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Citation: Mathur P, Thomas H, Cooper
A, Chechlacz M, Stathi A, Goodyear V, et
al. (2025) Supervised and self-directed
technology-based dual-task exercise training
programme for older adults at risk of falling
– Protocol for a feasibility study. PLoS ONE
20(3): e0314829. https://doi.org/10.1371/
journal.pone.0314829
Editor: Marianne Clemence, Public Library
of Science, UNITED KINGDOM OF GREAT
BRITAIN AND NORTHERN IRELAND
Received: November 18, 2024
Accepted: November 22, 2024
Published: March 24, 2025
Copyright: © 2025 Mathur et al. This is an open
access article distributed under the terms of
the Creative Commons Attribution License,
which permits unrestricted use, distribution,
and reproduction in any medium, provided the
original author and source are credited.
Data availability statement: Data sharing is
not applicable to this article as no datasets
were generated or analyzed. Data will be avail-
able after the completion of the study.
Funding: This work was supported by the
National Institute for Health and Care Research
STUDY PROTOCOL
Supervised and self-directed technology-
based dual-task exercise training programme
for older adults at risk of falling – Protocol
for a feasibility study
Prerna Mathur1, Helen Thomas2, Angela Cooper1, Magdalena Chechlacz 3,4,
Afroditi Stathi1, Victoria Goodyear1,5, Caroline Miller6,7, Taylor Krauss2, Natalie Ives8,
Laura Magill 9, Philip Kinghorn10, Daisy Wilson11, Shin-Yi Chiou 1*
1 School of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, Birmingham,
United Kingdom, 2 Solihull Community Specialist Falls Service, Solihull Hospital, University
Hospitals Birmingham NHS Foundation Trust, United Kingdom 3 School of Psychology, University of
Birmingham, Birmingham, United Kingdom, 4 Centre for Human Brain Health, University of Birmingham,
Birmingham, United Kingdom, 5 Institute for Mental Health, University of Birmingham, United Kingdom,
6 Physiotherapy Department, Queen Elizabeth Hospital Birmingham, University Hospitals Birmingham
NHS Foundation Trust, United Kingdom, 7 School of Infection, Inammation and Immunology, College
of Medicine, University of Birmingham, United Kingdom, 8 Birmingham Clinical Trials Unit, School of
Health Sciences, University of Birmingham, Birmingham, United Kingdom, 9 Birmingham Centre for
Observational and Prospective Studies (BiCOPS), School of Health Sciences, University of Birmingham,
Birmingham, United Kingdom, 10 Health Economics Unit, Department of Applied Health Sciences,
University of Birmingham, Birmingham, United Kingdom, 11 Institute of Inammation and Ageing,
University of Birmingham, United Kingdom
* s.chiou@bham.ac.uk
Abstract
Falls among older adults pose a signicant public health challenge, as they lead to severe
outcomes such as fractures and loss of independence. Research has shown that training
cognitive function and balance simultaneously, termed Dual-Task (DT) training, improves
mobility and reduces fall risks in older adults. This study aims to evaluate the feasibility
and acceptability of a blended supervised and self-directed technology-based DT train-
ing programme for older adults who have high risk of falling. This is a single-arm, non-
randomised feasibility study employing quantitative and qualitative methods. Fifty healthy
adults aged 65 years or above will be recruited from the NHS primary and secondary care
pathways and from the community. Participants will undergo supervised cognitive and
balance DT training for 12 weeks, followed by self-directed DT training for an additional
12 weeks. The cognitive training will be delivered using a commercial mobile application
(app) available from the AppStore or Google Play. The balance training will involve static
(Marching on the spot, Tandem Stand, Hip Abduction & Extension, Squats, Tiptoe Stand,
and Pendulum/Sideways Sway) and dynamic (Figure of Eight Walk, Walking Forwards and
Backwards, Lunges, Functional Reach, Toe Tapping, Upper Limb Strength Exercises, and
Side-Steps/Simple Grapevine) exercises focused on improving balance, postural stabil-
ity and strength. Feasibility outcomes will be recruitment, adherence, usage of the app,
and attrition. Outcomes measure data, that will be collected at baseline and at 24 weeks,
includes the Timed- Up and Go (TUG) test (likely primary outcome in any future trial),
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PLOS ONE Technology-based dual-task training in older adults
along with self-reported questionnaires assessing cognition, fear of falling, quality of life,
healthcare service usage, and the self-reported number of falls. Focus group interviews
will be conducted with thirty participants and thirty healthcare professionals for in-depth
exploration of the feasibility and acceptability of the DT training programme.
Introduction
Falls among older adults represent a significant public health issue. Around 1 in 3 adults aged
over 65, and half of adults aged over 80, have at least one fall a year, and in half of such cases
the falls are recurrent [1,2]. Falls can lead to severe consequences such as hip fractures, which
often result in reduced mobility and loss of independence [3]. An estimated £4.4 billion is
spent annually on treating fractures and fall-related injuries [4]. The prevalence of falls and
associated complications necessitates the development and implementation of effective inter-
vention strategies aimed at prevention.
Evidence suggests that age-related declines in cognition and mobility are risk factors
for falls in older adults [5–7]. Studies reveal that older adults with better mobility perform
better in assessments of global cognition, executive function, memory and processing speed
[7–10], suggesting the interplay between cognition and mobility. Research has shown that
the decreasing ability to multitask is associated with increasing risk of falling in older adults
[11,12] and that training cognitive and physical function simultaneously, termed Dual-Task
(DT) training, is superior to single-task (i.e., only physical function) training or no training
for improving walking speed in older adults [1,13].
