Utility of the RT3 triaxial accelerometer in free living: An investigationof adherence and data loss

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Applied Ergonomics xxx (2009) 1–8

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Applied Ergonomics

journal homepage: www.elsevier .com/locate/apergo

Utility of the RT3 triaxial accelerometer in free living: An investigationof adherence and data loss

Meredith A. Perry a,*, Paul A. Hendrick a, Leigh Hale a, G. David Baxter a, Stephan Milosavljevic a,Sarah G. Dean b,1, Suzanne M. McDonough c, Deirdre A. Hurley d

a Centre for Physiotherapy Research, University of Otago, PO Box 56, Dunedin, New Zealand, New Zealandb Rehabilitation Teaching and Research Unit, University of Otago, Wellington, New Zealand, New Zealandc Health & Rehabilitation Sciences Research Institute, University of Ulster, Northern Irelandd School of Physiotherapy and Performance Science, University College Dublin, Ireland

a r t i c l e i n f o

Article history:Received 14 June 2009Accepted 5 October 2009

Keywords:AdherenceUsabilityPhysical activityData lossTriaxial accelerometer

* Corresponding author. Tel.: þ64 4 3855357; fax:E-mail addresses: [email protected] (

otago.ac.nz (P.A. Hendrick), [email protected] (L.nz (G.D. Baxter), [email protected] (Sotago.ac.nz, [email protected] (S.G. Dean), s.mMcDonough), [email protected] (D.A. Hurley

1 Permanent address: Sarah Dean, Peninsula MedicUniversities of Exeter and Plymouth, United Kingdom

0003-6870/$ – see front matter � 2009 Elsevier Ltd.doi:10.1016/j.apergo.2009.10.001

Please cite this article in press as: Perry, M.A.loss, Applied Ergonomics (2009), doi:10.101

a b s t r a c t

There is strong evidence for the protective effects of physical activity on chronic health problems. Activitymonitors can objectively measure free living occupational and leisure time physical activity. Utility isan important consideration when determining the most appropriate monitor for specific populations andenvironments. Hours of activity data collected, the reasons for activity hours not being recorded, andhow these two factors might change over time when using an activity monitor in free living are rarelyreported. This study investigated user perceptions, adherence to minimal wear time and loss of datawhen using the RT3 activity monitor in 21 healthy adults, in a variety of occupations, over three (7 day)repeated weeks of measurement in free living. An activity diary verified each day of monitoring anda utility questionnaire explored participant perceptions on the usability of the RT3. The RT3 was worn foran average of 14 h daily with 90% of participants having complete data sets. In total 6535.8 and 6092.5 hof activity data were collected from the activity diary and the RT3 respectively. An estimated 443.3 h(6.7%) of activity data were not recorded by the RT3. Data loss was primarily due to battery malfunction(45.2%). Non-adherence to wear time accounted for 169.5 h (38.2%) of data loss, of which 14 h were dueto occupational factors. The RT3 demonstrates good utility for free living activity measurement, however,technical issues and strategies to manage participant adherence require consideration with longitudinaland repeated measures studies.

� 2009 Elsevier Ltd. All rights reserved.

1. Introduction

There is increasing evidence for the benefits of both occupationalphysical activity (PA) and sport and leisure time PA on a range ofhealth outcomes (Hildebrandt et al., 2000; Bauman, 2004; Zhanget al., 2006; Probert et al., 2008) including benefits in cardiovasculardisease, diabetes, stroke, mental health and musculoskeletal disor-ders. Occupational activity (or the physical requirements of the job)and occupational inactivity have been shown to influence the risk of

þ64 4 43855427.M.A. Perry), paul.hendrick@Hale), [email protected].. Milosavljevic), sarah.dean@[email protected] (S.M.).al School, St Luke’s Campus,.

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, et al., Utility of the RT3 triaxi6/j.apergo.2009.10.001

musculoskeletal work related disorders (Chan et al., 2004; Marraset al., 2009). Musculoskeletal work related disorders are thought toarise from prolonged periods of exposure to repetitive specific highor low load tasks causing tissue fatigue (Westgaard and Winkel,1996), coupled with a combination of other psychological andsociological factors (Marras et al., 2009). Exploring the accuracy andutility of methods to measure occupational activity is necessary forunderstanding the relative contribution of this specific work relatedfactor to occupational physical disorders.

Activity monitors are a common objective measure employed toassess PA in a range of populations and occupational settings (Busseret al., 1998; Ainsworth et al., 1999; Estill et al., 2000; Heil, 2002;Cuthill et al., 2008; Dall and Kerr, 2009) and in a variety of patientpopulations such as people with cardiovascular disease, neurolog-ical disability, and cancer survivors (Steele et al., 2000, 2003a,b;Balogh et al., 2004; Hertzog et al., 2007; Hale et al., 2008; Sloaneet al., 2009; Jerome et al., 2009). More recently, activity monitorshave been used to assess the PA of people with musculoskeletal

al accelerometer in free living: An investigation of adherence and data

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M.A. Perry et al. / Applied Ergonomics xxx (2009) 1–82

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disorders, including those with low back pain (Verbunt et al., 2005;Ryan et al., 2009); this is timely, as lower back complaints area prevalent occupational injury (Marras, 2000; N.R.C, 2001; Waddelland Burton, 2001). The importance of objectively measuring activityor inactivity in large population groups has led to the design anddevelopment of a number of commercially available activity moni-tors (Westerterp, 1999a, 1999b; Freedson and Miller, 2000; Wardet al., 2005). Determining the most appropriate monitor for a specificstudy design and occupational group requires accurate and easilyaccessible information on aspects of reliability, validity and utility ina variety of environments and populations to enable informeddecision making (Berlin et al., 2006).

