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SMARCOS PHILIPS RESEARCH LABS Maastricht University Educational Ffinal Report Master Thesis Sander Andrien
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SMARCOS PHILIPS RESEARCH LABS Maastricht University Educational Ffinal Report Master Thesis Sander Andrien

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  • 1. Persuasive messages have no effect on increasingphysical 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. AbstractIntroduction: The incidence of physical inactivity is rising in the current population.Morbidities are prevented by performing physical activity. Workplace interventions areeffective in increasing physical activity. DirectLife assists in creating a healthy lifestyletrough measuring the daily activity by use of an activity monitor. The goal of the study is toinvestigate whether persuasive (lunch walking) messages can increase the physical activity(during lunchtime) measured by a DirectLife activity monitor. Furthermore is looked ifpersuasive (lunch walking) messages influence the computer activity of participants.Methods: Seventy-six participants followed the DirectLife program for five weeks startingMarch 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 receivedpersuasive messages, and a control group (n=34), which received no messages. Persuasivemessages were displayed on a website. The link to the website was sent, in a text message, tothe participants if they had a working day. The persuasive messages were based on a theory ofCialdini.Results: There was no difference in total physical activity level (PAL) or total computeractivity for the assessment week and intervention weeks. No difference either was found inPAL lunchtime or computer activity lunchtime for the assessment week and interventionweek. The total PAL, PAL lunchtime, total computer activity or computer activity lunchtimeshowed no difference over time between the control and intervention group. There was norelation between the average total computer activity and average total PAL for anyexperimental group. Forty-eight procent of the send websites which were available for theparticipants were viewed.Discussion: Explanations for the lack of persuasive impact of the messages on physicalactivity could be that messages were not convincing enough, and were not tailored to theneeds 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 todevelop effective persuasive messages.IndexAbstract 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 10Methods 10 Study population 10 DirectLife equipment 11 Design 13 Intervention 13 Persuasive messages 14 Analysis 14Results 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 19Discussion 20 General 20 Lunch walking as intervention 20 Messages 21 PAL 21 PAL and computer activity 21 Limitations and recommendations 22Conclusions 23ReferencesAppendices 3
  • 4. 4
  • 5. IntroductionGeneral problem: Physical inactivityThere is a growing number of people with obesity in The Netherlands and Europe (1). Obesityis 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 exerciseinclude the prevention of coronary vascular disease (CVD) and diabetes mellitus type II (DMII) (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 millionmore deaths (4). To reduce mortality, guidelines for physical activity are introduced by thegovernment. These guidelines are described in the Dutch healthy exercise norm (NederlandseNorm Gezond Bewegen, NNGB) (1). The exercise norm states that people have to perform atleast 30 minutes of moderate physical activity five times a week to remain physically fit. Alarge portion of the population does not meet these guidelines and is at risk of developingmorbidities (1). Interventions are created to promote and increase the physical activity ofpeople.Workplace interventionsAn appropriate location where an intervention for increasing physical activity should takeplace is at a worksite. This is a place where (white collar) workers spend a long period of timeeach day being inactive (5). Workplace interventions in the past show an increase in physicalactivity (4, 6-8). Physical activity promotion is financially lucrative for organizations. Itlowers the chance of morbidities and therefore prevents absence among workers (9). Physicalactivity increases the productivity of employees by improving the confidence of theemployees and interpersonal relationship with colleagues (10). Persuasive messaging couldprovide 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 noengagements. Social pressure performed by colleagues could persuade a person to join alunch walk and increase his physical activity (12). Lunch walking which increases the stepcount 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). Inmany studies counseling (e.g. messaging) was proven to be effective in activating workers toperform physical activity (13-18). Prior research looks into providing persuasive messagestailored to a specific group, not into the timing of the message (19). 5
