Active buildings: modelling physicalactivity and movement in officebuildings. An observational studyprotocol

Lee Smith,1 Marcella Ucci,2 Alexi Marmot,2 Richard Spinney,2 Marek Laskowski,2

Alexia Sawyer,1 Marina Konstantatou,2 Mark Hamer,1 Gareth Ambler,3

Jane Wardle,1 Abigail Fisher1

To cite: Smith L, Ucci M,Marmot A, et al. Activebuildings: modelling physicalactivity and movement inoffice buildings. Anobservational study protocol.BMJ Open 2013;3:e004103.doi:10.1136/bmjopen-2013-004103

▸ Prepublication history andadditional material for thispaper is available online. Toview these files please visitthe journal online(http://dx.doi.org/10.1136/bmjopen-2013-004103).

Received 23 September 2013Accepted 9 October 2013

1Department of Epidemiologyand Public Health, UniversityCollege London, London, UK2Bartlett School of GraduateStudies, University CollegeLondon, London, UK3Department of StatisticalScience, University CollegeLondon, London, UK

Correspondence toDr Lee Smith;lee.smith@ucl.ac.uk

ABSTRACTIntroduction: Health benefits of regular participationin physical activity are well documented but populationlevels are low. Office layout, and in particular thenumber and location of office building destinations (eg,print and meeting rooms), may influence both walkingtime and characteristics of sitting time. No research todate has focused on the role that the layout of theindoor office environment plays in facilitating orinhibiting step counts and characteristics of sittingtime. The primary aim of this study was to investigateassociations between office layout and physical activity,as well as sitting time using objective measures.Methods and analysis: Active buildings is a uniquecollaboration between public health, built environmentand computer science researchers. The study involvesobjective monitoring complemented by a largerquestionnaire arm. UK office buildings will be selectedbased on a variety of features, including office floor areaand number of occupants. Questionnaires will includeitems on standard demographics, well-being, physicalactivity behaviour and putative socioecological correlatesof workplace physical activity. Based on surveyresponses, approximately 30 participants will be recruitedfrom each building into the objective monitoring arm.Participants will wear accelerometers (to monitor physicalactivity and sitting inside and outside the office) and anovel tracking device will be placed in the office (torecord participant location) for five consecutive days. Datawill be analysed using regression analyses, as well asnovel agent-based modelling techniques.Ethics and dissemination: The results of this studywill be disseminated through peer-reviewed publicationsand scientific presentations. Ethical approval was obtainedthrough the University College London Research EthicsCommittee (Reference number 4400/001).

INTRODUCTIONIncreasing population levels of physical activ-ity and reducing sedentary time are majorpublic health priorities in the UK.1 Regular

physical activity aids in the prevention andmanagement of over 20 chronic conditions,including heart disease, stroke, type 2 dia-betes, cancer, obesity, mental health pro-blems and musculoskeletal conditions.2

Sedentary time is also associated with nega-tive health outcomes such as an increasedrisk of metabolic syndrome, independent ofphysical activity levels3 and some data suggestthat interruptions in periods of sedentarytime are beneficially associated with meta-bolic health (eg, lower body mass index(BMI), blood glucose and triglyceridelevels).4 5

As a result of the growing awareness of thehealth benefits of physical activity andreduced sedentary time, public healthrecommendations have been established. It isrecommended that adults (aged 19–64 years)should participate in moderate intensityactivity for 30 min on at least 5 days a weekand all adults should minimise the amountof time being sedentary for extendedperiods.1 Most guidelines endorse the accu-mulation of physical activity in short boutsthroughout the day6 (eg, walking from anoffice to a meeting room or kitchen).Walking offers a feasible opportunity toincorporate physical activity into adults’ dailylives, and it has been suggested that the accu-mulation of 10 000 steps/day is comparableto achieving 30 min of moderate intensityphysical activity per day.7

Current levels of physical activity in the UKpopulation are extremely low. In 2008 just6% of men and 4% of women who took partin the Health Survey for England met phys-ical activity guidelines, determined by object-ive measurement. Estimates of physicalactivity levels for office-based workers suggestdaily step counts of not more than

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4000–6000.8 A previous UK study found a significant dif-ference in meeting physical activity guidelines betweendifferent Standard Occupational Classification (SOC)codes in an office environment (managerial, profes-sional and support staff). Male and female managerialworkers were 23% and 17%, respectively, more likely tomeet physical activity guidelines than support staff.9

