1、July 2022Picture:Jack Atkinson on Prof.Dr.Anna SchneiderHochschule Fresenius University of Applied Sciences,Cologne(Germany)Dr.Rene ArnoldHuawei,Shenzhen(China)Getting a move onHealth and fitness wearables and apps,a six country survey2 Sample size of over 18,000 respondents across six countries(Chi

2、na,France,Germany,Italy,United Kingdom,United States)to determine the impact of wearables and apps use on physical activity during the pandemic period.Across the six countries surveyed,respondents whose first use of fitness and health devices and apps occurred during and due to the pandemic were twi

3、ce as likely to have increased their physical activity and exercise intensity during the pandemic than the respondents who did not start using a wearable or app during the pandemic.The 3“I”s of health and fitness technology:Inspect:Users track on average between four and five metrics about their bod

4、ies and activity.Interpret:Tracking enables new insights based on the collected data.For instance,around half of users of sleep trackers only found out about their lack of sleep or sleep quality through the tracking output.Improve:Consistently,more than 70%of tracking users find their devices and ap

5、ps helpful in achieving their fitness and health goals.Health and fitness apps effect on exercise intensity is similar across income brackets.Virtually all income brackets in all countries surveyed increase their average daily exercise time when they use tracking functions.Among those who use fitnes

6、s and health technology,the 55+age group is not only using a similar set of functions as younger respondents,but also the elderly(age 55+)in Germany,France,and Italy keep track of more metrics than younger respondents.The 55+age group also sees higher increases in their physical activity by tracking

7、 than younger users.Consequently,there is substantial upward potential in terms of achieving SDG 3 and increasing awareness of health and fitness since overall usage levels of health and fitness technology drop below average around the age of 50.Employees are ready to welcome health and fitness tech

8、nology into the workplace if it makes employers more mindful of their employees specific needs.Around half of them agree that it would be great if the employer used such technology to tailor breaks to their needs.Generally,employees look out for technology that helps them to improve their mental per

9、formance even more than their physical performance.Project overview3Today,access to tracking technology is almost ubiquitous.Virtually any smartphone features some health and fitness tracking by default.Smart wristbands and watches have become more affordable.New devices to inspect,interpret,and imp

10、rove ones physical or mental activity gain traction with consumers.This report sets out to shed a spotlight on actual use of health and fitness wearables rather than ownership focused on in typical market reports.The findings are based on a six country survey of more than 18,000 consumers.Our starti

11、ng point was the obvious challenge of a further downgrade in physical activity for many due to the necessary mobility restrictions in the fight against the COVID-19 pandemic,such as work from home,gym closures,and more.We wanted to understand if and how health and fitness wearables and apps can alle

12、viate some of these curbs.With a uniquely large sample size,we were able to tease out specific effects for groups of consumers which are not usually studied in depth including different income brackets and age groups.Consequently,this report offers unmatched detail and insights into the use of healt

13、h and fitness wearables and apps.As todays technology stretches beyond physical activity to include also stress levels,emotional,and mental health,this research includes specific indices for satisfaction with life,body,and wellbeing,to investigate corresponding effects of wearable and app use.The ke

14、y differentiators of this report are as follows:1.Larger sample size(n=18,000+)and more global(six countries)than any other study publicly available 2.Built on very granular stocktaking of specific devices and apps use instead of broad brush categories(the questionnaire featured 23 different devices

15、 and the 10 most popular apps in each country surveyed in addition apps typically included in major digital device ecosystems)3.Separation of physical activity and exercise intensity from device and app use when surveying the population to produce unbiased estimates of effects4.Focus on actual use r

16、ather than merely ownership of wearables or download of apps5.Granular insights on specific functions and related user behaviorIntroduction4Wearables of the Past Wearables have been our steady companions for hundreds of years.Eyeglasses helped with our vision as early as 1289.Pocket watches told us

17、the time beginning in 1530.The first wearable computer emerged in 1961.The first“smartwatch”(with a built-in calculator)dates back to 1975.The first activity tracker followed only in 2009 prompting Gary Wolfs influential article on the“quantified self”.1Wearables of the Present According to IDC mark

