Evaluation of the usability and acceptability of the P-STEP (Personalised Space Technology Exercise Platform) ® mobile app: Feasibility study

Evaluation of the usability and acceptability of the P-STEP (Personalised Space Technology Exercise Platform) ® mobile app: Feasibility study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Evaluation of the usability and acceptability of the P-STEP (Personalised Space Technology Exercise Platform) ® mobile app: Feasibility study Hannah Worboys, Laura J Gray, Sarah Anthony, Rachel Hobson, Tim Lucas, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6123032/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 17 Oct, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Background The P-STEP® (Personalised Space Technology Exercise Platform) app is designed to bring together tailored exercise guidance and up-to-date air quality information for patients with long term health conditions. The app allows individuals to plan outdoor exercise walking routes while minimising their exposure to air pollution. Individuals with chronic long-term conditions, particularly respiratory and cardiovascular conditions, can use the app to minimise the risk of their symptoms being worsened by pollution, while gaining the benefits of outdoor exercise. Methods This study measured the usability and acceptability of the P-STEP® app. The study was a single-arm 12-week pilot study based in Leicestershire, United Kingdom (UK). We recruited 93 participants from an existing cohort study to evaluate the app for 12 weeks. Questionnaire data were collected at three timepoints; baseline, 6 weeks and 12 weeks. The primary outcome was the System Usability Scale at 12 weeks. Secondary outcomes included the User Engagement Scale Short Form, SF-12, Recent Physical Activity Questionnaire, bespoke app-specific usability questions and feasibility outcomes. Additional data collected include participant demographic information, technology self-efficacy, and adverse events. Weekly anonymised app usage data were collected and analysed separately to complement the questionnaire data. Results 342 individuals were assessed for eligibility, of whom 182 (53%) were eligible. 93 (51%) eligible participants were enrolled and given access to the app for 12 weeks. 61 (66%) participants completed the study. At 12 weeks, the mean (SD) System Usability Score was 61.68 (22.9), Bespoke usability score was 66.82 (14.75) and User Engagement Score was 3.08 (0.79). Completion rates across all questionnaires were high. Participants accepted the format of online questionnaires, with no participants requiring help to complete and no participants withdrawing from the study for this reason. Discussion This study helps to understand the feasibility and acceptability of administering this app in the community. The results will help inform the design of a future randomised controlled trial. Ethics and dissemination This study has received ethical approval from the South West Frenchay Research Ethics (23/SW/0060) Committee. There is no need for further approval from the Health Research Authority as the study is not taking place in the NHS. The ClinicalTrials.gov ID number is NCT05830318. Earth and environmental sciences/Environmental sciences Health sciences/Health care Health sciences/Medical research Health sciences/Risk factors Health sciences/Signs and symptoms Figures Figure 1 Figure 2 Introduction As of 2021, 6.6 million in the UK live with either a cardiovascular or respiratory long term health condition( 1 ). These conditions are associated with poorer health outcomes, reduced quality of life, hospitalisations, and premature death. Effective management through medication and lifestyle changes, particularly increased physical activity, can mitigate risk of these outcomes. Regular physical activity offers many benefits to an individual, including improved physical and mental health, improved cardiovascular outcomes and an increased risk of survival. Engaging in regular physical activity can also enhance cardiovascular fitness, which helps prevent the progression of long-term conditions (LTCs). Physical activity guidelines for the general population recommend at least 150 minutes of moderate-intensity exercise per week( 2 ), and often similar recommendations exist for those living with chronic conditions( 3 , 4 ). Those living with LTCs receive the same benefits from exercise as those without( 5 – 7 ), despite these guidelines, many individuals fail to meet current recommended activity levels( 8 ). One reason for reduced physical activity among individuals with LTCs could be the increased exposure to air pollution during outdoor exercise activities such as walking, cycling, or running. Air pollution can severely impact those with cardiac and respiratory diseases( 9 ), leading to exacerbated symptoms such as chest tightening or worsened coughing for those with asthma and COPD. This risk may discourage individuals from exercising, thus hindering their physical activity levels( 10 ). Mobile phone applications (apps) can be used