1. Persuasive messages have no effect on increasing
physical activity level measured by DirectLife: A
randomized controlled trial
S.G.J. Andriën
I532819
Sports and physical activity interventions
First Supervisor: Guy Plasqui
Second supervisor: Hein de Vries
Faculty of Health, Medicine and Life Sciences
Maastricht University
20th September 2011

2. Abstract
Introduction: The incidence of physical inactivity is rising in the current population.
Morbidities are prevented by performing physical activity. Workplace interventions are
effective in increasing physical activity. DirectLife assists in creating a healthy lifestyle
trough measuring the daily activity by use of an activity monitor. The goal of the study is to
investigate whether persuasive (lunch walking) messages can increase the physical activity
(during lunchtime) measured by a DirectLife activity monitor. Furthermore is looked if
persuasive (lunch walking) messages influence the computer activity of participants.
Methods: Seventy-six participants followed the DirectLife program for five weeks starting
March 2011. The first week was an assessment week followed by four weeks of intervention.
The participants were randomized into an intervention group (n=33), which received
persuasive messages, and a control group (n=34), which received no messages. Persuasive
messages were displayed on a website. The link to the website was sent, in a text message, to
the participants if they had a working day. The persuasive messages were based on a theory of
Cialdini.
Results: There was no difference in total physical activity level (PAL) or total computer
activity for the assessment week and intervention weeks. No difference either was found in
PAL lunchtime or computer activity lunchtime for the assessment week and intervention
week. The total PAL, PAL lunchtime, total computer activity or computer activity lunchtime
showed no difference over time between the control and intervention group. There was no
relation between the average total computer activity and average total PAL for any
experimental group. Forty-eight procent of the send websites which were available for the
participants were viewed.
Discussion: Explanations for the lack of persuasive impact of the messages on physical
activity could be that messages were not convincing enough, and were not tailored to the
needs of the recipient. Not enough messages were read within a short period after sending.
Hence, more research is needed on reasons for people to perform physical activity and how to
develop effective persuasive messages.
Index
Abstract
2

3. Introduction 5
General problem: Physical inactivity 5
Workplace interventions 5
Physical activity measurement 6
Social theory: Theory of Planned Behavior (TPB) 7
Social theory: Persuasion 8
Goal of the study 10
Methods 10
Study population 10
DirectLife equipment 11
Design 13
Intervention 13
Persuasive messages 14
Analysis 14
Results 15
Groups 15
Intervention vs. Control 15
Total PAL 15
PAL lunchtime 16
Total computer activity 17
Computer activity lunchtime 17
PAL and computer activity 19
Messages sent 19
Discussion 20
General 20
Lunch walking as intervention 20
Messages 21
PAL 21
PAL and computer activity 21
Limitations and recommendations 22
Conclusions 23
References
Appendices
3

4. 4

5. Introduction
General problem: Physical inactivity
There is a growing number of people with obesity in The Netherlands and Europe (1). Obesity
is caused by a long-term positive balance between energy intake and energy expenditure (2).
Increasing daily physical activity level restores this balance. Benefits of physical exercise
include the prevention of coronary vascular disease (CVD) and diabetes mellitus type II (DM
II) (3). Every year, physical inactivity is estimated to cause 600,000 deaths in the EU region
(about 6% of the total mortality), and conditions such as obesity contribute to over 1 million
more deaths (4). To reduce mortality, guidelines for physical activity are introduced by the
government. These guidelines are described in the Dutch healthy exercise norm (Nederlandse
Norm Gezond Bewegen, NNGB) (1). The exercise norm states that people have to perform at
least 30 minutes of moderate physical activity five times a week to remain physically fit. A
large portion of the population does not meet these guidelines and is at risk of developing
morbidities (1). Interventions are created to promote and increase the physical activity of
people.
Workplace interventions
An appropriate location where an intervention for increasing physical activity should take
place is at a worksite. This is a place where (white collar) workers spend a long period of time
each day being inactive (5). Workplace interventions in the past show an increase in physical
activity (4, 6-8). Physical activity promotion is financially lucrative for organizations. It
lowers the chance of morbidities and therefore prevents absence among workers (9). Physical
activity increases the productivity of employees by improving the confidence of the
employees and interpersonal relationship with colleagues (10). Persuasive messaging could
provide a cost effective means to promote physical activity (11). Walking during lunchtime
(lunch walking) could increase ones daily physical activity (4). At lunchtime, a worker has no
engagements. Social pressure performed by colleagues could persuade a person to join a
lunch walk and increase his physical activity (12). Lunch walking which increases the step
count shows promising results in increasing physical activity among sedentary workers (4, 5).
Little information is known of the effect of lunch walking on total physical activity (4). In
many studies counseling (e.g. messaging) was proven to be effective in activating workers to
perform physical activity (13-18). Prior research looks into providing persuasive messages
tailored to a specific group, not into the timing of the message (19).
5