  • 6. Physical activity measurementThere are different methods in measuring physical activity. The use of an activity monitor(accelerometer) within the study allows objective monitoring of physical activity among theparticipants. Objective methods are considered to be more accurate than self-reportedmeasures (20). Interventions at the workplace often use walking as outcome. Walking can bespecified 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 andwalking time do not give a clear representation of the total daily physical activity. EE is morerepresentative because all activities during a whole day are measured. EE can be expressed inphysical activity level (PAL) or arbitrary acceleration units (AAU). The PAL can bedetermined by dividing the total EE by the basal metabolic rate of an individual (24). AAUrepresent intensity and duration of an activity. EE can be determined based on the counts ofan accelerometer (23). Walking is measured by a pedometer or accelerometer. A pedometer measures on oneaxis and is therefore considered less accurate compared to the accelerometer which measureson 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 inarbitrary 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 classifythe intensity of the activity (30). This categorization is linked to the AAU. Categorizationonly applies if one performs the same activity for a longer period of time (e.g. running for halfan hour) (27). An accelerometer has to be validated against doubly labeled water, to convertthe measured AAU into a PAL (31, 32). To overcome the problem of incorrectly measure physical activity performed for ashorter period of time, algorithms (33), compensating for gait and walking speed (34, 35) andGPS (23) have been suggested as solution. By determining which physical activity isperformed (codation), a better estimation for EE can be made. Activity monitors based on accelerometry use algorithms to convert accelerometeroutput, into EE. Based on measurement on three different axes (x,y,z), an activity monitor candetermine which activity is performed (categorization) (e.g., figure 1) (26). Intensity of anaction 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 andhow much energy is spent.Figure 1: The circles represent decision nodes. In the decision nodes, activities are determined based ondifferent features. The features selected for the classification were the standard deviation of the acceleration inthe vertical, mediolateral, and anteroposterior direction (Rx Ry Rz); the average acceleration in the verticaldirection of the body (ax); and the cross-correlation of subsequent intervals of the acceleration in theanteroposterior direction (Rz) (26).Theories about health behaviorWhen influencing physical activity by messaging, the content of the provided messages isimportant. Social cognitive theories indicate which factors should be taken into considerationwhen forming the message. The Theory of Planned Behavior (TPB) and other social cognitivetheories 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 bythe intention to go lunch walking. Intention in turn is determined by three variables, namelyattitude 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 apositive attitude but a low self efficacy the message send should influence ones abilitybreaking 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, aswell as the evaluation, or value, of the likely outcomes (37). Messaging could influence thebeliefs by making one aware of the positive effects of lunch walking. The subjective normcomponent of the TPB (normative component) is comprised of the beliefs of significantothers 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 onlunch walking of these others. Perceived behavior control is the perceived ease or difficulty of lunch walking and isassumed 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 willthen be lower due to a lower perceived behavior control. When the intention is high, thechance 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 percievedbehavioral control determine intention which leads to behavior (37).PersuasionNext to the content of messaging, the method of messaging is important. The persuasivetheory indicates a method of messaging. Persuasive technology is already used in commercialform. Products like Philips DirectLife and Fitbug already make use of persuasive technologyto support a healthy lifestyle (40). Persuasive techniques are tested in studies in influencingpeople to lose weight (41) and influencing snacking behavior (42). Both studies shows thatthe effectiveness of the influencing strategies is different between subjects. Participants in thestudies had different susceptibility for a different persuasive strategy (41, 42). Effectivity ofthe persuasion techniques show to be variable throughout different studies (42). Other studieshave created applications to influence people in maintaining a health workout regime (19).This indicates that creating (tailored) persuasive messages which are effective in changingbehavior is difficult. The susceptibility for the different strategies has to be measured inadvance otherwise the messages have to be provided randomly. 8