Utility not only encompasses the reliability and validity of anoutcome measure or instrument, but also how easy it is for the user tointeract with the measure in their usual activities of daily living (ADL),the emotional connection between the user and the instrumentwhich incorporates design aesthetics (Seva et al., 2007), and whetherthe users’ and researchers’ expectations are met (Chamorro-Koc et al.,2009). Ideally, such measures should be simple, easily understood,unobtrusive and accurate (Law, 1987; Freedson and Miller, 2000;Trost et al., 2005; Ward et al., 2005). Utility efficacy is a combination ofmonitor factors that include technical limitations (such as malfunc-tion of hardware, incomplete data transfer and sensitivity to noise);and participant factors (such as adherence, experience, social contextand cognitive understanding) (Steele et al., 2003b; Slaven et al., 2006;Chamorro-Koc et al., 2009).

Data loss from activity monitors due to adherence or technicalissues negatively impacts daily and weekly estimates of occupa-tional and leisure time PA, and consequently necessitates anincrease in the number of days of data collection (Trost et al., 2005)therefore increasing the economic and participant burden involvedin longitudinal free living PA studies. Furthermore, such data losscan mask important or changing associations between specificpopulations and their participation in work, home and social PA(Conn et al., 2000; Paul et al., 2008). It is important therefore toestablish cause and magnitude of data loss, along with the effec-tiveness of any strategies employed to minimise such loss, as theseinsights are important for developing study designs for specificoccupational environments and populations, and for interpretingresults (Conn et al., 2000).

Data loss due to technical failure (including battery faults) andparticipant non-adherence is periodically reported in free living PAobservational studies (Williams et al., 1989; Sirard et al., 2000;Steele et al., 2000, 2003b; Verbunt et al., 2005). Estill et al. (2000)reported data quality and data loss issues during several specificergonomic tasks but concluded that the activity monitor beinginvestigated was user friendly and able to distinguish activity loadbetween different groups. Few other studies have reported on thepotential effects of occupation on activity monitor utility, and weare unaware of any research which has purposefully investigatedhours of activity data collected, the reasons for activity hours notbeing recorded, and how these two factors might change over timewhen using an activity monitor in free living. In addition, rarely areworkers’ opinions sought on the design and utility of the activitymonitor. The purpose of this study was to explore the magnitudeand reasons for observed RT3 data loss within a healthy populationin free living over three discrete periods of 7 days of data collection,and to explore participants’ perceptions of the monitor’s accept-ability and utility using a qualitative approach.

2. Method

Data for this study were gathered as part of a pilot repeatedmeasure’s observational study that has investigated the free livingstability of the RT3 activity monitor (Hendrick et al., 2008).

Please cite this article in press as: Perry, M.A., et al., Utility of the RT3 triaxiloss, Applied Ergonomics (2009), doi:10.1016/j.apergo.2009.10.001

2.1. Participants

A convenience sample of 24 participants was recruited by publicand University campus advertising over a four week period. Allparticipants were of good health with no current or past medicalconditions limiting PA. Prior to participation all participants readand signed an informed consent form approved by the University ofOtago, School of Physiotherapy Ethics Committee.

2.2. Procedures

Each participant’s sex, height and weight were downloadedonto the RT3 via the Stayhealthy software. The RT3 was clippedonto their belt or waistband in the centre of the lower back, andparticipants were advised to keep the monitor in this positionduring all waking hours, apart from water-based activities andsporting activities which precluded the use of an activity monitorsuch as contact sports, for example rugby. If the monitor causeddiscomfort in this position participants were advised to shift it tothe lateral right pelvis, to note the change of position in the activitydiary, and to return the monitor to its original position whenappropriate. We advised that the monitor should be placed ina prominent and clearly observable position overnight to avoid theparticipant forgetting to wear it the next morning.

Each participant was instructed to record the primary activityfor each waking hour in an activity diary; participants were alsoadvised to record the time and reason for removal of the RT3 in thediary. Researchers contacted each participant twice (via electronic-mail, short message service/text, or telephone) during the week todetermine any clinical utility issues with the RT3 and to encourageadherence to the protocol.

After one week the RT3 was collected and data downloaded toa computer using the Stayhealthy software. Wearing of the activitymonitor for 7 consecutive days, in conjunction with completion ofa new activity diary, was repeated three and seven weeks later (i.e.,weeks four and eight). A utility questionnaire, exploring partici-pants’ perceptions of the activity monitor’s acceptability, wascompleted at the end of week eight. Following data collection anddownload, completed data sets were then cleaned and categorisedfor statistical analysis.

2.3. Measurement

2.3.1. RT3 triaxial accelerometerThe RT3 (Stayhealthy, Inc., Monrovia, CA) is a small

(71�56� 28 mm), lightweight (65.2 g), battery (AAA) powereddevice that is calibrated to 5.3 Hz and has a dynamic range of0.05–2.00 g (Powell et al., 2003). The accelerometer in the RT3 issensitive to three orthogonal axes: vertical (x), anteroposterior (y),and mediolateral (z) and has four modes of recording and storingdata. Mode 4 calculates an average vector magnitude (VM) countover a one-minute epoch for each axis ([X2þ Y2þ Z2]0.5).

2.3.2. Utility questionnaireThe utility questionnaire (Hale et al., 2008) asked participants to

comment on the convenience and acceptability of the RT3 and anydifficulties associated with wearing the activity monitor. Thequestionnaire consisted of four statements where the level ofagreement with the statement was marked on a 100 mm anchoredline. Two closed question asked if participants would be agreeableto wear the RT3 again for future research projects and if they feltthe monitor was user friendly. A final open ended question askedparticipants for any further comments.


Table 1Occupational and sport characteristics (n¼ 21).