The cognitive element of DT training can be delivered via technology (e.g., mobile apps),
enabling professionals to select cognitive exercises that are suitable to be combined with physical
exercises, allowing for the DT training to be self-directed and performed outside of clinical envi-
ronments. Mobile apps are interactive, provide instant feedback, and can send reminders to users.
These features promote engagement and adherence to exercise [14]. Previous studies reported
improved balance and walking speed after self-directed, home-based DT training programmes
with mobile apps in older adults, with excellent adherence rate (85-90%) [15,16]. These findings
support the notion that technology-based exercise (not limited to DT exercise) may be a sustain-
able means of promoting physical activity and preventing falls in older adults [17–19].
Whilst a purely technology and home-based exercise programme seems attractive, it may
appear daunting to some older adults, such as those who are reported to have lower levels of
knowledge and competence in using mobile apps [20,21]. Barriers to the use of technology
in the medical context amongst older adults have been reported [22]. A blended approach,
combining supervised sessions with self-directed sessions, can help mitigate the challenges
older adults might face while using the mobile app by providing initial hands-on guidance
and ongoing support. The gradual transition from supervised to self-directed exercises allows
participants to build confidence and familiarity with the technology, ultimately improving
their engagement and adherence [23].
While it is evident that a DT programme can be administered well under supervision
[13,24], we have limited knowledge on how to best assure its quality, outcomes, and compli-
ance when administered unsupervised with the support of technology, such as a mobile app.
Therefore, the primary aims of this study are to evaluate; (1) the acceptability of a technology-
based DT programme with blended supervised and self-directed approaches in older adults at
higher risk of falling and (2) to determine the feasibility of the programme to be adopted by
the National Healthcare System as a treatment for falls prevention and management in older
adults in the United Kingdom.
(NIHR) Research for Patient Benefit in the form
of a grant [NIHR205389] to S-YC.
Competing interests: The authors have
declared that no competing interests exist.
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PLOS ONE Technology-based dual-task training in older adults
Objectives
1. To evaluate whether a blended supervised and self-directed DT training programme deliv-
ered via a mobile app is acceptable to older adults living in the community who have had
recurrent falls in the past 12 months.
2. To assess the feasibility of the technology-based blended DT training to be implemented in
the NHS for falls prevention and management in older adults.
The information collected will inform the design of a larger scale Randomised Controlled
Trial to evaluate the clinical and cost-effectiveness of the blended intervention in older adults
aged 65 years and above at risk of falls.
Methods and analysis
Study design
This is a single-arm, non-randomised feasibility study of a technology-based, blended DT
training programme in older adults with a history of falls (Fig 1) outlines the schedule of
enrolment, interventions and assessment and provides insight into the trial process and data
collection. The flow of the study is shown in Fig 2. This study was approved by the East of
England - Cambridge East Research Ethics Committee (REC reference: 24/EE/0059) and
registered on the International Standard Randomised Controlled Trials Number Registry
(ISRCTN15123197) on April 16, 2024. The study protocol is reported following the SPIRIT
check list (S1 Appendix).
Setting
The study will be conducted in a community setting in Birmingham, UK. There are two
phases: phase 1 is supervised cognitive and balance DT training for 12 weeks at local com-
munity centres, followed by a phase 2 which is self-directed DT training for an additional 12
weeks.
Participants and recruitment
Participants will be recruited from primary and secondary care pathways in the National
Health Services (NHS) in England and from the community in the West Midlands. The
study will be promoted via a number of methods including general practitioners sending
text messages to patients, healthcare professionals identifying eligible patients in the falls
clinics, and study flyers displayed in relevant organisations, such as retirement villages,
charity organisations, and interest groups. Interested individuals from the NHS and from the
community will be directed to an online participant information sheet (PIS) or given a copy
of the PIS by their healthcare professional and by the research team, respectively. They can
contact the research team to request further information of regarding participation and/or
to ask any study-related questions they may have. If they are interested and willing into be
enrolled in the study, the research team will confirm the eligibility of the potential partic-
ipant via telephone or a face-to-face appointment, explain the study and what is involved,
should they agree to take part, answer any questions they have. Written informed consent (S2
Appendix) will be obtained from all participants at community venues where the baseline
assessment and supervised intervention will be held. Recruitment was started on 29/04/2024
and is ongoing. Furthermore, the individual whose images are included in the S3 Appendix
has given written informed consent (as outlined in PLOS consent form) for their images to
be published.
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PLOS ONE Technology-based dual-task training in older adults
Eligibility criteria. The inclusion criteria are:
1) Aged 65 years and above
2) Able to give informed written consent
3) Having sufficient cognition/hearing/vision to follow instructions of the assessment and the
exercise programme
4) Able to stand with one hand support on the current walking aid for at least 60 seconds
5) Able to stand up from a chair independently and walk for 6 meters independently with the
current walking aid
6) Able to use toilet independently
7) Having access to a smartphone or tablet compatible to the Peak-brain training app [25,26]
on iOS or Android devices
Fig 1. Schedule of enrolment, interventions and assessment. Preparation (t-1), baseline (t0), week 12 (t1), week
24(t2). Everyday Cognition (ECog) 12-item scale; Falls Efficacy Scale – International (FES-I); EuroQol 5 Dimension-5
Levels (EQ-5D-5L); Modular resource-use measure (ModRUM).
https://doi.org/10.1371/journal.pone.0314829.g001
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PLOS ONE Technology-based dual-task training in older adults
8) Had two or more falls in the last 12 months.
