MOVEONPARKINSON: A MIXED METHODS STUDY FOR THE DEVELOPMENT OF AN
INNOVATIVE MOTIVATIONAL SOLUTION FOR PERSONALIZED EXERCISE TO SUPPORT PD
MANAGEMENT
Relatório de Dissertação de Mestrado de Prática Avançada de Fisioterapia em Neurologia
Orientador: Professora Doutora Carla Mendes Pereira
13 de março de 2023
ANA BEATRIZ ALVES
REBOLA
MOVEONPARKINSON: A MIXED METHODS STUDY FOR THE DEVELOPMENT OF AN
INNOVATIVE MOTIVATIONAL SOLUTION FOR PERSONALIZED EXERCISE TO SUPPORT PD
MANAGEMENT
JÚRI
Presidente: Professor Doutor Eduardo Brazete Cruz, Escola Superior de Saúde, Instituto Politécnico de Setúbal
Orientador: Professora Doutora Carla Mendes Pereira, Escola Superior de Saúde, Instituto Politécnico de Setúbal
Vogal: Professora Doutora Sofia Balula Dias,
Faculdade de Motricidade Humana, Universidade de Lisboa
13 de março de 2023
ANA BEATRIZ ALVES
REBOLA
Relatório de Investigação apresentado para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Fisioterapia em Neurologia, realizado sob a orientação científica de
Professora Doutora Carla Mendes Pereira.
[DECLARAÇÕES]
Declaro que este Relatório de Projeto de Investigação é o resultado da minha investigação/
projeto pessoal e independente. O seu conteúdo é original e todas as fontes consultadas estão devidamente mencionadas no texto, nas notas e na bibliografia.
O/A candidato/a, ____________________ Setúbal, .... de ... de ...
Declaro que este Relatório de Projeto de Investigação/ Trabalho de Projeto se encontra em condições de ser apresentada a provas públicas.
O/A orientador/a, ____________________ Setúbal, .... de ... de ...
To my parents, Olívia and Amaro; words can hardly describe their unconditional love and support. To my grandmother, Rosalina, who has guided me to believe that being provided resources to manage Parkinson’s Disease can be invaluable for PwPD and their caregivers.
Acknowledgements
I would like to express my deepest appreciation to my supervisor, Professor Carla Pereira, for sharing her knowledge and expertise, and for proving advice, support, and guidance along this journey.
This endeavour would not have been possible without the financial support provided to MoveONParkinson by the Polytechnic Institute of Setubal (IPS), to which I would like to express my gratitude. I would like to extend my sincere thanks to IPS for providing a ten-month research grant, during which I was able to work full-time on this project.
I would like to express my thankfulness to the members of the research team of the MoveONParkinson project, for their dedication and expertise on creating and improving the web platform and the mobile app that comprise the digital solution which development grounds this thesis. Within the research team, I would like to express my gratitude to the project coordinator, Professor Rui Madeira, for his guidance and efforts to coordinate a team comprising researchers from several academic backgrounds.
I would like to extend my sincere thanks to Associação Portuguesa de Doentes com Parkinson (APDPk) and Saudis health clinic, for their efforts as the recruitment places, and also for providing access to their facilities for the study procedures to be carried out.
I am also grateful to the study participants for their availability and willingness to complete the study procedures to the best of their capabilities.
Lastly, I would be remiss in not mentioning my family and friends. Their encouragement, feedback and support have been tremendous during the last 18 months, and made me feel nothing but gratefulness for every kind word and gesture.
MoveONParkinson: A mixed methods study for the development of an innovative motivational solution for personalized exercise to support PD management
Ana Beatriz Rebola1, Carla Pereira1
1Health School, Polytechnic Institute of Setubal, Setubal, Portugal Abstract
Introduction: Despite the effectiveness of physiotherapy and exercise to improve symptoms and delay disease progression, many people with Parkinson’s Disease (PwPD) do not exercise regularly. The development of the ONParkinson platform was grounded on the evidence supporting self-management technologies on PD, following the results of a survey to PwPD, their caregivers and health professionals in triad. MoveONParkinson project is focused on the platform’s exercise module, aiming to develop an innovative motivational solution for personalised exercise to promote sustained exercise adherence and PD’s more effective management.
Methods: The main stages of MoveONParkinson were based on the IDEAS framework, and the features of the platform were grounded by the Social Cognitive Theory, addressing behavioural, personal and socioenvironmental influences, along with exercise self-efficacy and self-management skills to instil behaviour change. A mixed methods convergent design, using quantitative (questionnaires and System Usability Scale) and qualitative (semi-structured and thinking aloud interviews) methods were used to evaluate the Web Platform’s usability and gather feedback and assess the acceptability of the Mobile and Web interfaces, which features were drawn on recommendations for improving the exercise module of the initial prototype.
Results: 28 individuals were included: 20 physiotherapists (mean age=34.50±10.4) and 8 PwPD (mean age=65.75±8.63; mean H&Y=2.0±0.76). Physiotherapists awarded the Web Platform a
“Good” usability score (mean SUS=79.50±12.40; 95%CI=73.70 to 85.30) and recommended modifying features to be less time consuming and adding hybrid exercise programs. The Web and Mobile interfaces were considered valuable resources to support PD management, by promoting sustained exercise adherence through personalized exercise prescription while addressing motivation and enhancing exercise self-efficacy.
Conclusions: The Web Platform’s usability scores and user’s feedback suggesting high acceptability of the digital solution make ground for evaluating its efficacy on enhancing exercise adherence trough a pilot study and subsequently its effectiveness on managing PD symptoms and improving PwPD’s quality of life.
300 words Keywords: Parkinson’s Disease; Mobile Health; Exercise Self-efficacy; Exercise Adherence;
Self-management
MoveONParkinson: estudo misto para o desenvolvimento de uma solução motivacional inovadora direcionada à prática de exercício personalizada para potenciar a gestão da DP Ana Beatriz Rebola1, Carla Pereira1
1Escola Superior de Saúde, Instituto Politécnico de Setúbal, Setúbal, Portugal Resumo
Introdução: Apesar da efetividade da fisioterapia e do exercício físico na melhoria dos sintomas e no retardar da progressão da Doença de Parkinson (DP), muitos utentes não o praticam regularmente. A plataforma ONParkinson foi desenvolvida com base na evidência que sustenta o desenvolvimento de tecnologias para a autogestão da DP, após um inquérito direcionado à tríade (utentes, cuidadores, profissionais de saúde). O projeto MoveONParkinson pretende desenvolver a componente da plataforma direcionada ao exercício como uma solução motivacional inovadora para a sua prática, promovendo uma gestão mais efetiva da DP.
Métodos: O desenvolvimento do projeto MoveONParkinson é baseado na framework IDEAS, e as funcionalidades da plataforma derivam dos construtos da Teoria da Cognição Social, aliados à autoeficácia para o exercício e estratégias de autogestão para promover a mudança comportamental. A avaliação da usabilidade da Plataforma Web, e da aceitabilidade e recolha de feedback das interfaces Web e Mobile foram efetuadas através de um estudo misto convergente, com recolha de dados quantitativa (questionários e Escala de Usabilidade do Sistema) e qualitativa (entrevistas semiestruturadas e thinking aloud).