6. Physical activity measurement
There are different methods in measuring physical activity. The use of an activity monitor
(accelerometer) within the study allows objective monitoring of physical activity among the
participants. Objective methods are considered to be more accurate than self-reported
measures (20). Interventions at the workplace often use walking as outcome. Walking can be
specified into step count (13, 14, 16), walking time (18, 21, 22) or energy expenditure (EE)
(23). Step count measures the steps taken and walking time calculates the time spend walking.
Both measure no other physical activities performed during a day. Therefore, step count and
walking time do not give a clear representation of the total daily physical activity. EE is more
representative because all activities during a whole day are measured. EE can be expressed in
physical activity level (PAL) or arbitrary acceleration units (AAU). The PAL can be
determined by dividing the total EE by the basal metabolic rate of an individual (24). AAU
represent intensity and duration of an activity. EE can be determined based on the counts of
an accelerometer (23).
Walking is measured by a pedometer or accelerometer. A pedometer measures on one
axis and is therefore considered less accurate compared to the accelerometer which measures
on three axes (25). Often accelerometers are used within large trials because of its small size,
low costs and non-invasive characteristics (26). An accelerometer measures acceleration in
arbitrary acceleration units (AAU) (25). Higher amount of AAU is equal to higher activity
(27-29).
Physical activities are categorized into light, moderate or vigorous activities to classify
the intensity of the activity (30). This categorization is linked to the AAU. Categorization
only applies if one performs the same activity for a longer period of time (e.g. running for half
an hour) (27). An accelerometer has to be validated against doubly labeled water, to convert
the measured AAU into a PAL (31, 32).
To overcome the problem of incorrectly measure physical activity performed for a
shorter period of time, algorithms (33), compensating for gait and walking speed (34, 35) and
GPS (23) have been suggested as solution. By determining which physical activity is
performed (codation), a better estimation for EE can be made.
Activity monitors based on accelerometry use algorithms to convert accelerometer
output, into EE. Based on measurement on three different axes (x,y,z), an activity monitor can
determine which activity is performed (categorization) (e.g., figure 1) (26). Intensity of an
action is determined by higher AAU from the activity monitor. By combining this information
6

7. a better assessment can be made in judging what type of physical activity is performed and
how much energy is spent.
Figure 1: The circles represent decision nodes. In the decision nodes, activities are determined based on
different features. The features selected for the classification were the standard deviation of the acceleration in
the vertical, mediolateral, and anteroposterior direction (Rx Ry Rz); the average acceleration in the vertical
direction of the body (ax); and the cross-correlation of subsequent intervals of the acceleration in the
anteroposterior direction (Rz) (26).
Theories about health behavior
When influencing physical activity by messaging, the content of the provided messages is
important. Social cognitive theories indicate which factors should be taken into consideration
when forming the message. The Theory of Planned Behavior (TPB) and other social cognitive
theories have different focus points. The TPB indicates the link between attitude and behavior
(figure 2) (36). Within the TPB the desired health behavior, lunch walking, is determined by
the intention to go lunch walking. Intention in turn is determined by three variables, namely
attitude towards lunch walking, subjective norms and perceived behavioral control.
Messaging should influence the variable within a person which is low. (i.e. if one has a
positive attitude but a low self efficacy the message send should influence ones ability
breaking barriers) (appendix 2: example of messages with matching theory indications)
The TPB states that attitude is a function of the beliefs held about lunch walking, as
well as the evaluation, or value, of the likely outcomes (37). Messaging could influence the
beliefs by making one aware of the positive effects of lunch walking. The subjective norm
component of the TPB (normative component) is comprised of the beliefs of significant
others and the extent to which one wishes or is motivated to comply with such beliefs (37). If
7

8. one values the opinion of others the intention is likely to be influenced by the thoughts on
lunch walking of these others.
Perceived behavior control is the perceived ease or difficulty of lunch walking and is
assumed to reflect past experience as well as anticipated impediments and obstacles (36, 38,
39). One can be perceive hesitation to go lunch walking when it is raining. Ones intention will
then be lower due to a lower perceived behavior control. When the intention is high, the
chance that lunch walking is performed is higher than when the intention is low.
Figure 2: Graphic representation of the theory of planned behavior. Attitude, subjective norm and percieved
behavioral control determine intention which leads to behavior (37).
Persuasion
Next to the content of messaging, the method of messaging is important. The persuasive
theory indicates a method of messaging. Persuasive technology is already used in commercial
form. Products like Philips DirectLife and Fitbug already make use of persuasive technology
to support a healthy lifestyle (40). Persuasive techniques are tested in studies in influencing
people to lose weight (41) and influencing snacking behavior (42). Both studies shows that
the effectiveness of the influencing strategies is different between subjects. Participants in the
studies had different susceptibility for a different persuasive strategy (41, 42). Effectivity of
the persuasion techniques show to be variable throughout different studies (42). Other studies
have created applications to influence people in maintaining a health workout regime (19).
This indicates that creating (tailored) persuasive messages which are effective in changing
behavior is difficult. The susceptibility for the different strategies has to be measured in
advance otherwise the messages have to be provided randomly.
8

