Using gaming technology to enhance rehabilitation for children:

findings from the Wii fit study and working with families

W J Farr1, I Male1, D Green2, C Morris3, H Gage5, S Bailey3, S Speller1, V Colville4, M Jackson4, S Bremner6, A Memon6

1Sussex Community NHS Trust, Brighton, West Sussex, ENGLAND 2Department of Rehabilitation, Oxford Brookes University, Oxford, ENGLAND3Medical School. University of Exeter, Exeter, ENGLAND 4, Parent partnership advisors, Sussex Community NHS Trust, Brighton, ENGLAND 5, School

of Economics, University of Surrey, Surrey, ENGLAND 6 Brighton and Sussex Medical School, Brighton, ENGLAND

“As a parent I know that my child, along with others, is keen to engage with modern technology in most aspects of life, from assisting with school work, communicating with others and as a form of entertainment. If therapy was

delivered using a "computer games" format, I feel that my child would be much keener to engage in undertaking necessary tasks and exercises".

What’s the problem?

• Children with cerebral palsy often struggle with home-based therapy. No intervention =

poor outcomes

• Ideal dose currently unknown for therapy programmes

• Children with CP in UK NHS experience decrease in therapy time as they age,

• 12 hours per year for 0–6 year olds,

• 7hours by 12–18 years of age.

• What can be done about it?

Home-based exercise programmes

Use of more motivating tools

• Children = ‘Digital natives’?

• Consoles in the home (now gathering dust!) – but how many?

• Pilot work: DCD study 2012 (Hammond et al 2012)

• Xbox versus Wii fit trial

• Feasibility trial 2015-2016

What is VRT?

• Virtual reality therapy (VRT) uses motion capture

digital technology to assist with therapy using

commercial systems like the Nintendo Wii, Wii

Fit, Xbox Kinect

• But what are the “active ingredients”?

Lessons from Families

1. Engage early and often – no conversation or question

is wasted

2. If there is evidence (anecdotal and published) let

families/patients guide you - they know their own

lives, you don’t!

3. Ignore naysayers – everyone seems to have an

opinion! (c/f education) e.g. Luddites in our case

4. Be thankful – write letters (e.g. handwritten),

postcards, keep families informed

Lessons from Families

• Useful conflict e.g. difference in

parent/child views – who should

you choose?

• Wider network - families a hidden

and powerful resource

CP Wii

A Feasibility Study of Virtual Reality as a Therapeutic Intervention in Children with

Ambulatory Cerebral Palsy

Cerebral Palsy Nintendo Wii fit Feasibility study

Lessons from Families

Lessons from Families

What is a feasibility study?

• Is the study do-able?

• Are there going to be enough recruits?

• Will there be enough interest?

• What does the population look like?

• What are the best outcome measures?

• Will there be any effect size?

Phase 1: Survey

• Finding: 90% of homes have some sort of

commercially available console

• Few are using them or have been advised to

use them for any sort of therapy

Method

• 300 surveys – out by post & face to face contact by 6 CDCs teams (teams visited, posters distributed)

• Inclusion: Parents of child with CP, 5-16YO, GMFCS I-V.

• Return rate 20% (61/300)

• Low response -postal recruitment with unsigned/un-headed/uncoloured letters

• High response - at or after clinic- (40/61), & direct face to face (19/61)

• CDCs departments under pressure e.g. some areas with 50% vacancies

Results

Must be treated with caution as small and possibly self-selecting sample

Q1 Respondent profile: Mean age: 11 years 3 months (SD 3Y 4M) – males 67%, females 33%

0

2

4

6

8

10

12

14

16

18

20

1 2 3 4 5

Fre

qu

en

cy

GMFCS level

Frequency of respondents by Gender and GMFCS

Females Males

Q3 Which of the following games consoles does your family possess?

0

5

10

15

20

25

30

35

40

Fre

qu

en

cy

Type of Console

Consoles Owned by Respondents

Results

Results

Q4 How many hours does your child play on each device in an average week?

0

50

100

150

200

250

300

350

Wii Wii Fit X Box Kinect PS PS Move Nin DS Wii U PS Vita iPad

Av.

min

sp

er

we

ek

Type of Console

Average number of minutes played on console per week

Active play (minutes)

Console play (minutes)

Q5 Has your child ever used a gaming system as treatment/therapy to improve their motor

function..