However, it is not clear where and when the majority ofthis physical activity took place (eg, in the office duringthe day or at home in the evening). The office may offera platform for activity promotion and reductions insitting time (one domain of sedentary behaviour), butresearch in this context is relatively limited.Two recent reviews showed that physical activity pro-

motion strategies in office buildings can be effective inincreasing physical activity levels.10 11 The reviews identi-fied that many interventions have been based on bolster-ing workers’ motivation or capability for translatingmotivation into action, or offering greater physical activ-ity opportunities to those motivated to be more active.However, such interventions have typically producedsmall effects. They also tend to favour those who aremotivated to change and neglect unmotivated workerswho may benefit the most.10 11 Some studies havefocused on office-based interventions to reduce sittingtime,12 but a recent systematic review showed that theytended to intervene at only the individual level and wereoften unsuccessful.12 Alternative approaches to increas-ing workplace physical activity and decreasing workplacesedentary time are needed.It seems feasible that office layout and, in particular,

the distance required to reach key destinations in officebuildings (eg, kitchens, print and meeting rooms) couldaffect both workers’ step counts and characteristics ofsitting time. In a sample of Australian adults (n=307),those who perceived their office building to have highoverall connectivity (eg, hallways and passageways in theoffice building frequently intersect each other) had sig-nificantly fewer breaks in occupational sitting time (b−0.11; 95% CI −0.17 to −0.06) than those who didnot.13 The author suggested that this may be partiallyexplained by office workers who perceive their officebuilding to have high connectivity not wanting to leavetheir desk because this may disturb their colleagues.Significant associations were also found betweencoworker visibility and coworker proximity and breaks insitting time.13 To our knowledge this is the only observa-tional study to investigate associations between officelayout and sitting behaviour, and no work has focusedon this association using objective measures. Moreover,the role that the layout of the office may play in facilitat-ing or inhibiting physical activity has yet to be systematic-ally investigated.Nudging (ie, unobtrusive alterations to social or physical

environments to make certain behaviours more likely)populations towards health behaviours is an approach thathas been embraced by both the UK and US government,10

and could potentially be utilised to increase physical

activity levels (eg, step counts) and reduce sitting time.Restructuring office layouts by providing greater physicalactivity opportunities (eg, manipulating distances to desti-nations) might nudge workers, whether motivated or not,to increase step counts and thus physical activity levels, aswell as to interrupt extended periods of sitting time.Although such interventions would, at best, result in onlymodest changes in behaviour, any increase in physicalactivity or reduction in sitting time may improve health,especially if performed on a daily basis.3 14 However,before an intervention is carried out, more research isneeded to identify and understand associations betweenoffice layout (eg, number and distribution of office build-ing destinations), step counts and the characteristics ofsitting time.

AimsThe primary aim of this project was to understand howand where office workers accumulate step counts andspend time sitting in their workplace, to determine thepotential for change as a result of spatial reconfigurationof the office layout. This aim will be achieved by testingthe hypothesis that features of the office layout (eg, dis-tance to destinations) are associated with step countsand sitting time of office workers. The secondary aimwas to identify potential socioecological correlates ofoccupational physical activity and sitting behaviour, suchas environmental perceptions or job role.This project will use a novel combination of movement

assessment technologies along with the application ofagent-based modelling (ABM) techniques to informfuture interventions on how to maximise step countsand reduce sitting time in office buildings. The ultimateaim was to produce (1) a model of the relationshipbetween spatial reconfiguration of office layout and stepcounts and sitting time and (2) practical guidance fordesigners/organisations about features required tocreate active buildings.

METHODS AND ANALYSISProject designThe active buildings project (http://www.activebuildings.co.uk) will be carried out in three phases.Phase I: Office-based organisations and their employ-

ees will be recruited. Data will then be collected onoffice workers’ occupational physical activity, includingstep counts, and sitting time, as well as potential socio-ecological correlates of these behaviours.Phase II: Data collected in phase I will be used to apply

ABM techniques to produce a model of how officebuildings could be planned to increase step counts andreduce sitting time.Phase III: Data collected in phases I and II will be com-

piled to inform future intervention design.This paper has a predominant focus on phase I and

briefly discusses potential techniques for phase II.Phases II and III will be the subject of future articles.