Resultados: Foram incluídos 28 participantes; 20 fisioterapeutas (média idades=34.50±10.4) e 8 utentes com DP (média idades=65.75±8.63; H&Y=2.0±0.76). Os fisioterapeutas atribuíram um bom score de usabilidade à Plataforma Web (média SUS=79.50±12.40; 95%IC=73.70;
85.30), recomendaram modificações para maior eficiência e poder criar programas híbridos.
Ambas as interfaces foram consideradas ferramentas valiosas na gestão da DP, promovendo a adesão ao exercício pela prescrição personalizada aliada à componente motivacional pelo reforço da autoeficácia para o exercício.
Conclusão: A boa usabilidade da interface Web, aliado ao feedback dos utilizadores e elevada aceitabilidade da plataforma ONParkinson viabilizam o planeamento de um estudo piloto para avaliar a sua eficácia em aumentar a adesão ao exercício, e posteriormente a sua efetividade na gestão da sintomatologia da DP e melhoria da qualidade de vida.
299 palavras Palavras-chave: Doença de Parkinson, Mobile Health; Autoeficácia para o Exercício; Adesão ao Exercício; Autogestão
Index
Introduction ... 1
Methods ... 9
Development of the digital solution and integration of MoveONParkinson ... 11
Study aims ... 17
Study design ... 17
Ethics ... 18
Sample and recruitment ... 18
Data collection... 19
ONParkinson Web Platform ... 19
ONParkinson Mobile App ... 21
Data Analysis ... 23
Results ... 25
Usability of the Web Platform ... 27
Assessment of the Mobile App ... 29
Insights from the perspective of physiotherapists and PwPD ... 30
Integration at the interpretation level ... 39
Discussion ... 40
Conclusion ... 48
Dissemination ... 49
References ... 50
Appendixes ... 65
Appendix 1 – Literature review on PD pathophysiology and symptoms and the relevance of exercise prescription for PwPD ... 65
Appendix 2: Summary of strategies to conduct and analyse interviews identified in the literature ... 72
Appendix 3 – Email sent to the physiotherapists for recruitment purposes ... 75
Appendix 4A – Informative document for physiotherapists... 76
Appendix 4B – Informative document for PwPD and caregivers ... 78
Appendix 5A – Informed consent for physiotherapists ... 81
Appendix 5B – Informed consent for people with PD and caregivers ... 83
Appendix 6A – Questionnaire directed to physiotherapists ... 85
Appendix 6B – Questionnaire directed for people with PD ... 86
Appendix 7 – Required tasks for the evaluation of the Web Platform ... 88
Appendix 8 – Screenshots of the Web Platform ... 91
Appendix 9 – Questionnaire to gather feedback on the Mobile App ... 94
Appendix 10 – Protocol for the tests conducted regarding the Mobile App ... 100
Appendix 11 – Screenshots of the Mobile App ... 105
Appendix 12 – Codebook derived from a deductive approach ... 107
Appendix 13 - Article submitted for publication to ICT for Health, Accessibility and Wellbeing (IC-IHAW 2022), and to the Pervasive Health 2022 conference ... 110
Appendix 14 – Abstract submitted to the 2023 World Parkinson Congress ... 121
Attachments ... 123
Attachment 1 – System Usability Scale ... 123
Attachment 2 - Hoehn and Yahr Scale ... 124
List of Tables
Table 1 – Milestones of MoveONParkinson according to the IDEAS framework ... 9
Table 2 - Characteristics of the sample included in the study ... 25
Table 3 - Socio-demographic characteristics of physiotherapists displayed as mean ± SD (%) ... 25
Table 4 - Characterization of the physiotherapists concerning their habits of exercise prescription and use of software for such purpose ... 26
Table 5 - Socio-demographic characteristics of PwPD displayed as mean ± SD (%) ... 26
Table 6 – SUS scores displayed per question (mean and SD); mean scores of positive questions highlighted in green and of negative questions in red. Heatmap for individual answers. ... 29
Table 7 – Scores displayed per participant and per question (mean and SD). Heatmap representing the answers regarding the evaluation of the CA. Legend: Q (Question); P (Participant). Observation: the 2nd and 3rd answers provided by P7 were not considered for data analysis since the test conditions did not allow for the listening component to be performed. 30 Table 8 - Thematic Map derived from an inductive approach ... 31
Table 9 - Joint display for integration at the interpretation level ... 39
Table 10 – Physiotherapy interventions for freezing of gait (FOG) and gait impairments in PD (Rutz & Benninger, 2020) ... 70
Table 11 - Description of sub-themes comprising the theme Web Platform ... 107
Table 12 - Description of sub-themes comprising the theme Exercise Database ... 107
Table 13 - Description of sub-themes comprising the theme Exercises Tab ... 108
Table 14 - Description of sub-themes comprising the theme Programs Tab ... 108
Table 15 - Description of sub-themes comprising the theme Patients Tab ... 108
Table 16 - Description of sub-themes comprising the theme PD Management ... 109
Table 17 - Description of themes regarding the Mobile App ... 109
List of Figures
Figure 1 - Features of the ONParkinson digital solution (Web Platform + Mobile App), highlighted in blue, addressing the determinants of human behaviour (according to SCT)
towards initiating and maintaining a target behaviour (sustained exercise adherence) ... 13
Figure 2 - Flow of information provided by the CA for answering exercise related questions. Note: the textboxes with a white background comprise future functionalities of the CA ... 14
Figure 3 - Integration of the exercises in the ONParkinson digital solution, highlighting the contribution of MoveONParkinson ... 16
Figure 4 - SUS scores attributed by participants, framed within the classification of Grade (Lewis, 2018), Acceptable and Adjective (Bangor et al., 2009). Legend: mean score (red), range (blue), upper and lower bound of the confidence interval (green); NPS: Net Promoter Score 28 Figure 5 - Phases in the course of PD: goals and possible interventions for physiotherapy in PD (Keus et al., 2007) ... 65
Figure 6 - Schematic representation of how exercise intervention may help to break the cycle of decline for both motor and nonmotor symptoms of PD as well as the sequelae of secondary comorbidity and mortality that result from a sedentary lifestyle (van der Kolk & King, 2013). ... 66
Figure 7- General Recommendations: clinical testing and training for Early PD ... 67
Figure 8 - General Recommendations: clinical testing and training for Moderate PD ... 67
Figure 9 - General Recommendations: clinical testing and training for Advanced PD ... 67
Figure 10 – Recommended exercise prescription for adults with mild to moderate PD ... 69
Figure 11 - Recommendations for improving gait function for PD stages H&Y 1 to 3 (Ni et al., 2018) ... 70
Figure 12 - Classification of compensation strategies for gait impairment in PD (Tosserams et al., 2020) ... 71
Figure 13 - Short-term carry-over of cueing effects tested in uncued conditions, immediately after the intervention ... 69
Figure 14 - Recommended amount and content of therapy for Movement Strategy Training Group ... 71
Figure 15 - Qualitative e-Research Framework ... 74
