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

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

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).

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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

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

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.

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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

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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

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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

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

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

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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.

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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.

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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

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.

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

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.

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Table 2: Number and percentage of sent messages

Total text

messages

send

Total

webpages

opened

Authority

message

Consensus

message

Commitment

message

Scarcity

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.

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

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.

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.

24

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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.

30

________________________ ____________________ __________

Naam Handtekening Datum

Verantwoordelijke onderzoeker

Ik heb alle vragen over dit onderzoeksproject beantwoord.

________________________ ____________________ __________

Naam Handtekening Datum

31

Appendix 2:

Persuasive messages

Message

ID Strategy Message Lunchwalking (Dutch) Categorie TPB

64 Authority

"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 "

Wandel tijdens je lunch!" Subjective Norm

65 Authority

Er zijn meer redenen om wel te bewegen dan

om dat niet te doen", zegt Pieter Jansen,

inspanningsfysioloog. Zijn advies: "Wandel

tijdens de lunch" Subjective Norm

66 Consensus

4000 mensen nemen actief deel aan het

DirectLife programma. Deze mensen wandelen

tenminste 1x per week tijdens de lunch. Voeg je

bij deze groep en ga wandelen tijdens de lunch!

Percieved Behavior

Control

67 Consensus

4000 mensen nemen net als jij actief deel aan

het DirectLife programma. Zij gaan wandelen

tijdens de lunch om sneller een gezond

bewegingsniveau bereiken, jij toch ook?

Percieved Behavior

Control

68 Consensus

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

een gezonder leven. Attitude

69 Authority

Ben je gaan wandelen tijdens de lunch? "Een

actieve levensstijl helpt om er goed uit te

blijven zien" zegt plastisch chirurg Robert

Schoemacher. Subjective Norm

70 Consensus

Beweeg tijdens de lunch, des te fitter je zult

worden. Attitude

71 Authority

De Wereld Gezondheidsorganisatie adviseert

om fysiek actief te zijn tijdens de lunch. Ga een

stuk wandelen. Lange tijd inactief zijn is slecht

voor je gezondheid! Subjective Norm

72 Consensus

Deelnemers die wandelen tijdens de lunch

hebben gemerkt/merken dat je een grotere kans

hebt om je doel op een gezonde leefstijl te

bereiken. Attitude

73 Scarcity

Dit onderzoek duurt slechts 7 weken: je hebt nu

de kans om je gezondheid te verbeteren door te

gaan wandelen tijdens de lunch. Attitude

74 Scarcity

Elke dag zonder lunchwandeling is een gemiste

kans. Attitude

32

75 Scarcity

Elke kans om een lunchwandeling te maken is

een mogelijkheid om je bewegingsniveau te

verhogen. Grijp je kans nu en ga bewegen! Attitude

76 Authority

Ervaren DirectLife coaches adviseren om te

wandelen tijdens de lunch. Hierdoor zal je

dagelijke niveau van fysieke activieteit stijgen. Subjective Norm

77 Authority

Fysiotherapeuten adviseren om dagelijks een

stuk te wandelen tijdens de lunch. Probeer

actiever te zijn, dit is goed voor je gezondheid. Subjective Norm

78 Commitment

Het doel van deze studie is om een gezondere

levenstijl te creëren. Wandelen tijdens de lunch

is een manier om dit te bereiken. Attitude

79 Authority

Het Nederlandse Verbond van Huisartsen

adviseert om dagelijks een half uur te bewegen.

Wandelen tijdens de lunch zal je helpen om dit

advies te bereiken. Subjective Norm

80 Consensus

Iedereen is het erover eens dat wandelen tijdens

de lunch zorgt voor een betere gezondheid. Attitude

81 Commitment

Je hebt al eerder gewandeld tijdens de lunch, ga

hiermee door!

Percieved Behavior

Control

82 Scarcity

Je hebt nu de kans om je fysieke activiteit te

verhogen. Pak die kans… ga wandelen tijdens

je lunch! Attitude

83 Commitment

Je investeert zelf in een gezonde levensstijl, ga

wandelen tijdens de lunch. Attitude

84 Commitment

Je lijkt heel gemotiveerd om deel te nemen aan

dit programma. Ga wandelen tijdens de lunch

om je doelen te bereiken.

Percieved Behavior

Control

85 Consensus

Mensen die met een groep gaan wandelen

zullen op de lange duur meer fysiek actief zijn.

Maak afspraken met collega's om te gaan

wandelen tijdens de lunch.

Percieved Behavior

Control

86 Commitment

Om je doelen te bereiken moet er voortgang

geboekt worden. We proberen je met het

DirectLife programma te stimuleren om te

wandelen, om zo je doel te bereiken. Attitude

87 Scarcity

Ook vandaag is er weer een kans om deel te

nemen aan het DirectLife programma en fit te

blijven, ga wandelen tijdens de lunch. Attitude

88 Commitment

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

wandelen!

Percieved Behavior

Control

33

89 Commitment

Probeer je doelen eerder te bereiken door te

gaan wandelen tijdens de lunch. Ga jij je doelen

halen? Attitude

90 Authority

Probeer te wandelen tijdens de lunch. Volgens

de Nederlandse Gezondheidsraad is dit een

gemakkelijke manier om een gezond leven te

ondersteunen. Subjective Norm

91 Authority

Barack Obama zweert bij een dagelijkse

lunchwandeling. Hij zegt: "Als er een

makkelijkere manier zou zijn om gezond te

blijven, dan zou ik die wel gekozen hebben". Subjective Norm

92 Scarcity

Stel je lunchwandeling niet uit naar morgen,

vandaag heb je de kans om gezonder te leven. Attitude

93 Scarcity

Vandaag is een unieke kans om bij te dragen

aan een gezonde levensstijl. Verhoog je fysieke

activiteit; ga lunchwandelen! Attitude

94 Consensus

Wandel tijdens je lunch. Al 95% van de

deelnemers hebben hun fysieke activiteit

(tijdens lunchtijd) verhoogd, volg hun

voorbeeld. Subjective Norm

95 Consensus

Doe net als de andere deelnemers aan het

project. Ga wandelen tijdens de lunch.

Percieved Behavior

Control