to support behavioural change in those with LTCs, such as to aid increasing physical activity levels( 11 ). However, an important factor to those living with LTC is being able to assess the air quality in the local area prior to outdoor exercising( 12 ). The Personalised Space Technology Exercise Platform (P-STEP®) app was designed to address this gap by integrating real-time air quality data with personalised exercise guidance, allowing individuals to plan safer outdoor activities. The P-STEP® app, developed with funding from the European Space Agency, brings together tailored exercise guidance, taking into account an individual’s LTCs, while also providing up-to-date information on air quality. The app allows individuals to plan exercise routes (walking routes) in order to minimise their exposure to air pollution, by using the information to avoid higher polluted areas. The app collects data on the time individuals have spent exercising, to reassess their “weekly walking target”, which is a bespoke evidence-based algorithm designed by a team of health experts that takes into account the individuals characteristics, LTC, and previous levels of exercise. The user can access a range of features in the app, including recording their walking route, planning when/where to go walking based on a 72-hour forecast, achieve walking badges/milestones, save their favourite walking routes. For such an application to be successful in real-world settings, it must be both usable and acceptable. This feasibility study is crucial as it evaluates the practical implementation of the P-STEP® app. By assessing usability, engagement, and feasibility outcomes, this study will inform the refinement of the app and the design of a future clinical trial. Understanding the barriers and facilitators to technology-driven behaviour change will help optimize future digital health interventions, ensuring their accessibility, relevance, and long-term sustainability while also improving the health outcomes for individuals. Methods Overview This feasibility study was a single arm 12-week pilot study based in Leicestershire, United Kingdom (UK). Questionnaire data were collected at three timepoints, baseline, 6 weeks and 12 weeks. Weekly anonymised usage data from the app were also collected. The South West Frenchay Research Ethics Committee (REC ref: 23/SW/0060) approved the study, confirming that no further Health Research Authority (HRA) approval was necessary. This study has been reported according to the CONSORT 2010 checklist for pilot or feasibility trials ( Table S6 ). The SPIRIT figure is included in the supplementary information ( Figure S1 ). The protocol for this study has been published elsewhere( 13 ). Recruitment methods and procedure Participants were recruited from the EXCEED cohort study. The EXCEED study (REC ref 13/EM/0226) is a longitudinal population-based cohort study that facilitates the investigation of genetic, environmental and lifestyle-related determinants of a broad range of diseases and multiple long-term conditions( 14 ). EXCEED participants have consented to be contacted about participating in other research studies. Recruitment was in two stages, first the criteria to mee the initial EXCEED call out, whereby participants who met the first stage of the criteria (Table 1 ) were emailed by a member of the EXCEED research team informing them about the study, providing them a copy of the participant information sheet and a link to the P-STEP website. Those interested in registering for the study could fill in a registration form (via MS Forms) with questions asking the second stage of inclusion criteria, detailed below in Table 1 . The MS forms were then reviewed by a member of the P-STEP study team. The MS forms had questions regarding the second stage of criteria, then additional criteria to be enrolled on the study. Table 1 Inclusion criteria for P-STEP study First stage of inclusion criteria: • Part of the EXCEED cohort study • Adult ≥ 18 years • Lives in Leicestershire • Does not have dementia, learning disability, severe mental health disorders (other than depression or anxiety), cancer or epilepsy. • Are not receiving palliative care • Diagnosed with at least one of the following conditions; asthma, chronic obstructive pulmonary disease (COPD), interstitial lung disease (ILD), coronary heart disease (CHD), heart failure (HF), type 2 diabetes Second stage of inclusion criteria: Does: • Can walk for a minimum of 5 minutes outside • Have an Android smartphone • Have access to the internet on smartphone • Have ability to give informed consent Does not: • Have chest pain at rest • Feel unsteady when standing or walking, which has led to a fall • Are pregnant • Are a current cancer patient • Are receiving palliative care • Have access to an iOS smartphone only • Have been advised not to take part in exercise in the past 12 months • Were part of the P-STEP User engagement group and provided PPI input. Data collection methods and procedure Participants who met the inclusion criteria were invited to complete an