9. In 2001 Cialdini came up with a cluster of influencing strategies to persuade people to
perform a specific action (43-45). The strategies can be considered as means to attain a certain
goal. There are six different strategies defined by Cialdini, for each category an example on
thoughts of a person on lunch walking is given;
Reciprocity indicates when a person (receiver) receives a favor, he/she is likely to return a
favor. In this way he/she is in debt with the person who supplies (supplier) the favor. When a
persuasive request is made by the supplier the receiver is likely to do so (46). People also
return the favor when there is no request given (42). (e.g. Peter asked me to join him during
his lunch walk today. I will join him because yesterday he helped me with my work).
If something is scarce people will value it more (scarcity). By indicating that there is
limitation to a product or time span people will increase the chance of buying the product or
spending their time effectively (47). (e.g. I should go walking today. Today I have got the
time, tomorrow I will be in meeting all day).
Advice given by a famous person, specialist, or person with authority will increase the
likelihood of performing the action by the receiver (42, 48). (e.g. My physiotherapist told me
that walking during the lunch is good for my health. I am going to walk during lunch).
Within commitment and consistency is indicated that one is likely to perform actions
which are in line with their earlier performed actions and statements in order to prevent
cognitive dissonance (42). (e.g. I said to Peter; “I am going to walk during the lunch every
day this week.” I am going lunch walking).
One feels connected to others, if others act one is likely to perform in consensus (46, 49).
(e.g. I saw the people at the workplace walk during lunch. I am going lunch walking today).
We say “yes” to people we like. If we like the person requesting the action we are likely to
agree to follow it‟s advice (43). (i.e. Peter is my friend, he told me that lunch walking is vital
to good health. I am going lunch walking today).
Goal of the study:
This study investigates whether physical activity of workers, with a merely sedentary job, can
be increased by sending them persuasive messages. Research indicate the importance of
timing in providing persuasive messages (50). Prior research looks into providing persuasive
messages to a specific group, not into the timing of the message (19). Interventions on
promoting physical activity at work are present (4, 6-8). Earlier performed intervention in a
workplace on messaging measures self-reported physical activity (51). Self-reported physical
activity is considered to be less accurate than measured physical activity. However little
9

10. information is known of the effect of lunch walking on total physical activity or physical
activity at lunchtime (4). This study intends to cover both gaps in literature by providing
persuasive messages on lunch walking to participants when physical inactivity is measured.
Therefore the goal of this study is to investigate whether a four week persuasive message
intervention on lunch walking, during lunchtime, can increase the physical activity measured
by the DirectLife activity monitor.
Methods
Study population
All participants (N=210) that were selected, were workers of different companies in The
Netherlands and native Dutch speakers. Compared to other age groups, the DirectLife has the
highest effect on people above the age of 30 years (unpublished pilot results). The participants
all self reported to have a merely sedentary job (desk job). Recruitment was done by sending
an email to potential participants by a recruitment agency. The inclusion of participants was
verified by an online questionnaire. The exclusion criteria were: persons, known not to have a
merely sedentary job; with activities at work not performed behind a computer which is only
used by the participant; not able to install the DirectLife connect application on the work
computer; age under 30 years; not in possession of a smart phone with internet connection to
open hyperlinks received by text message (see header persuasive messages); known physical
handicap, disorder or disease which makes performance of moderate physical activity (like
walking) impossible; participating in any other intervention which includes the use of the
DirectLife equipment
If the participants did not meet the exclusion criteria they received an email from the
recruitment company which contained the general information on the project and an informed
consent (appendix 1). All participants of the study filled in their informed consent and
returned this to the researchers. The total time of the intervention took five weeks and started
for the first person in the third week of May 2011. This is divided into one week assessment
and four weeks intervention.
DirectLife equipment
This research was part of a larger program (Smarcos) on the DirectLife equipment. The
DirectLife was developed by Philips (New Wellness Solutions;
http://www.directlife.philips.com). The DirectLife program allows people to monitor their
10

11. physical activity for each minute and therefore allows them to change their lifestyle. Within
the (commercial) DirectLife program a coach is provided to users for counseling.
In order to measure physical activity a DirectLife triaxial
accelerometer for movement registration (TracmorD, activity monitor)
(figure 9) was supplied to the participants. The activity monitor
measured 31 x 33 x 11 mm, and weighted 23 g. The monitor performed
measurements when attached to any clothing or used as a pendant around
the neck. Sampling rate of the equipment was 1 Hz. Intensity of a
movement was estimated. These estimations were done based on models
which included body characteristics and acceleration features (26). By including the measured
acceleration and the intensity it was possible to calculate the PAL of a person.
The equipment of DirectLife further consisted of a web-based program which
transferred the measurements into displayed data. When subjects logged in on the website, a
graphical representation of EE (in kcal) was displayed (fig 10).
Figure 10: Graphic representation of the performed physical activity showed to the participants when logged
into a website. The bars indicate the physical activity performed during the day specified for each hour. Data
can be viewed per month, week, day or hour. The total calories burned and the percentage of the personal goal
is indicated. The performed activity is divided into moderate and vigorous activity in minutes
(www.directlife.philips.com)
Participants set their own goals based on an assessment period of one week. Within
this week one carried the activity monitor along. The performed activity during the first week
was considered to be normal and set as 100%. A goal was then generated to be accomplished
11

