Arguments
• Exercise Interventions to reduce falls (robust and massive evidence base over the last 15-20 years) WITHOUT ICT!
• Interventions to reduce Fear of Falling require people talking and NO EVIDENCE FOR ICT!
• ICT still not completely accepted by both therapists/instructors and older people (though this will change eventually!)
Interventions in the community
• Update of 2009 review • 159 trials with 79,193
participants • most common
interventions tested – exercise as a single
intervention (59 trials) – Multi-factorial programmes
(40 trials)
Conclusions: • Group and home-based exercise
programmes, and home safety interventions delivered by an occupational therapist reduce rate of falls and risk of falling.
• Multi-factorial assessment and intervention programmes reduce rate of falls but not risk of falling;
• Tai Chi reduces risk of falling. • Insufficient evidence that interventions
designed to prevent falls will also prevent hip or other fall-associated fractures.
Gillespie et al. Interventions for preventing falls in older people living in the community. Cochrane Library 2012
Support and Encouragement A programme is more than a series of exercises
• Examples from successful falls and exercise programmes • A range of strategies that support participants eg.
– Goal setting and self monitoring – Overcoming obstacles and difficulties – Educating the participant – Highlighting successes – Providing individual and group support
Can ICT provide all this? Possibly, but a PERSON DEFINITELY CAN!
• Interview data reveal that relationships with professionals, families and friends (the existence of social networks) during and after the rehabilitation process can impact on uptake and continuation of exercise
• Development of a relationship with the professional led to a sense of responsibility to stick with the programme
Health Education Journal 2009
Can ICT address this? Probably NO….. BUT A PERSON DEFINITELY CAN
Fear of Falling
• Fear and lack of confidence in balance predict – Deterioration in physical functioning
(Arfken 1994, Vellas 1997)
– Decreases in physical activity, indoor and outdoor (Arfken 1994, Finch 1997)
– Increase in fractures (Arfken 1994)
– Admission to Institutional Care (Cumming 2000, Vellas 1997)
• Avoid activity and may be non compliant or require additional support..
Can ICT address this? Probably NO….. BUT A PERSON DEFINITELY CAN
No evidence for ICT in FoF Evidence suggests that Fear of Falling is reduced through two mechanisms: • via group exercise delivered by an instructor
(Kendrick et al. Cochrane Review, 2014) and • through cognitive behavioural modification
with counseling (Zijlstra et al. JAGS. 2007) (ie. It needs a person!)
Can ICT address this? Probably NO….. BUT A PERSON DEFINITELY CAN
Interventions in nursing care and hospitals
• 41 trials with 25,422 participants • Nursing care facilities
– 7 trials testing supervised exercise interventions were inconsistent.
Cameron et al. Interventions for preventing falls in older people in nursing care facilities and hospitals. Cochrane Library 2010
?? Frailty / multiple co-morbidity of residents requires clinical judgement / adaptation – not ICT!
• In hospitals – Supervised exercise
interventions showed a significant reduction in risk of falling (RR 0.44; 3 trials).
Cameron et al. Interventions for preventing falls in older people in nursing care facilities and hospitals. Cochrane Library 2010
Interventions in nursing care and hospitals
?? ICT would not work in these settings – only face to face contact with a therapist
Maybe ICT can help identify risk…
? Better than a person
Are risk factor tools (delivered through ICT or not)
better than clinical judgment??
Major risk factors
All fallers = fell at least once during follow up Recurrent fallers = fell at least twice during follow up
All fallers (Odds Ratio)
Recurrent Fallers (Odds Ratio)
History of Falls 2.8 3.5
Gait Problems 2.1 2.2
Walking Aids Use 2.2 3.1
Vertigo 1.8 2.3
Parkinson’s Disease 2.7 2.8
Antiepileptic Drug Use 1.9 2.7
Physical Disability 1.6 2.4
Disability in Instrumental Activities in Daily Life 1.5 2.0
Fear of Falling 1.6 2.5
Deandrea S et al. Epidemiology. 2010;21: 658-668.