0

2

4

6

8

10

12

Fre

qu

en

cy

Type of Console

Respondents who Indicated "yes" they have used a Gaming System as

therapy

Results

Advice

Levels of engagement &

accessibility

What is being

targeted?

Skills?

Functioning?

Muscle group?

Posture?

Balance?

How much help is required?

Will my child like it?

Will my child get frustrated or bored?

Can it be used unaided?

If not how can it be

adapted?

How much help is

needed?

Will my child

understand?

AccessibilityType of

therapy/Game

Main themes

Population

Q5d How do you think your child felt about having to do these games as

‘therapy’?:

Q5e How easy was it encourage your child to participate in the

games/programmes?:

Liked very much Liked Did not mind Did not like Strongly dislike

15 (58%) 4 (15%) 6 (23%) 1 (4%) 0

Self-initiated Minimal prompting

needed

Needed much prompting

14 (52%) 8 (30%) 5 (18%)

Phase 2: Method

• N = 30

• Randomization through minimisation to two groups:

• Therapist-directed games group (‘SG’ or supported

group)

• Group with freedom over game choice (‘USG’ or

unsupported group

• Participants asked to do:

• 30 minutes, 3 x wk x 12 wks of listed games (SG) or

free choice from a pack of games (USG)

Recruitment

• 44 children assessed for eligibility.

• 14 excluded: 3 outside age, 1 GMFCS III, 5

declined to participate, 4 no further response,

1 recruited/consented but not randomised

due to upcoming operation.

• 30(68% of approached) met inclusion criteria

and consented;

Phase 2 Results

Average age of participants overall 9.41 Y (s.d. 3.1)

SG mean age 10.1 Y (s.d. 3.0)

USG mean age 8.8 Y (s.d. 3.3)

Overall 70% of children completed trial (10 SG, 11 USG)

60% of recommended play completed, few problems

(no adverse events)

Adherence

SG

N

SG

Mean

SG

S.D.

USG

N

USG

Mean

USG

S.D.

No.

Sessions

(/36)

11 19/36 14.6 11 24/36 13.3

Av rating

(/5)

10 2.4 2 8 2.5 1.3

Total mins 10 819 634 11 1230 1003

Adherence

SG

N

SG

Mean

SG

S.D.

USG

N

USG

Mean

USG

S.D.

No.

Sessions

(/36)

11 19/36 14.6 11 24/36 13.3

Av rating

(/5)

10 2.4 2 8 2.5 1.3

Total mins 10 819 634 11 1230 1003

Results

Outcome measure Supported group

Unsupported

group Difference

n mean s.d. median n mean s.d. median in means

Gross Motor Function

Measurement-66 baseline 15 75.2 11.1 72.6 15 81.4 13.1 84 -6.2

6 weeks 12 79.2 8.5 79.1 11 82.8 10.4 88 -3.6

12 weeks 10 81.7 8.4 82.5 11 84.8 10.1 83 -3

Timed Up and Go test (in

seconds) baseline 15 6.2 1.6 5.7 14 6.6 1.8 6.4 -0.4

6 weeks 12 5.7 1.5 5.5 11 6.3 1.8 6.2 -0.6

12 weeks 10 5.5 1.5 5.3 11 5.7 1.8 5.3 -0.2

Goal attainment scale baseline 14 35.2 3.6 36.4 15 37.6 11.7 33.3 -2.4

12 weeks 10 54.9 15.5 55 11 58.8 7.1 56.7 -3.9

Strengths and Difficulties

Questionnaire baseline 15 12.5 6.8 11 15 12.6 6.7 10 -0.1

6 weeks 13 9.5 7.4 9 11 9.8 3.5 10 -1.3

12 weeks 10 10.9 6.8 13 11 9.4 3.4 10 0.1

C.I.* bias-corrected and accelerated

confidence interval

6.5 point change vs. 3.4 (15 percentile points)