Figure 16 - Screenshots pf the Web Platform. (a) Front page of the Web Platform; (b) Exercises Tab comprising the exercise database; (c) Edit an exercise; (d) Visualize the details of the exercise; (e) Programs Tab; (f) Add a new exercise program; (g) Visualize the details of an exercise program; (h) Patients Tab; (i) Associate an exercise program to a specific patient. . 91
Figure 17 - 5-point Likert scale handed to patients to facilitate their understanding of the answer options ... 103
Figure 18 - Required tasks according to the protocol ... 105
Figure 19 – Example of the features of the Conversational Agent ... 106
Figure 20 - Screens for biometric data reading ... 106
List of Abbreviations
▪ 1-RM – 1-Repetition Maximum
▪ ADLs – Activities of Daily Living
▪ APDPk – Associação Portuguesa de Doentes com Parkinson
▪ BCT – Behaviour Change Technique
▪ BCTTv1 – Behaviour Change Technique Taxonomy version 1
▪ CA – Conversational Agent
▪ CNS – Central Nervous System
▪ FAQ’s – Frequently Asked Questions
▪ HR – Heart Rate
▪ HRR – Heart Rate Reserve
▪ IBM – Information – Knowledge – Behavioural skills
▪ IPS – Polytechnic Institute of Setubal
▪ mHealth – Mobile Health
▪ MRC – Medical Research Council
▪ PD – Parkinson’s Disease
▪ PwPD – People with Parkinson’s Disease
▪ PDQ-29 – Parkinson’s Disease Questionnaire–39
▪ QoL – Quality of Life
▪ RCT – Randomized Controlled Trial
▪ RPE – Rate of Perceived Exertion
▪ SCT – Social Cognitive Theory
▪ WHO – World Health Organization
▪ UPDRS–MDS – Unified Parkinson’s Disease Rating Scale – Movement Disorder Society
Introduction
Parkinson’s Disease (PD) is the most common movement disorder and the second most common degenerative disease of the central nervous system (CNS) (Balestrino & Schapira, 2020; Simon et al., 2020). At disease onset, symptoms are often unilateral or markedly asymmetrical, becoming more pronounced with disease progression (Balestrino & Schapira, 2020; Hayes, 2019; Reich & Savitt, 2019). The cardinal motor signs of PD are rest tremor, slowness of movement, rigidity, and postural instability. Non-motor symptoms are classified into neuropsychiatric, sensory, sleep, and autonomic. These can precede motor symptoms (prodromal PD) or develop over the course of the disease (Reich & Savitt, 2019).
PD incidence ranges from 5 to 35/100,000 new cases yearly, increasing 5 to 10-fold from the sixth to the ninth decades of life. Prevalence increases with age, and mortality begins to increase after the first decade following the diagnosis (Simon et al., 2020). Within the Portuguese community-dwelling population aged ≥50 years, PD prevalence is 0.24%, with an estimated total number of cases of 180/100,000 inhabitants (Ferreira et al., 2017). As the global population ages, PD prevalence will increase, doubling in the next two decades. Therefore, the societal and economic burden of PD will escalate, unless more effective treatments, cures or means of prevention are identified (Simon et al., 2020).
Since no treatment is curative and PD remains relentless in its progression toward substantial disability, the role of effective physiotherapy has grown. Both physiotherapy and exercise interventions increase the efficacy of pharmacological treatment and delay disease progression in people with PD (PwPD) (Ellis et al., 2021; Feng et al., 2020a). Exercise training among PwPD improves motor (balance, gait, risk of falls and physical function) and nonmotor symptoms (cognitive function), and quality of life (QoL)1 (Feng et al., 2020), with emerging evidence linking high intensity exercise with a potential disease-modifying effect (Harpham et al., 2023). The most recent exercise guidelines for PD are supported by high quality evidence and a strong recommendation for PwPD to engage in aerobic exercise, resistance, and balance training, as well as gait and task specific training (Osborne et al., 2022). Exercise guidelines for
1 QoL is the perception of an individual of their position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standards and concerns (WHOQOL Group, 1995)
PD suggest engaging in aerobic exercise 3 to 5 times per week, progressing from 20 minutes up to 60 minutes per session, with a moderate intensity (13 out of 20 in Rate of Perceived Exertion (RPE) scale) or between 60% and 80% of peak Heart Rate (HRpeak), corresponding to 40% to 60% of Heart Rate Reserve (HRR). As to resistance exercise, evidence suggests frequency of 2 to 3 times per week, including 8 to 10 exercises per set targeting major muscle groups, with exercise bouts ranging from 1 to 3 sets of 8 to 12 repetitions, between 40% to 50% of 1- Repetition Maximum (1-RM) up to 60% to 80% 1-RM (Kim et al., 2019). Additionally, exercise guidelines were recently categorized according to disease severity (early, moderate, advanced) (Martignon et al., 2021), and recommendations for balance and gait training, as well as specific cueing strategies for PD were highlighted (Ellis et al., 2021), thus allowing greater specificity in exercise prescription.
Physical activity is characterized as any bodily movement produced by skeletal muscles resulting in energy expenditure including unstructured or incidental movement, whereas exercise is a subcategory of physical activity that is planned, structured, repetitive and purposeful with the aim to improve or maintain one or more components of physical fitness (Caspersen et al., 1985; World Health Organization, 2020). Guidelines recommend engaging in at least 150–300 minutes of moderate-intensity aerobic physical activity, at least 75–150 minutes of vigorous-intensity aerobic physical activity, or an equivalent combination of moderate and vigorous intensity throughout the week for substantial health benefits (World Health Organization, 2020).
However, despite the need for continuous engagement in exercise to sustain health benefits that support PD management (Domingos et al., 2022; Ellis et al., 2021), and achieving optimal levels of physical activity for further health benefits, many PwPD do not embrace such behaviour (Landers & Ellis, 2020). The literature suggests that only 30% to 52% of PwPD achieve the recommended physical activity levels. (Ahern et al., 2022; Hulbert & Goodwin, 2020), and the number of daily steps declines by 12% over 1 year on PwPD (Ellis et al., 2021).
The diminished engagement in exercise and physical activity elicits a vicious cycle of inactivity, resulting in deconditioning, which leads to reductions in muscle strength, flexibility, balance, aerobic fitness, and an increased risk of falls (Jones et al., 2021). This is heightened by the
increasing loss of dopamine and impairment of neurotransmitter systems related to experiencing pleasure and motivation. Therefore, non-adherence can lead to further decline since exercise enhances dopamine synthesis (Stevens et al., 2020). Thus, considering the expected increased prevalence and disease burden of PD, as well as the growing body of evidence supporting the role of exercise in PD management, the need to address the lower levels of physical activity and exercise, and ultimately promoting sustained exercise adherence on PwPD has been identified in the literature (Ellis et al., 2021; Hulbert & Goodwin, 2020; Osborne et al., 2022), where adherence is the extent to which a behaviour of an individual corresponds with agreed recommendations from a healthcare provider (Room et al., 2017).