12. by means of a plan that lasted for six weeks. The plan was created to improve the total
physical activity of a participant. Within this trial all the participants received the DirectLife
equipment.
Participants received the DirectLife kit containing an activity monitor, connect device
(usb), a pouch to carry the activity monitor in and a necklace where the activity monitor could
be attached to. In order to use the equipment, the activity monitor was first hooked through
the connect device. The DirectLife-connect software was installed and further instructions to
the participants were provided on the screen. The DirectLife-connect software allowed a
participant to synchronize the data collected from the activity monitor with the personal
website. Another function within the DirectLife-connect software was the measurement of
keyboard and mouse activity. This information was sent to the server (only available for the
researchers). In this way it was measured when a person was sitting behind his or her desk.
Design
After the participants signed the informed consent form, they were randomized over two
different conditions (control and intervention). They then received an invitation email which
allowed them to join and make use of the DirectLife program. If the participant completed the
registration of the DirectLife program they received the complete DirectLife equipment and
were able to start the program. The program started with an assessment week (7 days) which
constituted the baseline measurement. The participants did not receive any messages during
the assessment week. After the assessment week the participants started their 4 week plan.
Final assessments were realized after 4 weeks.
Intervention
During the plan the intervention group received persuasive messages. Keyboard and mouse
activity (computer activity) is measured by the DirectLife software installed on the
participants‟ computer. A person was only sent a text message when considered to have a
working day. Working days were days on which computer activity was registered any time
before the first message was send on a specific day. A (first) message was sent each working
day 15 minutes prior to the indicated lunchtime. The pre-specified time of consuming the
lunch was asked during the assessment.
After the first message was sent, DirectLife continued measuring computer activity. If
a person had more than 22 minutes of computer activity in a time span of 30 minutes, started
directly after the first text message was sent, another text message was sent. The person had to
12

13. show computer activity in the last minute before sending the text message to ensure the
inactivity of the participant.
Participants received a message trough a link provided to them within a text message
on their smartphone. The text message was always the same: “Hallo <voornaam>, volg deze
link: <hyperlink> voor een nieuw bericht! Groet coach Sander.”. (English: “Hello <First
name>, follow this link: <hyperlink> for a new message! Greetings coach Sander.”). The
hyperlink redirected to the website which was used to display the persuasive message
(appendix 2).
The control condition also received the DirectLife equipment but did not receive any
additional (persuasive) messages to motivate them to become physically active during
lunchtime.
Persuasive messages
The goal of the persuasive messages was to promote physical activity, specifically lunch
walking. All the persuasive messages targeted the different motivational factors as described
by TPB and thus addressed perceived behavior control, attitude or subjective norm. For the
method of delivering the messages the messages were based on the persuasion techniques
defined by Cialdini (2001). All the persuasive messages in this study were in Dutch. For each
category, within both theories, formulated in the introduction different persuasive messages
were created. The messages based on the reciprocity and liking from the theory of persuasion
were not formed because this requires a relation between the supplier and receiver of the
message. This relation is not present between the researchers and participants. In appendix 2
is indicated for each message what factor within the persuasion theory they influenced. The
messages were checked by several specialists, who worked on forming persuasive messages,
on their category within the theory of persuasion and TPB (46). Messages which had a
consensus, in each category of the TPB and theory of persuasion, lower than 80% where
excluded to be sent to the participants.
The database selected randomly one out of the total of 31 available messages which
was sent to the participant (not tailored). If a message was send to a participant there was a
lower chance that this message was chosen again. When a text message was sent this was
registered on a server. When a participants retrieved the website which contained a persuasive
message this was also registered on a server. The registration from the server shows how
many times a message was retrieved. If the link in the text message was opened the link
13

14. became inactive. Seven days after sending the text message the link to the website containing
the persuasive message became inactive.
Measurements
Within the study the age, height, weight and gender was acquired by registration of the
participants. The BMI was calculated out of the height and weight reported by the
participants. The total PAL was assessed by including the measurements of each second by
the activity monitor. The data measured each second in AAU was converted into PAL. The
PAL of each second was mediated and an average PAL each week was calculated. The PAL
lunchtime was the total PAL starting each day 15 minutes before the indicated lunchtime for
60 minutes mediated for each week. The total computer activity was the activity on the
computer measured each minute and mediated for each week. The computer activity
lunchtime was the total computer activity starting each day 15 minutes before the indicated
lunchtime for 60 minutes mediated each week. The amount of text messages sent to the
participants and the amount of opened webpages which contained the persuasive message was
registered.
Analysis
An ANOVA analysis (between groups; experimental condition and within groups; the
different weeks) was performed in SPSS 18.0 to compare the intervention and control
condition in total PAL. Specified results were acquired to investigate the effect of the
messages on the PAL lunchtime. The total computer activity was also measured and
compared between the groups. This was also specified for the computer activity lunchtime.
The difference between the groups over time was analyzed for the total PAL, the PAL
lunchtime, total computer activity and computer activity lunchtime. The relation between the
PAL and computer activity was analyzed to assess whether lower PAL is linked to higher
computer activity. The dependent variables were PAL and computer activity. The
independent variables were the experimental group and the different weeks. A relation was
made between PAL and computer activity through an ANOVA (dependent variable: PAL,
independent variable: computer activity). General information on the messages and
descriptive statistics were acquired. Each week during the plan the primary outcome, average
total PAL and PAL lunchtime was measured. The secondary outcome of this study was total
computer activity and the computer activity at lunchtime. Further the relation between the
PAL and computer activity was measured.
14