Occupation Percentageof timespentsittinga

Primary activityparticipation

Days per weekinvolved inorganisedactivity

1 AdministrationAssistant

75% Yoga 3

2 Secretary 84% Dancing 23 Physiotherapist 7% Running 74 Student Not listed Netball 55 Student Not listed Swimming, gym 16 Student Not listed Badminton, gym 27 Student Not listed Football, running 48 Student Not listed Gym 39 Physiotherapist 7% None 010 Beauty Therapist 43% None 011 Personal Trainer 36% Cycling, gym 512 Physiotherapist/

Education43% Golf 1

13 Administrator 75% Walking, gym 314 Medical Receptionist 87% Walking, pilates 315 Solicitor 84% Gym 416 Childminder 36% Netball 217 Business Analyst 86% Running 318 Physiotherapist 7% Pilates, walking 719 Network Engineer 74% Cycling, squash,

dancing6

20 Mother/Carer 33% Walking 521 Network engineer 74% Squash, cycling 4

a Occupational percentage of time spent sitting is classified by O*NET, http://online.onetcenter.org/.

M.A. Perry et al. / Applied Ergonomics xxx (2009) 1–8 3

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2.4. Data treatment and statistical analysis

Trost et al. (2005) recommend that the amount of data collectedshould be sufficient to reliably estimate the participant’s usualactivity status and Ward et al. (2005) recommended that theminimum hours of wear time should be set prior to data collection.Failure to collect the set number of valid days typically results inparticipants being excluded from statistical analyses. In this studyno participants were excluded from the analysis on the basis ofvalid wear time, however a theoretical threshold of a minimum of10 h of activity data on 5 of the 7 days (including one weekend day)as recommended by Gretebeck and Montoye (1992) was set. Thisbaseline point was used to evaluate how many of the participants inthis current study would have met an inclusion threshold and if thenumber of participants meeting the threshold decreased over therepeated weeks of testing.

Hours of RT3 wear time was calculated by subtracting the hoursof non-wear from 24 h (Troiano et al., 2008). Non-wear time wasdefined as periods during which excessively low RT3 counts wereidentified (60 min of continuous VM counts of 10 counts/min orbelow) (Buchheit et al., 2007). Hours of RT3 wear time were thencompared to the number of hours recorded as ‘awake’ in theactivity diary. Periods of RT3 non-wear time were cross referencedto the activity diary and the hours and reasons for RT3 removalwere manually transferred onto an Excel sheet for descriptiveanalysis. Activities which lasted less than 60 min and requiredremoval of the RT3, such as washing and bathing, were notaccounted for. Hours of sleep, as recorded in the activity diary, werenot considered to be activity data and were therefore not includedin any missing data analyses. Similarly, hours of RT3 data whichwere missing despite the participant recording that the monitorwas worn, were also estimated from the hours marked ‘awake’ inthe activity diary.

Descriptive statistics were used to analyse: 1) wear hours fromthe RT3; 2) the reasons for data loss; and 3) to summarise responsesfrom the utility questionnaire. A subsequent Bland and Altman(1986, 1999) analysis was performed to investigate agreementbetween week four and week eight daily hours of wear time forparticipants with complete RT3 data sets. In addition, the Bland–Altman analysis was used to confirm the estimated hours of weeklywear time for participants missing a whole week of RT3 data.

3. Results

Twenty four participants were recruited but three participantswithdrew over the first 2 days of week one due to work commit-ments. In total 21 participants (13 women, eight men) completedthe study. The 21 participants had a mean (SD) age of 35.5 (13.8)years; body weight of 70.8 (7.7) kg; height of 172.0 (6.8) cm andBMI of 23.9 (2.2) kg/m2 completed the study. On average partici-pants worked 35.0 (14.3) h a week. Table 1 shows participant’soccupation, percentage of time spent sitting during work hours,and the frequency/week involved in sport.

In total 6535.8 h of activity data as recorded in the activitydiaries, were collected from the participants (n¼ 21). The RT3contained no data for an estimated 443.3 (6.7%) hours of timemarked as ‘awake’ and active in the activity diary. RT3 activity dataloss increased from 42.0 h in week one, to 85.0 in week four to316.3 h in week eight. Most of the non-recorded activity hoursoccurred in weeks four and eight (91.0%). Fig. 1 illustrates thatmonitor (48.4%) and participant factors (52.8%) contributed equallyto the 443.3 h of data loss. Specifically, technical malfunction inweek eight resulted in two participants obtaining no RT3 datadespite wearing the monitor and accounted for 200.5 h (45.2%) ofthe 443.3 total hours of data loss. Forgetting to wear the RT3


accounted for 169.6 h (38.2%) of the total data loss. Three femaleparticipants reported removing the monitor due to the RT3 notblending in with their clothing. This accounted for 19.5 h of RT3data loss over the three measurement weeks and was categorisedas ‘Appearance’ in Fig. 1. Data loss due to participation in sports andwater-based activities were fairly uniform over the three recordedweeks and accounted for 18 h (4.2%) of data loss. This occurredwith: Soccer (6 h); Netball (4 h); Running (3.5 h); Cycling (2.5 h);Dancing (1 h) and Swimming (1 h). In weeks four and eight a totalof 7 h of data (1.6%) were lost due to fear of losing the RT3 whenengaged in social activities.

The mean (SD) hours of weekly wear time per individual perweek was reasonably consistent over the repeated three weekswith means of 101 (7.3), 100 (10.3), and 98 (10.0) h of data recordedfor week one, four and eight respectively; however, the variabilityof wear time increased from week one to weeks four and eight.Table 2 presents the hours of RT3 wear time containing activity data(week one and four n¼ 21, week eight n¼ 19). All participants metthe theoretical inclusion criteria threshold of a minimum of 5 dayswith 10 h of RT3 data collected in weeks one and four. The loss oftwo participants RT3 data due to a technical failure in week eightmeant that 91% of participants (n¼ 19) achieved the theoreticalthreshold in week eight. Table 2 presents the hours of RT3 weartime containing activity data (week one and four n¼ 21, week eightn¼ 19). The number of participants obtaining at least 10 h of dataon all days of the week declined from week one to week eight. Inweek one adherence was 100% with all (n¼ 21) participantsobtaining at least 10 h of data on all 7 days. In week four 18/21participants obtained 10 h of data on all 7 days, while in week eightthis number had decreased to 13/19 participants with 100%adherence (Table 2).