18、et data,the shipments of wearables globally have surged from around 85 million units in 2015 to 534 million units in 2021.The analysts expect further growth until 2026,when the market size is projected to reach 265 billion US$.2Wearables not nearly as new as we might thinkSource:1 Wolf,G.(2009):Know

19、 Thyself:Tracking Every Facet of Life,from Sleep to Mood to Pain,24/7/365.WIRED,22-June-2009.2 IDC(2022):Worldwide Wearable Computing Device Forecast,20222026,cited from https:/ Image:Ometov,et al.(2021):A Survey on Wearable Technology:History,State-of-the-Art and Current Challenges.Computer Network

20、s 193(2021)(CC BY 4.0)5Wearables and apps pushed physical activity and exercise intensity during the pandemic15.627.13.810.213.426.84.19.7ChinaGermanyFranceItalyUKUSGeneral physical activity1Exercise intensity213.425.43.85.511.924.52.55.211.923.53.76.110.623.62.96.811.420.53.411.011.121.53.010.113.7

21、26.63.79.013.725.82.97.511.825.24.920.611.527.13.922.1some increasesome increasestrong increase for respondents without first usestrong increase for first use respondentsx1.9x2.1x1.8x2.1x1.9x2.3x2.1x2.2x2.0 x2.0X2.7x3.2Share of first use of devices and apps during and due to pandemic329%15%14%17%13%

22、20%Physical activity in virtually all industrialized economies is insufficient compared to the levels recommended by the World Health Organization(WHO).Whilst the reduction of mobility has been a key success factor in fighting the pandemic,it has left a significant share of people with even diminish

23、ed physical activity levels.Across the six surveyed countries,we find on average 39%of respondents feeling their physical activity intensity has reduced due to the pandemic.For exercise intensity,the share of respondents who felt a reduction is similarly high at 37%.On the other hand,our survey iden

24、tifies a group of respondents who were disproportionately likely to increase their physical activity and exercise intensity.Those who started use of at least one wearable or app during the pandemic were twice as likely to see(strong)increases in their physical activity and exercise levels than those

25、 who did not add a new wearable or app.Our result firmly underscores the positive effect that wearables and apps for fitness and health can have on physical activity.The focus on a particularly challenging period for taking up or increasing physical activity suggests a strong link between the starti

26、ng use of health and fitness technology on the one hand and physical activity on the other.The remainder of the report provides further detailed insights into the role that health and fitness technology can play for physical activity and exercise intensity.Legend:An 11-point scale ranging from“-”to“

27、+”with 0 as the neutral midpoint was used by respondents to indicate their perceived change in physical activity and exercise intensity due to the pandemic.The categories in the figure summarize the top2 items(strong increase)and the remaining increase items(some increase).Respondents with first use

28、 include all respondents who have used at least one health and fitness related device or app during the four weeks prior to the survey and who have began to use at least one such device or app during and due to the pandemic.Respondents who did no meet these two conditions were categorized as respond

29、ents without first use.1 n(with first use)=2,950;n(without first use)=14,936(missing values omitted).2 n(with first use)=2,953;n(without first use)=14,705(missing values omitted).3 relative to the device and apps used within four weeks prior to the survey.6Exercise and higher satisfaction with life

30、and body are linked;women tend to see more increase with exercise than menSatisfaction with life index(average=100)ChinaGermanyFranceItalyUKUSSatisfaction with body index(average=100)ChinaGermanyFranceItalyUKUSFemale,no exerciseFemale,with exerciseMale,no exerciseMale,with exerciseLegend:The average

31、 refers to the specific gender within each country respectively;n(female no exercise)=4,474;n(female with exercise)=4,814;n(male no exercise)=3,957;n(male with exercise)=5,113.*p.10;*p.05;*p.01(t-test)100100100100100100100100100100100100+18*+6*+12*+12*+8*+2*+8*+4*+10*+12*+12*+18*+8*+4*+10*+8*+10*+4*