The exclusion criteria are:
1) Having an unstable or acute medical condition (such as fractures, acute coronary syn-
dromes) that preclude exercise participation
2) Suffer from a progressive neurological condition (such as Parkinson’s disease or multiple
sclerosis)
3) Not recommended to undertake any forms of exercise by their doctors
4) Currently participating in a different research study for managing their fall risks.
Sample size. The sample size (n = 50) was chosen based on published literature where a
sample size of between 50 and 100 participants (total; i.e., 25 to 50 per group) is recommended
for pilot studies [27–29]. If we identify 100 eligible participants, we will be able to estimate a
participation rate of 50% within a 95% confidence interval of ± 9.8%. With a sample size of
50 participants, we will be able to estimate an attrition rate of 20% within a 95% confidence
interval of ± 11%.
Intervention
All participants will receive the DT training programme for 24 weeks. The programme has
two phases (Table 1). Phase 1 is 12 weeks long. It consists of supervised group exercises once a
week, along with two other home-based sessions of self-directed, independent exercise similar
to the class exercises. The group exercise class of 5-10 participants will be led by a physiother-
apist 1 day/week. The classes will be approximately 50 minutes in duration and include 40
Fig 2. Study flow diagram. DT: dual-task; TUG: Timed Up & Go.
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PLOS ONE Technology-based dual-task training in older adults
minutes of DT training with 10 minutes of warm-up and cool-down. The exercise classes will
be held in local community centres that will be easy access for the participants.
Phase 2 is self-directed, with participants independently exercising at home using the
app, 50 minutes per day, 3 days per week, for 12 weeks. Participants will have access to the
Peak app [25] and will repeat the same exercises that they have performed in the phase 1but
without supervision. This phase reinforces the idea of performing DT training as part of one’s
routine for maintaining balance and mobility, thereby reducing the risk of recurrent falls.
DT training programme. The DT training programme requires participants to perform
both cognitive tasks and balance and strength exercises simultaneously. The cognitive
exercises are delivered via the Peak app [25] which is a commercial app that can be
downloaded from the App Store (iOS) or Google Play (Android). The research team will assist
participants to install the app on their own devices prior to the start of the first class. The
PEAK app [25] has multiple games, and the choices of the games are based on two criteria: 1)
whether a game can be safely performed with a balance exercise, and 2) the type of cognitive
function being trained. For the second criterion, we prioritise the games that require executive
function, memory, attention, and processing speed as they have been shown to relate to
balance control and falls [30–33]. Eighteen games covering the above cognitive domains were
chosen within 4 categories of games available from the Peak app, Focus, Memory, Mental
Agility, and Problem Solving (Must Sort, Rush Back, unique, Decoder; Perilous Path, Memory
Sweep, Spin Cycle, Apprentice Wizard, Partial Match; True Color, Face Switch, Refocus,
Turtle Traffic; Puzzle Box, Slider, Low Pop, Castle Block, Earth Defence).
For the physical exercise, the standardised static and dynamic balance and strength exer-
cises routinely prescribed to older adults for falls management and prevention are included
in the programme. The static exercises (Marching on the spot, Tandem Stand, Hip Abduc-
tion & Extension, Squats, Tiptoe Stand, and Pendulum/Sideways Sway; S3 Appendix) will be
performed concurrently with the cognitive exercises (S4 Appendix). The dynamic exercises
(Figure of Eight Walk, Walking Forwards and Backwards, Lunges, Functional Reach, Toe Tap-
ping, Upper Limb Strength Exercises using a resistance band, and Side-Steps/Simple Grape-
vine) will be performed independently (i.e., not concurrently with the cognitive exercises) (S3
Appendix). These exercises were selected by a specialist physiotherapist from the University
Hospitals Birmingham, considering the safety of participants in light of the dual task nature of
the training programme.
Supervised group exercise classes. In the Phase 1 of the training programme, participants
will be asked to attend an exercise class (of 5–10 participants) once a week for 12 weeks. In
each class participants will be shown three static and three dynamic exercises respectively
by a physiotherapist. The class will consist of a 5-minute warm-up at the start, after which
participants will perform the three static exercises, followed by the three dynamic exercises,
and finish with a 5-minute cool-down to complete the class. Each exercise will last for
Table 1. A summary of dual-task training programme.
Supervised group exercise Self-directed, home-based exercise
Duration: 50 minutes
Location: local leisure/wellbeing centres
Frequency: one class/week (Weeks 1-12)
Content: 5 minutes warm-up, 40 minutes of DT training,
5 minutes cool down.
DT training:
• Cognitive exercises delivered via the Peak app.
• Strength and balance exercises delivered by a
physiotherapist
Duration: 50 minutes
Location: at home
Frequency: twice/week (Weeks 1-12); thrice/week
(Weeks 12-24)
Content: 5 minutes warm-up, 40 minutes of DT train-
ing, 5 minutes cool down.
DT training:
• Cognitive exercises delivered via the Peak app.
• Strength and balance exercises in an exercise booklet
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PLOS ONE Technology-based dual-task training in older adults
approximately 6 minutes, with short breaks between each exercise. The three static exercises
will be performed with three different games from the Peak app for cognitive brain training.
The participant’s device will be placed on a height-adjustable music stand in front of the
participant at an appropriate distance that allows them to use the app comfortably. There will
be a chair placed next to the participant for support during the exercises if needed. The phys-
iotherapist leading the class will provide individual support and adjustment to the exercises to
each participant to ensure that everyone is able to engage with the DT exercise training as per
their capacity. The Peak app adapts the games (increase/decrease of the difficulty level) based
on the participant’s performance to maintain cognitive challenges as they progress. At the end
of the class, participants can note down the exercises and variations performed in the class in
an exercise diary.