15. Results
Groups
The intervention was completed by 67 participants (37 males); 34 subjects (23 male) were
part of the control group whereas 33 subjects (14 males) belonged to the intervention group.
Dropouts (N=147) were people which failed to install the DirectLife software, did not
complete 4 weeks of the program or reported to be unhappy with the use of the program.
Further descriptive of the participants can be found in table 1.
Table 1:General description participants
Control Intervention
Parameter Mean ±s.d. Range Mean ±s.d. Range
N (M/F) 34 (23/11) 33 (14/19)
Age. years 43 ± 7 27- 55 42± 8 25 – 62
Weight kg 90.9 ± 19.2 50.0 – 135.0 80.1 ± 18.6 54.0 – 137.0
Height. cm 179.6 ± 9.8 154.0 – 203.0 175.8 ± 10.2 160.0 – 196.0
BMI. kg/m3 25.8 ± 6.1 19.0 - 45.6 28.2 ± 4.7 16.9 - 39.9
The intervention and control group showed no significant differences in week 1 (assessment
week) for total PAL (figure 10) F = .23 p = .63, PAL lunchtime (figure 11) F = .52, p = .47,
total computer activity (figure 12) F = 1.28, p = .26 and computer activity lunchtime (figure
13) F = .02, p = .87. No significant differences between groups were found for gender, BMI
or age (p > .05).
Intervention vs. Control
The intervention and control group showed no significant differences for total PAL (figure
10) F = 1.25, p = .26, PAL lunchtime (figure 11) F = .02, p = .87, total computer activity
(figure 12) F = .75, p = .38, computer activity lunchtime (figure 13) F = .36, p = .55
Total PAL
The average total PAL of the participants for the different weeks were; week 1 – 1.65; week 2
– 1.69; week 3 – 1.67; week 4 – 1.68; week 5 – 1.68 (figure 10). For both groups the highest
PAL was measured during week two.
15

16. Figure 10: Average total PAL per day displayed per week for the control and intervention group
Analysis showed that there was no significant effect between the different groups over time in
PAL F(4,59) = 1.38, p = .25.
All though there is no significant effect found between the different groups over time. The
pairwise comparison analysis showed that there is a significant difference between week 1
and 2 (Mean difference week 1 – Mean difference week 2 (Mdif) = -.04; p = .02). There was a
short positive effect in total PAL of the used DirectLife equipment.
PAL lunchtime
Figure 11 shows the average PAL measured for 60 minutes starting 15 minutes before the
self-reported lunchtime. The average PAL for all the weeks is 1.15. For both groups the
highest PAL lunchtime was measured during the second week.
Figure 11: Average PAL lunchtime per day displayed per week for the control and intervention group
16

17. There was no significant difference in PAL lunchtime between the groups over time F(4,59) =
1.07; p = .38.
Total computer activity
The average total computer activity (minutes per day) of the participants for the different
weeks were; week 1 – 180; week 2 – 190; week 3 – 184; week 4 – 186; week 5 – 200 (figure
12). These values excluded the days that there was no computer activity at all. These days
were not considered as working days. For both groups the measured computer activity was
highest in the fifth week.
Figure 12: Average total computer activity in minutes per day for each week for the control and intervention
group
No significant difference in computer activity between the groups over time is found F(4,55)
= 3.73, p = .82
Computer activity lunchtime
Figure 13 shows the average computer activity measured for 60 minutes starting 15 minutes
before the self-reported lunchtime. The average computer activity varied between the 10 and
13 minutes per day. The computer activity of the intervention group was lower each week
compared to the control group.
17

18. Figure 13: Average computer activity lunchtime in minutes per day for each week for the control and
intervention group
There was no significant difference in computer activity lunchtime between the groups over
time F(4,58) = 1.44; p = .23.
Figure 14: Scatterplot of relation between average total computer activity (min/day) and average total PAL (per
day) for the control and intervention group
18