electronic consent form via REDCap, and enrolled onto the study. Participants then filled in the baseline questionnaire for the study, once completed they were then given access to the P-STEP® app. The baseline questionnaire asked demographic questions, about current experience using technology, the Recent Physical Activity Questionnaire (RPAQ) and the SF-12 quality of life questionnaire. Each participant had access to the app for 12 weeks. Follow-up questionnaires were sent via REDCap to participants for completion at 6- and 12-weeks. The follow-up questionnaires included the System Usability Scale (SUS), bespoke usability questions, the user engagement scale short form, RPAQ, SF-12, about non-routine GP visits or unexpected hospitalisations and general usage and feedback questions about the app. Two free text box feedback questions allowed for collection of free-text data. The questionnaires were designed through a process of iteration with our Patient and Public Involvement and Engagement (PPIE) members. Questionnaire data was collected in REDCap and the quantitative data analysed in Stata. Free text responses were summarised. Outcomes System Usability Scale (SUS) The primary outcome measure for this study was the SUS at 12 weeks. The SUS is a validated and popular instrument for measuring perceived usability( 15 ). There are 10 items in total, 5 with a positive tone and 5 with a negative tone. The responses range from strongly disagree to strongly agree. The original questionnaire asks about the “system” however it is acceptable practice to replace system with a relevant term such as website, or app, therefore this study replaces the word system with app. For scoring, the negative SUS responses are reversed and the scores were then transformed onto a 0-100 scale. A SUS score of 68 and above considers the usability score to be above average and anything less below average( 15 ). Bespoke Usability Questions (P-STEP® specific) Nine additional usability questions ( Table S2 ) that relate specifically to the features of the P-STEP® app, were asked at 6 and 12 weeks. These questions were formulated with input from the PPIE group, and through a process of iteration, finalised with nine questions on a Likert scale of strongly agree to strongly disagree. User Engagement Scale Short Form (UES-SF) The User Engagement Scale - Short Form (UES-SF) contains twelve items that measure user engagement( 16 ). There are 12 items which are categorised into; focused attention, perceived usability, aesthetic appeal, and reward. Focused attention refers to feeling absorbed in the interaction and losing track of time. Perceived usability refers to the experience of the interaction and the degree of control and effort expended. Aesthetic appeal refers to the attractiveness and visual appeal of the interface. Reward is the extent to which the experience was rewarding. An overall user engagement was calculated by converting the score to a numeric value of 1–5 (strongly disagree equals 1, strongly agree equals 5) and taking the mean( 16 ). Quality of Life This study was not powered to detect statistical differences over 12 weeks. Despite this, we used the SF-12 in this study to give an indication of change and assess the feasibility of the questionnaire in this sample. The Short Form 12-Item Health Survey (SF-12) is a health-related quality of life tool that measures functional health and well-being from the participant’s perspective( 17 ). It assesses eight domains including physical functioning, physical role, pain, general health, vitality, social functioning, social role and mental health. The 8 domains are then categorised into two summary scores; physical component score (PCS) and mental component score (MCS). Scores for the PCS and MCS range from 0-100, and a higher score indicates a higher quality of life. Recent Physical Activity Questionnaire (RPAQ) The RPAQ was used and enables assessment of the daily physical activity and sedentary behaviours of adults( 18 ). It includes questions on physical leisure and sports activities (frequency and duration), and activities performed in the home (television, computer, climbing stairs, etc.) and at work (quantity and type of work, home-work journeys, etc.). The analysis takes into account the duration and frequency of each activity, and its intensity. This study was not powered to detect statistical differences over 12 weeks. Despite this, we used the RPAQ in this study to give an indication of change and assess the feasibility of the questionnaire in this sample. As well as the RPAQ, two additional questions on self-perceived walking pace were collected at 6 and 12 weeks. Feasibility outcomes Anonymous usage data were extracted weekly. These data gave information on the features that were used in the app, which were used to inform the feasibility outcomes. The data extracted are a summary of all participants - the information is anonymous and therefore cannot be linked back to participants. These outcomes assess the feasibility of using certain study design features and outcome