32、+8*+4*+12*+10*+12*+16*780%Sleep trackers agreeing that they only learned about their lack of sleep(quality)by interpretation provided2Wearables as such are not new.Neither is the conceptual link between self-knowledge and self-improvement.As Crawford et al.(2015)note,the promises made about the weig

33、ht scale at the end of the 19th and early 20th century are essentially similar to the ones made about todays wearables.However,the weight scale provided only a single raw output metric by a mechanical measuring process.Users had to rely on(in)formal knowledge about how to interpret this information

34、and further how to act upon it.Todays wearables differ markedly from this pattern.Commonly,sensor readings are processed in a probabilistic manner to arrive at various data outputs.This enables a greater variety of metrics to be tracked with just one device or even just one integrated sensor unit.Th

35、us,it is possible to provide augmented outputs on ones sleep quality,gait or stress level.In addition,users can receive specific advice on how to make improvements and achieve their goals.Our survey shows that users of tracking functions on average follow between four and five metrics.As the example

36、 of sleep trackers demonstrates,respondents appreciate the interpretation functions offered with 39%(UK)to 73%(China)agreeing that they only realized that they were not getting enough or good enough quality of sleep after they started using the sleep tracking.We also find that goals associated with

37、exercise are strongly linked to either preserving or improving ones health and fitness status which underlines the demand for specific recommendations on how to achieve these goals.The majority of tracking users contend that the devices and apps they use actually contribute to achieving their exerci

38、se goals.From inspection over interpretation to improvementInspectionGaining self-knowledgeInterpretationActionable informationImprovementGoal setting&achievementAverage number of metrics tracked by tracking users1ChinaGermanyFranceItalyUKUSSource:Crawford,K.,Lingel,J.,&Karppi,T.(2015).Our metrics,o

39、urselves:A hundred years of self-tracking from the weight scale to the wrist wearable device.European Journal of Cultural Studies,18(4-5),479-496.Legend:1 n=4,938;tracking describes deliberate tracking instead of any metrics a device or app may track by default unless opted out.2 n=2,064.3 n=4,938 I

40、con:Rafael Garcia Motta from the Noun Project.5.14.44.24.94.04.443%55%56%39%52%ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ

41、ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZTrackers who found their devices and apps helpful in achieving top ranked goals373%71%75%78%74%78%8Only awareness can lead to action Health and fitness tech helps achieving SDG 3,in particular for the 55

42、+age groupThe World Health Organization(WHO)has long advocated for more physical activity especially in industrialized countries whose populations spend too much time seated and often follow unhealthy diets.Correspondingly,the United Nations Sustainable Development Goal 3(SDG 3)seeks to ensure healt

43、hy lives and promote well-being for all ages.Health and fitness technology provides a critical stepping stone to achieving this SDG as it can make accessible the required information through tracking of physical activity,body functions,or nutrition.Our survey finds that between 19%and 44%of responde

44、nts already track at least one such metric.As health and fitness typically deteriorate with age,it is particularly relevant for the achievement of SDG 3 that the elderly have access to this information and act on it.In spite of generally lower digital affinity typical among the 55+age group,we find

45、that in three of the six countries surveyed,these users are actually more avid trackers than younger respondents who track at least one metric.The metrics the 55+age group track hardly differ from the ones that younger respondents typically track.On average,metrics focusing on(general)physical activ

46、ity,body functions such as heart rate and blood pressure,and nutrition(calorie intake,calories burned,fluid intake)are most popular.Sleep and expert sports metrics(e.g.power output)are less interesting to users on average.ChinaGermanyFranceItalyUKUS44%23%19%28%22%26%Share of respondents who track at

47、 least one metric about their physical activity or bodyCountryAgePhysical activityBodyweight&CompositionBody functionsNutritionSleep&stress levelSports expert metricsChina=542218191715955+221422161511Germany=542811191915955+26112118159France=542815162014655+261320161510Italy=5424112018161255+2592318

48、1411UK=542810201916655+27102218167US=542512211915855+2412221714124.55.05.54.03.5ChinaGermany*France*Italy*UKUSDistribution of types of metrics tracked by tracking users by age group2Number of metrics tracked by age group(tracking user only)1=5455+Legend:1 n=4,834*p.10;*.05;*p.01(Mann-Whitney-U test)