  • 9. In 2001 Cialdini came up with a cluster of influencing strategies to persuade people toperform a specific action (43-45). The strategies can be considered as means to attain a certaingoal. There are six different strategies defined by Cialdini, for each category an example onthoughts of a person on lunch walking is given; Reciprocity indicates when a person (receiver) receives a favor, he/she is likely to return afavor. In this way he/she is in debt with the person who supplies (supplier) the favor. When apersuasive request is made by the supplier the receiver is likely to do so (46). People alsoreturn the favor when there is no request given (42). (e.g. Peter asked me to join him duringhis 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 islimitation to a product or time span people will increase the chance of buying the product orspending their time effectively (47). (e.g. I should go walking today. Today I have got thetime, tomorrow I will be in meeting all day). Advice given by a famous person, specialist, or person with authority will increase thelikelihood of performing the action by the receiver (42, 48). (e.g. My physiotherapist told methat 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 actionswhich are in line with their earlier performed actions and statements in order to preventcognitive dissonance (42). (e.g. I said to Peter; “I am going to walk during the lunch everyday 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 toagree to follow it‟s advice (43). (i.e. Peter is my friend, he told me that lunch walking is vitalto 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, canbe increased by sending them persuasive messages. Research indicate the importance oftiming in providing persuasive messages (50). Prior research looks into providing persuasivemessages to a specific group, not into the timing of the message (19). Interventions onpromoting physical activity at work are present (4, 6-8). Earlier performed intervention in aworkplace on messaging measures self-reported physical activity (51). Self-reported physicalactivity 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 physicalactivity at lunchtime (4). This study intends to cover both gaps in literature by providingpersuasive 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 messageintervention on lunch walking, during lunchtime, can increase the physical activity measuredby the DirectLife activity monitor.MethodsStudy populationAll participants (N=210) that were selected, were workers of different companies in TheNetherlands and native Dutch speakers. Compared to other age groups, the DirectLife has thehighest effect on people above the age of 30 years (unpublished pilot results). The participantsall self reported to have a merely sedentary job (desk job). Recruitment was done by sendingan email to potential participants by a recruitment agency. The inclusion of participants wasverified by an online questionnaire. The exclusion criteria were: persons, known not to have amerely sedentary job; with activities at work not performed behind a computer which is onlyused by the participant; not able to install the DirectLife connect application on the workcomputer; age under 30 years; not in possession of a smart phone with internet connection toopen hyperlinks received by text message (see header persuasive messages); known physicalhandicap, disorder or disease which makes performance of moderate physical activity (likewalking) impossible; participating in any other intervention which includes the use of theDirectLife equipment If the participants did not meet the exclusion criteria they received an email from therecruitment company which contained the general information on the project and an informedconsent (appendix 1). All participants of the study filled in their informed consent andreturned this to the researchers. The total time of the intervention took five weeks and startedfor the first person in the third week of May 2011. This is divided into one week assessmentand four weeks intervention.DirectLife equipmentThis research was part of a larger program (Smarcos) on the DirectLife equipment. TheDirectLife 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. Withinthe (commercial) DirectLife program a coach is provided to users for counseling.In order to measure physical activity a DirectLife triaxialaccelerometer for movement registration (TracmorD, activity monitor)(figure 9) was supplied to the participants. The activity monitormeasured 31 x 33 x 11 mm, and weighted 23 g. The monitor performedmeasurements when attached to any clothing or used as a pendant aroundthe neck. Sampling rate of the equipment was 1 Hz. Intensity of amovement was estimated. These estimations were done based on modelswhich included body characteristics and acceleration features (26). By including the measuredacceleration and the intensity it was possible to calculate the PAL of a person. The equipment of DirectLife further consisted of a web-based program whichtransferred the measurements into displayed data. When subjects logged in on the website, agraphical representation of EE (in kcal) was displayed (fig 10).Figure 10: Graphic representation of the performed physical activity showed to the participants when loggedinto a website. The bars indicate the physical activity performed during the day specified for each hour. Datacan be viewed per month, week, day or hour. The total calories burned and the percentage of the personal goalis 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. Withinthis week one carried the activity monitor along. The performed activity during the first weekwas 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 totalphysical activity of a participant. Within this trial all the participants received the DirectLifeequipment. 