Clinical judgment had a greater accuracy at predicting falls that two validated falls risk tools (Downton and Stratify) A trained and experienced person can differentiate risk better than a set of questions or tests People don’t always follow the rules, they may be at low risk as assessed by a set of questions but exhibit risky behaviour or lack of insight into movement patterns? Who/what can assess this risk?
Potentially ICT can help tailor interventions based on risk profile …
but
• BUT little proof any of it works well at the moment (only emerging evidence on falls risk, not falls .... And...)
• Most ICT evidence is in those at lowest risk (independent infrequent fallers) NOT those who are currently being admitted to hospital and suffering severe injuries
• Can ICT differentiate cognition and body awareness changes day to day?
• Can ICT provide safe, tailored interventions (exercise) to support the wide range of health and abilities of older people?
Can ICT address this? Probably NO….. BUT A PERSON DEFINITELY CAN
ICT to improve uptake and adherence to strength and balance exercise
• Allow people to exercise at home (preference or rurality) • Ability to offer progression of intensity/balance challenge • Ability to offer different options based on ability • Ability to maintain adherence to exercise • Ability to report back
– To Health Professionals – To Older People
• Ability to show improved outcomes – Adherence; Risk Factors such as strength, TUG, balance, falls?
• Many examples, including iStoppFalls, MIRA and other Exergames
✔ ?
✔ ✔ ?
✔
✔ ? ✔ ?
✔ ?
Overall (I-squared = 61.5%, p = 0.000)
Ebrahim, 1997
Barnett, 2003
Woo, Tai Chi, 2007
Luukinen, 2007
Campbell, 2005
Schoenfelder, 2000
Sihvonen, 2004
Lord, 2003
Buchner, 1997
Author,
Nowalk, Tai Chi, 2001
Mulrow, 1994
Day, 2002
Reinsch, 1992
Skelton, 2005
Wolf, Balance, 1996
Woo, Resistance, 2007
Wolf, Tai Chi, 1996
year
McMurdo, 1997
Korpelainen, 2006
Morgan, 2004
Campbell, 1999
Hauer, 2001
Voukelatos, 2007
Faber, Functional walking, 2006
Li, 2005
Lord, 1995
Schnelle, 2003
Steinberg, 2000
Faber, Tai Chi, 2006
Liu-Ambrose, Resistance, 2004
Lin, 2007
Bunout, 2005
Liu-Ambrose, Agility, 2004
Resnick, 2002
Latham, 2003
Madureira, 2007
Carter, 2002
Green, 2002
Toulotte, 2003
Wolf, 2003
Cerny, 1998
Sakamoto, 2006Rubenstein, 2000
Means, 2005
Protas, 2006
Suzuki, 2004
Campbell, 1997
Nowalk, Resist./Endurance, 2001
Robertson, 2001
0.83 (0.75, 0.91)
1.29 (0.90, 1.83)
0.60 (0.36, 0.99)
0.49 (0.24, 0.99)
0.93 (0.80, 1.09)
1.15 (0.82, 1.61)
3.06 (1.61, 5.82)
0.38 (0.17, 0.87)
0.78 (0.62, 0.99)
0.61 (0.40, 0.94)
Effect
0.77 (0.46, 1.28)
1.26 (0.90, 1.76)
0.82 (0.70, 0.97)
1.24 (0.77, 1.98)
0.69 (0.50, 0.96)
0.98 (0.71, 1.34)
0.78 (0.41, 1.48)
0.51 (0.36, 0.72)
size (95% CI)
0.53 (0.28, 0.98)
0.79 (0.59, 1.05)
1.05 (0.66, 1.68)