49、;2 n=4,834.Tracked metrics categories:Physical activity(steps distance and flights of stairs,gait,movement patterns),bodyweight&composition(bodyweight,body composition),body functions(heart rate,blood pressure,breathing rate,body temperature),nutrition(calorie intake and burn,fluid intake),sleep&str

50、ess level(sleep,stress level),sports expert metrics(power output,blood oxygen level,muscle electrical activity)9The 55+age group shows some preference for tracking,but overall surprising similarity to others in their health and fitness devices and apps functions use13 1312161516 171920219111381114 1

51、41314 1411910910211918 18177754499101110General trackingExercise trackingGoals&monitoringAchievements&awardsSocializing&CollaborationPlanning workoutsOnline trainingsSharing&broadcasting2320 2123 242019 1923221515 14 15 1411131411116875699979887737998122119202127161821192512111012 121714141813910955

52、1113913778985778661725232025171618191514138121215141815 157867613101211147668588887292323 2333191619201615181920191113 13161478646912876454324576418 17192736111213121516141522231413 13 1413111210751512 1287811107279741ChinaGermanyFranceItalyUKUS18 to 2425 to 3435 to 4445 to 5455+Legend:Relative shar

53、e in%of health and fitness devices and apps functions use among devices and apps users using at least one function by age group,n=4,938.Average number of functions used by age group2.42.62.62.42.32.02.02.02.11.82.12.01.91.61.72.32.32.02.01.91.62.22.21.91.92.22.22.22.21.910Young tracking users increa

54、se their exercise intensity less than older onesAge18 to 2425 to 3435 to 4445 to 5455+TrackingnoneeitherbothnoneeitherbothnoneeitherbothnoneeitherbothnoneeitherbothChina10013012910013314510016117410014216610015383Germany100134155100162208100138205100195160100173208France10015817710011919910016723210

55、0167198100153225Italy100116133100146224100151196100172226100122260UK10015389100143187100148209100212259100165309US100159277100168202100191228100146228100200248Average change+42+60+45+94+59+107+72+106+61+122none=no tracking of physical activityeither=either tracking general physical activity or exerc

56、ise related physical activity metricsboth=tracking both general physical activity and exercise related physical activity metricsIndexed average daily exercise time(index 100=average exercise time of those who do not track any metrics about their physical activity in each age group)1Legend:1 n=18,358

57、,exercise time was collected in great detail in the questionnaire encompassing mild,moderate,and strenuous exercise during paid work,unpaid work,and leisure separately for weekdays and weekends;for data analysis,exercise was defined as at least moderate exercise.Definitions used in the questionnaire

58、:mild exercise(e.g.,stretching,casual walking,fishing,golf using cart),moderate exercise e.g.,yoga,hiking,jumping on a trampoline),strenuous exercise(e.g.,martial arts,competitive soccer,football,hockey,high impact aerobics).As the preceding slides showed,the most avid trackers are in the age group

59、55+.This has a pronounced effect on their exercise intensity.The results in the above table clearly show a strong link between tracking of ones general physical activity and exercise activity on the one hand and daily exercise time on the other.This effect becomes stronger with increasing age.Conseq

60、uently,the 55+age group not only tracks more metrics than younger trackers,but also benefits disproportionately from doing so.Increased exercise intensity leads to improved health and a prolonged active life.This is particularly important for the 55+age group as physical health deteriorates with age

61、 and good exercise routine can slow down this process immensely.Notably,the respondents in the 55+age group who exercise consistently score not only higher than those in the same age group without exercise as regards their satisfaction with life,but also show the highest scores overall.This underlin

62、es the contribution that exercise can have for positive aging.11Further potential for uptake of health and fitness technology among the elderly406080100120140160180406080100120140160180406080100120140160180406080100120140160180406080100120140160180406080100120140160180ChinaGermanyFranceItalyUKUSInde