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 couldbe attached to. In order to use the equipment, the activity monitor was first hooked throughthe connect device. The DirectLife-connect software was installed and further instructions tothe participants were provided on the screen. The DirectLife-connect software allowed aparticipant to synchronize the data collected from the activity monitor with the personalwebsite. Another function within the DirectLife-connect software was the measurement ofkeyboard and mouse activity. This information was sent to the server (only available for theresearchers). In this way it was measured when a person was sitting behind his or her desk.DesignAfter the participants signed the informed consent form, they were randomized over twodifferent conditions (control and intervention). They then received an invitation email whichallowed them to join and make use of the DirectLife program. If the participant completed theregistration of the DirectLife program they received the complete DirectLife equipment andwere able to start the program. The program started with an assessment week (7 days) whichconstituted the baseline measurement. The participants did not receive any messages duringthe assessment week. After the assessment week the participants started their 4 week plan.Final assessments were realized after 4 weeks.InterventionDuring the plan the intervention group received persuasive messages. Keyboard and mouseactivity (computer activity) is measured by the DirectLife software installed on theparticipants‟ computer. A person was only sent a text message when considered to have aworking day. Working days were days on which computer activity was registered any timebefore the first message was send on a specific day. A (first) message was sent each workingday 15 minutes prior to the indicated lunchtime. The pre-specified time of consuming thelunch was asked during the assessment. After the first message was sent, DirectLife continued measuring computer activity. Ifa person had more than 22 minutes of computer activity in a time span of 30 minutes, starteddirectly 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 theinactivity of the participant. Participants received a message trough a link provided to them within a text messageon their smartphone. The text message was always the same: “Hallo <voornaam>, volg dezelink: <hyperlink> voor een nieuw bericht! Groet coach Sander.”. (English: “Hello <Firstname>, follow this link: <hyperlink> for a new message! Greetings coach Sander.”). Thehyperlink 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 anyadditional (persuasive) messages to motivate them to become physically active duringlunchtime.Persuasive messagesThe goal of the persuasive messages was to promote physical activity, specifically lunchwalking. All the persuasive messages targeted the different motivational factors as describedby TPB and thus addressed perceived behavior control, attitude or subjective norm. For themethod of delivering the messages the messages were based on the persuasion techniquesdefined by Cialdini (2001). All the persuasive messages in this study were in Dutch. For eachcategory, within both theories, formulated in the introduction different persuasive messageswere created. The messages based on the reciprocity and liking from the theory of persuasionwere not formed because this requires a relation between the supplier and receiver of themessage. This relation is not present between the researchers and participants. In appendix 2is indicated for each message what factor within the persuasion theory they influenced. Themessages 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 aconsensus, in each category of the TPB and theory of persuasion, lower than 80% whereexcluded to be sent to the participants. The database selected randomly one out of the total of 31 available messages whichwas sent to the participant (not tailored). If a message was send to a participant there was alower chance that this message was chosen again. When a text message was sent this wasregistered on a server. When a participants retrieved the website which contained a persuasivemessage this was also registered on a server. The registration from the server shows howmany 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 containingthe persuasive message became inactive.MeasurementsWithin the study the age, height, weight and gender was acquired by registration of theparticipants. The BMI was calculated out of the height and weight reported by theparticipants. The total PAL was assessed by including the measurements