measures which will help plan a future trial for effectiveness. One of the main feasibility outcomes is the acceptability of the questionnaires within this sample group. Statistical analysis Baseline characteristics are summarised using mean and standard deviation (SD) or median and interquartile range (IQR) for continuous variables and count and percentage/proportion for categorical. The mean and standard deviation of the SUS, usability and user engagement scores is reported at 6 and 12 weeks. A breakdown of responses to the SUS questionnaire are included both as a frequency table and bar graph. The SF-12 and RPAQ were collected at baseline, 6 and 12 weeks. An indication of changes over time are reported using a fixed effects model. Feasibility outcomes are reported as mean and standard deviations or count and percentages where appropriate. Subgroup analyses We conducted three subgroup analyses for the usability outcomes based on i) whether participants had one of the LTCs or not, ii) whether participants had experience using a fitness tracking device, and iii) removing users who enrolled but reported not using the app. Objective app usage data Walking data were exported from the app to completement the questionnaire data. Input from health professionals provided guidance on the thresholds to remove outliers. Outliers were removed under the assumptions that: Participants may have forgotten to pause and got into a moving vehicle and as a result, the distance for these walks would be high while the associated steps low. Participants may have forgotten to pause when getting back from a walk and as a result, the duration for these walks would be high while the associated distance and steps low. Non-routine GP visits and unexpected hospitalisations As the app is not an investigational medicinal product nor a medical device, no adverse effects are expected. Data on non-routine GP visits and unexpected hospitalisations, related or unrelated to the participant's chronic condition(s) were collected at 6 and 12 weeks, instead of adverse events. Any unexpected hospitalisations reported were treated as a potential serious adverse event (SAE) as per University of Leicester Sponsor SAE reporting policy, and followed up directly with participants to obtain further information. Patient and public involvement and engagement (PPIE) Members from the University Hospitals of Leicester NHS Trust Lifestyle PPIE group, and members from the Extended Cohort for E-health, Environment and DNA (EXCEED) study were involved in the design of this study. This included designing and reviewing the study documents such as the register your interest form, participant information sheet, informed consent form, baseline and follow-up questionnaires. PPIE members were also included in reviewing the participant pathway to identify ways to minimise participant burden. Results Recruitment and enrolment Recruitment to the study was open from August – October 2023. Recruitment was reviewed every two weeks by the study team and mitigation strategies were employed if the study team identified recruitment to be slower than expected. Mitigation strategies for recruitment included relaxing the inclusion criteria of a participant being diagnosed with one of the six long-term conditions. This is justified as while the app may be designed for those with cardiovascular or respiratory diseases, everyone can and would benefit from a reduction in exposure to air pollution. Another justification for this is that the primary outcome is the usability of the app and not its effectiveness in these condition groups. Logistically this mitigation strategy means the EXCEED research team would send out a second wave of invitations irrespective of long-term condition as long as all the other inclusion and exclusion criteria were met. The CONSORT flow diagram for the participants in this study is reported in Fig. 1. 342 people registered their interest in the study, of which 182 (53%) were eligible. All but 4 of the 182 were enrolled on the study, however 85 were lost at some point between enrolment and being given access to the app. Of these, 43 (51%) did not respond to emails moving them onto the next stage and 21 (25%) were non-Android users. 17 participants had to be withdrawn from the study due to a delay in getting the app verified by Google Fit. Baseline, demographics and technology self-efficacy 93 participants were given access to the app and all were included in the final analysis. The baseline demographics of the participants are included in Table 2. Of the final sample, 33 (35%) were diagnosed with one of the 6 long term conditions originally part of the inclusion criteria. A further breakdown for the conditions is included in Table 2. Previous experience and current usage of technology are recorded in Table S1 . All participants have experience using a smartphone at least once a week, with the majority (98%) using every day. Most (80%) participants have regular use of a computer and experience using weather apps (85%). However, none reported experience using