19. PAL and computer activity
Figure 14 indicates the relation between average total PAL and average total computer
activity separate for the intervention and control group. Both measurements were performed
for five weeks and then averaged. A similar graphic representation was performed for the
average PAL lunchtime and average computer activity lunchtime (figure 15). There was no
relation between the average total PAL and the average total computer activity for both
experimental groups clustered (F = 3.46, p = .06). If taking the experimental groups into
consideration no relation was found either (F = 1.35, p = .25 for the control group, F = 2.45, p
= .12 for the intervention group). For lunch walking no relation was found between the
average PAL and computer activity for all the participants (F = 1.35, p = .24). If taking the
experimental groups into consideration no relation was found either (F = 2.00, p = .16 for the
control group, F = .00, p = .93 for the intervention group).
Figure 15: Scatterplot of relation between average computer activity lunchtime (min/day) and average PAL
lunchtime (per day) for the control and intervention group
Messages sent
In total 610 text messages were sent. For 259 of the send text message the link to the webpage
was opened (42%). Table 2 indicates how many messages of each category was sent to the
participants in the intervention group.
19

20. Table 2: Number and percentage of sent messages
Total text Total
messages webpages Authority Consensus Commitment Scarcity
send opened message message message message
610 259 165 178 129 130
100% 42% 27% 29% 21% 21%
The time between sending a message and opening a message had an average of 3.96 hours
(std 3.04) (range: 37 sec – 29.93 hours).
Discussion
General
This study aimed to investigate whether a four week persuasive message intervention on
lunch walking, during lunchtime could increase the physical activity measured by the
DirectLife activity monitor. We assumed that persuasive messages would increase the
physical activity of participants. However the results indicated that there were no significant
effects of persuasive messages on physical activity or computer activity over time.
Additionally no relation was found between the computer activity in minutes per day and
PAL. This means that there is no further increase or decrease in PAL from the intervention
group compared to the control group. The persuasive messages did not seem to have an
additional effect.
Lunch walking as intervention
The participants in the study were selected based on their self-reported daily pattern of
inactivity during the (working) day. An average total PAL of 1.67 indicated a normal daily
activity among the participants (52). The average BMI of 27 is a normal value found in
studies considering physical activity (31). However higher BMI could indicate general
inactivity in the past.
Inactivity is found during lunch time with a PAL lunchtime average of 1.15.
Promotion of lunch walking during lunchtime forms possibilities within the population to
increase the physical activity. The measured values also indicate that improvement of PAL
during lunchtime is possible.
20

21. Messages
There was no significant difference found between the control and the intervention group over
time for the total PAL, PAL lunchtime, total computer activity or computer activity
lunchtime. This means that there was no further increase or decrease in computer activity or
PAL from the intervention group compared to the control group. The persuasive messages do
not seem to have an additional effect.
A part of the research population had no or low computer activity any time during the
day (figure 14). These people reported incorrectly to perform work activities at a computer.
When no computer activity (lunchtime) is measured, no messages were sent (during
lunchtime).
The use of another computer (at work or home) any time during the day without
DirectLife software is not registered as computer activity. Because the software was not
installed on other computers that were used, average total computer activity could be higher.
For 42% of the text messages the link provided to the website that contained the persuasive
message was opened. Underestimation of computer activity, no or low computer activity for a
part of the intervention group, 42% of all the send websites opened and a average period of
almost 4 hours between sending and opening a persuasive message make it unable to find a
significant effect of the messages on computer activity or PAL.
PAL
There was an increase in average total PAL between week 1 and week 2 in both the
experimental and control group. The second week enabled the participants to view their
physical activity through the website. Awareness of daily physical activity is then achieved
(53). Based on their PAL at baseline (assessment week), individual goals were set to
gradually increase physical activity over a period of 6 weeks. The awareness and goal setting
seem to have a positive effect on the promotion of physical activity (54-57). This could
explain the significant difference between the first and second week.
PAL and computer activity
There is no significant relation found between the computer activity and PAL. This means
that higher computer activity is no indicator for lower PAL. Physical activity is often
performed in the evening, while during the day participants have no possibility of performing
physical activity accept for lunchtime. This could explain why people with high computer
activity still have high PAL. Computer activity is only measured during the time spent at
21

22. work. The measured PAL is for a total day. This could indicate another reason why there was
no relation found between the computer activity and PAL.
For computer activity during lunchtime the same measurement is performed. No
relation is found there either between computer activity lunchtime and PAL lunchtime. People
do not necessarily make use of the computer to be inactive. Often meetings are scheduled or
other physical sedentary activities are performed which do not involve the use of the
computer. In this time people are being physically inactive (low PAL) but also have low
computer activity. Perhaps a different measure, like minutes of moderate physical activity
could better estimate the activity of a person for one hour.
Limitations and recommendations
Further qualitative research could be done in the selected participants e.g. interviewing them
about the DirectLife program. This study indicates that inactivity measurements by the
DirectLife activity monitor should form the base of sending a text message. This way, timely
feedback is provided during several moments a day compared to using a computer. With the
increasing use of smartphones with motion sensor and GPS present, applications for
measuring physical activity appear rapidly. With this technique it is possible to deliver
messages to the people without making use of computer activity. The messages are then
directly provided on the screen and do not have to be displayed on a webpage through a link.
In this way, it would be better able to test the effect of the persuasive messages, through
timely feedback. Prior studies indicate the importance of tailoring the messages. Messages
within this study are not tailored to the needs of the participants but send randomly. This
indicates that it is not clear if the messages are considered to be persuasive to a specific
participant.
Future interventions should look into the motivations of people to start physical
activity. Within an intervention the messages can then be tailored to the current needs of the
participants. By piloting the messages the usability can be verified.
The PAL measured during lunchtime is done for 60 minutes. PAL is most of the times
considered to be more reliable when used for daily activity or longer periods of time. Other
measures like minutes of moderate physical activity do not include basal metabolic rate and
require a cutoff point between classification of intensity of activity. Activity counts could
form possibilities in further research of the acquired data during lunchtime.
22

