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The Effects of “Physical Activity on Prescription” in Persons With Transient Ischemic Attack

A Randomized Controlled Study

Morén, Carina MSc, PT; Welmer, Anna-Karin PhD; Hagströmer, Maria PhD; Karlsson, Emelie MSc, PT; Sommerfeld, Disa K. PhD

Journal of Neurologic Physical Therapy: July 2016 - Volume 40 - Issue 3 - p 176–183
doi: 10.1097/NPT.0000000000000134
Research Articles
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Background and Purpose: Transient ischemic attack (TIA) is a strong predictor of stroke, and physical inactivity is one risk factor for TIA/stroke. “Physical activity on Prescription” (PaP) can increase physical activity, but the effect of PaP after TIA has not been described. Our goal was to objectively measure the effect of PaP on physical activity and physical capacity, as well as self-rated health at 3 and 6 months after TIA.

Methods: The primary outcome was moderate to vigorous intensities of physical activity objectively assessed by accelerometry. Secondary outcomes were steps per day assessed by accelerometry, physical capacity assessed by the 6-minute walk test, and self-rated health assessed by EQ-5D VAS.

Results: Eighty-eight individuals with TIA were randomized to an intervention group (n = 44) that received conventional treatment and PaP or to a control group (n = 44) that received conventional treatment alone. There was a 30% dropout among the participants at 6 months. No significant differences between groups were found in physical activity at 3 and 6 months. At 6 months, participants in the intervention group were significantly more likely to have improved their physical capacity than the control group. There was no significant difference between groups in self-rated health.

Discussion and Conclusions: PaP did not increase physical activity after TIA; however, there was an increase in physical capacity. The nonsignificant results for physical activity may be the result of a relatively high baseline physical activity level. The results may also indicate that prior studies suggesting that PaP increases physical activity overestimated effects because of the self-reported nature of the previous outcomes.

Video Abstract available for more insights from the authors (see Supplemental Digital Content 1,

Department of Physiotherapy, Norrtälje Hospital, Norrtälje, Sweden (C.M.); and Department of Neurobiology, Care Sciences and Society, Aging Research Center, Karolinska Institutet and Stockholm University (A.-K.W.), Department of Physical Therapy, Karolinska University Hospital (A.-K.W., M.H., D.K.S.), Department of Neurobiology, Care Sciences and Society, Division of Physiotherapy, Karolinska Institutet (M.H., E.K., D.K.S.), Department of Occupational and Physiotherapy, Södersjukhuset (E.K.), Stockholm, Sweden.

Correspondence: Carina Morén, MSc, PT, Department of Physiotherapy, Norrtälje Hospital, Lasarettsgatan 6-8, 761 29 Norrtälje, Sweden (

Tiohundra AB funded part of this study.

The RCT is registered in Clinical Trials. Registration number NCT01509924 and the results are reported according to the Consolidated Standards of Reporting Trials (CONSORT statement) and was approved by the Ethical review board in Stockholm (2010/671-31/3), Sweden.

Supplemental digital content is available for this article. Direct URL citation appears in the printed text and is provided in the HTML and PDF versions of this article on the journal's Web site (

The authors declare no conflicts of interest.

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Transient ischemic attack (TIA) is a strong predictor of stroke and often signals imminent health threats.1 It has also been suggested that TIA may be an independent predictor of long-term mortality in the general population.1,2 Population-based studies report the risk of stroke after TIA as high as 10% to 20%.1–3 Stroke is the third leading cause of death in Europe and the leading cause of physical disability in adults.3 Prevention of stroke is the best approach in reducing the burden of this major public health problem.4

Transient ischemic attack and ischemic stroke share the same risk factors: for example, hypertension,5 abnormal blood lipids5 and lipoproteins,5 cigarette smoking,5 metabolic syndrome,6 diabetes and obesity,5 and physical inactivity.7 Studies have shown that physical activity can optimize physical capacity and quality of life among individuals with cardiovascular disease, including TIA.5,8 Moreover, physical activity has been shown to reduce some of the risk factors, such as hypertension, abnormal blood lipids, and metabolic syndrome8 with the strongest evidence being for physical activity of moderate to vigorous intensity performed on a regular basis.5,9

The effect of physical activity is dose-dependent; more time spent on physical activity and less on sedentary behavior is associated with a lower risk of developing lifestyle-related diseases such as TIA and stroke.7,10 A review of stroke prevention concludes that healthy individuals who are physically active according to current recommendations have a 25% to 30% lower risk of stroke compared with inactive individuals.11 There is general agreement on the usefulness of enhancing physical activity as a preventive measure against cardiovascular disease.5,8,12 Although some findings must be interpreted with caution, as energy expenditure during activity may not be representative of metabolic cost in persons with stroke.13 It has also been suggested that poor cardiorespiratory fitness may be an independent determinant of stroke incidence.14 One study has found that individuals having a diagnosis of TIA who increase their physical activity report fewer days with poor physical health and self-rated ill health compared with those who do not increase their physical activity.15

