Journal of Rehabilitation Medicine 51-3 | Page 8

study by Frederix et al. (22) did not provide p-values of the effect on PA. Eight studies showed a significant positive effect in favour of using feedback from a wearable monitor in the intervention group (p < 0.05) (23–25, 27, 29, 30, 32, 34). Intervention strategies H. E. M. Braakhuis et al. 154 Fig. 2. Risk of bias assessment of included studies (n  = 14). pulmonary disease (COPD), stroke, various cardio- vascular diseases, Parkinson’s disease, and geriatric patients. The duration of interventions varied between 20 days (28) and 2 years (34). The duration of 2 in- terventions was dependent on the length of inpatient rehabilitation (28, 35). In 12 studies, all participants received usual care (UC), and the intervention group received an objective feedback PA intervention in addition to UC (Table I). In the 2 other studies the control group received no care or wait list control (25, 29). Five interventions were performed in an inpatient setting (22, 27, 28, 31, 35) and the other studies were outpatient- or home-based. Outcome measures used to calculate the significance of the effect on PA were steps per day, walking time per day, energy expenditure (in kJ or kcal per day or per week), accelerometer counts per day, and time in moderate intensity PA per week. These outcomes were measured using a pedometer or accelerometer (Table I). Steps/day was the most frequently used outcome measure. The significance of the effect on PA was calculated by the authors in 3 different ways: p-value of (i) difference in mean change between intervention and control group; (ii) difference between intervention and control group at follow-up; and (iii) difference between baseline and follow-up of the intervention and control group calculated separately (Table I). The www.medicaljournals.se/jrm Intervention strategies used in each study are shown in Table I. Table II shows the frequency of intervention strategies used in the included studies. Five studies used a pedometer for feedback (24–26, 29, 30) and the others studies used accelerometers. The most frequently used feedback parameter is steps per day (Table III). Furthermore, frequency of feedback varied between daily and monthly. In 4 studies, patients could choose when to view their PA level (23, 25, 32, 34). In 8 studies, subjects could see their real-time PA on a display (24–26, 29–32, 35). Four studies (22, 25, 30, 34) used no verbal interaction with a coach or therapist in real-life consultations or by telephone to provide feedback. The following BCT components mentioned in the studies were identified: education (E), goal-setting (GS), barrier identification (BI) and/or problem- solving (PS), action planning (AP) and social support (SS) (Table I). BCT components were used in a wide variety of combinations. Table II shows the frequency of BCT components present in all included studies. Five studies used 3 or more BCT components as con- current intervention strategies (23, 25, 29, 32, 34). GS was the most-often used BCT component (Table II). GS and E were frequently combined with BI and/or PS. Only 1 study used social support (25). Effect estimates Authors were contacted when data on PA to calculate SMD post-intervention were missing (22, 24, 26, 29, 34, 35). SMDs of 11 studies were calculated based on original data, data sent by authors, or a combination of both. In 3 studies, the SD of the outcome measure at follow-up was estimated (29, 31, 33). One of the inter- vention arms of McMurdo et al. (29) and Shoemaker et al. (33) was excluded from meta-analysis based on inclusion criteria. SMD of Frederix et al. (22) and Peel et al. (27) (respectively SMD = 4.64 and 4.73) was more than 3 times as large as SMD of other studies (SMD between –0.09 and 1.17), as shown in Fig. 3. Leave-one- out sensitivity analysis showed that after removing the study of Frederix et al. (and Peel et al.), the overall ef- fect changed to SMD with a smaller confidence interval (SMD = 0.34 with 95% CI 0.23–0.44, z = 6.27, p < 0.01) and considerable less heterogeneity (I 2  = 49%) (Fig. 3) compared with the overall effect size when they were