63、xed level of health and fitness technology use(avg=100)Indexed level of general digital technology use (avg=100)Legend:Level of fitness and health technology use based on the number of corresponding smart devices and apps used*as well as the number of functions of these used and the number of metric

64、s tracked digitally;level of general digital technology based on use of smartphone,tablet,PC,and smart TV as well as communications,Social Media,work-related,gaming,education,and streaming apps.Scores were normalized and indexed to the respective country average(avg=100);some results for China in th

65、e age bracket from 53 to 72 have been smoothed.N=18,358;*Base:The top10 most popular local health and fitness apps in each country based on the average monthly active user(MAUs)in six months prior to the survey taken from Apple App Store and Google Play Store data;COVID-specific,health insurance and

66、 period tracker apps were replaced by the next most popular apps on the respective MAUs rankings.12Income groupLow income 200%of medianTrackingnoneeitherbothnoneeitherbothnoneeitherbothChina10013916810012416210010651*Germany100155166100143169100146184France100123223100146219100159136Italy10014721910

67、0152227100120188UK100151270100171199100126188US100191290100180232100135204Average change+48+112+49+95+31+49none=no tracking of physical activityeither=either tracking general physical activity or exercise related physical activity metricsboth=tracking both general physical activity and exercise rela

68、ted physical activity metricsLittle difference in added exercise time from tracking across income groupsAs many smartphones offer tracking of physical activity through pre-installed apps,access and affordability become less and less of an issue for following ones physical activity.Nonetheless,variou

69、s studies report about digital inequality in the effect of tracking(and other digital solutions that promise to increase physical activity)rather than access to or use of such technology.2Whilst confirming similar patterns of access and use,our survey does not reflect the same digital inequality for

70、 the effect of tracking physical activity.The average increase of daily exercise time for low and medium income level groups for those who track their physical activity is very similar.For respondents in the highest income bracket,this effect is smaller than for other groups.Indexed average daily ex

71、ercise time(index 100=average exercise time of those who do not track any metrics about their physical activity in each income bracket)1Legend:1 n=18,358,exercise time was collected in great detail in the questionnaire encompassing mild,moderate,and strenuous exercise during paid work,unpaid work,an

72、d leisure separately for weekdays and weekends;for data analysis,exercise was defined as at least moderate exercise.Definitions used in the questionnaire:mild exercise(e.g.,stretching,casual walking,fishing,golf using cart),moderate exercise e.g.,yoga,hiking,jumping on a trampoline),strenuous exerci

73、se(e.g.,martial arts,competitive soccer,football,hockey,high impact aerobics)*very small sample size in this cell(average change excl.this cell=+80).2 See for instance Western,M.J.et al.(2021):The effectiveness of digital interventions for increasing physical activity in individuals of low socioecon

74、omic status:a systematic review and meta-analysis.International Journal of Behavioral Nutrition and Physical Activity 09-November-2021.13Taking a closer look at the average daily physical activity as captured in our survey reveals that Germany shows the highest overall physical activity intensity(13

75、2)while respondents in China have the highest level of exercise.Independent from considering general or exercise-related physical activity,we find that paid work con-tributes the smallest share in all countries.Leisure on the other hand,contributes the highest share of physical activity.Wearables an

76、d apps could be leveraged by em-ployees and employers to increase physical activity during paid work even for occupations that normally require little physical activity.However,as wearables and apps offer an increasing number of augmented functions,they can also help to reduce stress or provide tail

77、ored breaks depending on the task,environment,and individual.Our survey tested the attitudes of employees among the respondents towards such technical solutions.We find that employees would be particularly open to health and fitness technology being used for their benefit.Interestingly,they showed s

78、lightly more interest in solutions that could up their mental per-formance rather than their physical performance.The greatest leverage of health and fitness technology may be found during paid work hours152926263122231416131316201721191618723325263229353331956558CNDEFRITUKUSLeisure general physical

79、 activityLeisure exercisePaid work general physical activityPaid work exerciseUnpaid work general physical activityUnpaid work exerciseRelative contribution to average daily physical activity time in%Physical activity index avg=10089132100949392384342394438192422182337354038392735Exercise time index