There are different methods to enhance people's physical activity.16 One of these methods is “Physical activity on Prescription” (PaP), wherein a health care professional provides an individualized prescription of activity for a person with symptoms or diseases for which physical activity is known to improve health. PaP always starts with a patient-centered conversation using a motivational interviewing technique. The prescription provides personalized suggestions for training based on the diagnosis, personal interest, personal fitness, and life situation.

PaP can be prescribed by physical therapists, physicians, nurses, or other licensed health care professionals. The prescription is written on a specific prescription form similar to the prescription form for drugs. The prescribed activity may include walking, water activities, weight training, aerobics session, qigong, yoga, or gardening. The activity may be carried out individually or in group activities. The PaP chosen are in accordance with the motivation and request of the respective person. If someone already has a walking behavior and is motivated to perform that activity, that activity shall be supported as well as an increase in intensity and/or duration and frequency of the activity.

There are several studies showing that PaP increases the level of physical activity in many different health conditions.17 Physical activity on prescription PaP has also been shown to have positive effects on the metabolic syndrome, which is a risk factor for TIA, and on cardiovascular disease.18,19 Pap prescribed by health care professionals in primary health care settings has been found to be effective in increasing physical activity in individuals with low levels of physical activity, especially in persons with cardiovascular risk factors such as overweight/obesity and diabetes.19–23 Moreover, PaP has been shown to have good compliance in a Swedish context.22

The effect of PaP in individuals with TIA has not been established. Furthermore, few studies examining the effectiveness of PaP have used objective assessment tools to evaluate the effects of the intervention.18,24 The purpose of our study was to assess the value of PaP for individuals with TIA using objective measures of physical activity and physical capacity. Basing our assumptions on previous research, we hypothesized that PaP will improve physical activity, physical capacity, and self-rated health among persons having a diagnosis of TIA.

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The study was constructed as a randomized controlled trial (RCT) on the effectiveness of PaP among patients having a diagnosis of an acute TIA. The participants were included between June 2010 and October 2013 and they were followed up 3 and 6 months after TIA. The participants were randomly allocated to receive either conventional treatment or conventional treatment and PaP. The study was approved by the Ethical Review Board in Stockholm (2010/671-31/3), Sweden. Informed oral and written consent was obtained from all participants.

Patients having a diagnosis of TIA were consecutively recruited from the stroke unit at Norrtälje Hospital, Norrtälje, Sweden. Inclusion criteria were: medically stable; and able to understand, read, speak, and write Swedish language. Patients with previous stroke, dementia, or serious health conditions that might interfere with safe participation were excluded. The power calculation was based on an unpublished pilot study, in which the mean time spent on moderate to vigorous physical activity (MVPA) among participants with TIA was 20 minutes per day. At the time the study was initiated, the recommended time for health promotion was 30 minutes per day,25 that is, 10 minutes more. As we wanted the participants to reach a clinically relevant level of physical activity, we chose to increase MVPA by 10 minutes over our pilot study. When the pilot data were adjusted for an additional 10 minutes of MVPA, a sample size of 100 participants was found to be necessary to detect a between-groups difference due to MVPA at α = 0.05, with power of 0.80.

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Randomization and Intervention

After inclusion, the participants were randomly allocated into an intervention group or a control group by means of drawing a note from an envelope containing 10 notes, 5 for allocation to the intervention group and 5 for allocation to the control group. When the first envelope was empty, the next envelope was opened and so on.

The participants in both the intervention group and the control group received conventional treatment including oral and written information on the risk factors for stroke, such as hypertension, abnormal blood lipids, metabolic syndrome, and physical inactivity. In addition, participants in the intervention group also received a written PaP, 2 weeks after discharge from the hospital. A physical therapist, with advanced training in how to support persons at different levels of readiness for change regarding physical activity, including motivational interviewing technique, constructed all the prescriptions and personally gave them to the participants. Each PaP was based on the participant's individual health status, symptoms, diagnoses, potential risk factors, prior experiences, and wishes. A patient-centered approach inspired by motivational interviewing technique26 was used to identify the most suitable physical activity to prescribe and to help build and strengthen motivation and strategies for change. The prescription was based on current evidence including specific advice on the reason for the prescription, assessment of current physical activity level, the participant's own goal, and 1 or 2 prescribed physical activities. The prescriptions included intensity, frequency, and duration of the activity prescribed. No target for heart rate was given, but we supported them to do their activity at an intensity level such that they would score approximately 12 to 13 on the RPE (Ratings of Perceived Exertion) scale,27 which means that they were warm and breathless. At the end of the session, the participants were asked to repeat the instructions in the PaP to ensure that they had understood the prescription. At 3 and 6 months follow-up, the patient-centered approach was also used.