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Phase I study designPhase I of the study is cross-sectional in design. Data col-lection will be administered through two arms: anobjective monitoring (ie, accelerometry and locationtracking) arm and a questionnaire arm. Both arms willbe carried out in 10 buildings (approximately 1.2 build-ings per month over 12 months). Within each building,all workers will be asked to complete a questionnaire,and a maximum of 30 workers (to allow for 25 workersafter drop out; see sample size calculation) from eachbuilding will be recruited to take part in objective moni-toring. To maximise data collected and enrich the dataon socioecological correlates of workplace physical activ-ity and sitting behaviour (research aim two), only thequestionnaire will be administered to all workers in anumber of additional buildings (figure 1).

Building inclusion criteriaUK organisations will be recruited that are within a rea-sonable travelling distance from the research centre inLondon. Buildings that the organisations are housed inwill be included only if they (1) have a floor area≥2000 m2 (to provide sufficient scale and variation inoffice layout), (2) house predominantly desk-basedworkers and (3) have available floor plans.

Participant inclusion and exclusion criteriaThis study will investigate a sample of UK working adults(≥18 years). There is no mandatory retirement age inthe UK; consequently, no upper age limit has been setfor this study. All staff in buildings that are participatingin both data collection arms will be invited to complete

questionnaires. Based on specific questionnaireresponses (ie, desk-based worker and no health condi-tion affecting movement), approximately 30 participantswill be recruited from each office building into objectivemonitoring from the four SOC codes that cover officeworkers (managers and senior officials, professionaloccupations, administrative and secretarial occupationsand telephone operatives). Although an equal distribu-tion of participants across SOC codes will be sought, thismay not be achievable as many office buildings may nothouse workers across all SOC codes, particularly man-agers/senior officials and telephone operatives, andsome groups may be less likely to take part than otherSOC groups owing to time constraints. All staff in build-ings that are participating in the questionnaire arm onlywill be invited to complete questionnaires.

RecruitmentPotential organisations will be identified through exist-ing links with companies and by engaging companiesthrough presentations at a variety of academic andindustry focused events, especially those targeting facilitymanagers or occupational health professionals. Afterorganisations have been recruited, their employees willbe recruited using a number of techniques, including:mass emails, posters and presentations, within theorganisations.

ProceduresData collection procedures will take place over a periodof 12 months. Consenting participants will first be askedto complete either a paper or an electronic version of

Figure 1 Study design.

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the questionnaire, delivered by the research staff or viaemail, respectively, at a convenient time.Next, in the 10 buildings participating in both data

collection arms, objective monitoring devices (acceler-ometer and location tracking device) will be given to asmaller sample of consenting participants, along withverbal and written instructions. At this time, an activitydiary/logbook will also be given and anthropometricmeasurements will be taken. Between 4 and 7 days ofaccelerometer data are needed to provide a reliable esti-mate of habitual physical activity.15 Thus, participantswill be asked to wear objective devices and keep an activ-ity diary for five full days. On day 6 they will returndevices and the diary to research staff. The accelerom-eter will monitor step counts and sitting characteristicsthrough postural allocation (total sitting time; time inprolonged sitting; transitions from sitting to standing/walking) in and outside the office and the trackingdevice will only record time-stamped location in theoffice.Anthropometric measurements will take place in a

private area within the office buildings. Weight will bemeasured using standard digital bathroom scales.Height will be measured using Leicester height mea-sures. Waist circumference will be measured twice,mid-way between the iliac crest and lower rib using Secameasuring tapes. Blood pressure will be recorded twiceusing Omron M2 digital blood pressure monitors, afterthe participant has been sitting at rest for 5 min. Datacollection sessions will last approximately 15 min andwill be carried out one-on-one by trained research staffin accordance with standard operating procedure forms.On return of the objective measuring devices, partici-

pants will be interviewed on their preferred routesaround the office. Interviews will last approximately10 min.