Self-directed, home-based exercise. Participants will be instructed to perform the same
DT exercises at home on another two days in the same week after each class in phase 1, and
three times a week during phase 2, the self-directed, home-bases DT part of the programme.
The scope of the blended approach is to allow participants time to learn the exercises and the
technology, to develop an exercise routine, to improve their ability[34,35], and potentially
enhance their confidence to use the app. All participants will be given a handbook which has
images and instructions of all the physical and cognitive exercises (S3 and S4 Appendices) to
help them exercise at home. They will also have access to online videos demonstrating how
to perform each exercise correctly and safely. Equipment required (height-adjustable music
stand, and resistance bands) for exercising at home will be provided to the participants.
Participants will be asked to record their adherence to the programme. In phase 1, participants
will document, in an exercise diary provided to them at the start of the training programme,
the cognitive games performed with the physical exercises. In phase 2, participants will be
asked to document both the cognitive games and the physical exercises performed in the
exercise diary. Participants will be able to contact the research team (via email or SMS) for
technology assistance and/or to ask questions during the self-directed home-based exercise.
Educational session. An in-person educational session for falls awareness will be
presented to the participants at the end of phase 1. This session will be conducted by the
physiotherapist delivering the training programme. In the education session, participants will
be reminded of the content of phase 2, access to the resources (i.e., the handbook and videos),
and support they can receive if they run into any technical difficulties with the app.
Participants will also be asked to consider ways that may help them stay motivated in
doing the exercise in the next 12 weeks, such as creating WhatsApp groups or using Facebook
Messenger, and supplemented by face-to-face “coffee shop” get-togethers to stay in touch with
other participants in the same age and/or living in the same area.
Measures
Feasibility outcome measures. The feasibility outcomes of the study are whether the
study is appealing to participants (assessed by the recruitment and retention rate) and if the
intervention is acceptable (measured by adherence and usage of the app).
1. Recruitment. Recruitment will be calculated as (number recruited/number approached) x
100. The source of recruitment (e.g., primary care, secondary care, and community) will be
documented to evaluate which recruitment route is the most appropriate for the main trial.
2. Adherence. Adherence will be calculated as: (self-reported number of exercise days/number
of prescribed days) x 100 using the information recorded on the exercise diary.
3. Usage of the app. This will be analysed based on the self-reported number of games per-
formed and the repetition of each game during the DT programme.
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4. Study attrition. Attrition will be calculated as: [(number of dropouts)/ number recruited) x
100].
5. A self-reported online EXIT survey (S5 Appendix) will be completed by participants to
provide feedback on the usability, perceived effectiveness and satisfaction from the training
programme based on the feasibility assessment framework [36].
Stop-go criteria. A ‘traffic light’ system based on recruitment, adherence, app usage and
retention will be used to provide guidance as to whether the project should progress to a
full trial with an internal pilot (green), progress to full trial with internal pilot with adaption
(amber), or no progression (red).
• Green: recruitment ≥ 50%; adherence and usage of the app over the programme is ≥ 80%
of the time (i.e., completed the physical exercises and cognitive exercises in 58 sessions or
more out of a total of 72 sessions over 24 weeks); and retention is ≥ 80%. Focus group results
support the feasibility and acceptability of the study and the blended intervention, and there
are no safety concerns.
• Amber: recruitment 30-49%; adherence and usage of the app is 50-79%; and retention rate
is 50-79% of the time. Focus group results indicate that changes in the design and delivery
of the programme are required, and there are no safety concerns. Potential changes could
be technical support required for the phase 2 where participants undertake the exercise
independently.
• Red: recruitment < 30%; adherence and usage of the app is < 50%; and retention is < 50% of
the time. Focus group results do not support the study progressing to a larger-scale RCT,
and/or there are safety concerns, which cannot be addressed.
Data from the feasibility study will directly feed into the above stop-go to provide guidance
on progression to the full trial. Any decision will also be informed by the findings of the focus
groups (see below qualitative methods for details).
Exploratory outcomes. The study has three assessment periods – baseline (t0), Week
12 (t1), Week 24 (t2) where data collection is undertaken (Fig 2). Information on participant
demographics (age, sex, ethnicity, post code and level of education) will be collected in order
to describe the study participants and assess inclusion and reach of the study.
Data will be collected on the following outcomes which are planned outcome measures in
any future trial in order to assess data collection procedures, data completeness and to help
inform sample size calculation for the future trial.
1. Mobility and dynamic balance. Timed Up and Go (TUG) [37] with and without concurrent
undertaking of a cognitive task will be carried out in the presence of the physiotherapist to
evaluate mobility and dynamic balance of the participant. Participants will be asked to rise
from a standard armchair, walk to a marker 3 meters away, turn, walk back, and sit down
again. This will be completed three times, with the first TUG will be a practice round [38].
For the TUG with cognitive tasks (TUG Cognitive) [37], participants will be asked to count
backwards in sevens from a random start point while completing the TUG. The perfor-
mance from the TUG and TUG Cognitive will be recorded.
The following self-reported questionnaires will be collected via an online survey (using RED-
Cap software) at baseline and after the delivery of the training programme.
2. Decline of cognition and everyday functional abilities. Everyday Cognition scales short
version (ECog-12; 12 questions in total) [39,40] will be used to evaluate the decline of
cognition and everyday functional abilities linking to independence in the activities of daily
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living. The ECog-12 questionnaire has 12 items on a scale from 1-4, being 1 (better or no
change compared to 10 years ago) and 4 (consistently much worse). The results from this
questionnaire will reflect any effect of the training programme on the cognitive function
affecting daily living which declines with ageing.