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Each participant received an accelerometer (Actigraph GT3X; ActiGraph, Pensacola, Florida).28 This accelerometer has shown good test-retest reliability29 and good validity for assessment of physical activity in both younger30 and older populations including stroke.30–32 Furthermore, it has been used to evaluate the relationship between physical activity and cardiovascular risk factors.33 The participants were instructed to secure the unit in the middle of the back34 on an elasticized belt provided, to wear the unit while they were awake, and to take it off for swimming or bathing.35 The Actigraph GT3X measures acceleration in 3 axis as “counts” providing an indication of the intensity of physical activity associated with locomotion.36

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Outcomes and Follow-up

The primary outcome was MVPA as assessed by accelerometry. An intensity of MVPA was chosen because it has proved to be better associated with good health than physical activity of lower intensity.9 Assessments of the primary outcome were conducted 2 weeks after discharge from hospital and at 3 and 6 months' follow-up.

Secondary outcomes included total physical activity in terms of steps per day assessed by accelerometry, physical capacity assessed by the 6-minute walk test (6MWT), and self-rated health assessed by the EQ-5D VAS questionnaire. Steps per day assessed with accelerometer were conducted 2 weeks after discharge from hospital and at 3 and 6 months' follow-up. Physical capacity assessment by the 6MWT and self-rated health assessment by the EQ-5D VAS were conducted at baseline (in hospital) and at 3 and 6 months' follow-up. Assessment of body mass index (BMI) was conducted at baseline. All assessments were conducted by a specially trained and blinded assessor.

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Assessment of Physical Activity

Before being discharged from hospital, the participants in both groups received an accelerometer to assess physical activity for baseline data. The participants were instructed to wear the accelerometer all day for 7 consecutive days once they got home. Seven days' wear is a standard for accelerometry studies and has proved to reflect an average activity pattern.37 At an appointment 2 weeks after discharge home, the accelerometer was returned and the participants had the opportunity to ask questions about their health, risk factors, and their physical activity level measured by the accelerometer. Before the 3 and 6 months' follow-up, the participants again wore the accelerometers for 7 days, respectively.

For compliance, a valid day consisted of 10 valid hours. “Non-wear time” was defined as an interval of at least 60 consecutive minutes of no recordable activity, with an allowance of 1 to 2 minutes of counts between 0 and 100.35 Data were cleaned and scored using data analysis software (ActiLife version 6.8.0; ActiGraph). Total physical activity was expressed as total counts in the y-axis per day and steps per day. Time spent on MVPA was based on application of an existing count-based intensity thresholds using the y-axis, that is, MVPA ≥ 2020 counts per minute corresponding to greater than 3 METs (metabolic equivalents)38 and walking greater than 4 km per hour. Average intensity was expressed as total counts divided by wear time in minutes per day (counts per minutes) and averaged over the days worn.

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Assessment of Physical Capacity

Physical capacity was assessed by the 6MWT according to standard procedures. The 6MWT has shown good reliability,39 is commonly used in younger and elderly populations,40 and is validated to assess physical capacity.39,40 To avoid differences in encouragement given to the participants, a standard procedure was used (the American Thoracic Society statement).41 An increase of 50 m is proposed to be a clinically meaningful improvement (CMI) in the 6MWT.41

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Assessment of Self-rated Health

Self-rated health was assessed using the EuroQol 5 dimension visual analogue scale (EQ-5D VAS).42 The instrument has good test-retest reliability43 and good validity regarding both younger44 and older45 populations.

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Assessment of Body Mass Index

For baseline characteristics, weight and height were measured to determine BMI (kg/m2) on arrival at the stroke unit. Measurements were made while the participant wore indoor clothing and socks but without shoes. Individuals with BMI >25 and <30 are considered to be overweight, and individuals with BMI ≥30 are considered to be obese.

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Data Analysis

Demographic factors (age and gender), clinical characteristics (BMI), and all the outcome variables (physical activity, physical capacity, and self-rated health) of the intervention and the control groups at baseline are presented using mean ± standard deviation (SD) for continuous variables and frequency (%) for categorical variables. Between-group differences were examined using t test or chi-square test.