of each second bythe activity monitor. The data measured each second in AAU was converted into PAL. ThePAL of each second was mediated and an average PAL each week was calculated. The PALlunchtime was the total PAL starting each day 15 minutes before the indicated lunchtime for60 minutes mediated for each week. The total computer activity was the activity on thecomputer measured each minute and mediated for each week. The computer activitylunchtime was the total computer activity starting each day 15 minutes before the indicatedlunchtime for 60 minutes mediated each week. The amount of text messages sent to theparticipants and the amount of opened webpages which contained the persuasive message wasregistered.AnalysisAn ANOVA analysis (between groups; experimental condition and within groups; thedifferent weeks) was performed in SPSS 18.0 to compare the intervention and controlcondition in total PAL. Specified results were acquired to investigate the effect of themessages on the PAL lunchtime. The total computer activity was also measured andcompared 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 PALlunchtime, total computer activity and computer activity lunchtime. The relation between thePAL and computer activity was analyzed to assess whether lower PAL is linked to highercomputer activity. The dependent variables were PAL and computer activity. Theindependent variables were the experimental group and the different weeks. A relation wasmade between PAL and computer activity through an ANOVA (dependent variable: PAL,independent variable: computer activity). General information on the messages anddescriptive statistics were acquired. Each week during the plan the primary outcome, averagetotal PAL and PAL lunchtime was measured. The secondary outcome of this study was totalcomputer activity and the computer activity at lunchtime. Further the relation between thePAL and computer activity was measured. 14
  • 15. ResultsGroupsThe intervention was completed by 67 participants (37 males); 34 subjects (23 male) werepart 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 notcomplete 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 participantsControl InterventionParameter Mean ±s.d. Range Mean ±s.d. RangeN (M/F) 34 (23/11) 33 (14/19)Age. years 43 ± 7 27- 55 42± 8 25 – 62Weight kg 90.9 ± 19.2 50.0 – 135.0 80.1 ± 18.6 54.0 – 137.0Height. cm 179.6 ± 9.8 154.0 – 203.0 175.8 ± 10.2 160.0 – 196.0BMI. kg/m3 25.8 ± 6.1 19.0 - 45.6 28.2 ± 4.7 16.9 - 39.9The intervention and control group showed no significant differences in week 1 (assessmentweek) 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 (figure13) F = .02, p = .87. No significant differences between groups were found for gender, BMIor age (p > .05).Intervention vs. ControlThe intervention and control group showed no significant differences for total PAL (figure10) 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 = .55Total PALThe 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 highestPAL was measured during week two. 15
  • 16. Figure 10: Average total PAL per day displayed per week for the control and intervention groupAnalysis showed that there was no significant effect between the different groups over time inPAL F(4,59) = 1.38, p = .25.All though there is no significant effect found between the different groups over time. Thepairwise comparison analysis showed that there is a significant difference between week 1and 2 (Mean difference week 1 – Mean difference week 2 (Mdif) = -.04; p = .02). There was ashort positive effect in total PAL of the used DirectLife equipment.PAL lunchtimeFigure 11 shows the average PAL measured for 60 minutes starting 15 minutes before theself-reported lunchtime. The average PAL for all the weeks is 1.15. For both groups thehighest 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 activityThe average total computer activity (minutes per day) of the participants for the differentweeks were; week 1 – 180; week 2 – 190; week 3 – 184; week 4 – 186; week 5 – 200 (figure12). These values excluded the days that there was no computer activity at all. These dayswere not considered as working days. For both groups the measured computer activity washighest in the fifth week.Figure 12: Average total computer activity in minutes per day for each week for the control and interventiongroupNo significant difference in computer activity between the groups over time is found F(4,55)= 3.73, p = .82Computer activity lunchtimeFigure 13 shows the average computer activity measured for 60 minutes starting 15 minutesbefore the self-reported lunchtime. The average computer activity varied between the 10 and13 minutes per day. The computer activity of the intervention group was lower each weekcompared to the control group. 17
  • 18. Figure 13: Average computer activity lunchtime in minutes per day for each week for the control andintervention groupThere was no significant difference in computer activity lunchtime between the groups overtime F(4,58) = 1.44; p = .23.Figure 14: Scatterplot of relation between average total computer activity (min/day) and average total PAL (perday) for the control and intervention group 18