Addressing the low levels of sustained exercise adherence has been recognised as a priority towards meeting the needs of patients with chronic neurological diseases. Resolving this issue can encompass the adoption of a population health approach, personalised care management, and empowerment of the triad (health professionals, patients, and caregivers), which are recognized strategies to achieve the Quadruple Aim for healthcare systems, a proposed model for integrated and patient-centred care in PD, aiming to enhance patient experience, reduce costs, improve population’s health and the work-life balance of clinicians.
(Bloem et al., 2020; Tenison et al., 2020).
As in other chronic health conditions, self-management is considered an important factor for improving QoL and managing symptoms in PD (Lim et al., 2020), and consists of a dynamic, interactive, and daily process which individuals engage in to manage their chronic illness (Shah et al., 2022). Programs that embed self-management support are recommended within rehabilitation (Kessler & Liddy, 2017), contributing to informed and activated individuals and improved outcomes (Lim et al., 2020), such as slowing disease progression, reducing complications, and lowering costs, thus helping PwPD maintaining independence and optimising QoL (Armstrong et al., 2021).
When addressing self-management, supported behaviour change must be provided to sustain new health behaviours, as without it transition from health care provision to true self- management is unlikely (Milne-Ives et al., 2022). Social cognitive theory (SCT) is one of the most widely used models to explain and improve self-management in patients with chronic
illnesses and has been applied to both initiation and achievement of personal behavioural changes and maintenance of the change (Lim et al., 2020). SCT explains individual behaviour in terms of a triadic and dynamic model in which behaviour, personal cognitive factors, and socioenvironmental influences all interact, subsequently determining each individual behaviour (Bandura, 2004; Bandura & Erlbaum, 2001). Self-efficacy and social support are core concepts of this model and have been shown to affect self-management in patients with chronic illness (Lim et al., 2020). The latest refers to the perception of encouragement and support of an individual from their social network and is important for the maintenance of desired personal change (Bandura, 2004). Self-efficacy is the self-perceived ability of the individual to perform a behaviour that leads to an outcome and is hypothesised to be directly related to their subsequent likelihood of success (Bandura & Erlbaum, 2001).
Framing exercise adherence as the target behaviour, self-efficacy reflects the belief or confidence of an individual that they can successfully engage in exercise (Bandura, 1977). Thus, exercise self-efficacy predicts the type of exercise an individual partakes in, their effort level, and their sustained adherence when facing barriers to participation (McAuley & Blissmer, 2000). Self-efficacy has both direct and indirect pathways with health behaviours. The indirect pathway includes physical, social, and self-evaluative outcome expectations, socio-structural factors (barriers and facilitators), and goal setting as intermediate variables between self- efficacy and health behaviour (Bandura, 1977; Bandura & Erlbaum, 2001; Ellis & Motl, 2013).
The literature suggests that poor outcome expectations and low self-efficacy are stronger predictors of exercise adherence than disease severity and its inherent difficulties for engaging in exercise (Ahern et al., 2022). Thus, addressing these predictors by embedding exercise as part of a self-management approach, combined with behaviour change interventions, could empower PwPD, enhance exercise self-efficacy, and subsequently instil behaviour change towards sustained exercise adherence (Jones et al., 2021). Behaviour change interventions can be defined as coordinated sets of activities designed to change specified behaviour patterns and are used to promote uptake and optimal use of effective clinical services, and to promote healthy lifestyles (Michie et al., 2011). These interventions comprise an interplay of several Behaviour Change Techniques (BCTs), which are observable and replicable components designed to change behaviour (Michie et al., 2013). A hierarchically ordered taxonomy of 93 BCTs is categorized
into 16 groups comprising the Behaviour Change Technique Taxonomy version 1 (BCTTv1), which is the most established method to classify BCTs (Michie et al., 2013).
The role of digital interventions on promoting self-management and health-related behaviour change has grown over the years (Lee et al., 2022; Park et al., 2022), and has been further investigated since the beginning of the COVID-19 pandemic (Domingos et al., 2022;
Yogev-Seligmann & Kafri, 2021). Digital Behaviour Change Interventions are a coordinated sets of activities or products designed to change specified behavioural patterns (e.g., physical activity) of individuals through digital technology, such as mobile applications, wearable technology (e.g., activity trackers), or websites (Michie et al., 2017). Social cognitive theory has been considered well suited to ground the development of mHealth2 interventions, considering its tenets of self-monitoring, self-evaluation, and modification of current behaviour, tasks that mHealth apps have the capacity to assist the user with (Voth et al., 2016). There is evidence on the effectiveness of digital interventions based on the SCT for self-management of several chronic conditions and health domains, including exercise and physical activity. Research supports the use of SCT in increasing physical activity in adults with cardiovascular disease (Walsh et al., 2019), post cardiac rehabilitation (Park et al., 2021), in chronic kidney disease (Lightfoot et al., 2022) and in youths with multiple sclerosis (Stephens et al., 2022).
Additionally, a systematic review has found SCT as the predominant theory applied in stroke self-management interventions, while the most frequent BCT categories were goals and planning (Lau et al., 2022). A randomized experimental pilot study with 56 participants assessed the effectiveness of a mHealth app (application) grounded on SCT constructs and demonstrated greater engagement in exercise and more frequent self-monitoring in the intervention group (28 participants), while perceived self-management of exercise behaviour was unaffected. The successful integration of SCT in a mHealth app supports future research to feasibly integrate theoretical constructs in exercise apps (Voth et al., 2016). Taken together, this evidence led to choosing the SCT to inform the design of the exercise module of the digital solution.
2 Mobile health (mHealth): a public health practice supported by using wearable or mobile devices, such as smartphones and smartwatches, respectively, and the systems incorporated in these devices (namely mobile applications), that provide objective measures (Linares-del Rey et al., 2019; Espay et al., 2019).