23. Conclusion
The physical activity level was not influenced by providing timely persuasive messages to
participants. However, no hard conclusion can be drawn in the effect of supporting people to
become more physically active trough persuasive messages. Further research with timely
provided messages, tailored to the population, without constrains of reading the messages
should be performed to draw a stronger conclusion. Other effects of supportive messages
were not investigated.
23

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28

29. Appendix 1:
Informed consent form
INFORMED CONSENT Werkplek interventie voor ‘Situated Coaching’
Vrijwilliger
√ Ik heb de informatiebrief over dit onderzoek gelezen en begrepen. Al mijn vragen zijn
beantwoord door de verantwoordelijke onderzoekers.
√ Ik heb voldoende tijd gehad om mijn deelname aan dit onderzoek te overwegen en ben
er mij van bewust dat deelname aan dit project geheel vrijwillig is.
√ Ik weet dat ik op elk moment mijn deelname aan dit onderzoek kan stilzetten zonder
hier een rede voor op te geven.
√ Ik begrijp en ga ermee akkoord dat mijn persoonlijke informatie wordt verkregen,
gebruikt en verwerkt met als doel dit project. De persoonlijke informatie verkregen
kan gerelateerd zijn aan mijn gezondheid en etnische achtergrond. Ik begrijp dat mijn
persoonlijke identificerende informatie (e.g. naam, adres) gescheiden zal worden van
de onderzoeksgegevens en vervangen wordt door een nummer/code. Toegang tot de
sleutel/link tussen het toegewezen nummer en mijn identiteit zal beschermd zijn en is
alleen zichtbaar voor de verantwoordelijke onderzoeker en zal alleen worden
bekendgemaakt aan nationale regelgevende instanties of ethische commissies indien
nodig voor rapportage aan deze; of de onafhankelijke medisch adviseur in geval van
medische noodzaak.
√ Ik geef toestemming aan Philips om de verkregen data van de „DirectLife‟ apparatuur
te gebruiken.
√ Ik ga ermee akkoord dat mijn persoonlijke gegevens worden gebruikt voor ander
onderzoek of ontwikkeling doelen.
√ Ik ga ermee akkoord dat de gegevens verzameld door DirectLife in overeenstemming
zijn met de DirectLife Privacy verklaring. Gegevens die geregistreerd en opgeslagen
worden, onthullen geen inhoud of informatie van uw computer.
√ Ik weet dat ik het recht heb om een overzicht van mijn persoonlijke data welke
verworven zijn te ontvangen voor correctie of verwijdering.
√ Ik heb een kopie van de informatie brief ontvangen.
√ Ik ga akkoord met deelname als vrijwilliger aan dit onderzoeksproject.
√ Ik zal zorgvuldig met het ontvangen pakket omgaan en op verzoek van de
onderzoekers aan het eind van het project compleet terugsturen.
29

30. ________________________ ____________________ __________
Naam Handtekening Datum
Verantwoordelijke onderzoeker
Ik heb alle vragen over dit onderzoeksproject beantwoord.
________________________ ____________________ __________
Naam Handtekening Datum
30