The Bland–Altman analysis demonstrated that the averagedifference (SD) in wear hours from week four to week eight forthe 19 participants with complete RT3 data sets was 0.57 h (1.4).The 95% confidence interval for the average difference in wearhours was �0.6 to 1.2. The limits of agreement around the


http://online.onetcenter.org/


Fig. 1. Total activity hours not recorded by the RT3, by reason, for all participants (n¼ 21) over the three weeks. Black based bars represent monitor factors for data loss and lightgrey bars represent participant factors for data loss.


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average hours of daily wear time was 14.3 h� 3.3 (Fig. 2). Fromthe activity diary, we estimated that 93, (13.3 average hours ofdaily wear time), and 107.5 h, (15.4 average hours of daily weartime), were lost for the two participants missing all RT3 data inweek eight.

The utility questionnaire demonstrated that the median scoreand inter quartile (IQR) range along a 100 mm line for agreementwith the statement ‘‘The RT3 was acceptable to wear for 7 days’’was 83 mm (72, 100). The median (IQR) for the statement ‘‘It iseasy to remember to wear the RT3 daily’’ was 100 mm (78, 100)(Table 3). Sixteen participants responded to the open question: intotal 37 comments were made. Discomfort due to the position ofthe RT3 on the back, especially with sitting at work or driving,was reported by 12 of the 16 (75.0%) responding participants, andwas the strongest theme to emerge from the open question. Fiveof the 16 responding participants (31.3%) mentioned shifting orremoval of the RT3 during specific manual aspects of their job forperiods of up to 1 h (network engineer, physiotherapist, personaltrainer and two students). Two other participants (businessanalyst and solicitor) removed the monitor when seated at workdue to discomfort. Three participants (18.8%) felt that themonitor limited the clothing they could wear. Other themeswere: catching and breaking the monitor clip on a chair whenarising (n¼ 3); excessive movement of the monitor with highintensity activities (n¼ 3); catching of the monitor on a satchel/backpack (n¼ 4); one participant felt that the RT3 was too big,one felt that it interfered with lifting children, and anotherworried that the RT3 might fall into the toilet.

Table 2Total weekly and mean (SD) daily hours of RT3 wear time of collected activity data,and the number of participants with 100% adherence.

Week Total hours/week weartime

Mean hours/day weartime (SD)

No. of participantswith �10 h ofdata on 5 day

No. of participantswith �10 h of data onall 7 day

1 (n¼ 21) 2134 14.5 (1.0) 21 214 (n¼ 21) 2101 14.3 (1.5) 19 188 (n¼ 19) 1858 14.0 (1.4) 19 13Total 6093


4. Discussion

This study assessed the utility of the RT3 activity monitor byinvestigating the magnitude of data loss compared to the totalnumber of activity hours collected, explored the reasons for RT3data loss, and investigated participant perceptions of the monitor.Results indicate that most participants found the RT3 acceptable towear for the 7 days, corroborated by the high hours of daily wear.Total RT3 data loss was estimated to be 6.7% (443.3) of the 6535.8 hof data collected from the activity diary. Technical factors (48.4%)and participant factors (52.6%) were equally attributable to causesof RT3 data loss. While the percentage hours of RT3 data loss isrelatively small, the combined loss of data due to either forgetful-ness (adherence) or battery malfunction increased over time.

Data loss due to battery connection faults in the final week ofdata gathering caused 45.2% of the total data loss and accounted for93.3% of the activity monitor related factors. New batteries wereused for each week of monitoring and all RT30s were purchasedthree months prior to study commencement and had not previ-ously been used except for laboratory based calibration tests.Therefore, it is unlikely that this result was due to either batteryfault or ‘wear and tear’ on the monitors. The lack of a data memorysystem in the RT3 meant that any loss of battery connection causedan irretrievable loss of all data accumulated to that point in time.This was despite diligent wearing by the participant as documentedin the activity diary.

The complete loss of a week’s data for the two participants inthis study due to an inexplicable technical fault is a serious utilityconcern as it necessitates statistical manipulation on the non-complete data to minimise group effects (Coleman and Epstein,1998; Catellier et al., 2005; Slaven et al., 2006). Previous studieshave also reported ‘technical faults’ or battery failure with the RT3.In a study investigating people with low back pain, Verbunt et al.(2005), reported a similar percentage loss of participants’ data(10%); Hertzog et al. (2007), in a repeated measures study with 65cardiac patients, reported the need to replace 20 monitors froma pool of 72 RT30s over a three month period; and Sloane et al.(2009) reported that 13% (15/115) of participants data at baselinewas unusable in an activity activation programme in cancer


Fig. 2. Hours of RT3 daily wear time measured for week four and week eight.


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survivors. While Chen et al. (2009) did not provide an exact figureon the amount of data loss they did state the battery failure was themost common cause of data loss in a weight loss study comprising1685 participants. Technical problems have also been reported inan occupational setting, but not with the RT3. Estill et al. (2000)found that 8% of data files were unusable (technical issues such asdata quality, wear time and instrument quality were cited) froma wrist worn accelerometer used for 1 h over 4 days in office andline production workers. It is likely that the rate of technical failurein the current study is related to the number of repeat measuresand the number of monitors used (9) relative to the number ofparticipants (21), as well as monitor design limitations, and is notnecessarily related to the population being investigated.

The current study found high levels of wear time with 90%(14.5 h), 89% (14.3 h) and 87.5% (14.0 h) of a standard 16 h daycontaining activity data over the three separate weeks of study. A16 h day represents the likely maximum hours of wear time if anactivity monitor is to be removed while sleeping (Macfarlane et al.,2006). Similar percentages and hours/day of wear time have beenreported previously, within a free living population, over a single 7

Table 3RT3 utility questionnaire data (n¼ 21).

