SCOping the Use of Translation Technology (SCOUTT)
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SCOping the Use of Translation Technology (SCOUTT)
Dr Anita Panayiotou
Research Fellow
National Ageing Research Institute
Project Team: Frances Batchelor, Sue Williams, Kerry Hwang, Betty Haralambous,
Xiaoping Lin, Emiliano Zucchi, Terence Chong, Monita Mascuitti-Meuter, Dina
LoGiudice, Christiana Leontiou, Anita Goh, Emily You
Diversity of Older Australians
• Australia has a diverse population (ABS, 2016):
• 300 languages spoken in Australian homes in 2016
• >20% of Australians spoke a language other than English at home
• 25% of older Australians are from a CALD background
• By 2021, 30% of older Australians will be from a CALD background
• 27% of older Australians from CALD backgrounds did not speak
English well or at all
Language Barriers
• The diversity of spoken language in older Australians may
result in language barriers between the healthcare provider
and the individual
• Interpreters are gold standard
• Not always available or feasible in every situation
• Usually used for key phases of care (e.g. assessment)
• Outside of these key phases, healthcare workers “get by”
• Use gestures, facial expressions, change volume, minimal
key words, cards, pictures etc.
• But this may result in miscommunication and frustration
Melbourne Ageing Research Collaboration
(MARC)
Is there a role for technology?
• Mobile technology is becoming increasingly widespread & medical
translation apps are now available
• A few studies have evaluated these translation apps in the healthcare
setting
• Most of these have trialled technology for translation of medical history and
assessment, medical consultations and seeking consent
• However accuracy levels between languages a concern (Nguyen-Lu, Reide, and
Yentis, 2010; Patil and Davies, 2014)
• More suitable for short or simple phrases containing no technical
information (Beh and Canty, 2015)
• Apps are not suitable for translating complex medico-legal information
(Chang et al., 2014; Patil & Davies, 2014)
Melbourne Ageing Research Collaboration
(MARC)
Our Aims
• To explore the role of technology to communicate basic,
everyday conversations in health care setting
• To evaluate the feasibility and acceptability of using
translation technology to communicate of basic, everyday
conversations in healthcare
Melbourne Ageing Research Collaboration
(MARC)
Method
• Reviewing existing translational apps suitable
1. Scoping
for hospital setting
• With older Greek and Chinese community
2.Consultations members
• With nursing/allied health staff at 3 hospitals
• Trial at 3 hospitals:
• Royal Melbourne Hospital
3. Trial
• St Vincent’s Hospital
• Northern Health
Melbourne Ageing Research Collaboration
(MARC)
Method
• Reviewing existing translational apps suitable
1. Scoping
for hospital setting
• With older Greek and Chinese community
2.Consultations members
• With nursing/allied health staff at 3 hospitals
• Trial at 3 hospitals:
• Royal Melbourne Hospital
3. Trial
• St Vincent’s Hospital
• Northern Health
Melbourne Ageing Research Collaboration
(MARC)
1. Scoping Translation Apps
• Search on the Apple iTunes Store, published & grey literature
• Inclusion criteria
• Free or minimal cost
• Include 1 of top 10 languages spoken by older people in
Australia
• Able to translate everyday health-related information
• Findings
• 15 applications met criteria
• Experts on project team reviewed apps for their suitability for
everyday communication in healthcare setting
Melbourne Ageing Research Collaboration
(MARC)
1. Scoping Translation Apps
TalkToMe CALD Assist
Melbourne Ageing Research Collaboration
(MARC)
Languages supported= 7 (Italian, Greek, Vietnamese, Mandarin, Cantonese, Arabic and Spanish)
CALD Assist Languages supported=10 (Italian, Greek, Vietnamese, Mandarin,
Cantonese, Arabic, Spanish, Serbian, Croatian, and Macedonian)Preliminary consultations indicated that Google
Translate was being widely used in pilot sites
Languages
supported=103
Varying degrees
of support:
Text support=103
Photo support=37
Voice-to-voice=32Method
• Reviewing existing translational apps suitable
1. Scoping
for hospital setting
• With older Greek and Chinese community
2.Consultations members
• With nursing/allied health staff at 3 hospitals
• Trial at 3 hospitals:
• Royal Melbourne Hospital
3. Trial
• St Vincent’s Hospital
• Northern Health
Melbourne Ageing Research Collaboration
(MARC)2. Consultations – Greek & Chinese
Community (n = 12)
Community 4-Greek Community
8-Chinese Community
Gender 7/12 (58%) Male
5/12 (42%) Female
Age (mean) 76yrs (range: 65-86)
Years living in 25yrs (range: 8-58)
Australia (mean)
Education 1/12 (8%) None
4/12 (33%) Primary school
2/12 (17%) Secondary school
1/12 (8%) Certificate /diploma
4/12 (33%) University degreeDemonstration of Translation Apps
• Overcome communication issues:
• “I can speak English pretty good but when I can’t express myself this would
work.”
• “Now I am officially Australian Chinese”
• “Allows doctor to communicate with the client”.
• Features of the apps most liked:
• Apps spoke the language of the participants
• Can see and hear what is being spoken
• Easy and convenient to use
• Features of the apps disliked:
• Can’t change the language of the app- can’t drive or lead the conversation.
• Google Translate has accuracy issues:
• “Love it but it is not accurate- not coming out right, I said- ‘I can’t see
clearly because of the old age eyes, it said: ‘I Spent my eyes’”.