3. Self-efficacy in performing daily activities. Falls Efficacy Scale-International (FES-I), having
16 items on a scale from 1-4, being 1 (not concerned at all), and 4 (very concerned), will be
used to evaluate the confidence in the performance of activities of daily living in levels of
fall risk (>24 points) [41].
4. Quality of life. The EQ-5D-5L will be used to assess the quality of life [42]. The question-
naire has 5 items each with five response options, being 1 (no problems) and 5 (unable).
5. Resource use. The ModRum questionnaire will be used to evaluate the use of healthcare
services, providing basic health economics information of the intervention [43].
6. Number of falls. Self-reported number of falls.
Qualitative methods. Focus groups: We will conduct face-to-face semi-structured focus
groups with a purposive sample of 30 participants who have completed the programme to
discuss the content and delivery of the training programme. We will also conduct online
semi-structured focus groups with 30 healthcare professionals including GPs, district nurses,
paramedics, and physiotherapists who are part of the NHS falls prevention care pathways in
the West Midlands, via MS Teams. The healthcare professionals and physiotherapists involved
in the study will be invited to take part in the focus groups to discuss the feasibility and
deliverability of the training programme by the NHS. Discussions will be downloaded from
MS Teams and transcribed verbatim. The focus group recordings will be coded using Nvivo9
software. Analysis will be deductive, informed by the study objectives, and will follow a
thematic analysis approach. A deliberative approach will be used to interpret emerging themes
with the diverse interdisciplinary author team, and this serves as a marker of quality [44,45].
Statistical analysis. Given the study is a feasibility study, the analysis undertaken will
mainly be descriptive. The feasibility outcome measures will be reported as proportions and
percentages with 95% confidence intervals calculated. Outcome data will be summarised
at baseline and follow-up using appropriate summary statistics. Exploratory analysis may
compare the data form the two assessment time points using a paired t-test (depending on the
distribution of the data) to provide preliminary data on the effect of the blended intervention.
Analyses will be undertaken in SPSS [46].
Data management. Paper based study records will be kept in locked cabinets within a
locked office at the University of Birmingham. Electronic records will be stored on RedCap
which is a secure data management software application managed by the Birmingham Centre
for Observational and Prospective Studies (BiCOPS) at the University of Birmingham. The
recordings from the focus groups will be held on a secure device and will be uploaded to the
University of Birmingham server. Access to the files will be restricted and password protected.
Study management and safety. The DT training programme and the behavioural
assessments are considered low risk. The research team will meet monthly to monitor the
progress of the study, supervise the study, and discuss data and adverse events to ensure that
the study is conducted in accordance with the approved protocol and regulations. Three
members of the public will be recruited to the PPIE steering group and meet three times a
year. The chief investigator will report the study progression to the PPIE steering group.
The DT programme was designed by experienced physiotherapists and a member of the
public with lived experience to reduce risks and burdens as much as possible. Risks will be
outlined in the PIS and verbally explained to all participants before they provide written
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informed consent. Participants will also be verbally reminded after each class on how to safely
undertake the intervention at home.
Dissemination. We anticipate that the study will be completed by 31/12/2025 and that
results will be disseminated at international conferences and in published peer-reviewed
journals in 2026.
Discussion
Falls among older adults are a significant public health concern as they not only result in
physical injuries but can also lead to psychological consequences, such as fear of falling, which
further exacerbates the risk of subsequent falls [47]. Given the multifactorial nature of falls,
interventions that target both physical and cognitive function are crucial for fall prevention in
older adults [48]. This study seeks to evaluate the feasibility and acceptability of a technology-
based dual tasking exercise training program designed specifically for older adults at risk of
falling.
The information in this study will inform the feasibility and design of a larger scale
randomised controlled trial evaluating the clinical and cost-effectiveness of the blended DT
intervention in older adults at risk of falls. The knowledge generated will also have wider
implications on other clinical conditions, where home exercise is a commonly used tool for
maintaining/improving health. This study is especially relevant, given population ageing and
the increased use of technology and mobile apps in older adults during the global pandemics.
However, there is limited understanding on how technology can facilitate dual tasking
exercise programs for older adults. Data published by the Office for National Statistics show
that 69% of adults over 65 years and 55% of adults over 75 years owned a smartphone in 2021
[49]. The number is likely to increase, meaning that it is now the time to evaluate how to best
incorporate these digital tools into standard care and to determine if the quality, outcomes and
compliance of technology-based interventions are comparable or superior to standard care.
Supporting information
S1 Appendix. SPIRIT Checklist 2013.
(PDF)
S2 Appendix. Consent Form.
(DOCX)
S3 Appendix. Exercise Handbook.
(PDF)
S4 Appendix. Peak app Handbook.
(PDF)
S5 Appendix. Exit questionnaire.
(DOCX)
S1 File. UoB protocol v3.
(DOCX)
Acknowledgment
We thank Liz Hensel and Tom Tierney from the PPIE steering group for their contributions
in reviewing participant facing documents and feedback on the study design and manage-
ment. We also thank Terry Hughes for setting up the RedCap database, which is critical to the
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successful management of this study. The University of Birmingham will host the study and
hold negligent harm and non-negligent harm insurance policies.
Author contributions
Conceptualization: Helen Thomas, Angela Cooper, Magdalena Chechlacz, Afroditi Stathi,
Victoria Goodyear, Caroline Miller, Natalie Ives, Laura Magill, Philip Kinghorn, Daisy
Wilson, Shin-Yi Chiou.
Data curation: Prerna Mathur, Helen Thomas, Afroditi Stathi, Victoria Goodyear, Taylor
Krauss, Laura Magill, Philip Kinghorn, Shin-Yi Chiou.