Measurement instrumentsAccelerometerParticipants taking part in objective monitoring will beasked to wear the ActivPal (http://www.paltech.plus.com; figure 2) all day every day (including during sleepand bathing) for five consecutive days. The ActivPal is asmall (53×35×7 mm), lightweight accelerometer attachedto the thigh mid-way between the hip and the knee. Inthe present study waterproof adhesive tape will be fittedover the device permitting bathing and swimmingwithout the need for removal. The device classifies free-living activity into periods spent sitting, standing andwalking, and it also records step count, cadence andtransitions between sitting and standing. The ActivPalhas been successfully used in studies of office workersand adults,16 17 and has been validated for step count,cadence, time spent sitting, standing, walking and foridentifying postural transition.18 Grant et al18 found themean percentage difference between the ActivPalmonitor and observation for total time spent sitting,standing and walking was 0.19%, 1.4% and −2%,

respectively. The main advantage of this device in thecontext of sedentary research is that it employs posturalallocation rather than inherently limited methods thatuse time outside specified count thresholds.19

Radiofrequency identification location tracking systemIn addition to the ActivPal, participants in the objectivemonitoring arm will be given ‘OpenBeacon TagPRO’

Active Radiofrequency Identification (RFID) badges to beworn on lanyards around the neck (figure 2) every day(but not during sleep or at home) for five consecutivedays. These badges are part of the OpenBeacon(http://www.openbeacon.org) sensor system, previouslyused to study contact patterns between individuals forsocial20 and epidemiological21 22 research. The badgesuse low-power radio transmissions to detect proximitybetween badges as a proxy for close human interaction.Our study extends this method by inferring individuals’interactions with destinations in office buildings (eg,kitchen, print and meeting rooms) by placing badges atthe respective destinations. Using this methodology wewill infer participants’ proximity to the tagged destina-tions (including participants’ desks), in order to ascer-tain movement patterns within buildings and extractoutputs such as the number of trips individuals makefrom their desk to each destination type. Additional tagsalong corridors will allow specific routes to be detected.Note that, because of sensitivity to excessive personaldata collection or to transmission of data across corpor-ate IT systems, it is anticipated that some participatingorganisations may be reluctant to permit the RFID loca-tion tracking system to be installed.

Figure 2 ActivPal accelerometer and radiofrequency

identification tracking system to be worn by participants.

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Activity diary/logbookParticipants taking part in objective monitoring will beasked to complete an activity diary/logbook. This isdesigned to complement the tracking system by gather-ing information on movement performed during theworking day. Activity type and time will be recorded, inaddition to information on whether and how partici-pants travelled to other floors in the building. Thissection of the diary was adapted from the 4-day activitydiary used in the Eat Smart study.23 It will be completedfor 2 days only, minimising the burden on participants.The diary will also be used to help interpret data from

the objective monitoring devices. Additional sections inthe diary adapted from logbooks used in the Impact ofConstructing Non-motorised Networks and Evaluating Changesin Travel: The Travel to School case study (http://www.iconnect.ac.uk) will record information on times ofentering and leaving the office building, days the partici-pant worked away from the office, days they were notworking and activities performed while one or bothdevices were removed. This information will be collectedfor each day participants wear the objective devices.

Route interviewsInterviews with participants taking part in objective mon-itoring will be carried out by trained interviewers.Participants will be shown a floor plan of their officeand will be asked to draw the routes they usually take tovarious office destinations. The interviewer will provideassistance with reading floor plans when needed. Theparticipant will then be asked four questions about theroutes they take (1) ‘Why did you choose this routerather than taking an alternative route’ (2) ‘How oftendo you walk this route in a day’ (3) ‘What do you likemost about this path’ and (4) ‘What do you like leastabout this path.’ Finally, participants will be asked aboutmultipurpose trips, for example: ‘Do you often go tomore than one destination within a single trip and if so,why do you combine these destinations.’

Movement at work questionnaireAll participants taking part in the study will be asked tocomplete the Movement at Work Questionnaire (seeonline supplementary additional file 1). The question-naire includes questions on standard demographics,physical activity and sedentary behaviour, as well aspotentially important socioecological correlates of work-place activity. Questionnaire completion is estimated totake approximately 10 min.The Epic Norfolk Physical Activity Questionnaire-2

