156
H. E. M. Braakhuis et al.
Table II. Overview of frequency of specific intervention strategies
used in the included studies
Intervention strategies
Type of feedback monitor
Pedometer
Accelerometer
Feedback parameter
Steps/day
Energy expenditure (kcal/day)
Duration of (MV)PA/day
Feedback frequency*
Daily
≥ Once per week
< Once per week
Login by choice
Feedback visualization*
n/a
Web portal or mobile application
Real-life display
Therapist/coach contact*
Real-life consultation
Phone call
None
BCT components*
Education
Goal-setting
Barrier identification
Action planning
Social support
Frequency in the 14 included studies
N (total n = 14 Pooled mean SMD
studies)
[95% CI]
Study characteristics
5
9
9
2
3
2
7
5
4
2
6
8
8
4
3
7
12
6
4
1
*Multiple studies used a combination of multiple components.
n/a: not applicable; MV: moderate to vigorous; PA: physical activity; BCT:
behavioural change techniques.
Table III. Pooled standardized mean differences per group of
study characteristics
included (SMD = 0.64 with 95% CI 0.52–0.73, z = 11.97,
p < 0.01) and heterogeneity (I 2 = 97%). Therefore, the
SMD of Frederix et al. (and Peel et al.) were excluded
from the meta-analysis and weight was reduced to 0%
(Fig. 3). Heterogeneity was moderate but significant
(I 2 = 49%, p = 0.03, Fig. 3), which supported the explora-
tion of the contribution of different study characteristics
to the overall SMD. Pooled mean SMD per study cha-
racteristic is shown in Table III. Outpatient- and home-
based interventions had a larger effect (SMD = 0.37)
on PA than inpatient interventions (SMD = 0.17). The
shortest intervention durations (< 10 weeks) had the
largest effect (SMD = 0.70). In populations with cardiac
diseases objective feedback PA interventions had the
largest effect (SMD = 0.70) on PA compared with other
patient populations (SMD = 0.19–0.35).
Setting
Inpatient
Outpatient-/home-based
Duration
Dependent on rehabilitation length
0.17 [–0.08, 0.43] a,b
0.37 [0.26, 0.49]
2 0.19 [–0.08, 0.46]
0.70 [0.20, 1.20] b
<10 weeks 4 10–20 weeks
>20 weeks
Population
Stroke 3
5 0.30 [–0.06, 0.66] a
0.35 [0.23, 0.48]
2 0.19 [–0.08, 0.46]
Cardiac 4
Geriatric
Parkinson’s disease
COPD 2
1
5
0.75 [0.16, 1.33] a
0.35 [0.01, 0.69] b
0.45 [0.28, 0.62]
0.23 [0.05, 0.41]
a
Analysed without Frederix 2015 (22) based on leave-one-out sensitivity analysis
Analysed without Peel 2016 (27) based on leave-one-out sensitivity analysis
CI: confidence interval; SMD: standardized mean difference; COPD: chronic
obstructive pulmonary disease.
b
DISCUSSION
To our knowledge, this is the first review to focus on
interventions aiming at promoting PA that include
feedback based on objective measurements of PA in
healthcare settings. Overall, meta-analysis showed a
moderately positive effect on PA, with the weight of
evidence being in favour of the interventions using
objective feedback on PA. Study characteristics varied
widely across included studies. Pooled analysis of
characteristics provided more insight into the effec-
tiveness of setting, intervention duration, and target
population. In addition, there was high variability in
intervention strategies.
These results complement those of previous studies
in finding that using objective feedback of PA via
wearable monitors increases levels of PA. Previous
meta-analyses (13, 15, 16, 20) also showed positive
effects on PA in favour of the intervention groups. In
contrast, the overall effect size of the current study
(0.34) was lower than effect sizes of the other meta-
analyses (> 0.50) (13, 15, 16). This may be explained
by the type of populations included in the current
Fig. 3. Forest plots for physical activity outcome measures, overall estimate of the intervention effect.
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