Formal analysis: Prerna Mathur, Afroditi Stathi, Victoria Goodyear, Natalie Ives, Shin-Yi Chiou.
Funding acquisition: Angela Cooper, Magdalena Chechlacz, Afroditi Stathi, Victoria
Goodyear, Caroline Miller, Natalie Ives, Laura Magill, Daisy Wilson, Shin-Yi Chiou.
Investigation: Prerna Mathur, Helen Thomas, Angela Cooper, Magdalena Chechlacz,
Afroditi Stathi, Victoria Goodyear, Caroline Miller, Taylor Krauss, Natalie Ives, Laura
Magill, Daisy Wilson, Shin-Yi Chiou.
Methodology: Prerna Mathur, Helen Thomas, Angela Cooper, Magdalena Chechlacz,
Afroditi Stathi, Victoria Goodyear, Caroline Miller, Natalie Ives, Laura Magill, Philip
Kinghorn, Daisy Wilson, Shin-Yi Chiou.
Project administration: Prerna Mathur, Afroditi Stathi, Victoria Goodyear, Caroline Miller,
Natalie Ives, Laura Magill, Shin-Yi Chiou.
Resources: Prerna Mathur, Afroditi Stathi, Caroline Miller, Laura Magill, Shin-Yi Chiou.
Software: Laura Magill.
Supervision: Helen Thomas, Afroditi Stathi, Victoria Goodyear, Caroline Miller, Natalie Ives,
Laura Magill, Philip Kinghorn, Shin-Yi Chiou.
Validation: Helen Thomas.
Visualization: Prerna Mathur.
Writing – original draft: Prerna Mathur, Shin-Yi Chiou.
Writing – review & editing: Prerna Mathur, Helen Thomas, Angela Cooper, Magdalena
Chechlacz, Afroditi Stathi, Victoria Goodyear, Caroline Miller, Taylor Krauss, Natalie Ives,
Laura Magill, Philip Kinghorn, Daisy Wilson, Shin-Yi Chiou.
References
1. Schoene D, Valenzuela T, Lord SR, de Bruin ED. The effect of interactive cognitive-motor train-
ing in reducing fall risk in older people: a systematic review. BMC Geriatr. 2014;14:107. https://doi.
org/10.1186/1471-2318-14-107 PMID: 25240384
2. Falls – Overview; 2021 [cited 2024 Aug 23]. Available from: https://www.nhs.uk/conditions/
falls/#:~:text=Around%201%20in%203%20adults,not%20result%20in%20serious%20injury.
3. Varela-Vásquez LA, Minobes-Molina E, Jerez-Roig J. Dual-task exercises in older adults: a structured
review of current literature. J Frailty Sarcopenia Falls. 2020;5(2):31–7. https://doi.org/10.22540/JFSF-
05-031 PMID: 32510028
4. Falls: applying All Our Health; 2022 [cited 2024 Jul 15]. Available from: https://www.gov.uk/government/
publications/falls-applying-all-our-health/falls-applying-all-our-health
5. Chantanachai T, Sturnieks DL, Lord SR, Payne N, Webster L, Taylor ME. Risk factors for falls in older
people with cognitive impairment living in the community: Systematic review and meta-analysis. Ageing
Res Rev. 2021;71:101452. https://doi.org/10.1016/j.arr.2021.101452 PMID: 34450352
6. Allali G, Launay CP, Blumen HM, Callisaya ML, De Cock A-M, Kressig RW, et al. Falls, cognitive impair-
ment, and gait performance: results from the GOOD initiative. J Am Med Dir Assoc. 2017;18(4):335–40.
https://doi.org/10.1016/j.jamda.2016.10.008 PMID: 27914848
PLOS ONE | https://doi.org/10.1371/journal.pone.0314829 March 24, 2025 12 / 14
PLOS ONE Technology-based dual-task training in older adults
7. Li KZH, Bruce H, Downey R. Cognition and mobility with aging. Oxford Research Encyclopedia of
Psychology. 2018. https://doi.org/10.1093/acrefore/9780190236557.013.370
8. Buchman AS, Boyle PA, Leurgans SE, Barnes LL, Bennett DA. Cognitive function is associated with
the development of mobility impairments in community-dwelling elders. Am J Geriatr Psychiatry.
2011;19(6):571–80. https://doi.org/10.1097/JGP.0b013e3181ef7a2e PMID: 21606900
9. Demnitz N, Esser P, Dawes H, Valkanova V, Johansen-Berg H, Ebmeier KP, et al. A systematic
review and meta-analysis of cross-sectional studies examining the relationship between mobil-
ity and cognition in healthy older adults. Gait Posture. 2016;50:164–74. https://doi.org/10.1016/j.
gaitpost.2016.08.028 PMID: 27621086
10. Demnitz N, Hogan DB, Dawes H, Johansen-Berg H, Ebmeier KP, Poulin MJ, et al. Cognition and
mobility show a global association in middle- and late-adulthood: Analyses from the Canadian Longi-
tudinal Study on Aging. Gait Posture. 2018;64:238–43. https://doi.org/10.1016/j.gaitpost.2018.06.116
PMID: 29945095
11. Muir-Hunter SW, Wittwer JE. Dual-task testing to predict falls in community-dwelling older adults: a
systematic review. Physiotherapy. 2016;102(1):29–40. https://doi.org/10.1016/j.physio.2015.04.011
PMID: 26390824
12. Bayot M, Dujardin K, Dissaux L, Tard C, Defebvre L, Bonnet CT, et al. Can dual-task paradigms pre-
dict Falls better than single task? - A systematic literature review. Neurophysiol Clin. 2020;50(6):401–
40. https://doi.org/10.1016/j.neucli.2020.10.008 PMID: 33176988
13. Wang X, Pi Y, Chen P, Liu Y, Wang R, Chan C. Cognitive motor interference for preventing falls in
older adults: a systematic review and meta-analysis of randomised controlled trials. Age Ageing.