(EPAQ-2)24 will be embedded within the Movement atWork Questionnaire to obtain a subjective measure ofphysical activity levels for all participants. The EPAQ-2investigates past year physical activity behaviour. It asksquestions on three physical activity domains: at work,during leisure time and in the home. Workplace physicalactivity items were derived from the Modified TecumsehOccupational Activity questionnaire,25 and recreation

items were derived from the Minnesota Leisure TimeActivity instrument.26 Age-adjusted and sex-adjusted cor-relations between objective measures of daytime energyexpenditure and the sum of recreational and occupa-tional reported physical activity (in MET hour/week) inthe EPAQ-2 was 0.28 (p<0.001), which is largely consist-ent with correlations between other self-reported andobjective measures of activity. The repeatability of thesum of recreational and occupational reported activitywas high, r=0.73.24

The Movement at Work Questionnaire also includesitems from the Self-Report Habit Index (SRHI) appliedto workplace activity behaviour.27 The SRHI assesses therepetition and automaticity of behaviour and the extentto which it corresponds with self-identity. This measurehas been incorporated to assess whether current work-place activity is carried out automatically, without think-ing (ie, habitually). Example questions include ‘Isclimbing stairs at work something you do automatically’and ‘Is climbing stairs at work something you do withoutconsciously having to remember.’Questions about movement around the office are also

in the Movement at Work Questionnaire, for example,‘How many floors do you travel to reach the printer youmost often use,’ ‘Do you usually take the stairs or theelevator’ and ‘How many times do you usually visit thedestination each working day.’ Other items in the ques-tionnaire include the 12-item General HealthQuestionnaire to measures psychological health,28 andthe Effort-Reward Imbalance Instrument to measurestressful work conditions.29 Items to measure percep-tions of the physical work environment (eg, my work-place is comfortable/safe from crime/helps me feelcreative) are asked, as well as items to measure product-ivity (eg, doing the following would aid my productivity;going outside at lunch time for a breath of fresh air/using the stairs instead of the lift whenever I can, etc)and questions on job title, job description and hoursworked. Items to capture key demographics (eg, SOC,socioeconomic status, age and sex) and otherhealth-related characteristics (eg, height, weight, historyof blood pressure medication and having a health condi-tion that may impair movement) are included.

Spatial metricsSpatial variables thought to influence step count andsitting time will be measured in participating buildingstaking part in both data collection arms (n=10; figure 1),using floor plans complemented by building audits.Building audits, conducted by trained researchers, willcollect general information about the building (eg, loca-tion, access to public transport, availability of parkingspaces, overall number of floors, age of construction andfloor area), and identify the location of different types ofoffice building destinations (eg, meeting room, kitchen,toilet and office area). Office areas will be subdivided intoprivate-enclosed, shared or open-plan, based on classifica-tions similar to those used by Duncan et al.13

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Floor plans will be used to generate ‘axial’ and‘segment maps,’ concepts developed as part of SpaceSyntax and Depthmap software, which in turn will beused to calculate distances between each participant’sdesk and various office building destinations, usingmethods similar to those described by Sailer andMcCulloh.30 An axial map is defined as the least set ofall longest straight lines covering all parts of the buildingand minimising depth or steps between spaces.30 Linesin an axial map can be considered a way of representingpotential routes of movement to and from individuals’workstations, as well as to and from office building desti-nations. The connection between floors through stairsor elevators is also modelled as a route. A segment mapis a refined version of an axial map, where every axialline is broken down into smaller segments at each inter-section. Axial and segment maps will be used to calcu-late four types of distances from each desk to each officebuilding destination (as well as to stairs/elevators): (1)shortest walking distance in metres, (2) fewest steps inan axial map, (3) fewest steps in a segment map and (4)least angle change. These four measurements of dis-tance represent slightly different ways of describing thedistance between destinations, in terms of the cognitive,perceived or actual effort involved to overcome thosedistances. Further details and examples of these metricscan be found in Sailer and McCulloh.30 In most cases,distances will be calculated from each desk to its closestoffice building destination type. In the case of meetingrooms, the distances from each desk to all meetingrooms will be computed and then averaged. If a particu-lar destination type is on a different floor from a desk,then distances including stair and elevator will both becalculated. Proximity of coworkers will also be calculatedfor each participant, by computing the average distancebetween the participant’s desk to all other desks (1) ontheir floor and (2) in the entire organisation within thatbuilding.Aside from metrics specific to each participant, overall

building metrics will also be calculated from the floorplans, including: floor areas (gross, net internal and netusable) and respective densities (ie, floor area per desktype), as well as floor areas of office buildingdestinations.