The effects of the intervention on physical activity, physical capacity, and self-rated health were examined by analyzing average group differences (control vs intervention group) in baseline scores and change in each outcome between baseline and 3 and 6 months' follow-up using linear mixed-effects models. Each model included the follow-up time as an indicator variable (coded as the 3 testing occasions: baseline, and 3 and 6 months' follow-up), treatment, and the interaction between treatment and follow-up time in association with each outcome. The coefficients of treatment versus time interactions were equivalent to the estimates for the group differences in the units of each measure. The within-person residual covariance matrix was evaluated with the unstructured correlation structure. Interactions were tested by including simultaneously the independent variables and their cross-product variables in the same model.

We analyzed the results, using the mixed-model approach without any ad hoc imputation. The mixed model provides a natural way to deal with missing values because it can accommodate different numbers of measurements for different subjects. Thus, investigators can base inference on all available measurements. A previous paper compares type I errors and power between 3 commonly used ad hoc methods including the last observation carried forward, the best value replacement and the worst value replacement approaches, and mixed model without any ad hoc imputation. The authors conclude that the mixed-model approach without any ad hoc imputation is more powerful than the other options to deal with missing values in longitudinal data sets.46 Statistical significance for all analyses was set at P < 0.05. Statistical analyses were performed using Stata, version 13 (StataCorp, College Station, Texas).

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One hundred twenty-seven patients were eligible. Of these, 9 patients (4 women), declined and 30 patients (18 women) did not meet the inclusion criteria (previous stroke, n = 17; dementia, n = 5; interfering health condition, n = 8) leaving 88 participants (47 women), mean age 71 years, range 49 to 90 years, to be included (Figure 1). Because of slower admission rate than anticipated, we did not reach the calculated sample size. The 88 participants were randomized to the intervention group (n = 44) that received conventional treatment and PaP or the control group (n = 44) that received conventional treatment. There were no significant differences between the intervention group and the control group in any of the demographic or clinical characteristics at baseline (Table 1).

Figure 1

Figure 1

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Primary and Secondary Outcomes at Baseline

At baseline, there were no significant differences between the intervention group and the control group in physical activity, physical capacity, or self-rated health (Table 1).

Table 1

Table 1

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Physical Activity on Prescription

The most frequently prescribed activity was different types of walking with or without poles, while 2 participants had swimming among their prescribed activities.

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Primary and Secondary Outcomes at 3 and 6 Months' Follow-up

Raw data for primary and secondary outcome at 3 and 6 months are presented in Table 1. There was no significant difference between the groups in MVPA at 3 and 6 months' follow-up (Table 2). Average change in MVPA over time by group affiliation (intervention vs control) is presented in Figure 2. At 6 months, there was a tendency (P = 0.079) toward a difference between the groups in favor of the intervention group in the number of steps per day (Table 2). Wearing adherence to the accelerometer, that is, the time the participants wore the equipment 10 or more hours per day for 4 or more days was 68% at 3 months and 93% at 6 months. Wearing time was equally distributed over the period the accelerometer was worn.

Figure 2

Figure 2

Table 2

Table 2

For physical capacity, there was a significant difference (P = 0.01) between the groups in favor of the intervention group at 6 months but not at 3 months. Median improvement in the intervention group was 70 m and in the control group 31 m. A CMI (≥50 m) was seen for 12 participants in the intervention group and for 8 participants in the control group at 6 months. One participant in each group used a walking aid. There was no significant difference between the groups in self-rated health at 3 and 6 months. The different number of subjects (n) for accelerometer data in Tables 1 and 2 was due to missing data.

No adverse events or side effects were experienced by any of the participants. A contributing reason for the nonsignificant results may be the low number of participants, as we did not reach the target enrollment identified a priori as necessary for achieving statistical significance in our primary outcome measure.

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To our knowledge, this is the first study to examine the effect of PaP on physical activity, physical capacity, and self-rated health after TIA, and the first study to examine the effect of PaP on MVPA with objective methods. The main finding derived from this study was that persons having a diagnosis of TIA who received PaP did not increase their physical activity even though they increased their physical capacity significantly more than the control group. Results approaching significance (P = 0.079) were observed for physical activity in terms of steps per day in favor of the intervention group. No significant difference between the groups regarding self-rated health was observed.

We did not find significant differences in objectively measured physical activity at 6 months between those who received PaP and those who did not. Physical activity (minutes per day of MVPA) among our participants was close to suggested normal values,47 although the age classifications are not fully comparable. However, few studies have measured physical activity objectively in older adults. In other RCTs evaluated with self-reporting assessments, significant differences in physical activity in favor of those receiving PaP have been reported.19–21 Neither the age groups nor the diagnoses, however, are comparable with the present study. The participants in this study were older than those in other studies, and elderly persons have been shown to be less adherent to PaP.48 This, together with other methodological differences, might contribute to the differences in results between prior studies and this study.