0.87 (0.36, 2.10)
0.75 (0.46, 1.25)
0.67 (0.46, 0.97)
1.32 (1.03, 1.69)
0.45 (0.33, 0.62)
0.85 (0.57, 1.27)
0.62 (0.38, 1.00)
0.90 (0.79, 1.03)
0.96 (0.76, 1.22)
1.80 (0.67, 4.85)
0.67 (0.32, 1.41)
1.22 (0.70, 2.14)
1.03 (0.36, 2.98)
0.71 (0.04, 11.58)
1.08 (0.87, 1.35)
0.48 (0.25, 0.93)
0.88 (0.32, 2.41)
1.34 (0.87, 2.07)
0.08 (0.00, 1.37)
0.75 (0.52, 1.08)
0.87 (0.17, 4.29)
0.82 (0.64, 1.04)0.90 (0.42, 1.91)
0.41 (0.21, 0.77)
0.62 (0.26, 1.48)
0.35 (0.14, 0.90)
0.68 (0.52, 0.89)
0.96 (0.63, 1.46)
0.54 (0.32, 0.91)
100.00
2.64
1.88
1.22
3.85
2.74
1.40
0.98
3.38
2.21
%
1.88
2.75
3.80
2.04
2.81
2.86
1.41
2.67
Weight
1.48
3.05
2.04
0.88
1.89
2.56
3.31
2.87
2.38
1.98
3.97
3.34
0.72
1.13
1.67
0.65
0.11
3.46
1.34
0.70
2.21
0.10
2.58
0.31
3.341.11
1.40
0.88
0.80
3.13
2.27
1.84
0.83 (0.75, 0.91)
1.29 (0.90, 1.83)
0.60 (0.36, 0.99)
0.49 (0.24, 0.99)
0.93 (0.80, 1.09)
1.15 (0.82, 1.61)
3.06 (1.61, 5.82)
0.38 (0.17, 0.87)
0.78 (0.62, 0.99)
0.61 (0.40, 0.94)
Effect
0.77 (0.46, 1.28)
1.26 (0.90, 1.76)
0.82 (0.70, 0.97)
1.24 (0.77, 1.98)
0.69 (0.50, 0.96)
0.98 (0.71, 1.34)
0.78 (0.41, 1.48)
0.51 (0.36, 0.72)
size (95% CI)
0.53 (0.28, 0.98)
0.79 (0.59, 1.05)
1.05 (0.66, 1.68)
0.87 (0.36, 2.10)
0.75 (0.46, 1.25)
0.67 (0.46, 0.97)
1.32 (1.03, 1.69)
0.45 (0.33, 0.62)
0.85 (0.57, 1.27)
0.62 (0.38, 1.00)
0.90 (0.79, 1.03)
0.96 (0.76, 1.22)
1.80 (0.67, 4.85)
0.67 (0.32, 1.41)
1.22 (0.70, 2.14)
1.03 (0.36, 2.98)
0.71 (0.04, 11.58)
1.08 (0.87, 1.35)
0.48 (0.25, 0.93)
0.88 (0.32, 2.41)
1.34 (0.87, 2.07)
0.08 (0.00, 1.37)
0.75 (0.52, 1.08)
0.87 (0.17, 4.29)
0.82 (0.64, 1.04)0.90 (0.42, 1.91)
0.41 (0.21, 0.77)
0.62 (0.26, 1.48)
0.35 (0.14, 0.90)
0.68 (0.52, 0.89)
0.96 (0.63, 1.46)
0.54 (0.32, 0.91)
100.00
2.64
1.88
1.22
3.85
2.74
1.40
0.98
3.38
2.21
%
1.88
2.75
3.80
2.04
2.81
2.86
1.41
2.67
Weight
1.48
3.05
2.04
0.88
1.89
2.56
3.31
2.87
2.38
1.98
3.97
3.34
0.72
1.13
1.67
0.65
0.11
3.46
1.34
0.70
2.21
0.10
2.58
0.31
3.341.11
1.40
0.88
0.80
3.13
2.27
1.84
Favours exercise Favours control
1.25 .5 1 2 4
RR = 0.83 95%CI 0.75-0.91 P<0.001
17% reduction in falls
Sherrington et al., JAGS 2008 and NSWPHB 2011
All study interventions
delivered by PEOPLE
What makes the difference? • Greatest effects of exercise on fall rates from
interventions including:
– Highly challenging balance training
– High dose (50+ hours)
– No walking program
Sherrington et al., JAGS 2008, NSWPHB 2011
Exercise instructors can ensure adherence
to these principles over time by building
relationships and constant clinical
judgement assessments on what is best
for that individual
ICT delivered home exercise: • Do people challenge themselves or take the
easy option? • Do people understand the risks and could we
see an increased risk (cognitive ability) • Can people self identify safe progression and
adaptation?
