Older Adults Activity and Social Inclusion Study

Activity and Social Inclusion:
Adding Digital Technology as a Helpful Tool

Wearable tech proves a valuable social connector

The Study
• We conducted a 3 month research project on how technology might
assist already active retirees to maintain and/or better understand
their activity and sociability levels on a daily basis.
• The results are intended to give deeper insights into how technology
may assist older adults to maintain their independence, feel safe in
their mobility activities (walking about) and keep actively part of their
usual social networks (or even invigorate new connections).

What is it?
• From this we plan to conduct a larger study aimed at helping those
who need motivating to be more independent (physically and socially)
so they can stay longer (and safer) in their own homes.
• The group wear trackers that collect their individual steps, km, heart
rate, sleep, calories used, stairs climbed and activities, as well as the
challenges between each other as a small group. They can see each
other’s daily activities.

How did it roll?
• We met once a week in a café and the group socially interacts and we
conduct short interviews recording any changes (or not) in
communication and/or activity.
• Participants re-suggested a number of cafes and we found the
quietest most welcoming one that still had accessible electricity and
big tables and was happy to host us each week.
• Of course, we had coffee so we were not so bad for business either.

How did it roll?
Kms, heart rate Steps

Measures…
• Steps,
• Distance,
• Heart rate
• Floors climbed
• Activity intensity
• Move - Reminds you to stay active with move bar and vibration alert
• Learns your current activity level, then assigns an attainable daily step
goal
• Notifications - receive text, call, email, calendar and social media
alerts

The Set Up
• Week 1, we set up the participants with Garmins in two sessions (split
the group.
• Meant we had time to set up with their individual and different
devices—so we paired with old iphones, gave one an ipad, a computer
at home, newer and older Samsung, etc etc –we deliberately wanted
them to use what they ‘usually’ worked with.
• We also gave them USB wall plugs and it took some time (weeks)
before all issues were settled!

What we started seeing…
• It had been established (for the researchers anyway) that the steps etc were not the
interesting thing happening here.
• What was happening was an exceptional group of motivated retirees were implementing their
everyday strategies for health and well being into the study in a very overt way.
• We saw how they overcame things, what small changes and strategies were in place there.
• As a group they also fed and inspired each other—yes with their step prowess to some degree,
and also sharing info over their common devices and uncovering bits of information as they go
(we deliberately were self declared and self-effacing non-experts—Neil, I know Apple but not
Samsung, Ann and Tamara—not familiar with Apple really—Ann, terrible interface, all different,
we do the best we can—oh look what I discovered this week!).
• It would have been easy to be the holders of the knowledge and fix it, but they were all richer
for discovering and sharing and exclaiming over their discoveries with each other. And it was a
warm friendly group of people happily getting on with stuff, bettering their condition (or just
doing what they usually do).
• Each was accepted, their philosophies were respected and this became part of the sharing,
and the inspiring between each other.

Added other Questionnaires
• In some ways from week to week there were often not big changes so we
added some questionnaire items to drill into the gaps that the technology
didn’t uncover.
• Garmin VivoSmart HR+ is not a medical standard device. E.g. The sleep
algorithms assume deep sleep if you do not move (yet you might be reading
or watching a movie).
• We added questionnaires on sleep, motivation, sense of autonomy, exercise
and mood.
• For 3 weeks (weeks 4-6) on how they ‘felt’ they slept (before looking at
Garmin) and on week 7, we gave them the MDBF Scale for mood and
‘feeling’ 2 days… give how feel at that moment in time.