Results

Outcome measure Supported group

Unsupported

group Difference

n mean s.d. median n mean s.d. median in means

Gross Motor Function

Measurement-66 baseline 15 75.2 11.1 72.6 15 81.4 13.1 84 -6.2

6 weeks 12 79.2 8.5 79.1 11 82.8 10.4 88 -3.6

12 weeks 10 81.7 8.4 82.5 11 84.8 10.1 83 -3

Timed Up and Go test (in

seconds) baseline 15 6.2 1.6 5.7 14 6.6 1.8 6.4 -0.4

6 weeks 12 5.7 1.5 5.5 11 6.3 1.8 6.2 -0.6

12 weeks 10 5.5 1.5 5.3 11 5.7 1.8 5.3 -0.2

Goal attainment scale baseline 14 35.2 3.6 36.4 15 37.6 11.7 33.3 -2.4

12 weeks 10 54.9 15.5 55 11 58.8 7.1 56.7 -3.9

Strengths and Difficulties

Questionnaire baseline 15 12.5 6.8 11 15 12.6 6.7 10 -0.1

6 weeks 13 9.5 7.4 9 11 9.8 3.5 10 -1.3

12 weeks 10 10.9 6.8 13 11 9.4 3.4 10 0.1

C.I.* bias-corrected and accelerated

confidence interval

6.5 point change vs. 3.4 (15 percentile points)

Dropout

• Tiredness (3), after-school activities (1),

homework (1), surgery (1), or difficulties with

using the technology, no time (2), comorbidity

with autism could not adhere to

measurements (1). Participants willing to be

randomised.

• Non-compliance with intervention

Conclusions and future work

• Therapeutic use of Nintendo Wii Fit in-home

inexpensive

• Acceptable in short periods of around six

weeks.

• Need to compare effectiveness with standard

physiotherapy

• Console maker willing to donate 70+ wii fits

for definitive national trial

• Patients will vote with feet – so listen

Selected References

Dempsey, W., Liao, P., Klasnja, P., Nahum-Shani, I., & Murphy, S. A. (2015). Randomised trials for the Fitbit generation.Significance, December 2015, 20-23.

Farr, W., & Male, I. (2013). A Meta-Analysis of “Wii Therapy” in Children with Cerebral Palsy. Archives of Disease in Childhood,98(1), A97.

Farr, W., Male, I., Green, D., Morris, C., Gage, H., Bailey, S., et al. (in submission). Methodological Issues of using Placebos inInterventions Based on Digital Technology. Journal of Mobile Technology in Medicine

Farr, W., Male, I., Speller, S., Morris, C., Green, D., Bailey, S., et al. (2015). A Survey of Home Ownership and Therapeutic Use ofCommercially Available Consoles in Children with Cerebral Palsy. Paper presented at the Annual Scientific Meeting BritishAssociation for Community Child Health 2015, Leeds Beckett University

Huckvale, K., Tomas Prieto, J., Tilney, M., Benghozi, P., & Car, J. (2015). Unaddressed privacy risks in accredited health andwellness apps: a cross-sectional systematic assessment. BMC Medicine, 13(214).

Klasjna, P., Consolvo, S., & Pratt, W. (2011). How to evaluate technologies for health behaviour change in HCI. Paper presented atthe CHI'11 Proceedings of the 29th International Conference on Human factors in Computing Systems.

Labrique, A., Vasudevan, L., Chang, L. W., & Mehl, G. (2013). H_pe for mHealth: More “y” or “o” on the horizon? InternationalJournal of Medical Informatics, 82, 467-469.

Morris, C., Simkis, D., Busk, M., Morris, M., Allard, A., Jacob Denness, et al. (2015). Setting research priorities to improve thehealth of children and young people with neurodisability: a British Academy of Childhood Disability-James Lind Alliance ResearchPriority Setting Partnership. BMJ Open, 5(1). doi: doi:10.1136/bmjopen-2014-006233

Pagoto, S., & Bennett, G. G. (2013). How behavioral science can advance digital health. Translational Behavioral Medicine, 3,271-276.

World_Health_Organisation. (2007). International Classification of Functioning, Disability and Health: Version for Children andYouth. from Geneva, World Health Organisation

Zaczynski, M. (2013). Efficacy Before Novelty: Establishing Design Guidelines in Interactive Gaming for Rehabilitation andTraining. Master of Applied Science, Carleton University, Ottawa, Canada•

Disclaimer: This presentation summarises independent research funded by the NIHR under its Research for Patient Benefit Programme (Grant Number PB-PG-0613-31046). The views expressed are those of the authors and not

necessarily those of the NHS, the NIHR or the Department of Health