Question Mean (SD) Scoreon 100 mm linea

Median(IQR)

Min,Max

1. The RT3 was acceptableto wear for 7 days

82 (18) 83(72, 100)

44, 100

2. It was easy to rememberto wear the RT3 daily

89 (17) 100(78, 100)

39, 100

3. The RT3 interfered withdaily activities

24 (20) 22 (6, 33) 0, 67

4. The RT3 was annoyingto wear

23 (20) 22 (0, 39) 0, 56

5. Would you wear theRT3 again for research

Yes¼ 21 (100%)

6. Was the RT3 user friendly Yes¼ 17 (81%),Maybe¼ 4 (19%)

a A high score indicates increasing agreement with the statement and low scoreindicates increasing disagreement except for questions 5 and 6 which requireda yes, no or maybe answer.


day period with a waist mounted activity monitor (Macfarlaneet al., 2006; Matthews et al., 2008; Troiano et al., 2008). Troianoet al. (2008) also found that as age of the population increased, themean hours/day wear time likewise increased. In people withchronic obstructive pulmonary disease a lower average (13.1) h/daywear time was reported over a 3 day time period (Steele et al.,2000). Hale et al. (2008) reported an average of 11 h/day with theRT3 monitor over two periods of 7 days in patients with a mixtureof neurological disorders. The lower average hours/day wear timemay arise from increased hours of rest due to the underlying healthcondition. However, few studies report on actual wear hours and tothe authors’ knowledge, no studies have reported on the change inwear hours in a repeated measurement design. Best practiceguidelines for field use of activity monitors recommend thatminimal wear time for inclusion and wear days are reported(Mathie et al., 2004; Ward et al., 2005), and also that the percentageof participants meeting minimum wear time and the reasons fordata loss be routinely reported (Masse et al., 2005). Furthermore,Mathie et al. (2004) suggested that consideration and correction ofunequal wear time of activity monitors should be considered.Therefore, the reporting of wear hours and the variability(mean� SD), in addition to current practice guidelines, wouldimprove standardization of field study practice and also allow fora better comparison of results between studies.

Most participants reported that the RT3 was acceptable to wear;application was easy to remember and did not interfere with dailyactivities. However, forgetting to wear the RT3 increased over thethree repeated weeks and was responsible for an estimated 169.5 h(38.2%) of total RT3 data loss. Despite the twice weekly contact withparticipants, as well as use of an instruction sheet and an activitydiary, this was the primary cause of participant related data loss(74.2%).

Forgetting to wear the monitor has been reported extensively inthe literature (Kochersberger et al., 1996; Steele et al., 2003b). VanCoevering et al. (2005) noted that only 50% of adolescent partici-pants collected a continuous 7 days of data in a one week study,whilst Conn et al. (2000) found that 28% of participants (averageage 74 years) did not complete a full complement of 7–9 days of



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data collection. In our study placement site and bulk of the RT3 wasmost problematic for the two participants whose occupations(Solicitor, and Business Analyst) involved sitting for a highproportion of their day. Five participants removed the monitorduring more manual aspects of their job or studies. Removal of themonitor during work time accounted for a relatively smallpercentage of data loss in predominantly sedentary occupations;however, this factor could potentially result in an underestimationof participant physical inactivity recognised as an important factorin musculoskeletal work related disorders (Chan et al., 2004;Marras et al., 2009).

The results from our study suggest that, regardless of age andthe use of cues there is decreased adherence to monitor wear overtime. Previously, Van Coevering et al. (2005) and Trost et al. (2005)have suggested that a variety of frequent cues and incentivepayments may increase participant adherence. In our study noincentive payment was provided; however, a cue was deliveredtwice via the participant’s stated preferred method of communi-cation. It is possible that the cues were not varied or frequentenough to encourage adherence, as time progressed. Our findingsalso suggest that the additional use of an activity diary is beneficialto not only provide more detail of daily activity, but also to act asa cross reference to the activity monitor output (Buchheit et al.,2007) and provide a prompt to wear the activity monitor daily.

Other reasons for non-recording of data included misplacement,removal for sporting activity, discomfort, appearance, and fear oflosing the activity monitor. Forgetting to reattach the RT3 alsooccurred after prior removal for sport (e.g. swimming, netball andsoccer) or after showering/bathing post activity. These hours ofdata loss are therefore linked to the sporting activities of theparticipant; consequently, as a participant becomes more active theopportunity for more data to be lost due to removal of the monitor,may at times exceed the actual participation in the sport or leisureactivity. In a recent study of preadolescent girls an estimated 10%data loss due to PA participation was adjusted by imputation of anestimation of activity energy expenditure for the activity that wasnot monitored (Buchheit et al., 2007). A monitor which could beworn during all sporting and occupational activities may minimisethis loss; however as many contact sports discourage the wearingof any hard attachments, further consideration of size andconstruction of activity monitors is required before this may berealised.

Results from the utility questionnaire highlighted that sitting ordriving with the monitor situated on the central lumbar spine wasuncomfortable and necessitated removal in some occupationalsituations; caused the monitor to get caught under the backrest ofchairs; to get knocked off during sit to stand activities, and to fall offwhen going to the bathroom. This resulted in a fear of losing theRT3 which accounted for 7 h of data loss. Hale et al. (2008) previ-ously explored various psychometric properties of the RT3 and alsofound, despite the differences in population groups, major themesof discomfort and fear of losing the monitor. These results may nothave occurred if the monitor had been placed on the belt line orwaistband over the lateral pelvis. However, the monitors wereplaced in a more posterior position as previous research by Steeleet al. (2003b) had noted that too lateral a placement over the pelviscould result in either the monitor getting knocked off or breakageof the clip (under the armrest of the chair) when participants wentfrom sitting to standing. Activity monitor placement may thereforebe a compromise between participant comfort and the position inwhich calibration equations to interpret the activity monitor outputwere derived (Welk, 2005). Placement of the monitor to minimiseloss of data due to occupation or sporting activity requires carefulconsideration. This study determined that placement in the centreof the lower back would not be acceptable for those complaining of


lower back pain and for those in occupations which require highperiods of time spent sitting. Leg, waist and arm mounted monitorsare all available but it is unlikely that one monitor will be suitablefor all job related tasks and all occupations. Alternative methods ofmonitor attachment and the aesthetics of the monitor may addressthis mechanism of data loss. While data loss due to activityparticipation is important to recognise, the majority of non-recor-ded activity hours in this current study was not linked to partici-pation in a particular sporting or occupational activity.