Previous studies have assessed interventions involving mHealth apps aimed at promoting sustained exercise adherence in PwPD. A 12-month pilot study with 51 participants comparing mHealth-supported exercise with exercise alone has found the addition of the app to provide additional benefits to the more sedentary participants. However, the mHealth approach was not grounded on behavioural theory, despite containing key elements shown to be effective in facilitating behavioural change among healthy older adults and those with other chronic conditions; those included remote monitoring, more accessible communication, and more frequent program adaptation by a physiotherapist (Ellis et al., 2019). A pilot study aimed to assess feasibility, safety, and signal of efficacy of the 9zest app, which includes behaviour change techniques, including prompts/cues, goal setting, graded tasks, and performance feedback. This app uses self-report questions and app-guided performance tests to assess baseline status and progress the exercise program. Using a prospective, single-cohort design with 21 PwPD, results of this study suggest the usage of the app to be safe and feasible and provides preliminary efficacy data with an 8-week home-based exercise program (Landers &
Ellis, 2020). A prospective, open-label, single-arm pilot study aimed to evaluate the effects of home-based exercise management with a customized mobile app. 28 participants reported improved exercise adherence, physical activity levels, depression management, and QoL after a 12-week intervention period. This intervention was not underpinned by behaviour change theory. Instead, it was grounded on aspects such as motivation, accessibility, and compliance and facilitators and barriers for exercise adherence. Thus, its features comprised alarm notifications, professional supervision, collaborative goal setting, and intermittent monitoring (Kim et al., 2021). A randomized controlled trial aimed to evaluate the effects of a mHealth intervention for self-management on self-efficacy, motor and non-motor symptoms, self- management, and QoL in PwPD. Intervention design was grounded of the Information- Motivation-Behavioural skills model, since it has proven to be effective in studies of patients with chronic diseases requiring complex and extensive self-management. Following a 16-week period, 20 participants on the intervention group have reported significant improvements only on self-efficacy and non-motor symptoms (Park et al., 2022). The Park-in-Shape study aimed at evaluating the effectiveness of home-based aerobic exercise on relieving motor symptoms in PwPD (H&Y ≤ 2). 130 PwPD were randomly assigned to the intervention (aerobic exercise) or
control group (active stretching), and completed a 30 to 45-minute training, 3 times per week for 6 months. Exercise training was supported by gamification, remote supervision, and a motivational app (which included training tips and instructions, support from loved ones via messages, and progress monitoring) (van der Kolk et al., 2015). However, the added value of this approach over simple home-based exercise and the relative influence of the individual components was not evaluated. Nevertheless, PwPD completed 75% and 83% of the training sessions for the intervention and the control group and drop-out rate was 15.4% for each group (van der Kolk et al., 2019). These results were comparable to the pilot study that preceded this RCT (92% adherence and 5.4% drop-out rate). Both results were better than findings in previous home-based exercise trials in PD (drop-out rates of 10%–25%, exercise adherence of 70%–
87%) (van der Kolk et al., 2018). Furthermore, a systematic review conducted between 2011 and 2016 has found 69 Mobile Apps specifically designed for PD, targeting PwPD, health professionals, or both. 23 of those apps were informative, 29 aimed for assessment, 13 targeted treatment and 4 integrated assessment and treatment. However, scientific evidence of their usefulness was scarce and of poor quality (Linares-del Rey et al., 2019). As such, there is a need to engage in quality research for the development and evaluation of mHealth solutions, to provide useful and reliable tools for PwPD and health professionals. Furthermore, developing self-management interventions through mobile apps must incorporate health promotion behaviours, symptom monitoring, and behaviour change in PwPD (Lee et al., 2022).
Considering the evidence supporting the role of self-management technologies on PD and the needs identified in the literature, a survey was undertaken in the Portuguese Association of Parkinson’s Disease, literally Associação Portuguesa de Doentes com Parkinson (APDPk), to PwPD, their caregivers and health professionals in triad, who have highlighted the relevance of developing a Mobile App to support remote health assistance, helping health professionals search for reliable data to support clinical decisions, and for patients to find answers about PD, writing notes, having medication and exercise alerts and communicating with health professionals. Based on the study regarding the needs of the triad (Pereira et al., 2015) and the available literature, the first prototype of the mHealth app was designed, and the usability tests suggested high acceptance from potential end-users (Madeira et al., 2018). The ONParkinson mHealth solution comprises a Mobile and Web interface. The Mobile App is the main interface,
where each user has their own profile and exercise programs assigned by their physiotherapists.
Alongside its role on enhancing exercise adherence, it is intended to provide patients and caregivers self-management skills to empower them to find strategies in a more informed and collaborative way, enabling access to reliable information on PD and facilitating communication with health professionals responsible for their care. The Web Platform was designed to optimize therapy outside the clinical context, providing remote support from physiotherapists, as a complement to the Mobile App access. The features of the Web interface are directed to exercise prescription, including adding new exercises and programs, monitoring the performance of PwPD and providing feedback. (Macedo et al., 2018; Madeira et al., 2018).
Taking the existing prototype of the broader ONParkinson platform as a starting point, the MoveONParkinson project is focused on the exercise module of the platform, thus aiming to develop an innovative and motivational solution for personalised exercise, with the intent of promoting sustained exercise adherence and subsequently a more effective management of PD by the triad. A secondary aim includes integrating a Conversational Agent (CA)3 into the Mobile App, with the intent of answering exercise related questions and further contributing to the motivational component of the solution by providing exercise reminders and motivational messages. These aims will be attained by ensuring the features of the digital solution, mainly the Mobile App, are framed within the main constructs of SCT, thus taking into consideration the interplay between behaviour, personal cognitive factors, and socioenvironmental influences, while addressing exercise self-efficacy and self-management skills to achieve the initiation and maintenance of the target behaviour (sustained exercise adherence).
This thesis is subdivided into seven chapters. Firstly, the theme was introduced by conducting a review of the literature, thus outlining its relevance as a research topic. Related studies were analysed to provide a critical appraisal of the evidence and the aim of this study was stated. The following chapter describes the methods for the development of the digital solution, comprising the integration of MoveONParkinson. Then, the specific aims for the evaluation of the digital solution were stated, and the study design, ethical matters and
3 Conversational agents (CAs), also known as Chatbots, are computer systems that communicate with users through natural language user interfaces involving images, text, and voice (Sawad et al., 2022).
procedures of data collection and analysis were described. The Results chapter elaborates on the analysis and integration of the quantitative and qualitative results obtained from the evaluation of the digital solution. Afterwards, the results were analysed and compared to the findings reported in the literature regarding the research topic and the study limitations were presented.
Furthermore, the main conclusions derived from this study regarding implications for theory and practise were drawn, and perspectives for future research were described. Ultimately, the dissemination plan for this study was presented.
Methods
The research methodology was implemented according to the recommendations for the development of interventions to improve health and healthcare (O’Cathain et al., 2019).
MoveONParkinson aims to develop the exercise module of the ONParkinson platform.
As a digital intervention, its main developmental stages are based on the IDEAS framework, which provides guidance in the development of effective digital health behaviour change interventions (Fedele et al., 2019; Hartson et al., 2022). It comprises 10 phases, grouped into 4 overarching stages: Integrate, Design, Assess, and Share (IDEAS) (Mummah et al., 2016). The main developments of the project are described according to the IDEAS framework on Table 1, and the contribution of this thesis towards its aims is outlined in orange.
Table 1 – Milestones of MoveONParkinson according to the IDEAS framework Ideate
[1]
Empathize
Qualitative insights were gathered from users through in-depth interviews, with research questions inquiring on current health behaviours, technology usage, needs of the users, motivations, successes, and challenges in behaviour change.
[2]
Specify
Broad behavioural goals were translated into a specific target behaviour, sustained exercise adherence. Regarding the target behaviour, actionability, health impact and acceptability were considered.