2015;44(2):205–12. https://doi.org/10.1093/ageing/afu175 PMID: 25377745
14. Sullivan AN, Lachman ME. Behavior change with tness technology in sedentary adults: a review of
the evidence for increasing physical activity. Front Public Health. 2017;4:289. https://doi.org/10.3389/
fpubh.2016.00289 PMID: 28123997
15. Callisaya ML, Jayakody O, Vaidya A, Srikanth V, Farrow M, Delbaere K. A novel cognitive-motor
exercise program delivered via a tablet to improve mobility in older people with cognitive impair-
ment - StandingTall Cognition and Mobility. Exp Gerontol. 2021;152:111434. https://doi.org/10.1016/j.
exger.2021.111434 PMID: 34098009
16. Papi E, Chiou S-Y, McGregor AH. Feasibility and acceptability study on the use of a smartphone
application to facilitate balance training in the ageing population. BMJ Open. 2020;10(12):e039054.
https://doi.org/10.1136/bmjopen-2020-039054 PMID: 33268409
1 7. Valenzuela T, Okubo Y, Woodbury A, Lord SR, Delbaere K. Adherence to technology-based exercise
programs in older adults: a systematic review. J Geriatr Phys Ther. 2018;41(1):49–61. https://doi.
org/10.1519/JPT.0000000000000095 PMID: 27362526
18. Netz Y, Yekutieli Z, Arnon M, Argov E, Tchelet K, Benmoha E, et al. Personalized exercise programs
based upon remote assessment of motor tness: a pilot study among healthy people aged 65 years
and older. Gerontology. 2022;68(4):465–79. https://doi.org/10.1159/000517918 PMID: 34515118
19. Smith-Ray RL, Makowski-Woidan B, Hughes SL. A randomized trial to measure the impact of a
community-based cognitive training intervention on balance and gait in cognitively intact Black older
adults. Health Educ Behav. 2014;41(1 Suppl):62S-9S. https://doi.org/10.1177/1090198114537068
PMID: 25274713
20. Rasche P, Wille M, Bröhl C, Theis S, Schäfer K, Knobe M, et al. Prevalence of health app use
among older adults in Germany: national survey. JMIR Mhealth Uhealth. 2018;6(1):e26. https://doi.
org/10.2196/mhealth.8619 PMID: 29362211
21. McGarrigle L, Boulton E, Todd C. Map the apps: a rapid review of digital approaches to support the
engagement of older adults in strength and balance exercises. BMC Geriatr. 2020;20(1):483. https://
doi.org/10.1186/s12877-020-01880-6 PMID: 33208117
22. Wilson J, Heinsch M, Betts D, Booth D, Kay-Lambkin F. Barriers and facilitators to the use of e-health
by older adults: a scoping review. BMC Public Health. 2021;21(1):1556. https://doi.org/10.1186/
s12889-021-11623-w PMID: 34399716
23. Hughes KJ, Salmon N, Galvin R, Casey B, Clifford AM. Interventions to improve adherence to
exercise therapy for falls prevention in community-dwelling older adults: systematic review and meta-
analysis. Age Ageing. 2019;48(2):185–95. https://doi.org/10.1093/ageing/afy164 PMID: 30358800
24. Wang R-Y, Huang Y-C, Zhou J-H, Cheng S-J, Yang Y-R. Effects of exergame-based dual-task training
on executive function and dual-task performance in community-dwelling older people: a randomized-
controlled trial. Games Health J. 2021;10(5):347–54. https://doi.org/10.1089/g4h.2021.0057 PMID:
34491113
PLOS ONE | https://doi.org/10.1371/journal.pone.0314829 March 24, 2025 13 / 14
PLOS ONE Technology-based dual-task training in older adults
25. PEAK-Brain Training App. Available from: https://www.peak.net/science/
26. Ltd. SL. Peak (Version 5.34.9) [Mobile Application Software]; 2024.
2 7. Sim J, Lewis M. The size of a pilot study for a clinical trial should be calculated in relation to con-
siderations of precision and efficiency. J Clin Epidemiol. 2012;65(3):301–8. https://doi.org/10.1016/j.
jclinepi.2011.07.011 PMID: 22169081
28. Teare MD, Dimairo M, Shephard N, Hayman A, Whitehead A, Walters SJ. Sample size requirements
to estimate key design parameters from external pilot randomised controlled trials: a simulation study.
Trials. 2014;15:264. https://doi.org/10.1186/1745-6215-15-264 PMID: 24993581
29. Lancaster GA, Dodd S, Williamson PR. Design and analysis of pilot studies: recommendations for
good practice. J Eval Clin Pract. 2004;10(2):307–12. https://doi.org/10.1111/j.2002.384.doc.x PMID:
15189396
30. Alexander NB, Hausdorff JM. Guest editorial: linking thinking, walking, and falling. J Gerontol A Biol
Sci Med Sci. 2008;63(12):1325–8. https://doi.org/10.1093/gerona/63.12.1325 PMID: 19126844
31. Liu Y, Chan JSY, Yan JH. Neuropsychological mechanisms of falls in older adults. Front Aging Neuro-
sci. 2014;6:64. https://doi.org/10.3389/fnagi.2014.00064 PMID: 24782761
32. Clouston SAP, Brewster P, Kuh D, Richards M, Cooper R, Hardy R, et al. The dynamic relationship
between physical function and cognition in longitudinal aging cohorts. Epidemiol Rev. 2013;35(1):33–
50. https://doi.org/10.1093/epirev/mxs004 PMID: 23349427
33. Divandari N, Bird M-L, Vakili M, Jaberzadeh S. The association between cognitive domains and
postural balance among healthy older adults: a systematic review of literature and meta-analysis.