Can ICT offer this?
• A trained exercise instructor is able to: – Adapt exercise for an individual (not based on age or
risk factors) – Tailor to how the person is THAT DAY – Offer support if someone is fearful to let go of their
support – Risk assess the safety of the person within their
environment (home or group) – Notice changes in level of cognition / dehydration /
changing function with new medications / presence of a urinary tract infection
– Etc…
Get rid of the personal touch?
• Robot teaches exercise to older people https://www.youtube.com/watch?v=TStB3HH4pZk
Improved outcomes
• Retirement village residents – good vision and cognition
• No adverse events • Good compliance • Improved outcomes in choice step reaction time,
falls risk (PPA), dual task ability (TUG) • But… FALLS not assessed In the past many exercise studies have shown reduced falls risk but not a reduction in falls
• Reduced falls risk (PPA) • Better outcomes in adherers vs non-adherers • DID NOT assess actual falls • And participants:
– Able to walk 20m without walking aid – Good vision and cognition
What might ICT solutions be missing? • Safe Progression • Adaptation to ability • Preferences/Choice • Ability to check
– Good technique / movement quality
• Ability to Feedback – To Health Professional
• Ability to Interact – With a Health Professional – With their peers
Would ICT be able to determine if cognition was declining and whether the participant would be ‘at risk’ to exercise unsupervised?
• LLT Inspire Video – https://player.vimeo.com/video/119397743
Transitioning onto other exercise opportunities
• Important – to encourage an active lifestyle beyond
rehabilitation – to ensure a change in exercise habits and continue
to improve social involvement – to ensure the opportunities continue to improve
strength and balance and offer different opportunities dependent on needs, preferences and abilities
Can ICT provide all this? NO…..
Counter argument - Why the therapist using ICT will replace the one who
doesn’t… Easily managed to produce the robust and
massive evidence base for exercise to reduce falls over the last 15-20 years WITHOUT ICT!
There will ALWAYS be people who avoid / are cynical about ICT and so we NEED instructors prepared/able to work without!
Conclusions • Huge Potential of ICT but… • The personal touch and expertise of an exercise
instructor has KNOWN positive outcomes to: – Falls and Fear of falling reduction – Improved outcomes – self efficacy, locus of control, social
engagement, reuse of public transport…. • Need long term RCTs to look at:
– safety and cost effectiveness of ICT to deliver exercise to the full range of function, health and ability
– Comparisons of traditional delivered exercise with addition of ICT to support instructor/participants
– with outcomes of falls prevented (not risk factor reduction!)
Videos
• Robot teaches exercise to older people – go to at least 35 secs in to see exercise instructor showing those who cannot see the robot! – https://www.youtube.com/watch?v=TStB3HH4pZ
k
• LLT Inspire Video – just over 1 min – https://player.vimeo.com/video/119397743
ICT to improve risk assessment and offer advice?
• Address multifactorial nature of falls • Ability to provide advice based on self report OR objective
risk factors • Ability to tailor information based on responses
– To health professionals – To older people
• Ability to allow a health professional without distinct expertise to offer advice
• Ability to provide tailored advice in the form of video clips, leaflets, onward referrals
• Many examples, including iStoppFalls
Is there a history of any fall in the previous year? How assessed? Ask the person.
Is the patient / client on four or more medications per day? How assessed? Identify number of prescribed medications.
Does the patient / client have a diagnosis of stroke or Parkinson's Disease? How assessed? Ask the person.
Does the patient / client report any problems with their balance? How assessed? Ask the person.
Is the patient/client unable to rise from a chair of knee height? How assessed? Ask the person to stand up from a chair of knee height without using their arms.