[3]
Ground
Intervention design was grounded in behavioural theory. Social Cognitive Theory was the behaviour change model applied to act on the target behaviour, and behavioural change strategies were identified.
This framework was further complemented by grounding MoveONParkinson on a person-based approach, an iterative process of collecting data to understand the views, context, and experiences of the users, and using it to design, adapt and optimise the intervention, ensuring
[4]
Ideate
Considering the aim of MoveONParkinson to develop the exercise module for the ONParkinson platform, a large number of ideas were generated through brainstorming strategies for translating theory and user insights into features.
Design
[5]
Prototype
Rough prototypes of the Mobile App and the Web Platform were developed iteratively, in the form of mock-ups and clickable prototypes. These prototypes were based on the insights of the users, the literature guiding the development of digital interventions and features of the broader ONParkinson platform, since its initial assessment has demonstrated high acceptance (Madeira et al., 2018).
Within the research team, prototypes were shared, discussed, and improved, and the most promising ones were selected.
[6]
Gather
Encompassing the iterative design process, user feedback on prototypes of the Mobile App and the Web Platform was gathered through interviews and questionnaires, to assess interest in overall product, eagerness to use regularly, and potential impediments to regular use. Recommendations for improvement and new insights informed product development with the specific focus on the exercise module.
[7]
Build
A fully functional minimum viable product will comprise the most essential features. As the solution is developed, decisions will be made iteratively regarding user experience, visual design, and content. App analytics were incorporated to collect data on usage patterns.
Assess [8]
Pilot
Pilot testing will consist in a small-scale evaluation to refine the study protocol and evaluate a signal of efficacy of the intervention on behaviour change.
[9]
Evaluate
The effectiveness of the intervention in improving target health behaviour will be evaluated along with its influence on QoL and symptomatology of PD.
Share
[10]
Share
Findings have been submitted for publication to advance science and practise, and the intervention will be disseminated to populations that could benefit from it. Once publicly released, usage data will continue to be analysed, and the final product will be refined to increase its usability.
it is meaningful, feasible and engaging (Morrison et al., 2018). It adapts methods from user- centred design, which within mHealth-mediated care, represents a systematic process that ensures applications remain patient-focused (Mccurdie et al., 2012).
Furthermore, a theoretical and evidence-informed approach complemented this methodology, by grounding intervention design on published research and behavioural change theory (O’Cathain et al., 2019). The framework provided by the UK Medical Research Council (MRC) divides complex intervention research into four phases: development, feasibility, evaluation, and implementation, where assessing feasibility and acceptability is a standard requirement before progressing to next stage of evaluation (Skivington et al., 2021).
Acceptability is defined as the affective attitudes of an individual toward a new digital health intervention, usage intentions, actual usage, and satisfaction after having engaged with it (Perski
& Short, 2021; Sekhon et al., 2017). It can be improved within and between phases by undergoing several iterative cycles based on feedback from end-users, restarting the cycle until the iterations produce few suggestions for change (O’Cathain et al., 2019), aiming to improve the usability of the intervention (Skivington et al., 2021). Usability represents the capacity to provide users the conditions to perform tasks safely, effectively, and efficiently while enjoying the experience (Imbesi & Scataglini, 2021). Moreover, both concepts of acceptability and usability relate to the Technology Acceptance Model (Brown et al., 2013; Perski & Short, 2021), which theorizes that perceived ease of use and perceived usefulness of a given technology positively influence usage intentions, which in turn drive the adoption of new technologies (Davis et al., 1989). Perceived usefulness is the prospective of the user that using the system will increase their performance, while perceived ease of use refers to the degree to which the user expects the system to be free of effort (Davis et al., 1989).
Development of the digital solution and integration of MoveONParkinson
Using established psychological and behavioural theories in the design, implementation, and evaluation of interventions has been suggested to enhance behaviour change (Giacobbi, 2016). The progressive nature of PD and its non-motor symptoms also present as further physical and psychosocial challenges. Hence, supported behaviour change models need to be condition specific if the target behaviour is to be instigated and maintained at a clinically
meaningful level (Hulbert & Goodwin, 2020). According to the Social Cognitive Theory, the theoretical framework for behaviour change that underpins the development of the MoveONParkinson digital solution, the first step to promote the engagement of users consists of identifying predictors of human behaviour, comprising cognitive, behavioural, and environmental factors (Bandura, 2004; Bandura & Erlbaum, 2001; Lim et al., 2020). In this paradigm, the target behaviour is sustained exercise adherence, accomplished by increasing exercise self-efficacy and self-management skills through the functionalities of the mobile app, outlined in Figure 1.
Behavioural factors reflect the need to promote goal setting, practical skills acquisition and self-efficacy, since exercise self-efficacy is a not only a significant determinant of initial exercise participation and sustained adherence but also a catalyst for maintaining exercise motivation (Stevens et al., 2020). Reinforcing it can be achieved by mastering experiences, facilitated by personalizing exercise prescription, thus promoting a successful performance, and by answering questions and doubts related to the exercise programs. This feature is provided by the CA embedded in the app; its knowledge database for exercise related questions is further described on Figure 2. Environmental factors include optimizing available resources, by identifying barriers and facilitators to exercise practise. Barriers such as non-motor symptoms (anxiety, depression, fatigue, and apathy) and personal beliefs (low self-efficacy, low outcome expectation) can be addressed through the motivational component of the app embedded in the CA. These features endorse persuasion, encouragement, and emotional reinforcement (Bandura, 1977; Bandura & Erlbaum, 2001), by including notifications and reminders for exercise practise, and motivational messages providing positive reinforcement during and after task completion.
The content of these messages will depend on the motivational status identified by the CA through information such as program attendance and completion. Environmental barriers (poor accessibility, financial burden, cultural challenges, awareness of moving in a crowded environment, and discomfort of seeing advancing symptoms of peers) (Schootemeijer et al., 2020; Zaman et al., 2021), will be addressed by providing free access to the app, which will include exercise programs that can be performed at home using everyday items as equipment.
Figure 1 - Features of the ONParkinson digital solution (Web Platform + Mobile App), highlighted in blue, addressing the determinants of human behaviour (according to SCT) towards initiating and maintaining a target behaviour (sustained exercise adherence)
Facilitators for exercise engagement that can be enhanced through the app include slowing disease progression, improving fitness, mood, and ease of access, social interaction, as well social support from physiotherapists, caregivers and family (Zaman et al., 2021). Social support is defined by the perception of encouragement and support of an individual from their social network, (Bandura, 2004; Lim et al., 2020) and is a significant contributor to exercise
behaviour in inactive individuals, as it enhances motivation and exercise self-efficacy (Domingos et al., 2022). Considering its role in the maintenance of desired personal change, social support is addressed by exercising along with peers and including the caregiver in the exercise programs. Additionally, visualising exercise photographs and videos in the Mobile App while exercising may further promote adherence by learning from others through the demonstration of the exercises. The development and evaluation of the features addressing cognitive factors (knowledge of PD, beliefs, and outcome expectations) is outside the scope of this thesis. Nevertheless, this dimension is embedded in the Mobile App through a section of Frequently Asked Questions (FAQs) and by enabling communication with physiotherapists (Madeira et al., 2018). The interplay between behavioural, environmental and cognitive factors as they are integrated in the ONParkinson digital solution is expected to empower patients, motivating them to adopt a behaviour (sustained exercise adherence) they can perform with efficacy that will, in their perspective, produce a valuable outcome (enhance PD management).