80、 avg=100136111987873104Legend:1 n=18,358,physical and exercise time was collected in great detail in the questionnaire encompassing mild,moderate,and strenuous physical activity and exercise during paid work,unpaid work,and leisure separately for weekdays and weekends;for data analysis,physical acti

81、vity and exercise was defined as at least moderate physical activity and exercise.Definitions used in the questionnaire:mild(e.g.,sitting,stretching,casualwalking),moderate(e.g.,light lifting,hiking),strenuous(e.g.,heavy lifting,competitive soccer);(Un)paid work includes commuting which can arguably

82、 a significant source of exercise as part of these categories,but there can also be others.Results rounded.14Wearables and apps can help employees to get the rest they need,improving their health and performance16.223.012.021.629.61.55.57.46.16.07.22.28.810.110.08.49.06.218.217.819.120.018.417.116.7

83、16.320.917.815.225.413.410.815.311.38.725.121.314.716.814.812.022.5USUKItalyFranceGermanyChinastrongly disagreedisagreesomewhat disagreeneutralsomewhat agreeagreestrongly agreeShare agreement73%36%44%53%43%51%An increasingly competitive work environment and the pandemic have drained the batteries of

84、 many.High stress levels must be cushioned by phases of recovery so that performance can be maintained for as long as possible.In times when employees exceed their own physical and mental stress limits,the desire for a decelerating and protective capacity is therefore not surprising.Health and fitne

85、ss technology can fulfill that role.Particularly in high-performance societies such as China and the US,we find a potentially strong demand for the idea of having apps suggest tailored break times based on ones own measured state of exhaustion.1001101209080China*Germany*FranceItalyUKUS*Indexed mean

86、response(respective country average=100)Working momsWorking dadsOthers employedLegend:n=8,401(only employed respondents in both figures on this slide),Statement:“I wish my employer would let me take breaks when my app says I am fatigued.”Agreement on 7-point Likert-scale ranging from 1=“strongly dis

87、agree”over 4=“neutral”to 7=“strongly agree”;working moms and dads were identified in the survey based on the number of children currently living the respondents household and the respondents stated gender.*.1;*.05;*.01 for Tukeys HSD referring to working moms and dads(highest p-value across groups)d

88、ifference to others.15ChinaSimilar top tech used for fitness and health across countriesGermanyFranceItalyUKUSLegend:1 used in the past four weeks prior to the survey in%of all respondent per country referring to(1)health and fitness apps on the smartphone,(2)smartwatches,and(3)smart sports headphon

89、es.2 Future use as indicated by the respondents in each country in%;the dark shading reflects“very likely to use”and the light shading reflects“somewhat likely to use”respectively;notably,future use does not equal future purchase,but may be interpreted as reflecting market potential generally.3 Shar

90、e of respondents in each country who stated to have never heard of the respective devices.N=18,358 Icons:Aneeque Ahmed,Bence Beyeredy,and Satawat Anukul from the Noun Project.Top 3 are the same across countries182%49%45%57%48%54%28%20%17%24%19%22%34%11%5%20%6%11%1048661212819161227837541311617121324

91、826441310618101022VR glassesSmartwatchSmart scaleTop 3 user growth potential2Except in China,smartwatches represent the wearables with the greatest growth potential.Next to already well-established sports headphones,on body monitors and VR glasses appear to be significant drivers of growth.73%Smart

92、tattoo67%Smart underwear64%Smart ringTop 3 consumer blind spots3Consumers are least familiar with a very similar selection of(future)wearables regardless of which country they are from.Smart tattoos feature on the first rank in all surveyed countries.PEMF headbands and smart underwear feature in the

93、 Top 3 in almost all countries.SmartwatchSmartwatchSmartwatchSmartwatchSmartwatchSmart headphonesOn body monitor82%Smart tattoo79%PEMF headband79%Smart underwearSmart scaleSmart wristband84%Smart tattoo76%Smart insoles75%Smart underwearOn body monitorSmart headphones83%Smart tattoo78%PEMF headband76