In a 2006 systematic review examining whether PaP increases the activity level in sedentary adults with signs of lifestyle diseases, self-reported physical activity increased significantly in 6 of 12 studies.49 A couple of nonrandomized uncontrolled trials have also shown that PaP significantly increases self-reported physical activity levels in individuals who were considered inactive.18,23 In a 2011 review, in which 8 RCTs involving sedentary individuals with or without medical diagnosis are included, weak evidence was found for an increase in self-reported physical activity in favor of those receiving PaP compared with usual care.17 In the present study, some participants were relatively active, that is, in terms of time spent on MVPA and steps per day, and perhaps less likely to show improvement. This might have contributed to the nonsignificant improvements in physical activity in this study.

The participants in this study walked a median of 430 m at the baseline 6MWT physical capacity assessment, which is shorter than published reference values (>500 m)50 and therefore indicates potential for improvement. Some participants, both in the intervention group (n = 12) and in the control group (n = 8), showed a CMI in distance walked (ie, ≥50 m). The finding that 6MWT distance increased significantly more at 6 months among those receiving PaP is in agreement with another RCT evaluating PaP among persons with coronary diseases.51 There are methodological differences between the studies, including age, diagnoses, and test instruments. In both studies, however, the participants included had cardiovascular diseases, making them comparable in that important respect.

This study failed to identify significant improvements in self-reported health assessed with EQ-5D VAS, in individuals having a diagnosis of TIA after participation in PaP. This is in accordance with some studies that did not17,20 and in contrast with others that did18,23 report improvements in health-related quality of life (HRQOL) after PaP. However, variations in methodological aspects, that is, design, age, diagnoses, and test instruments, limit the comparison. At the time of inclusion, the participants in this study already rated their health high, which may have limited the potential for improvements.

To enhance physical activity among individuals with TIA, we chose the PaP method, which has been shown to increase physical activity in general populations19,24 and which has a low cost for health care providers.52,53 It has been suggested that PaP has great potential to become an important method for enhancing physical activity and reducing cardiometabolic risk.19 The present study, however, failed to show increased physical activity using objective assessment methods. This was true even though we performed the PaP as proposed; that is, the prescribed activities were chosen according to the motivation and request of the respective participant, and if someone already had a walking behavior and was motivated to perform that activity, we supported that activity as well as an increase in intensity and/or duration and frequency of walking.

The wide confidence interval observed in this study indicates variability of the results. The participants could not be blinded to the intervention and the control group did not receive any placebo intervention, which may be considered a limitation. Furthermore, the fact that the participants were recruited from a single hospital may affect the ability to generalize the result to the general population with TIA.

A strength of this study is that physical activity was assessed objectively using accelerometry. This method is recommended since self-report assessments of physical activity are hampered by assessment biases.54 In the elderly, the bias may be due to bad health status and cognitive impairments.55 Most of the studies evaluating PaP have used self-reported assessment tools,18,21,23 which may be one reason for the different results compared with the present study. Risks associated with self-reported data may be recall or social desirability bias as well as a low response rate to the follow-up questionnaires, which may affect the results. Furthermore, self-reported physical activity levels are likely to be overestimated.28,56 Even though these objective devices poorly assess nonwalking activities, such as swimming, cycling, or strength training, we believe the activity older adults tend to engage in most frequently is of an ambulatory nature, such as walking, an activity that is well captured with the accelerometer.57 In the present study, most participants were prescribed some kind of walking activity and only 2 persons had swimming among their prescribed activities.

Despite our inability to achieve our target recruitment goal, another strength of this study is that few patients declined participation: that is, 90% of the eligible patients having a diagnosis of TIA were recruited. There was, however, a 30% dropout and a contributing factor may be the absence of reminders between the follow-up assessments. In other studies on PaP, up to 80% dropouts have been reported.58

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This study indicates that PaP does not increase time spent in MVPA, as assessed using objective measures, in persons having a diagnosis of TIA. The results may indicate that prior reports showing that PaP increases physical activity overestimate the effects due to self-reported outcome measures. The nonsignificant results may also be related to the fact that physical activity was already relatively high among the participants at baseline, and that we were unable to attain the target samples size. Future studies with sufficient power need to determine whether PaP has an objective effect on physical activity after TIA.

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PaP; physical activity; physical capacity; self-rated Health; TIA

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