  • 19. PAL and computer activityFigure 14 indicates the relation between average total PAL and average total computeractivity separate for the intervention and control group. Both measurements were performedfor five weeks and then averaged. A similar graphic representation was performed for theaverage PAL lunchtime and average computer activity lunchtime (figure 15). There was norelation between the average total PAL and the average total computer activity for bothexperimental groups clustered (F = 3.46, p = .06). If taking the experimental groups intoconsideration 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 theaverage PAL and computer activity for all the participants (F = 1.35, p = .24). If taking theexperimental groups into consideration no relation was found either (F = 2.00, p = .16 for thecontrol group, F = .00, p = .93 for the intervention group).Figure 15: Scatterplot of relation between average computer activity lunchtime (min/day) and average PALlunchtime (per day) for the control and intervention groupMessages sentIn total 610 text messages were sent. For 259 of the send text message the link to the webpagewas opened (42%). Table 2 indicates how many messages of each category was sent to theparticipants in the intervention group. 19
  • 20. Table 2: Number and percentage of sent messagesTotal text Totalmessages webpages Authority Consensus Commitment Scarcitysend 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).DiscussionGeneralThis study aimed to investigate whether a four week persuasive message intervention onlunch walking, during lunchtime could increase the physical activity measured by theDirectLife activity monitor. We assumed that persuasive messages would increase thephysical activity of participants. However the results indicated that there were no significanteffects of persuasive messages on physical activity or computer activity over time.Additionally no relation was found between the computer activity in minutes per day andPAL. This means that there is no further increase or decrease in PAL from the interventiongroup compared to the control group. The persuasive messages did not seem to have anadditional effect.Lunch walking as interventionThe participants in the study were selected based on their self-reported daily pattern ofinactivity during the (working) day. An average total PAL of 1.67 indicated a normal dailyactivity among the participants (52). The average BMI of 27 is a normal value found instudies considering physical activity (31). However higher BMI could indicate generalinactivity 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 toincrease the physical activity. The measured values also indicate that improvement of PALduring lunchtime is possible. 20
  • 21. MessagesThere was no significant difference found between the control and the intervention group overtime for the total PAL, PAL lunchtime, total computer activity or computer activitylunchtime. This means that there was no further increase or decrease in computer activity orPAL from the intervention group compared to the control group. The persuasive messages donot seem to have an additional effect. A part of the research population had no or low computer activity any time during theday (figure 14). These people reported incorrectly to perform work activities at a computer.When no computer activity (lunchtime) is measured, no messages were sent (duringlunchtime). The use of another computer (at work or home) any time during the day withoutDirectLife software is not registered as computer activity. Because the software was notinstalled 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 persuasivemessage was opened. Underestimation of computer activity, no or low computer activity for apart of the intervention group, 42% of all the send websites opened and a average period ofalmost 4 hours between sending and opening a persuasive message make it unable to find asignificant effect of the messages on computer activity or PAL.PALThere was an increase in average total PAL between week 1 and week 2 in both theexperimental and control group. The second week enabled the participants to view theirphysical 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 togradually increase physical activity over a period of 6 weeks. The awareness and goal settingseem to have a positive effect on the promotion of physical activity (54-57). This couldexplain the significant difference between the first and second week.PAL and computer activityThere is no significant relation found between the computer activity and PAL. This meansthat higher computer activity is no indicator for lower PAL. Physical activity is oftenperformed in the evening, while during the day participants have no possibility of performingphysical activity accept for lunchtime. This could explain why people with high computeractivity 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 wasno relation found between the computer activity and PAL. For computer activity during lunchtime the same measurement is performed. Norelation is found there either between computer activity lunchtime and PAL lunchtime. Peopledo