94、%Smart underwearSmart headphonesOn body monitor89%Smart tattoo89%PEMF headband88%Smart underwearVR glassesOn body monitor75%Smart tattoo75%Smart underwear73%PEMF headband16So far,few people use recorded and live trainings through health and fitness apps1Interactive training apps show great promiseCh

95、inaGermanyFranceItalyUKUS11%5%4%5%2%8%but their attitudes towards online trainings are very positive.2797571676371-11-14-13-12-20-12Online trainings let me to train anywhere I choose.Online trainings can fully replace training sessions outdoors or in a gym.Training online makes my schedule more flex

96、ible.705252605659-17-28-32-22-24-22767571716973-12-11-14-14-19-8Training online is significantly cheaper than other guided trainings.I can access the best trainers from around the world with online trainings.I get a strong sense of community when training online.796469715574-10-19-13-17-23-107069566

97、25266-15-20-20-17-28-12674148464262-22-41-31-37-35-17Legend:1 n=18,358;2 n=1,075.Agreement on a Likert scale ranging from 1=“Strongly disagree”to 7=“Strongly agree”,red depicts all“disagree”and green depicts all“agree”,neutral,dont know,and missing values omitted.1779777872798111101114107For their g

98、oals,in-app rewards and achievements motivate users,but they rarely share them with others onlineChinaGermanyFranceItalyUKUS25%8%8%14%8%12%Share of respondents using completion and progress rewards2817976757776879998 I feel good about myself.When I receive an award3 I feel motivated to continue exer

99、cising.422327273258477060585821 I share the awards I receive with other users.401522272960537865636021 I share the awards with my connections on social media.41474844503944463939404015713171021People prefer setting personal goals and tracking their progress towards them to collaborative and team goa

100、ls1All disagree(in%)All agree(in%)A different goal-setting function(e.g.team goals,collaborative goals)Tracking my progress in fitness/performanceSetting personal goals Legend:1 Share of tracking and goal setting functions used on all tracking and goal setting functions used(multiple choice question

101、),average number of goal setting and tracking functions used by respondents=1.5;n=2,255.2 n=18,358.3 n=2,333(respondents who use the in-app achievements functions),Agreement on a Likert scale ranging from 1=“Strongly disagree”to 7=“Strongly agree”,red depicts all“disagree”and green depicts all“agree

102、”,neutral,dont know,and missing values omitted.18Sleep tracking helps people to understand their sleep cycle and feel healthierSleep-related metrics tracked by those who use the sleep tracking function(in%)USUKItalyFranceGermanyChinaTime spent awake or sleepingSleep phases(light sleep,deep sleep,REM

103、 sleep)Snoring noiseNumber of times you wake up per night626565797762847664617066188116614434039374552Agreement with the statement“Using a sleep tracker has helped me better understand my sleep cycle.”(in%)795063646670Agreement with the statement“I feel much healthier when I follow the recommendatio

104、ns of my sleep tracker.”(in%)703342423658Legend:n=2,064(sleep tracking users only),Agreement on a Likert scale ranging from 1=“Strongly disagree”to 7=“Strongly agree”,the portion of each pie depicts all“agree”,dont know,and missing values omitted.19Method:CAWI:Computer Assisted Web InterviewSample s

105、ize(s):n=18,358(Germany n=3,073;Italy n=3,065;France n=3,078;China n=3,007;UK n=3,052;US n=3,083)Sampling time:2022/04/26 to 2022/05/09Length of interview:The median length of interview varied between 21 and 24 minutes depending on the country.Sampling frame:The sample type is a non-probability samp

106、le recruited and stratified on basis of representative quota distributions(quota sample).Sampling procedure:Using YouGovs proprietary sampling technology,quotas are framed based upon the census or profile of the required populationin the beginning.This frame is the basis on which the sampling softwa

107、re controls the flow of members into each survey.The sampling software randomly selects from the available panel,and allocates to surveys according to the quotas set.YouGovs sampling software includes a router.This removes the potential for self-selection on surveys,and increases the ability to deli