AnalysisOutcomesThe primary outcomes for this study will be average stepcount and average time spent sitting during officehours, collected by the ActivPal. In addition, the studyhas been designed to examine the following secondaryoutcomes, collected by objective measuring devices andparticipant survey: (1) total overall step counts for theentire wear protocol, (2) total overall sitting (and stand-ing) time for the entire wear protocol, (3) number oftransitions made from sitting to standing (breaks insitting time) during office hours and overall, (4)number of prolonged sitting bouts greater than 1 h

during office hours and overall, (5) total time spent inmoderate-to-vigorous physical activity during officehours and overall (min/day), (6) average number ofdaily trips to each type of office building destination and(7) BMI and other health outcomes (eg, bloodpressure).

Quantitative analysesTo investigate associations between exposures (eg,density of office building destinations; high/low) andoutcomes (eg, occupational step count and sitting time)hierarchical regression models will be carried out,adjusted for clustering of outcomes among adults withinthe same office building, as well as other potential con-founding variables (eg, SOC code and ethnicity, etc).

Sample sizeA sample of 250 participants (10 buildings with approxi-mately 25 participants in each) will give 90% power todetect a difference of 40 min/day in occupational sittingtime at the 5% significance level using a two-sample ttest between participants in high-office and low-officebuilding destination groups. This is assuming a commonSD of 100 min/day.13 This sample size calculationassumes clustering of outcomes among adults within thesame office-building is minimal.

ABM techniquesAn exploratory model to understand and predict howoffice layout influences individual step count as well assitting time of office workers will be developed. A princi-pal methodology that will be explored will be that ofABM. ABM is a set of approaches used to modelcomplex systems composed of interacting autonomousagents. The use of ABM in physical activity research isrelatively novel. ABM is an alternative approach to thestandard multilevel models used in physical activityresearch31 since it ‘grows’ associations by means of care-fully chosen ‘bottom-up’ rules encoded into the agents’behaviours and interactions. The causal link betweenexposures and outcomes can then be explored throughsuch mechanisms and can include dynamic processesthrough which people interact with each other and theirenvironment. This is in contrast to, and in many respectsconsidered as an advancement on, standard multilevelmodels, since they, like all regression-based approaches,necessarily simplify complex relationships betweenpeople and their environment.The model’s structure and methodology will be based

on the empirical findings concerning the measured out-comes and their measured correlates from phase I. Themodel will be designed to explain the findings andpredict changes in outcomes by altering various expos-ure variables such as the number and location of eachtype of office building destination alongside other attri-butes such as an individual’s likelihood to move. It isanticipated that an agent based approach would consistof numerous agents imbued with attributes such as an

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individualised propensity for movement which wouldthen react to features of the indoor environment and totheir colleagues. This would be developed based onbehavioural rules on choice of destinations, routefinding and so on, derived from subjective and objectiveevidence gathered during data collection. Detailed back-ground and protocol describing the exploratory modelthat will be used for the current study will be publishedelsewhere.

ETHICAL CONSIDERATION AND DISSEMINATIONExplicit written informed consent will be sought from allstudy participants. All participants will be informed thatthey have the right to withdraw from the study at anypoint without giving reason.The results of this study will be disseminated to aca-

demic audiences through presentations at national andinternational conferences in physical activity, publichealth and architecture and through peer-reviewed pub-lications in relevant journals. Results will be dissemi-nated to the public, policy makers, and buildingdesigners through seminars and press releasesco-ordinated through the UCL Press Office.

Contributors JW, AM, MU, AF, MH and GA designed the active buildingsstudy. All authors contributed to development of the study protocol. LSdrafted the manuscript. JW, AM, MU, AF, ML, MH, AS, RS and MK assisted indrafting the manuscript. All authors read and approved the final manuscript.

Funding This work was funded by the National Institute for Health Research'sSchool for Public Health Research (NIHR SPHR). The views expressed arethose of the authors and not necessarily those of the NHS, NIHR and theDepartment of Health.

Competing interests None.

Ethics approval Ethical approval was obtained through the University CollegeLondon Research Ethics Committee (Reference number 4400/001).

Provenance and peer review Not commissioned; internally peer reviewed.

Open Access This is an Open Access article distributed in accordance withthe Creative Commons Attribution Non Commercial (CC BY-NC 3.0) license,which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, providedthe original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/3.0/

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