There are several limitations to this research. We did notcompare the RT3 to any other activity monitor and thus it is difficultto determine if our population would have found the RT3 prefer-able or easier to remember to wear than any other monitor. Inaddition the small number of participants means our results shouldbe considered carefully; however our findings appear to beconsistent with larger studies and a range of populations.

It is difficult to accurately establish the cause and magnitude ofdata loss. We cross referenced the RT3 data to the activity diaryhowever participants were only asked to record their main activityfor each hour. Consequently, we only noted RT3 data as missingwhen 60 min of continuous VM counts of 10 counts/min or belowwere recorded. Therefore, numerous activities of less than 60 minin duration but also requiring removal of the RT3 were possiblyunaccounted for. Increasing the frequency of activity diary input toevery 30 min, for example, might have yielded further categories ofdata loss. Diaries are however subject to recall bias and, dependingon the frequency of recording required, diaries can also placeconsiderable burden on participants which can further affect theirreliability (Stone et al., 2002). Therefore, while we acknowledgethat the results presented in this paper may not accurately reflectthe participant factors for data loss because the 60 min interval ofrecording was so wide, a pragmatic decision to not increase thefrequency of diary recording was made.

The Bland–Altman analysis found that the average daily hours ofwear time for weeks four and eight was 14.3 h with limits ofagreement of�3.3 h for the 19 participants with complete RT3 datasets. The Bland–Altman plot demonstrated that the averagedifference in wear hours from week four to week eight was evenlyspread above and below the zero intercept and that the averagedifference in daily wear hours from week four to week eight wasnot statistically significant. There was an increase in variability,shown by an increase in the scatter of the differences, as themagnitude of measurement dropped below 13 h of daily wear time.However, as the number of participants for this analysis was smallthese findings should be treated cautiously until future studieshave investigated the change in wear hours from week to week inlarger sample sizes and in a range of populations.

In addition, the Bland–Altman plot was conducted to confirmthe estimation of data loss for two participants. From the activitydiary we estimated that 93, (13.3 average hours of daily wear time),and 107.5 h, (15.4 average hours of daily wear time), of RT3 activityhours were lost due to a technical fault. The estimation of this dataloss was found to be consistent with the weekly variationdemonstrated by the remaining 19 participants with complete dataand lies within the Bland–Altman limits of agreement.

5. Recommendations and conclusions

While reliability and validity aspects of activity monitors areextensively documented within the literature, utility issues are notso widely published. Accurate documentation of adherence issueswith specific activity monitors as well as technical limitations mayinfluence study design and monitor selection with respect tooccupational groups and environment.



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This study shows that extensive data were lost due to batteryconnection faults, which provision of an internal memory systemwithin the RT3 would address. Increasing non-adherence to wearover time should also be taken into account when planning furtherstudies, particularly for determining power calculations.

We would recommend careful consideration of the require-ments of specific populations and occupational groups whendetermining minimally acceptable hours of wear time and place-ment site of the monitor prior to data collection. Pilot testing ofactivity monitors, in a repeated measures design, should beconsidered, to ascertain any specific participant or technical issuesin the population of interest. Effective protocols to maintainadherence to wear time require further development, and esti-mated hours of data loss over time should be routinely reported.Reporting on the mean hours/day wear time and the cause andmagnitude of data loss is particularly important when accel-erometry is being employed to assess PA change over time, as itenables effective comparisons between data collection points. It ishoped this report may contribute to further development of thistechnology by manufacturers in response to user commentary, andalso encourage other researchers to be more transparent as tocauses of data loss.

Utility, reliability and validity are important issues when logis-tically determining where to invest resources. The intent of thisstudy was to formally report on the magnitude of data loss due totechnical issues and adherence to wear time with the RT3 activitymonitor in a healthy population over three repeated 7 days ofmeasurement. This study found that the RT3 was acceptable towear in a healthy population over 21 days in a variety of occupa-tional groups. Missing data were equally due to monitor andparticipant factors and the ratio of hours of data collected to hoursof data loss requires consideration in future studies. Further studieson usability issues with specific occupational groups and settingsare warranted.

Acknowledgments

The authors would like to thank Dr Mark Weatherall for hisstatistical advice. This research was supported by the Centre forPhysiotherapy Research, University of Otago.

References

Ainsworth, B.E., Richardson, M.T., Jacobs Jr., D.R., Leon, A.S., Sternfeld, B., 1999.Accuracy of recall of occupational physical activity by questionnaire. J. Clin.Epidemiol. 52, 219–227.

Balogh, I., Orbaek, P., Ohlsson, K., Nordander, C., Unge, J., Winkel, J., Hansson, G.A.,2004. Self-assessed and directly measured occupational physical activitie-s–influence of musculoskeletal complaints, age and gender. Appl. Ergon. 35,49–56.

Bauman, A.E., 2004. Updating the evidence that physical activity is good for health:an epidemiological review 2000–2003. J. Sci. Med. Sport 7, 6–19.

Berlin, J.E., Storti, K.L., Brach, J.S., 2006. Using activity monitors to measure physicalactivity in free-living conditions. Phys. Ther. 86, 1137–1145.

Bland, J.M., Altman, D.G., 1986. Statistical methods for assessing agreement betweentwo methods of clinical measurement. Lancet 1 (8476), 307–310.

Bland, J.M., Altman, D.G., 1999. Measuring agreement in method comparisonstudies. Stat. Methods Med. Res. 8, 135–160.

Buchheit, M., Platat, C., Oujaa, M., Simon, C., 2007. Habitual physical activity,physical fitness and heart rate variability in preadolescents. Int. J. Sports Med.28, 204–210.