All Interviews were Transcribed.
Discarded words below…
“1101 1103 110413 2000 2001 2004 2005 2006 2009 a about above active actual actually adult advance
advocate after again against airedales all always am america american an and any are aren’t aren't as at banks
be because becoming been before being below best better between black born both brain bring brown buddy
burst but by can can’t cannot can't cause causes change charles child comes coming common conference could
couldn’t couldn't course crack designer developed did didn’t didn't difference different do does doesn’t doesn't
doing don’t don't down during each early elderly elena engage especially every everybody everyone extra
familiar family few fixed for forms from further getting girlfriend going great had hadn’t hadn't hall happen has
hasn’t hasn't have haven’t haven't having he he’d he’ll he’s he'd he'll henry her here here’s here's hers herself
he's him himself his holiday hound how how’s how's i i’d i’ll i’m i’ve i'd if i'll i'm in interviewer into is isn’t isn't
issue it it’s its it's itself i've judge kinds let’s let's liver london longtime making married marx match matter me
meeting mention more morning most mouse mouth must mustn’t mustn't my myself natural neighbour never
no nor normal not notice object of off older olds on once only or other ought our ours ourselves out over own
owner parsons party past person personally place point previous previously produce program really report
rutherford said same say says schnauzer scientist scientists secure seminar senior service shall shan’t shan't she
she’d she’ll she’s she'd she'll she's should shouldn’t shouldn't simple smith so some someone something
somewhere speaker sport standard start statement stimulation stuff such sweet terrier terriers than that that’s
that's the their theirs them themselves then there there’s there's these they they’d they’ll they’re they’ve
they'd they'll they're they've thing things this those though through to too toowoomba under until up upon us
used very was wasn’t wasn't we we’d we’ll we’re we’ve we'd we'll were we're weren’t weren't we've what
what’s what's when when’s when's where where’s where's which while who who’s whom who's whose why
why’s why's will wilson with wolfhound wolfhounds woman won’t won't worst would wouldn’t wouldn't write
writing yeah you you’d you’ll you’re you’ve you'd you'll young your you're yours yourself yourselves you've”.

Word cloud of most frequent words in interviews

Mood Questionnaire Scales
We applied the MDBF, a German multidimensional mood
questionnaire. We used the short form (version A) with 12 items
(Hinz, Daig, Petrowski, & Brähler, 2012).
The questionnaire measures three bipolar dimensions:
pleasantness (pleasant-unpleasant), calmness (calm-restless)
and wakefulness (awake-sleepy).
Each of the three dimensions includes four items, whereof two
describe positive and two negative moods. Participants rated the
12 items on a 5-point Likert scale.
Participants rated the 12 items on a 5-point Likert scale (Not at all-
extremely). For analysis, we re-coded the scale from the negative
items. Thus, a high scale number shows a positive mood in each
dimension. For each dimension, points from four till 20 were
possible.

MDBF
We were interested in the general mood of our participants and
possible effects on their activity.
To validate the data, participants filled out the questionnaire twice;
two times during one week between weeks 6 and 8
(except one participant who submitted the sheets after week 12).
Pleasantness Wakefulness Calmness
content rested composed
good alert relaxed
bad worn-out restless
uncomfortable tired uneasy

The participants’ mood is on a high level, with
average values over 15.8 for all
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#1 #2 #3 #4 #5 #6 #8
Pleasantness
Wakefulness
Calmness
Figure 1. Mood levels of each participant over the three dimensions of MDBF.

Overall…
• Despite a few exemptions, all participants show similar values at both times they
did the questionnaire. Participants #5 and #8 have the lowest value (13.5) for
wakefulness.
• However, #5’s values are equal (14 and 13), whereas the low value for #8 is based
on the very low value in the 2nd questionnaire (8).
• Participant #7 has the lowest average value (12) for calmness. As well, #7’s values
for pleasantness differ: #7’s first value for pleasantness is 18, whereas the second
is 14 (the lowest value).
• The most interesting participant for MDBF is #8. There is a large difference in her
wakefulness. During the first report (weekday) it was very high (scale value = 19),
whereas she reported to be very tired four days later (scale value = 8). This
difference is reasonable when looking at the participant’s activities and lifestyle.
[telling story about #8 activity etc., data informed that depending in the lifestyle,
activity and mood, and perhaps sleep changed).]

