diseases. These patients
may experience more barriers to increasing their PA
compared with healthy individuals (6). In addition,
participants in the current study were slightly older
(mostly around 65 years of age) compared with other
studies. It is possible that older individuals increase
their PA less because they experience difficulty using
new technologies, such as activity monitors, to increase
PA. Nevertheless, the overall positive results suggest
that using wearable technology is also a promising tool
to promote PA in healthcare settings.
Similar to other reviews (14, 16), large heterogeneity
was found in the study characteristics. However, after
excluding 2 studies based on leave-one-out sensitivity
analyses, heterogeneity was acceptable. Mediating
effects of study characteristics (setting, duration and
population) were explored by calculation of pooled
SMDs of grouped characteristics (Table III). Regarding
intervention setting, the effect sizes of studies were
smaller in an inpatient setting compared with home-
based interventions, suggesting that the difference
between the intervention and control groups is smaller
when both groups are situated in an inpatient setting,
as stated by Dorsch et al. (28), who found comparable
results. It can be assumed that both the intervention
and control groups in inpatient populations were more
dedicated to a strict treatment schedule. Thus, the
chance that behaviour of both the control and interven-
tion groups was similar was higher compared with an
outpatient- or home-based setting. In other words, a
free-living environment allows more voluntary phy-
sical behaviour. This statement may also explain the
difference in magnitude of the overall effect in the
current study (0.34) in comparison with, for example,
the overall effect in the meta-analysis by Kang et al.
(20) amongst mostly healthy and younger free-living
populations (0.68).
Analysis of intervention duration in the current
study agreed with the study of Goode et al. (17), since
shorter intervention durations showed larger effects
on PA compared with longer-lasting interventions.
SMD calculation in the current study was based on
post-intervention measurements. Adherence to use of
wearables for a longer time in daily life may be more
difficult, and thus the chance of relapsing to previous
behaviour is higher. Future studies should include more
follow-up measurements to examine the sustainability
of behaviour change due to these interventions.
The frequency of applying different intervention
strategies was explored in this study and the results em-
phasize the importance of combining objective PA feed-
back with BCT strategies (Table II). All interventions
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included in this review were combined with multiple
BCT components (Tables I and II), assuming that re-
searchers find BCT a substantial element for designing
RCTs for promotion of PA in healthcare. In addition,
Nolan et al. (26) explained the lack of improvement in
PA by the low levels of added behavioural counselling.
Nevertheless, BCT is an umbrella construct, and the
BCT components in the studies included in the current
review varied considerably. Not all studies described
the content of the BCT sufficiently in the intervention
and control groups, hence BCT could only be assessed
approximately. Therefore, only careful suggestions
for effect directions could be drawn regarding specific
BCT components. Goal-setting, education and barrier
identification are factors that are probably important,
since they were often present in interventions with a
relatively large positive effect size. Nevertheless, in 12
of the 14 included studies, the control group received
usual care, and it can be assumed that, in most cases,
BCT was also present in usual care. As Hakala et al. (16)
have suggested previously; the effect size is influenced
by the load of the control treatment. With respect to the
current study, this could mean that the magnitude of
the effect is relatively small because of the amount of
BCT that is already present in usual care, and thereby
also in control groups.
Study limitations
First, due to the heterogeneity in intervention strategies
and treatments of control groups, the specific effect
of the objective PA feedback component could not be
determined.
Furthermore, the SMDs of PA were calculated
based on post-intervention measurements assuming
that the RCTs in this meta-analysis included an ac-
ceptable randomization procedure. However, baseline
comparison of PA was often not taken into account in
randomization procedures. Therefore, intervention and
control groups may have differed in baseline PA, which
might have influenced the results. Future studies should
compare the intervention and control group based on
mean changes between pre- and post-measurements.
Another methodological limitation in the current meta-
analysis concerns comparison of the intervention ef-
fects based on SMD. In the included studies, the SMDs
were calculated using diverse PA outcome measures
and generated by different methods of data-processing
using various devices. These methodological differen-
ces between studies in accelerometer data-processing
limit comparability (36). Using a standardized version
of the effect size, such as the SMD, only partly resol-
ves the problem of comparing different PA outcomes
measured using different devices.
J Rehabil Med 51, 2019