Busser, H.J., De Korte, W.G., Glerum, E.B.C., Van Lummel, R.C., 1998. Method forobjective assessment of physical work load at the workplace. Ergonomics 41,1519–1526.

Catellier, D.J., Hannan, P.J., Murray, D.M., Addy, C.L., Conway, T.L., Yang, S., 2005.Imputation of missing data when measuring physical activity by accelerometry.Med. Sci. Sports Exerc. 37, S555–S562.

Chan, C.B., Ryan, D.I.A.J., Tudor-Locke, C., 2004. Health benefits of a pedome-ter-based physical activity intervention in sedentary workers. Prev. Med. 39,1215–1222.


Chamorro-Koc, M., Popovic, V., Emmison, M., 2009. Human experience and productusability: principles to assist the design of user-product interactions. Appl.Ergon. 40, 648–656.

Chen, C., Jerome, G.J., LaFerriere, D., Young, D.R., Vollmer, W.M., 2009. Proceduresused to standardize data collected by RT3 triaxial accelerometers in a large-scale weight-loss trial. J. Phys. Act Health 6, 354–359.

Coleman, K.J., Epstein, L.H., 1998. Application of generalizability theory tomeasurement of activity in males who are not regularly active: a preliminaryreport. Res. Q. Exerc. Sport 69, 58–63.

Conn, V.S., Minor, M.A., Meh, D.R., Burks, K.J., 2000. Recording activity in olderwomen with TriTrac. Am. J. Health Behav. 24, 370–378.

Cuthill, J.A., Fitzpatrick, K., Glen, J., 2008. Anaesthesia a sedentary specialty?Accelerometer assessment of the activity level of anaesthetists while at work.Anaesthesia 63, 279–283.

Dall, P.M., Kerr, A., 2009. Frequency of the sit to stand task: an observational studyof free-living adults. Appl. Ergon. 41, 58–61.

Estill, C.F., Macdonald, L.A., Wenzl, T.B., Petersen, M.R., 2000. Use of accelerometersas an ergonomic assessment method for arm acceleration-a large-scale fieldtrial. Ergonomics 43, 1430–1445.

Freedson, P.S., Miller, K., 2000. Objective monitoring of physical activity usingmotion sensors and heart rate. Res. Q. Exerc. Sport 71, 21–29.

Gretebeck, R.J., Montoye, H.J., 1992. Variability of some objective measures ofphysical activity. Med. Sci. Sports Exerc. 24, 1167–1172.

Hale, L.A., Pal, J., Becker, I., 2008. Measuring free-living physical activity in adultswith and without neurologic dysfunction with a triaxial accelerometer. Arch.Phys. Med. Rehabil. 89, 1765–1771.

Heil, D.P., 2002. Estimating energy expenditure in wildland fire fighters usinga physical activity monitor. Appl. Ergon. 33, 405–413.

Hendrick, P.A., Perry, M.A., Hale, L., Milosavljevic, S., Bell, M.L., McDonough, S.M.,Hurley, D.A, Baxter, G.D., 2008. Clinical reliability and utility of an RT3 activitymonitor in the measurement of free-living physical activity. In: New ZealandSociety of Physiotherapists conference proceedings, 18–20 April, Dunedin,p. 76.

Hertzog, M.A., Nieveen, J.L., Zimmerman, L.M., Barnason, S.A., Schulz, P.M.,Miller, C.L., Rasmussen, D.A., 2007. Longitudinal field comparison of the RT3 andan activity diary with cardiac patients. J. Nurs. Meas. 15, 105–121.

Hildebrandt, V.H., Bongers, P.M., Dul, J., van Dijk, F.J.H., Kemper, H.C.G., 2000. Therelationship between leisure time, physical activities and musculoskeletalsymptoms and disability in worker populations. Int. Arch. Occup. Environ.Health 73, 507–518.

Jerome, G.J., Young, D.R., Laferriere, D., Chen, C., Vollmer, W.M., 2009. Reliability ofRT3 accelerometers among overweight and obese adults. Med. Sci. Sports Exerc.41, 110–114.

Kochersberger, G., McConnell, E., Kuchibhatla, M.N., Pieper, C., 1996. The reliability,validity, and stability of a measure of physical activity in the elderly. Arch. Phys.Med. Rehabil. 77, 793–795.

Law, M., 1987. Measurement in occupational therapy: scientific criteria for evalua-tion. Can. J. Occup. Ther. 54, 133–138.

Macfarlane, D.J., Lee, C.C., Ho, E.Y., Chan, K.L., Chan, D., 2006. Convergent validity ofsix methods to assess physical activity in daily life. J. Appl. Physiol. 101,1328–1334.

Marras, W.S., 2000. Occupational low back disorder causation and control. Ergo-nomics 43, 880–902.

Marras, W.S., Cutlip, R.G., Burt, S.E., Waters, T.R., 2009. National occupationalresearch agenda (NORA) future directions in occupational musculoskeletaldisorder health research. Appl. Ergon. 40, 15–22.

Masse, C.L., Fuemmeler, B.F., Anderson, C.B., Matthews, C.E., Trost, S.G., Catellier, D.J.,Treuth, M., 2005. Accelerometer data reduction: a comparison of four reductionalgorithms on select outcome variables. Med. Sci. Sports Exerc. 37, S544–S554.

Mathie, M.J., Coster, A.C.F., Lovell, N.H., Celler, B.G., 2004. Accelerometry: providingan integrated, practical method for long term, ambulatory monitoring of humanmovement. Physiol. Meas. 25, R1–R20.

Matthews, C.E., Chen, K.Y., Freedson, P.S., Buchowski, M.S., Beech, B.M., Pate, R.R.,Troiano, R.P., 2008. Amount of time spent in sedentary behaviors in the UnitedStates, 2003–2004. Am. J. Epidemiol. 167, 875–881.