Curr Neurol Neurosci Rep. 2023;23(11):681–93. https://doi.org/10.1007/s11910-023-01305-y PMID:
37856048
34. Hawley-Hague H, Horne M, Campbell M, Demack S, Skelton DA, Todd C. Multiple levels of inu-
ence on older adults’ attendance and adherence to community exercise classes. Gerontologist.
2014;54(4):599–610. https://doi.org/10.1093/geront/gnt075 PMID: 23899623
35. Lucidi F, Grano C, Barbaranelli C, Violani C. Social-cognitive determinants of physical activity atten-
dance in older adults. J Aging Phys Act. 2006;14(3):344–59. https://doi.org/10.1123/japa.14.3.344
PMID: 17090810
36. Avan BI, Berhanu D, Umar N, Wickremasinghe D, Schellenberg J. District decision-making for health
in low-income settings: a feasibility study of a data-informed platform for health in India, Nigeria and
Ethiopia. Health Policy Plan. 2016;31(Suppl 2):ii3–11. https://doi.org/10.1093/heapol/czw082 PMID:
27591204
3 7. Shumway-Cook A, Brauer S, Woollacott M. Predicting the probability for falls in community- dwelling
older adults using the timed up & go test. Physical Therapy. 2000;80(9):896–903. https://doi.
org/10.1093/ptj/80.9.896
38. Zasadzka E, Borowicz AM, Roszak M, Pawlaczyk M. Assessment of the risk of falling with the use of
timed up and go test in the elderly with lower extremity osteoarthritis. Clin Interv Aging. 2015;10:1289–
98. https://doi.org/10.2147/CIA.S86001 PMID: 26300633
39. Tomaszewski Farias S, Mungas D, Harvey DJ, Simmons A, Reed BR, Decarli C. The measurement
of everyday cognition: development and validation of a short form of the everyday cognition scales.
Alzheimers Dement. 2011;7(6):593–601. https://doi.org/10.1016/j.jalz.2011.02.007 PMID: 22055976
40. Farias ST, Weakley A, Harvey D, Chandler J, Huss O, Mungas D. The measurement of everyday
cognition (ECog): revisions and updates. Alzheimer Dis Assoc Disord. 2021;35(3):258–64. https://doi.
org/10.1097/WAD.0000000000000450 PMID: 33901047
41. Delbaere K, Close JCT, Mikolaizak AS, Sachdev PS, Brodaty H, Lord SR. The Falls Efficacy Scale
International (FES-I). A comprehensive longitudinal validation study. Age Ageing. 2010;39(2):210–6.
https://doi.org/10.1093/ageing/afp225 PMID: 20061508
42. Herdman M, Gudex C, Lloyd A, Janssen M, Kind P, Parkin D, et al. Development and preliminary test-
ing of the new ve-level version of EQ-5D (EQ-5D-5L). Qual Life Res. 2011;20(10):1727–36. https://
doi.org/10.1007/s11136-011-9903-x PMID: 21479777
43. Gareld K, Thorn JC, Noble S, Husbands S, Hollingworth W. Development of a brief, generic, modular
resource-use measure (ModRUM): piloting with patients. BMC Health Serv Res. 2023;23(1):994.
https://doi.org/10.1186/s12913-023-10011-x PMID: 37710265
44. Goodyear VA, Boardley I, Chiou S-Y, Fenton SAM, Makopoulou K, Stathi A, et al. Social media use
informing behaviours related to physical activity, diet and quality of life during COVID-19: a mixed
methods study. BMC Public Health. 2021;21(1):1333. https://doi.org/10.1186/s12889-021-11398-0
PMID: 34229651
PLOS ONE | https://doi.org/10.1371/journal.pone.0314829 March 24, 2025 14 / 14
PLOS ONE Technology-based dual-task training in older adults
45. Stathi A, Greaves CJ, Thompson JL, Withall J, Ladlow P, Taylor G, et al. Effect of a physical activity
and behaviour maintenance programme on functional mobility decline in older adults: the REACT
(Retirement in Action) randomised controlled trial. Lancet Public Health. 2022;7(4):e316–26. https://
doi.org/10.1016/S2468-2667(22)00004-4 PMID: 35325627
46. IBM SPSS Statistics for Windows. 29.0.2.0 ed. Armonk, NY: IBM Corp; 2023.
4 7. Tinetti ME, Baker DI, McAvay G, Claus EB, Garrett P, Gottschalk M, et al. A multifactorial inter-
vention to reduce the risk of falling among elderly people living in the community. N Engl J Med.
1994;331(13):821–7. https://doi.org/10.1056/NEJM199409293311301 PMID: 8078528
48. Anne Shumway-Cook MW. Translating research into clinical practice. Abstracts of the Seventh
International Symposium on Osteoporosis. April 18-22, 2007. Washington, DC, USA. Osteoporos Int.
2007;18(Suppl 2):S193–244. https://doi.org/10.1007/s00198-007-0358-4 PMID: 17384973
49. Percentage of homes and individuals with technological equipment; 2022 [cited 2024 Aug 19]. Avail-
able from: https://www.beta.ons.gov.uk/aboutus/transparencyandgovernance/freedomonformationfoi/
percentageofhomesandindividualswithtechnologicalequipment