108、ver lower incidence samples within a short time frame.Panelists receive an invitation email containing a survey link.When they access the link the router checks against quotas on all live surveys and allocates them to a survey for which they qualify.Thus,panelists are not invited to a specific singl

109、e survey,reducing the risk of early response bias,social desirability or othermotivational biases.Survey pretest:For testing functionalities,the online survey was soft launched from 2022/04/25 to 2022/04/26.On the basis of the results,minor adjustments were implemented.Respondents from the soft laun

110、ch were removed from the final sample.Questionnaire:Huawei in collaboration with Prof.Dr.Anna Schneider provided the master questionnaire in English.YouGov reviewed the questionnaire and translated it into the local languages required for the target countries.Data preparation and analysis:The survey

111、 data was processed by YouGov and provided in a SPSS data set.Incomplete cases were removed from the data set.Cases from the pretest as well as cases with duplicate cookie ids were removed.Analyses were done in R.Methodology20 Deloitte consumer survey(n=2,009 US consumers,2021)finds that 58%of house

112、holds have a smartwatch or fitness tracker.Among device owners,14%bought their smartwatch during the pandemic.Typical metrics tracked are daily steps(59%),workouts(42%),heart health(37%),and sleep quality(35%).PwC“The wearable life 2.0”(n=1,000 US consumers plus n=500 respectively in Australia,Mexic

113、o,Singapore,UK,2016)indicates an already strong diffusion of wearable technology in the US as well as other markets even for niche wearables(e.g.12%owning smart clothing and 15%owning smart glasses).Trajectory Partnership“The future of wearable technology”(n=1,500 UK consumers,2021)sees a tipping po

114、int when it comes to wearable technology,with mainstream adoption driven by a combination of low-powered fitness trackers and feature-packed smartwatches from the tech giants.They find around 35%in their sample owning a wearable device of some sort.Ericsson Consumer Lab(n=5,000,Brazil,China,South Ko

115、rea,UK,and US,2016)provides some high-level insights as regards the future use cases of emerging wearables.The report provides some general insights into adoption and use of current wearables.AARP 50+Tech Trends(n=2,807,US,2021)shows the growth of wearables and tracking adoption among other general

116、tech trends in the age group 50+.On average,27%of 50+US consumers owned a wearable in 2020,and 38%said they were tracking health and fitness metrics.Review of other mainstream studies21Prof.Dr.Anna SchneiderHochschule Fresenius University of Applied SciencesSince 2017,Anna Schneider is Professor of

117、Business Psychology.Her research interests and teaching revolve around the impact of digitalization on consumer behavior,and in particular how people communicate and interact with emerging technology.Anna is a member of various research associations and sits on the scientific board of the Wissenscha

118、ftliches Institut fr Infrastrukturund Kommunikationsdienste(WIK)a renowned communications and internet policy think tank.Drawing on more than 20 years of hands-on experience in market research she regularly advices public and private organizations on surveys as well as qualitative research projects.

119、The authorsDr.Ren ArnoldHuawei Technologies Ltd.Ren Arnold is Vice President Public Affairs Strategy at Huawei Technologies.Previously,he worked at high-profile think tanks in Germany(German Economic Institute and WIK)and Brussels(Bruegel)where his research focused on digital economy,internet policy

120、 and impact assessments of regulatory frameworks.Over the past ten years,Ren has(co-)authored more than 100 conference papers,journal articles and white papers.He is a frequent speaker at both academic and industry events contributing among other fora to the ITU economic and industry round table,the

121、 Digital Summit of the German government and the research committee of the Munich Circle.Copyright2018 Huawei Technologies Co.,Ltd.All Rights Reserved.The information in this document may contain predictive statements including,without limitation,statements regarding the future financial and operati

122、ng results,future product portfolio,new technology,etc.There are a number of factors that could cause actual results and developments to differ materially from those expressed or implied in the predictive statements.Therefore,such information is provided for reference purpose only and constitutes neither an offer nor an acceptance.Huawei may change the information at any time without notice.Bring digital to every person,home and organization for a fully connected,intelligent world.Thank you.