Exercise, autonomy, motivation of participants.
• In addition we applied the Index of Autonomous Functioning (IAF;
Weinstein, Przybylski, & Ryan, 2012),
• Treatment Self-Regulation Questionnaire (Exercise) (TSRQ [Exercise];
Williams, Deci, & Ryan, 1998),
• and the Perceived Competence Scale (Exercising Regularly) (PCS
[Exercising Regularly], Williams, Ryan, & Deci, 1999) were
administered at different points in the study.

Index of Autonomous
Functioning (IAF)
• The IAF offers self report a measure of dispositional
autonomy, that is a measure of trait autonomy.
• Within our study and in keeping with self-
determination theory (SDT; Ryan & Deci, 2017)
autonomous functioning is theorised to be strongly
associated with self-congruence, taking, interest,
and a low susceptibility to control.
• In the context of this study such autonomous
functioning would be associated with a disposition
towards being autonomous in everyday life which is
strongly associated with self-regulation and
management of one’s personal wellbeing.

Process of IAF
• The IAF contains 15 items arranged across three subscales (authorship/self-
congruence, interest taking, and low susceptibility to control) with each
subscale containing 5 items.
• All questions are randomised and measured on five point Likert Scale ranging
from 1 (not at all true) to 5 (completely true).
• The IAF was administered to each participant in paper form at the beginning
of interview sessions in Week 1 and Week 12.
• Given that the instrument is designed to measure constructs related to
autonomy that would be expected to be consistent, the second measurement
was used for the purposes of confirming the description of each participant.
• The mean scores across the 15 items was calculated for each time to give a
measure of autonomous functioning.

IAF Results
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Autonomous functioning
Figure 1: Autonomous functioning scores for all participants in Weeks 1 and 12 of study
• In general autonomous
functioning was reasonably
consistent for all participants
as expected.
• As a small cohort, all
participant scored relatively
high for autonomous
functioning with participants
3, 7, 8 scoring slightly lower.

Method Treatment Self-Regulation
Questionnaire [TRSQ] (Exercise).
• The TRSQ (Exercise) is a self-report instrument that
assists in measuring the quality of motivation
individuals have towards exercise.
• The theoretical underpinnings of the instrument
group items into scales that measure:
• a) amotivation towards exercise i.e., limited or no
motivation towards undertaking exercise due to
such reasons as it is not being personally important
or feelings of incompetence;
• b) controlled motivation towards undertaking
exercise i.e., the source of motivation comes from
external pressures e.g., a doctor or family member
or internal pressures e.g., feeling guilty about
exercising;
• and
• c) autonomous motivation i.e., undertaking
exercise e.g., because it is enjoyable, reasons for
doing so are valued and personally important, or
consistent with other identifications in life such as
living healthily and managing personal wellbeing.

Example Questions
• The reason I would exercise regularly is:
• 1. Because I feel that I want to take responsibility for my own health.
• 2. Because I would feel guilty or ashamed of myself if I did not exercise regularly.
• 3. Because I personally believe it is the best thing for my health.
• 4. Because others would be upset with me if I did not.
• 5. I really don't think about it.
• 6. Because I have carefully thought about it and believe it is very important for many aspects of my life.
• 7. Because I would feel bad about myself if I did not exercise regularly.
• 8. Because it is an important choice I really want to make.
• 9. Because I feel pressure from others to do so.
• 10. Because it is easier to do what I am told than think about it.
• 11. Because it is consistent with my life goals.
• 12. Because I want others to approve of me.

The Process of TRSQ
• The TRSQ Exercise is a validated and reliable 15 item scale made up of three subscales measuring
autonomous (6 items), controlled (6 items), or amotivation (3 items). Responses are self-reported on
a 1-7 scale where lower end scores (i.e., 1-3) represent not at all true, scores around the median (i.e.,
3-5) represent somewhat true, and higher end scores (i.e., 5-7) represent very true. All items refer to
a single question which is
• The following question relates to the reasons why you would either start to exercise regularly or
continue to do so. Different people have different reasons for doing that, and we want to know how
true each of the following reasons is for you. All 15 response are to the one question.
• An example item that considers amotivation is “I really don't think about it.”, an example item
measuring controlled motivation is “Because I feel pressure from others to so”, and an example
item that refers to autonomous motivation is “Because I feel that I want to take responsibility for
my own health.”
• In keeping with the other self-reported measures in this study, the instruments were administered to
assist in describing this particular cohort of participants and were administered at the administered
to each participant in paper form at the beginning of interview sessions in Week 1 and Week 12.