Figure 2 - Flow of information provided by the CA for answering exercise related questions.
Note: the textboxes with a white background comprise future functionalities of the CA
Supporting chronic disease self-management and delivering lifestyle change interventions (eg.; physical activity) have increasingly been supported by CAs, which design incorporates elements of behaviour change. CAs appear to be acceptable to users and effective at improving patient outcomes (Martinengo et al., 2022). A recent review of underpinning theories for the development of CAs in healthcare has identified 12 out of 47 studies (26%) where behaviour change theory guided intervention design. The Transtheoretical Model combined with the SCT were the most frequent approaches. Additionally, the most common BCTs delivered by CAs included problem solving, instruction on how to perform a behaviour, prompts/cues, and habit formation (Martinengo et al., 2022).
Considering the aims of MoveONParkinson for developing the exercise module of the ONParkinson digital solution, a comprehensive literature review on physical exercise guidelines for PwPD was undertaken (Appendix 1). It has highlighted the relevance of developing exercise programs that ae 2ddress aerobic conditioning, strength, balance and Activities of Daily Living (ADLs) (Ellis & Rochester, 2018; Ellis et al., 2021; Feng et al., 2020; Mak & Wong-Yu, 2019;
Martignon et al., 2021; Osborne et al., 2022; Radder et al., 2020). The development of exercise programs started by building a comprehensive exercise database. Each exercise included a detailed description, sub-divided in starting position, commands, safety precautions and equipment. A visual demonstration was provided by recording videos of each exercise, where an individual repeated the intended movement pattern while following the corresponding description. The videos were approximately 15 to 45 seconds long, and were recorded either in a frontal, sagittal or intermediate plane of movement, to provide a better overall understanding of the exercise. The description of each exercise was audio recorded and embedded in the videos, to provide both visual and auditory sources of information. These tasks were accomplished using software for video and audio edition along with Microsoft Office Word.
Afterwards, the exercises were individually added to the database embedded in the Web Platform, through the feature “Add exercise”. The name of the exercise and its description were copied to the corresponding text fields and the training phase was chosen (warm-up, training, or cool-down). Choosing the exercise type was directly related to the phase; training comprised one of the four types of exercises previously identified as relevant, and warm-up and cool-down
comprised mobility and flexibility exercises, respectively. Lastly, the video (also containing the audio description) was uploaded. When the exercise database included the major exercise types, the exercise programs were added to the Web Platform, through the feature “Add program”.
The name of the program and a summary description (comprising its aims, estimated length, equipment, and safety advice), were added to the corresponding text fields, and the exercises were selected from the database. Then, the prescription for each exercise was individualized according to the number of series and repetitions or set time, and rest time between sets. Once this process was completed, exercise programs were assigned to PwPD by their physiotherapist, trough the feature “Assign program”, embedded in the section comprising clinical and personal information of PwPD. After selecting the desired weekly frequency or specific days, the program becomes available on the Mobile App for PwPD to access and complete. The stages of developing the exercises and adding them to the Web Platform are summarized in Figure 3.
Upon program completion, PwPD will receive summary feedback of their performance, and physiotherapists will be able to access more comprehensive feedback and adjust the exercise program based on the information previously obtained. The development of this feature is an ongoing process, and its evaluation is outside the scope of this thesis.
The assessment of the technical performance of the CA embedded in the Mobile App had previously been conducted with physiotherapists experienced in PD, to validate the domain coverage, by having a glossary for PD as a reference and comparing the percentage of correctly identified terms. Coherence response capacity was assessed by submitting a list of questions to the CA and verifying the percentage of relevant and coherent answers. Dialog management capacity was assessed by building and running several conversation scenarios and identifying the percentage of correct answers and non-understandable questions. A comprehensive description of the evaluation plan for the CA was described by (Macedo et al., 2019).
Figure 3 - Integration of the exercises in the ONParkinson digital solution, highlighting the contribution of MoveONParkinson
Study aims
The aims of this thesis are grounded on the developmental stages of MoveONParkinson for the exercise module of the ONParkinson platform. The aims regarding the Mobile App (including the embedded CA) and the Web Platform are: to assess the acceptability of the digital solution and to gather feedback on interest of the users, their eagerness to use regularly, perceived barriers to regular use, and recommendations for future implementation. Additionally, it aims to assess the usability of the Web Platform.
Study design
Considering the Design phase of the IDEAS framework, the iterative cycles of developing the intervention involve using quantitative and qualitative research methods to assess the acceptability, feasibility, desirability and potential unintended harms of the intervention (O’Cathain et al., 2019).
Thus, a mixed methods convergent approach was applied to provide complementarity, through a more comprehensive and complete feedback on the Web and Mobile interfaces comprising the digital solution. Qualitative data (semi-structured interviews, analysed using a hybrid approach for thematic analysis) and quantitative data (questionnaires and System Usability Scale, analysed using descriptive statistics and heatmaps) were collected and analysed during a similar timeframe (Creswell & Creswell, 2018). Integration is defined as the explicit interrelating of the quantitative and qualitative component in a mixed methods study (Clark &
Ivankova, 2016) and is a core component of mixed methods research (Hong et al., 2018).
Integration was taken into consideration at the design, methods and interpretation levels of research. Within the convergent design, an interactive approach was used, where data collection and analysis iteratively drove changes in the data collection procedures. Integration through methods was accomplished through merging, where the two databases were brought together for analysis and comparison, after analysing quantitative and qualitative data. At the interpretation level, integration occurred through narrative, using a weaving approach, where qualitative and quantitative findings were written together on a theme-by-theme basis (Fetters et al., 2013). Integration was complemented through a joint display, which illustrates the process
of discovering linkages between the qualitative and quantitative constructs, organizing, and reorganizing the findings into a matrix to optimize the presentation of the data (Fetters & Tajima, 2022; McCrudden et al., 2021).
Ethics
The study protocol grounding the stages of the MoveONParkinson project that comprise this thesis was submitted and approved by the Specialized Committee on Ethics for Research of the Health School of Polytechnic Institute of Setubal, literally Comissão Especializada de Ética para a Investigação – Escola Superior de Saúde / Instituto Politécnico de Seúbal (CEEI, ESS/IPS), (nº 76/CC/2021). All participants who met the inclusion criteria were informed of the purpose, risks, confidentiality, and benefits before they voluntarily decided to participate in this study. The ethical elements of the study were made clear to participants as following:
confidentiality of information, written informed consent to participate in the study procedures, and the right to withdraw at any time during the study without any negative consequences. All the data collection procedures were conducted according to the guidelines issued by Direção Geral de Saúde regarding the COVID-19 pandemic, assuring safety and protection of the participants.