not necessarily make use of the computer to be inactive. Often meetings are scheduled orother physical sedentary activities are performed which do not involve the use of thecomputer. In this time people are being physically inactive (low PAL) but also have lowcomputer activity. Perhaps a different measure, like minutes of moderate physical activitycould better estimate the activity of a person for one hour.Limitations and recommendationsFurther qualitative research could be done in the selected participants e.g. interviewing themabout the DirectLife program. This study indicates that inactivity measurements by theDirectLife activity monitor should form the base of sending a text message. This way, timelyfeedback is provided during several moments a day compared to using a computer. With theincreasing use of smartphones with motion sensor and GPS present, applications formeasuring physical activity appear rapidly. With this technique it is possible to delivermessages to the people without making use of computer activity. The messages are thendirectly 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, throughtimely feedback. Prior studies indicate the importance of tailoring the messages. Messageswithin this study are not tailored to the needs of the participants but send randomly. Thisindicates that it is not clear if the messages are considered to be persuasive to a specificparticipant. Future interventions should look into the motivations of people to start physicalactivity. Within an intervention the messages can then be tailored to the current needs of theparticipants. By piloting the messages the usability can be verified. The PAL measured during lunchtime is done for 60 minutes. PAL is most of the timesconsidered to be more reliable when used for daily activity or longer periods of time. Othermeasures like minutes of moderate physical activity do not include basal metabolic rate andrequire a cutoff point between classification of intensity of activity. Activity counts couldform possibilities in further research of the acquired data during lunchtime. 22
  • 23. ConclusionThe physical activity level was not influenced by providing timely persuasive messages toparticipants. However, no hard conclusion can be drawn in the effect of supporting people tobecome more physically active trough persuasive messages. Further research with timelyprovided messages, tailored to the population, without constrains of reading the messagesshould be performed to draw a stronger conclusion. Other effects of supportive messageswere not investigated. 23
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  • 29. Appendix 1:Informed consent formINFORMED 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 DatumVerantwoordelijke onderzoekerIk heb alle vragen over dit onderzoeksproject beantwoord.________________________ ____________________ __________Naam Handtekening Datum 30
  • 31. Appendix 2:Persuasive messagesMessageID 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 te75 Scarcity verhogen. Grijp je kans nu en ga bewegen! Attitude Ervaren DirectLife coaches adviseren om te wandelen tijdens de lunch. Hierdoor zal je76 Authority dagelijke niveau van fysieke activieteit stijgen. Subjective Norm Fysiotherapeuten adviseren om dagelijks een stuk te wandelen tijdens de lunch. Probeer77 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 lunch78 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 dit79 Authority advies te bereiken. Subjective Norm Iedereen is het erover eens dat wandelen tijdens80 Consensus de lunch zorgt voor een betere gezondheid. Attitude Je hebt al eerder gewandeld tijdens de lunch, ga Percieved Behavior81 Commitment hiermee door! Control Je hebt nu de kans om je fysieke activiteit te verhogen. Pak die kans… ga wandelen tijdens82 Scarcity je lunch! Attitude Je investeert zelf in een gezonde levensstijl, ga83 Commitment wandelen tijdens de lunch. Attitude Je lijkt heel gemotiveerd om deel te nemen aan dit programma. Ga wandelen tijdens de lunch Percieved Behavior84 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 collegas om te gaan Percieved Behavior85 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 te86 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 te87 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 Behavior88 Commitment wandelen! Control 32
  • 33. Probeer je doelen eerder te bereiken door te gaan wandelen tijdens de lunch. Ga jij je doelen89 Commitment halen? Attitude Probeer te wandelen tijdens de lunch. Volgens de Nederlandse Gezondheidsraad is dit een gemakkelijke manier om een gezond leven te90 Authority ondersteunen. Subjective Norm Barack Obama zweert bij een dagelijkse lunchwandeling. Hij zegt: "Als er een makkelijkere manier zou zijn om gezond te91 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 fysieke93 Scarcity activiteit; ga lunchwandelen! Attitude Wandel tijdens je lunch. Al 95% van de deelnemers hebben hun fysieke activiteit (tijdens lunchtijd) verhoogd, volg hun94 Consensus voorbeeld. Subjective Norm Doe net als de andere deelnemers aan het Percieved Behavior95 Consensus project. Ga wandelen tijdens de lunch. Control 33