Results: Amotivation
• Mean scores for each subscale of the TRSQ
(Exercise) were calculated for both data
collection points for each participant in the
study. The scores are described in the figures
below:
• Exercise amotivation: All
participants scored extremely low
on exercise amotivation (Figure 2)
with the exception of participant 8
on the second dataset.
• The higher score may be related to personal
circumstances at the time the study was
administered. In general, the data would
suggest that the participant group were
motivated towards taking regular exercise.
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3
4
5
6
7
1 2 3 4 5 6 7
Exercise Amotivation
Figure 2. Exercise amotivation scores for all participants in Weeks 1 and 12 of study

Controlled exercise motivation.
• All participants scored
relatively low on
controlled motivation
(Figure 3) with
participants 3 and 4 and 7
scoring marginally higher.
• The results suggest that
the participants in
general perceived limited
internal or external
pressure to exercise.
Figure 3. Controlled exercise motivation scores for all participants in Weeks 1 and 12 of study
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6
7
1 2 3 4 5 6 7
Exercise Controlled Motivatation

Autonomous exercise motivation.
Without exception, all
participants scored extremely
highly on the subscale
suggesting authentic personal
endorsement of exercise
behaviours.
Building on the IAF the
participants already having a
high autonomous disposition
also are autonomously
motivated toward their
exercise regime.
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6
7
1 2 3 4 5 6 7
Exercise Autonomous Motivation

Method TRSQ (Exercise Regularity) Competence.
• PCS (Exercising Regularly). In addition to describing the motivational status of the participants in the study, a
description of their sense of competence in exercising regularly was also required. Many theoretical
positions e.g., self-efficacy theory, theory of planned behaviour, and self-determination theory suggest that
individuals will adopt and continue with behaviours in which they feel
competence.
• In this particular cohort in which competence may be easily threatened by ill health for example it was
useful to get a sense of how competent they felt towards their exercise and if this changed during the study.
• The scale used to measure perceived competence was the PCS (Exercising regularly). It is a valid and reliable
self-reporting four item scale which examine both the confidence about and attitudes towards maintenance
of exercise behaviours. Like the TRSQ (Exercise) it is a 7-point Likert Scale with the lowest scores (i.e., 1-3)
represent not at all true, scores around the middle (i.e., 3-5) represent somewhat true, and high scores (i.e.,
5-7) represent very true.
• The single question being asked to participants is “Please indicate the extent to
which each statement is true for you, assuming that you were intending either to
begin now a permanent regimen of exercising regularly or to permanently
maintain your regular exercise regimen.”
• An example item was “I feel confident in my ability to exercise regularly.”

Results Exercise Competence
• A mean score for the PCS (Exercising
regularly) was calculated for both
data collection points for each
participant in the study.
• In general, five participants (1, 2, 3,
4, and 8) felt very competent about
their exercise with 5 and 7 self-
reporting lower scores.
• These scores were maintained
throughout the study with only small
changes in competence either up or
down.
• Interestingly participant 7 reported
very low competence at the end of
the study which perhaps can be
explained by the qualitative data.
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3
4
5
6
7
1 2 3 4 5 6 7
Exercise Competence

Overview
With one or two exceptions, the cohort of participants were high both
in their disposition and experience of autonomy as well as feel
competent about their exercise.
Put differently, this group reported feeling motivated about their
exercise as well as recognizing its importance and value in their life.
Not only did they see its value, but with the exception of one or two
participants felt competent being able to exercise regularly.