Sample and recruitment
Recruitment occurred between June and October 2022. A purposive sample was used to maximise the possibility of obtaining accurate and detailed feedback. Physiotherapists attending the Master’s course of Advanced Neurological Physiotherapy at the Polytechnic Institute of Setubal and lecturers were invited to participate. PwPD were recruited in APDPk, in Lisbon, where they attended physiotherapy and Pilates classes.
Physiotherapists were included if they had current or past experience with patients diagnosed with a neurological condition. PwPD were included if they were aged ≥18 years, with a clinical diagnosis of PD (Park et al., 2022; Seregni et al., 2021), with the ability to understand the study aim and to compromise with the required tasks, as well as the capacity to fill out a written consent form. Participants were excluded if: they had severe vision or hearing impairments (Kim et al., 2021; Landers & Ellis, 2020; Park et al., 2022; Siegert et al., 2019); a
diagnosis of severe neuropsychiatric symptoms, such as major depression (Siegert et al., 2019);
severe cognitive or physical impairment (Hoehn and Yahr stage 5) interfering with participation in the study procedures (Kim et al., 2021).
The invitation to enrol in the study was sent to physiotherapists by email (Appendix 3), whereas PwPD were invited by the physiotherapist responsible for their care, who had previously been informed of the study procedures. Then, an individual explanation of the study procedures was provided to the potential participants who were eligible and have demonstrated interest to enrol. Physiotherapists were informed by email, and the informative document (Appendix 4A) and consent form (Appendix 5A) were sent by email. For PwPD the explanation took place at the recruitment facilities, and the informative document (Appendix 4B), and consent form (Appendix 5B) were handed in paper.
Data collection
Participants were characterized through an online questionnaire. The usability of the Web Platform was evaluated by the System Usability Scale (SUS). Feedback of user experience and acceptability of the exercise module of the ONParkinson platform were assessed by an online questionnaire (regarding the Mobile App) and semi-structured and thinking aloud interviews. The topics of questioning for thinking aloud interviews were continuously informed by the contents of previous interviews and usability results, which were briefly analysed beforehand to ensure integration at the data collection stage. The researcher has undergone skills training for conducting interviews according to the recommendations provided in the literature (Carter et al., 2021; DiCicco-Bloom & Crabtree, 2006; Doody & Noonan, 2013; McGrath et al., 2019; Roberts et al., 2021), which are further described on Appendix 2.
ONParkinson Web Platform
Physiotherapists were asked to provide socio-demographic data through an online questionnaire (Appendix 6A), and details of their clinical practice, such as their experience with PwPD and the use of technology and exercise prescription software in their practise. It consisted of six closed questions, two checkboxes, and three questions with 5-point Likert scales. The
questionnaire was sent by email, and participants were asked to submit the answers before initiating the remaining study procedures.
The Web Platform was assessed by conducting usability tests, where an end-user, works independently through scenarios representing usage of the platform, while thinking aloud. With physiotherapists as the potential end-users, their behaviours, comments, and issues were listed, helping to uncover functional and interface design flaws (Mccurdie et al., 2012). Additionally, participants were asked to verbalize their thoughts during the test, and to report everything going through their minds, not attempting to interpret or analyse it, using the thinking aloud method (Güss, 2018; Lundgrén-Laine & Salanterä, 2010). The usability tests were conducted online, through Zoom, lasting between 30 and 60 minutes, and were audio and video recorded.
Participants were introduced to the key features of the interface through a video and audio tutorial, after which they were allowed 5 minutes to explore the platform without any specific instructions. Then, they were asked to create a new exercise, exploring its details, and editing its contents. Afterwards, they were asked to create a new exercise plan and to attribute the same plan to one of the patient profiles added to the platform. The final task consisted in reviewing the exercise and program records of PwPD inserted in the platform. A comprehensive description of this tasks is available on Appendix 7, They are also visually represented with screenshots of the Web Platform on Appendix 8.
These tests were followed by a semi-structured interview, where physiotherapists were asked questions regarding the functionalities of the platform, the suitability of the library of exercises for PwPD to exercise at home, unsupervised by their physiotherapist, advantages and disadvantages of using the platform to support their clinical practise and recommendations for improvement. They were also asked questions regarding the impact of the exercises on the daily lives of PwPD, whether the exercises uploaded to the platform contribute to their autonomy, if the exercises are specific for PD, and about the potential of PwPD for sustained adherence to these exercises. This method not only provides a framework, but also gives the interviewer the flexibility to probe on certain issues with more open and follow-up questions (Belotto, 2018).
The interviews were audio and video recorded, and the comprehensive interview guide is available on Appendix 7.
The usability of the Web Platform was assessed by the Portuguese version of the System Usability Scale (SUS) (Attachment 1). SUS is one of the usability evaluation questionnaires most widely used. It comprises 10 statements scored on a 5-point Likert scale of strength of agreement (Bangor et al., 2009; Hyzy et al., 2022; Lewis, 2018). Its final score ranges from 0 to 100, where higher scores indicate better usability, with 68 points being considered the average (50th percentile) and 70 points as the acceptability threshold. A score above 80 is considered high usability and a level at which participants are likely to recommend the product to peers (Bangor et al., 2009; Hyzy et al., 2022; Lewis, 2018). The psychometric properties of the SUS have been widely studied. Estimates of reliability using coefficient alpha ranged from 0.83 to 0.97 (x̄ =0.91), indicating excellent reliability, although sample sizes varied between 18 to 9156.
Estimates of concurrent validity had significant correlations with other measures of perceived and objective usability, ranging from 0.22 to 0.96 (Lewis, 2018). The Portuguese version has construct validity as it presents high and significant correlation with other usability metrics, the Post-Study System Usability Questionnaire (r = 0.70) and a general usability question (r = 0.48).
Reliability results show less than satisfactory Intraclass Correlation Coefficient values (ICC=
0.36), but the percentage of agreement is satisfactory (76.67%) (Martins et al., 2015).
ONParkinson Mobile App
Quantitative data collection included two online questionnaires, to characterize participants (Appendix 6B) and to gather feedback and assess the acceptability on the Mobile App (Appendix 9). Both were answered through interview since it was according to the preference of every participant.
Regarding the first questionnaire, PwPD were asked to provide socio-demographic and clinical data, including disease staging according to the Hoehn and Yahr Scale (H&Y) (Attachment 2). H&Y scale is a five-point (1–5) descriptive staging scale that provides an estimate of clinical function in PwPD, combining functional deficits and objective signs. Motor impairment can be charted from unilateral (Stage 1) to bilateral (Stage 2) without balance difficulties, the presence of postural instability (Stage 3), loss of physical independence (Stage 4), and being wheelchair or bed-bound (Stage 5). In research settings, it is useful for defining inclusion/exclusion criteria at baseline. Since the modified H&Y scale with 0.5 increments