31. Appendix 2:
Persuasive messages
Message
ID Strategy Message Lunchwalking (Dutch) Categorie TPB
"Elke persoon is verantwoordelijk voor zijn of
haar eigen fysieke activiteit ongeacht leeftijd en
gezondheid. Er zijn meerdere redenen om fysiek
actief te zijn" zegt Jaap van Vleuten,
inspannings fysioloog. Hij geeft als tip "
64 Authority Wandel tijdens je lunch!" Subjective Norm
Er zijn meer redenen om wel te bewegen dan
om dat niet te doen", zegt Pieter Jansen,
inspanningsfysioloog. Zijn advies: "Wandel
65 Authority tijdens de lunch" Subjective Norm
4000 mensen nemen actief deel aan het
DirectLife programma. Deze mensen wandelen
tenminste 1x per week tijdens de lunch. Voeg je Percieved Behavior
66 Consensus bij deze groep en ga wandelen tijdens de lunch! Control
4000 mensen nemen net als jij actief deel aan
het DirectLife programma. Zij gaan wandelen
tijdens de lunch om sneller een gezond Percieved Behavior
67 Consensus bewegingsniveau bereiken, jij toch ook? Control
90 procent van de mensen die wandelen tijdens
de lunch hebben er baat bij. Het zorgt voor een
toename in energie en zorgt op den duur voor
68 Consensus een gezonder leven. Attitude
Ben je gaan wandelen tijdens de lunch? "Een
actieve levensstijl helpt om er goed uit te
blijven zien" zegt plastisch chirurg Robert
69 Authority Schoemacher. Subjective Norm
Beweeg tijdens de lunch, des te fitter je zult
70 Consensus worden. Attitude
De Wereld Gezondheidsorganisatie adviseert
om fysiek actief te zijn tijdens de lunch. Ga een
stuk wandelen. Lange tijd inactief zijn is slecht
71 Authority voor je gezondheid! Subjective Norm
Deelnemers die wandelen tijdens de lunch
hebben gemerkt/merken dat je een grotere kans
hebt om je doel op een gezonde leefstijl te
72 Consensus bereiken. Attitude
Dit onderzoek duurt slechts 7 weken: je hebt nu
de kans om je gezondheid te verbeteren door te
73 Scarcity gaan wandelen tijdens de lunch. Attitude
Elke dag zonder lunchwandeling is een gemiste
74 Scarcity kans. Attitude
31

32. Elke kans om een lunchwandeling te maken is
een mogelijkheid om je bewegingsniveau te
75 Scarcity verhogen. Grijp je kans nu en ga bewegen! Attitude
Ervaren DirectLife coaches adviseren om te
wandelen tijdens de lunch. Hierdoor zal je
76 Authority dagelijke niveau van fysieke activieteit stijgen. Subjective Norm
Fysiotherapeuten adviseren om dagelijks een
stuk te wandelen tijdens de lunch. Probeer
77 Authority actiever te zijn, dit is goed voor je gezondheid. Subjective Norm
Het doel van deze studie is om een gezondere
levenstijl te creëren. Wandelen tijdens de lunch
78 Commitment is een manier om dit te bereiken. Attitude
Het Nederlandse Verbond van Huisartsen
adviseert om dagelijks een half uur te bewegen.
Wandelen tijdens de lunch zal je helpen om dit
79 Authority advies te bereiken. Subjective Norm
Iedereen is het erover eens dat wandelen tijdens
80 Consensus de lunch zorgt voor een betere gezondheid. Attitude
Je hebt al eerder gewandeld tijdens de lunch, ga Percieved Behavior
81 Commitment hiermee door! Control
Je hebt nu de kans om je fysieke activiteit te
verhogen. Pak die kans… ga wandelen tijdens
82 Scarcity je lunch! Attitude
Je investeert zelf in een gezonde levensstijl, ga
83 Commitment wandelen tijdens de lunch. Attitude
Je lijkt heel gemotiveerd om deel te nemen aan
dit programma. Ga wandelen tijdens de lunch Percieved Behavior
84 Commitment om je doelen te bereiken. Control
Mensen die met een groep gaan wandelen
zullen op de lange duur meer fysiek actief zijn.
Maak afspraken met collega's om te gaan Percieved Behavior
85 Consensus wandelen tijdens de lunch. Control
Om je doelen te bereiken moet er voortgang
geboekt worden. We proberen je met het
DirectLife programma te stimuleren om te
86 Commitment wandelen, om zo je doel te bereiken. Attitude
Ook vandaag is er weer een kans om deel te
nemen aan het DirectLife programma en fit te
87 Scarcity blijven, ga wandelen tijdens de lunch. Attitude
Probeer door te gaan waar je mee bent
begonnen; neem deel aan dit programma om
een gezondere levensstijl te ontwikkelen.
Verhoog je activiteit tijdens de lunch, ga Percieved Behavior
88 Commitment wandelen! Control
32

33. Probeer je doelen eerder te bereiken door te
gaan wandelen tijdens de lunch. Ga jij je doelen
89 Commitment halen? Attitude
Probeer te wandelen tijdens de lunch. Volgens
de Nederlandse Gezondheidsraad is dit een
gemakkelijke manier om een gezond leven te
90 Authority ondersteunen. Subjective Norm
Barack Obama zweert bij een dagelijkse
lunchwandeling. Hij zegt: "Als er een
makkelijkere manier zou zijn om gezond te
91 Authority blijven, dan zou ik die wel gekozen hebben". Subjective Norm
Stel je lunchwandeling niet uit naar morgen,
92 Scarcity vandaag heb je de kans om gezonder te leven. Attitude
Vandaag is een unieke kans om bij te dragen
aan een gezonde levensstijl. Verhoog je fysieke
93 Scarcity activiteit; ga lunchwandelen! Attitude
Wandel tijdens je lunch. Al 95% van de
deelnemers hebben hun fysieke activiteit
(tijdens lunchtijd) verhoogd, volg hun
94 Consensus voorbeeld. Subjective Norm
Doe net als de andere deelnemers aan het Percieved Behavior
95 Consensus project. Ga wandelen tijdens de lunch. Control
33