Quantitative Data from Garmins

Quantitative Data from Garmins
• Basic description:
• The variables in raw dataset were described with basic statistical analysis of mean, max,
and min values. The increase/decrease trend of variables were identified by single linear
regression with the time series of weeks (week 1 to 13) or month (August to November)
in this experiment. The basic description was presented for individuals and whole
population of this experiment.
• Group category:
• Duncan multiple group test with significant level of 0.95 (P<0.05) was applied to compare
the differences between different individuals. The results were referenced to categorize
individual into two groups, mainly identify the active/inactive individuals.
• MLR modelling analysis:
• The MLR modelling was used to find the key factors which influenced the heart health
condition (general heart rate, rest heart rate, and ratio of heart rate in the target zone),
sleep condition (hours) and activities. The analysis was conducted for groups and whole
population.

Basic descriptions for all: Temperature, WindSpeed, RainFall
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RH(%)
Temperature(oC)
Windspeed(km/h)
Thermal data
T WS RH
Temp reached to the highest in September, while the RH reached to the top after indicating an
increased ratio of rain. No clear trend with wind speed.

The change of Speed and Intensity are always
inverse.
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Intensityminutes(mins/day)
Speed(m/s)
Acitivity I
SpeedAvg IntensityAvg

Same change trend of distance, duration and
walking calories.
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Speed(m/s)
Distance(m)
Duration(seconds)
Activity II
Series1 Series2 Series3

Inverse trend of HR and Sleep
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Sleep(hours)
Heartrate(bpm)
Health I
HRavgAvg rHRavgAvg SleepAvg

Average and Max Heart Rate
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RatioofmaxheartrateinZone(%)
RatioofaverageheartrateinZone(%)
Health II
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G1
SpeedAvg IntensityAvg DistanceAvg DurationAvg WalkCALAvg HRavgAvg rHRavgAvg HRavgInZone HRmaxInZone
max 1.02 77.15 9823.25 11808.57 392.43 81.63 74.77 100.00% 85.71%
min 0.78 62.34 6536.38 7040.60 202.29 66.64 57.31 28.57% 28.57%
mean 0.92 71.64 8258.06 9160.55 278.17 77.69 62.94 59.01% 62.97%
STD 0.07 4.36 1073.91 1516.42 53.88 3.58 5.45 24.07% 17.75%
Trend NS NS NS NS NS NS NS NS NS
G2
max 0.60 81.01 5372.34 9536.43 373.43 85.55 72.55 100.00% 50.00%
min 0.46 73.54 2407.45 4690.43 192.71 80.08 60.34 71.43% 14.29%
mean 0.53 77.41 3663.23 7003.24 265.89 83.76 68.36 95.60% 27.29%
STD 0.04 2.78 820.17 1331.90 56.45 1.76 3.33 9.01% 13.84%
G3
max 0.61 86.33 4697.41 9553.75 290.75 87.25 74.69 100.00% 57.14%
min 0.38 72.44 1422.67 3538.00 92.14 81.13 65.26 85.71% 0.00%
mean 0.50 79.85 3648.45 7213.11 224.68 84.60 69.80 98.90% 26.56%
STD 0.07 4.00 1000.30 1571.31 59.38 1.98 3.14 3.96% 19.96%
G4
max 0.85 81.35 5419.40 7383.67 802.43 84.02 73.02 100.00% 71.43%
min 0.62 68.23 3174.11 3989.33 355.00 73.81 59.53 33.33% 14.29%
mean 0.71 75.77 4312.35 6299.04 609.35 79.42 66.67 72.53% 42.49%
STD 0.07 3.75 674.32 946.77 120.16 2.39 3.07 17.08% 16.43%
Trend NS NS "+" “+” “+” "+" NS "+" NS
G5
max 1.08 73.75 4906.61 5589.71 128.33 75.67 65.31 71.43% 100.00%
min 0.73 64.01 2915.80 3710.29 70.29 71.14 59.17 0.00% 66.67%
mean 0.95 69.37 3976.25 4385.95 99.84 73.06 62.24 24.54% 87.55%
STD 0.11 3.48 635.70 615.58 17.88 1.46 1.82 20.65% 12.07%
G7
max 0.83 90.44 8039.98 10868.57 319.14 89.91 78.52 100.00% 85.71%
min 0.41 75.07 2673.35 6196.00 116.43 82.00 71.00 71.43% 42.86%
mean 0.61 81.51 5212.16 8212.53 212.22 86.40 74.34 96.70% 61.72%
STD 0.15 4.33 1893.29 1234.85 75.13 1.80 2.50 8.56% 15.07%
G8
max 1.76 79.26 13800.00 11771.33 245.67 78.56 55.88 33.33% 100.00%
min 0.88 69.74 7637.45 6373.43 87.29 69.70 44.77 0.00% 33.33%
mean 1.17 75.10 10338.14 9248.99 157.85 73.59 52.45 7.14% 73.63%
STD 0.21 2.88 1804.74 1827.82 56.98 2.87 3.05 10.56% 17.45%
Trend "+" "-" NS NS NS "-" NS NS NS
Basic description for
individuals
Only G4 and G8 get
significant change
during the 3 months.