FRAT – Falls Risk Assessment Tool Multi - professional guidance for use by the primary health care team,
hospital staff, and social care workers
Score >3 = high risk of falls
Nandy et al, J Publ Health. 2004
Case Study – High risk or low risk?
• Mr Moss – Age 65 – Married and lives in a flat on 2nd floor (with no lift!) – Retired builder, does voluntary work twice a week in a
charity shop and has an allotment – On 5 meds (to keep blood thin, cholesterol and bp down) – One fall 2 years ago whilst rambling, hairline fracture in
patella – Severe knee pain (from old injury) when squatting or
getting up from chair, not painful on walking – Moderately deaf – Normal weight
QIS Case Finding Workshop 9/9/09
Is there a history of any fall in the previous year? How assessed? Ask the person.
Is the patient / client on four or more medications per day? How assessed? Identify number of prescribed medications.
Does the patient / client have a diagnosis of stroke or Parkinson's Disease? How assessed? Ask the person.
Does the patient / client report any problems with their balance? How assessed? Ask the person.
Is the patient/client unable to rise from a chair of knee height? How assessed? Ask the person to stand up from a chair of knee height without using their arms.
FRAT – Falls Risk Assessment Tool Multi - professional guidance for use by the primary health care
team, hospital staff, and social care workers
So, Mr Moss would be considered a HIGH RISK faller………. But is he more important to identify early, rather than Mrs Ferguson……..
Case Study – High risk or low risk?
• Mrs Ferguson – Age 93 – Lives alone and has home help – Cannot manage the garden or house cleaning anymore – Walks with a stick and only with company, concerned
about falling – On 3 meds (for high bp and osteoporosis) – previous falls - minor injuries but cannot get up from floor
unaided – Poor vision, wears bifocals – Big toe amputation on right foot – Urinary urge and frequency problems – Low weight
QIS Case Finding Workshop 9/9/09
Is there a history of any fall in the previous year? How assessed? Ask the person.
Is the patient / client on four or more medications per day? How assessed? Identify number of prescribed medications.
Does the patient / client have a diagnosis of stroke or Parkinson's Disease? How assessed? Ask the person.
Does the patient / client report any problems with their balance? How assessed? Ask the person.
Is the patient/client unable to rise from a chair of knee height? How assessed? Ask the person to stand up from a chair of knee height without using their arms.
FRAT – Falls Risk Assessment Tool Multi - professional guidance for use by the primary health care
team, hospital staff, and social care workers
So, Mrs Ferguson would be considered a LOW RISK faller !!!! Yet, at high risk of fracture, hospital admission and would benefit from further assessment and intervention
Set up
Laboratory studies Home studies
Intended environment
Limited space
Controlled environment
Ample space
Exergames
User chooses character
Speed of movement controlled by game
Objects collected have different scores
- Score improves as technique improves - Feedback to participant if too fast/slow or not an appropriate range of movement
Uzor, Skelton, Baillie. Trials 2013; Uzor, Baillie, Skelton, Fairlie. In Proc. INTERACT 2011; Uzor, Baillie, Skelton. In Proc. CHI 2012.
What do the experts want from home
rehabilitation games?
Participatory design with
older adults at risk of falling
Sensor task
Average time
- 30 seconds first attempt
- 20 seconds on next
Easy to use
- Placement
- Switching on and off
Acceptable
- Happy to use given the
benefits
User error
- Instructions were not
always observed
Exergame showed best adherence to exercises over a 12 week period and with guaranteed good movement quality
Uzor, Skelton, Baillie. Trials 2013
“I only hope I’ll be able to stop playing because
it is fun”
“To get a better score I had to move better – I had
a sense of achievement”
“This could give me the
confidence and discipline that I
need”
BUT…
• Falls not assessed as an outcome • No idea if this would work over a longer
period of time • No feedback to therapist • No feedback to participant, except better
score • No progression of balance challenge
• Group-based exercise is effective for falls prevention, quality-of-life enhancement, and balance improvements in the older adults, comparable with traditional home exercise programs.
• Group-based exercise promotes greater patient satisfaction and exercise adherence.
It is important to consider patient satisfaction for adherence!! Will ICT provide this?