• Might be a learning curve in using the translation apps.
Melbourne Ageing Research Collaboration
(MARC)Demonstration of Translation Apps
• Most feedback was positive and older people were
interested to use the technology
• However, it was not suitable for everyone
• 2 participants withdrew
• Did not feel it was for them (n=1)
• Unable to use due to visual impairment (n=1)
• 1 participant found it difficult to use due to poor literacy
Melbourne Ageing Research Collaboration
(MARC)Focus Group Discussion
• How do you see technology being used for communication in a healthcare
setting?
• All believed it would be useful
• Gave examples of using Google Translate in other settings (e.g. at shops or
with electrician)
• “Especially in situations in the hospital when you have an interpreter is
booked, or the appointment is delayed or cancelled, we can use the
technology to speak with the doctor. Can’t always bring children to the
hospital”.
• “It’s the worst thing which happens when you are in a place when you can’t
understand and express yourself. It would be good.”
• What are the barriers to translation apps?
• Don’t know how to use technology:
• “We would like to be able use our phones like our children do.”
• “We feel technology blind.”
• “ I have no idea about technology. I would like to. It would be good, even
to pay a bill-it all involves technology. My children are busy so it would be
good to do (it) myself.”
Melbourne Ageing Research Collaboration
(MARC)Consultations - Nursing & Allied Health
Staff (n=17)
Gender 14/17 (82%) Female
3/17 (18%) Male
Age (mean) 43 years (range: 24-62)
Country of 8/17 (47%) born in Australia
birth 9/17 (53%) born elsewhere
Years worked 2/17 (12%)Perception of Translation Apps
• Useful for addressing communication barriers:
– “Cool…Might be helpful in some situations” (Referring to pen/camera
input)
– “Great choice of languages… (communication is) hardest when language
is something different”.
– “Good source of main languages”.
• Good Accessibility:
– “Pictures are excellent”
– “I think pictures will be good for people with cognitive impairment”
– “Large text, good for people with sensory impairment”.
• Appropriate for their work & workflow:
– “a lot of phrases we use in our work”
– “Doesn’t seem too cumbersome”
Melbourne Ageing Research Collaboration
(MARC)Focus Group Discussion
• How do you normally communicate everyday care needs with patients who do
not speak your language?
• Family members
• Cue cards, body language
• Bilingual staff member
• Some reported being discouraged from using interpreters due to costs
• Some were using Google Translate
• Is there a role for technology?
• Useful for basic needs
• “Good for basic day-to-day stuff…not for family meeting or
appointments…still need interpreter.”
• Helps to build rapport with patients
• May help to reduce agitation
• What are the barriers to using translation apps?
• Language dialects
• Accuracy of translation
• Workplace policy and infection control
• Sensory impairments
• Technology confidenceSummary of Consultation Findings
• All participants were positive about technology playing a role in basic
communication healthcare conversations
o Some staff were using translation apps to communicate with
patients
• Barriers to technology were acknowledged
o Lack of technology experience and understanding, but enthusiasm
to learn (older community members)
o Practice and policy related (i.e. accuracy of translation, sensory
impairments, language dialects)
Melbourne Ageing Research Collaboration
(MARC)Method
• Reviewing existing translational apps suitable
1. Scoping
for hospital setting
• With older Greek and Chinese community
2.Consultations members
• With nursing/allied health staff at 3 hospitals
• Trial at 3 hospitals:
• Royal Melbourne Hospital
3. Trial
• St Vincent’s Hospital
• Northern Health
Melbourne Ageing Research Collaboration
(MARC)3. Trial to Test Feasibility & Acceptability
• 2 month trial on 4 aged care / subacute wards
• No specific language targeted; based on needs & app capability
• Observational, frequency of use, & survey data will be collected
• Observations by an interpreter - to check content and accuracy of
information
Site: Trial app 1st Trial app 2nd Month
Month
Site 1 TalkToMe CALD Assist
Site 2 CALD Assist Google Translate
Site 3 Google Translate CALD Assist
Site 4 CALD Assist TalkToMe
Melbourne Ageing Research Collaboration
(MARC)Definition of Everyday Conversations
Definition of Everyday Conversations
Trial Feedback (so far)….
• Observations from trial coordinators:
– One patient with dementia responded positively
– Another patient with dementia was too agitated
– Staff often feel too busy to use it
– Security vs. accessibility – can result in forgetting to use it
– Pre-set phrases are good, but some are too directive and
limiting (i.e. ‘sit on the chair’ instead of ‘can you please sit on
the chair’)
– Families have commented on minor dialect issues
Melbourne Ageing Research Collaboration
(MARC)Acknowledgements
Chinese Community Social Mei Yau, Brigitta Lee
Services Centre Inc.
NARI Frances Batchelor, Sue Williams, Kerry Hwang,
Betty Haralambous, Xiaoping Lin
Northern Health Drew Aras, Emiliano Zucchi, Paula McPherson,
Kirralee Jensen, Yue Hu, Stefania Zen
Pronia Nikki Efromidis, Mary Sophou, Tania Samartza
St Vincent’s Hospital Terence Chong, Monita Mascuitti-Meuter,
Patrick Aninon
Royal Melbourne Hospital Kwang Lim, ina LoGiudice, Christiana Leontiou,
Janelle Walters
University of Melbourne Anita Goh, Emily You
Dr Anita Panayiotou
National Ageing Research Institute
a.panayiotou@nari.edu.auYou can also read