Rank and group of the data
• The Duncan test of Speed, Intensity, HR, rHR, HRavgInZone, and HRmaxInZone had a
clear difference between [1,5,8] and [2,3,4,7].
• However, inconsistency happened with grouping by Distance, Duration and Walking
Calorie.
• NOTES
1. The inverse of Speed and Intensity is caused by the definition of these two variables.
The simple explanation is people with better ability for sports (higher speed) will be
accounted for intensity hours more difficult than the one with lower ability for sports.
2. This can be also demonstrated by looking at the Speed and HR, which showing people
which had better sports ability owns lower HR avg, as the Intensity Minutes was
defined as the activity with HR higher than a recommend level, these guys will be
more difficult to reach that level than the one with lower ability for sport.

Notes contin
3. Pay attention to G8 with very low ratio of the HR in Zone. It is also
wired that people 1 5 8 with higher activity had lower ratio of HR avg in
Zone but their ratio of HRmax in Zone is higher than the others.
4. It is hard to put G4 in activity or inactivity group, his data is just
between the groups.
5. In the Histogram, HRavgInZone of Active group is low because of G8;
Intensity Min was higher with Inactivity group because they are easier
to be account for Insensitive activities; WalkingCal was higher with
Inactivity group because they do less running or other sports.

SpeedAvg G8 G5 G1 G4 G7 G2 G3
1.1683835 0.9510564 0.9159669 0.7061993 0.613968 0.5318761 0.4995239
a b b c cd cd d
IntensityAvg G7 G3 G2 G4 G8 G1 G5
81.50892 79.85058 77.41115 75.77439 75.0991 71.64246 69.36699
a ab abc bcd cd de e
DistanceAvg G8 G1 G7 G4 G5 G2 G3
10338.138 8258.063 5212.157 4312.351 3976.248 3663.226 3648.451
a a b b b b b
DurationAvg G8 G1 G7 G3 G2 G4 G5
9248.993 9160.546 8212.525 7213.107 7003.242 6299.044 4385.945
a a ab bc bc c d
WalkCALAvg G4 G1 G2 G3 G7 G8 G5
609.34798 278.16924 265.89378 224.67674 212.21978 157.85165 99.83516
a b b bc bc bc c
HRavgAvg G7 G3 G2 G4 G1 G8 G5
86.3969 84.60328 83.76432 79.42403 77.69202 73.59254 73.06462
a a ab bc cd d d
rHRavgAvg G7 G3 G2 G4 G1 G5 G8
74.34122 69.80222 68.3642 66.67201 62.93544 62.24179 52.44514
a ab abc bcd cd d e
HRavgInZone G3 G7 G2 G4 G1 G5 G8
0.98901099 0.96703297 0.95604396 0.72527474 0.59010991 0.24542123 0.07142856
a a a ab b c c
HRmaxInZone G5 G8 G1 G7 G4 G2 G3
0.8754579 0.7362638 0.6296703 0.6172161 0.4249084 0.2728937 0.2655678
a ab bc bc cd d d