N.R.C, 2001. Musculoskeletal Disorders and the Workplace: Low Back and UpperExtremities. National Academy Press, Washington, DC.

O*NET OnLine, 2008. Summary of Tasks for Job Descriptions. Available from.Occupational Information Network [Online]. http://online.onetcenter.org/(Accessed 5 November 2008).

Paul, D.R., Kramer, M., Stote, K.S., Spears, K.E., Moshfegh, A.J., Baer, D.J., 2008.Estimates of adherence and error analysis of physical activity data collected viaaccelerometry in a large study of free-living adults. Available from. BMC Med.Res. Methodol. [online] 8 (1), 38. http://www.biomedcentral.com/1471-2288/8/38. Accessed 23 November 2008.

Powell, S.M., Jones, D.I., Rowlands, A.V., 2003. Technical variability of the RT3accelerometer. Med. Sci. Sports Exerc. 35, 1773–1778.

Probert, A.W., Tremblay, M.S., Gorber, S.C., 2008. Desk potatoes: the importance ofoccupational physical activity on health. Can. J. Public Health 99, 311–318.

Ryan, C.G., Grant, P.M., Dall, P.M., Gray, H., Newton, M., Granat, M.H., 2009. Indi-viduals with chronic low back pain have a lower level, and an altered pattern, ofphysical activity compared with matched controls: an observational study.Aust. J. Physiother. 55, 53–58.

Seva, R.R., Duh, H.B.-L., Helander, M.G., 2007. The marketing implications of affec-tive product design. Appl. Ergon. 38, 723–731.



http://www.biomedcentral.com/1471-2288/8/38

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ARTICLE IN PRESS

Sirard, J.R., Melanson, E.L., Li, L.I., Freedson, P.S., 2000. Field evaluation of theComputer Science and Applications, Inc. physical activity monitor. Med. Sci.Sports Exerc. 32, 695–700.

Slaven, J.E., Andrew, M.E., Violanti, J.M., Burchfiel, C.M., Vila, B.J., 2006. A statisticaltest to determine the quality of accelerometer data. Physiol. Meas. 27,413–423.

Sloane, R., Snyder, D.C., Demark-Wahnefried, W., Lobach, D., Kraus, W., 2009.Comparing the 7-day physical activity recall with a triaxial accelerometer formeasuring time in exercise. Med. Sci. Sports Exerc. 41, 1334–1340.

Steele, B.G., Belza, B., Cain, K., Warms, C., Coppersmith, J., Howard, J., 2003a. Bodiesin motion: monitoring daily activity and exercise with motion sensors in peoplewith chronic pulmonary disease. J. Rehabil. Res. Develop 40, 45–58.

Steele, B.G., Belza, B., Hunziker, J., Holt, L., Legro, M., Coppersmith, J., Buchner, D.,Lakshminaryan, S., 2003b. Monitoring daily activity during pulmonary reha-bilitation using a triaxial accelerometer. J. Cardiopulm. Rehabil. 23, 139–142.

Steele, B.G., Holt, L., Belza, B., Ferris, S., Lakshminaryan, S., Buchner, D.M., 2000.Quantitating physical activity in COPD using a triaxial accelerometer. Chest 117,1359–1367.

Stone, A.A., Shiffman, S., Schwartz, J.E., Broderick, J.E., Hufford, M.R., 2002. Patientnon-compliance with paper diaries. BMJ 18, 1193–1194.

Troiano, R.P., Berrigan, D., Dodd, K.W., Masse, L.C., Tilert, T., McDowell, M., 2008.Physical activity in the United States measured by accelerometer. Med. Sci.Sports Exerc. 40, 181–188.

Trost, S.G., McIver, K.L., Pate, R.R., 2005. Conducting accelerometer-based activityassessments in field-based research. Med. Sci. Sports Exerc. 37, S531–S543.


Van Coevering, P., Harnack, L., Schmitz, K., Fulton, J.E., Galuska, D.A., Gao, S., 2005.Feasibility of using accelerometers to measure physical activity in youngadolescents. Med. Sci. Sports Exerc. 37, 867–871.

Verbunt, J.A., Sieben, J.M., Seelen, H.A., Vlaeyen, J.W., Bousema, E.J., van derHeijden, G.J., Knottnerus, J.A., 2005. Decline in physical activity, disability andpain-related fear in sub-acute low back pain. Eur. J. Pain 9, 417–425.

Waddell, G., Burton, A.K., 2001. Occupational health guidelines for the managementof low back pain at work: evidence review. Occup. Med. 51, 124–135.

Ward, D.S., Evenson, K.R., Vaughn, A., Rodgers, A.B., Troiano, R.P., 2005. Acceler-ometer use in physical activity: best practices and research recommendations.Med. Sci. Sports Exerc. 37, S582–S588.

Welk, G.J., 2005. Principles of design and analyses for the calibration of accel-erometry-based activity monitors. Med. Sci. Sports Exerc. 37, S501–S511.

Westerterp, K.R., 1999a. Assessment of physical activity level in relation to obesity:current evidence and research issues. Med. Sci. Sports Exerc. 31, S522–S525.

Westerterp, K.R., 1999b. Physical activity assessment with accelerometers. Int. J.Obes. 23, S45–S49.

Westgaard, R.H., Winkel, J., 1996. Guidelines for occupational musculoskeletal loadas a basis for intervention: a critical review. Appl. Ergon. 27, 79–88.

Williams, E., Klesges, R.C., Hanson, C.L., Eck, L.H., 1989. A prospective study of thereliability and convergent validity of three physical activity measures in a fieldresearch trial. J. Clin. Epidemiol. 42, 1161–1170.

Zhang, Y., Cantor, K.P., Dosemeci, M., Lynch, C.F., Zhu, Y., Zheng, T., 2006. Occupa-tional and leisure-time physical activity and risk of colon cancer by subsite. J.Occup. Environ. Med. 48, 236–243.


Utility of the RT3 triaxial accelerometer in free living: An investigationof adherence and data loss

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