1.01
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0.20
0.40
0.60
0.80
1.00
1.20
1 2 3
Series1 Series2
72.04
74.78
59.21
78.64
83.55
69.79
0.00
10.00
20.00
30.00
40.00
50.00
60.00
70.00
80.00
90.00
1 2 3
Series1 Series2
75.24 75.98
178.62
42.09
71.81
328.03
0.00
50.00
100.00
150.00
200.00
250.00
300.00
350.00
DistanceAvg(100m) DurationAvg(100seconds) WalkCALAvg(?)
Active Inactive

Group Dependent Temp RH WS WalkCal Speed Intensity Sleep HRavg rHRavg HRinZ maxHRinZ R2
All
HR - - -
0.03
**
-8.73
*
- - Null Null Null Null 0.71
rHR -
-0.09
**
- - - - - Null Null Null Null 0.70
HR
in Zone
- - - - - - - - - Null Null -
HR max
in Zone
-
-0.01
**
-0.02
*
0.003
*
-1.59
*
-
-0.21
*
-0.22
***
- Null Null 0.90
Sleep -
-0.02
*
-0.05
*
-
-4.56
*
- Null
-0.51
*
- Null Null 0.81
WalkCAL - - - Null - - -
24.13
*
- - - 0.77
Intensity - - - - - - - - - - - -
Speed - - - - - - - - - - - -
Activity
HR - -
-0.36
*
0.06
*
- - - Null Null Null Null 0.77
rHR -
-0.18
***
-0.47
**
- - - - Null Null Null Null 0.70
HR
in Zone
- - -
0.01
*
0.51
*
- - - - Null Null 0.92
HR max
in Zone
- -
0.07
*
-0.01
*
-0.60
*
- - - - Null Null 0.86
Sleep - - -
0.07
*
- - - - - - - 0.61
WalkCAL - -
2.42
*
- - - -
6.36
*
-
89.99
*
- 0.82
Intensity - - - - - - - - - - - -
Speed - - - - - - - - - - - -
Inactivity
HR
-0.06
**
-0.03
***
-
0.01
***
-
-4.69
**
0.08
*
Null Null Null Null 0.99
rHR -
-0.12
*
-
-0.03
*
- - - Null Null Null Null 0.74
HR
in Zone
0.01
**
0.00
*
-
-0.00
**
-
1.16
**
-
0.14
*
-0.02
**
Null Null 0.99
HR max
in Zone
-
-0.02
*
-
0.01
*
-
-3.07
*
0.08
*
-0.73
*
- Null Null 0.76
Sleep - - - -
5.6
**
- - - - - - 0.81
WalkCAL - -
-4.96
**
- - -
-9.62
*
55.6
***
- - - 0.92
Intensity
-0.01
*
- - - - -
-0.02
*
-
0.04
*
1.64
**
- 0.91
Speed -
0.02
*
- - - - -
0.48
**
- -
1.39
*
0.77
Regression
analysis

Notes
1.For all three group, higher T RH and W reduce the heart rate
level, indicating the changing of climate in Spring season
benefit the heart health
2.Speed could increase the rate of HR in Zone for activity group,
but insignificant for inactivity group. But speed increase the
Sleep for inactivity group
3.Intensity reduce the HR and increase the rate of HR in Zone,
but not for the activity group
4.For Intensity and Speed, activity group had no change with
different HR, rHR and other factors. However, in inactivity
group can be influenced by health and climate factors.

Upcoming Pathways and Paws Project
Call for Walkers and Dog Walkers
Developing an App to Find and Share the Best Paths
and Routes through Urban Spaces
Looking at easy walking, different levels of difficulty,
ways to get around/through traffic busy areas etc.

Behaviourists like Sue Bloom of Dogknowledgy pack
walks https://www.facebook.com/Dogknowledgy/

https://www.facebook.com/Dogknowledgy/videos/140746315268
0265/

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