pollution tracking apps. A third (35%) of participants have experience using health apps and half (49%) reported experience using exercise tracking apps. Table 2 : Baseline characteristics experience Mean Std. dev Min Max Variable Age 66.25 7.58 48.15 78.61 Freq % Sex, Female 59 63.44 Ethnicity White 83 89 Mixed/multiple ethnic groups 1 1 Asian/Asian British 6 6 Black/African/Caribbean/Black British 3 3 Prefer not to say 0 0 Other 0 0 Long term condition(s) Asthma 18 19 Type 2 Diabetes 13 14 Chronic obstructive pulmonary disease 4 4 Interstitial lung disease 1 1 Coronary heart disease 2 2 Heart failure 1 1 At least one LTC 33 35.48 English first language 89 95.70 Has previously attended an exercise rehabilitation programme 3 3.23 Usability and acceptability of the app System usability scale Table 3 reports a mean (SD) SUS at 12 weeks of 61.62 (22.09). 34 (56%) reported a SUS score of less than 68, representing somewhat below average usability. Itemised responses at 12 weeks from the SUS are included in Table S2 , 50% of participants agreed they would use the app frequently, found it easy to use, 64% felt confident using the app, 66% of participants agreed “most people would learn to use the app quickly”, 76% disagreed additional assistance would be needed to use the app, and 57% disagreed it was awkward to use. Additional usability and user engagement Table 3 reports a mean (SD) overall score at 12 weeks of the bespoke usability questions of 66.82 (14.75), out of a possible 100. These results indicate a good usability in the user specific functions of the P-STEP app. Itemised responses at 12 weeks are included in Table S2 , 82% agreed the app provided them with up-to-date air quality information, 56% felt it was suitable for their age group, 61% agreed the app allowed them to track their own progress, 52% felt reassured the app would keep their data secure, 33% agreed the app provided guidance specific to their needs, 38% disagreed that the app allowed them to plan their walking routes, and 39 agreed the walking guidance recommended matches their walking ability. Table 3 reports a mean (SD) overall score from the UES-SF of 3.08 (0.79) out of a possible 5, indicating avergae4 user engagement. Itemised responses at 12 weeks are included in Table S2 , 54% disagreed they felt absorbed or lost their selves in the experience of using P-STEP, 60% did not find P-STEP confusing to use, 69% did not find it physically or mentally demanding, 56%, 54% neither agreed or disagreed P-STEP was an attractive app or visually appealing, and 61% agreed they found the app interesting. Table 3 Outcome Scores Baseline, mean (SD) (n = 93) 6 weeks, mean (SD) (n = 72) 12 weeks, mean (SD) (n = 61) Effect size mean change over time (95% CI) p System Usability Score 57.92 (20.12) 61.68 (22.09) Bespoke Usability Questions 65.62 (15.14) 66.815 (14.75) UES-SF Overall 3.06 (0.80) 3.083 (0.79) Focused Attention 2.57 (0.89) 2.519 (0.96) Perceived Usability 3.37 (0.97) 3.55 (0.99) Aesthetic Appeal 3.06 (0.84) 3.077 (0.85) Reward 3.23 (1.10) 3.224 (1.03) SF-12 Physical Component Score 49.57 (6.79) 50.30 (6.51) 49.53 (7.50) -0.066 (-0.656 to 0.523) 0.826 SF-12 Mental Component Score 54.18 (6.23) 53.72 (5.89) 54.03 (6.47) -0.433 (-0.978 to 0.113) 0.120 Sedentary (RPAQ) 6.56 (2.80) 6.29 (2.76) 6.39 (2.50) -0.075 (-0.331 to 0.182) 0.568 Light (RPAQ) 1.08 (1.40) 0.81 (1.32) 0.687 (1.46) -0.117 (-0.220 -0.014) 0.027 Moderate (RPAQ) 4.96 (1.92) 5.56 (1.61) 3.88 (1.56) -0.430 (-0.639 to 0.222) < 0.001 Vigorous (RPAQ) 1.02 (0.22) 0.88 (0.23) 0.72 (0.23) -0.136 (-0.156 to 0.117) < 0.001 Completeness of questionnaires SUS - 99.86% 100% Bespoke - 100% 99.84% UES-SF - 100% 99.84% SF-12 99.73% 99.31% 96.45% RPAQ 99.33% 93% 88.28% Freq (%) Change in perceived walking pace 22 (24%) SF-12 There was no indication of change in quality of life over the 12-week period (Table 3 ) . The SF-12 had a very high completion rate across all 3 time periods (Table 3 ) . RPAQ There was no indication of change in the sedentary domain, while light, moderate and vigorous domains all indicated a negative change in physical activity over the 12 weeks (Table 3 ) . Self-perceived walking pace At 12 weeks, 24% of participants agreed that their walking pace had positively changed as a result of using P-STEP (Table S2). Usage and feedback Figure 2 presents graphically responses on usage and feedback of the app. Participants were asked on average how many times they used the app per week. 80% reported using the app at least once every week, almost 20% reported using the app every day. 60% of participants reported they would be likely to recommend the app to a friend or family member, and 60% rated the app 4–5 stars. Feasibility outcomes 6.5% of those originally emailed about the study registered their interest. The proportion of interested individuals who met the eligibility criteria was 53%, and reasons for ineligibility are recorded in Fig. 1. 98% of eligible participants enrolled on the study. We offered participants the opportunity to receive a phone call to assist with downloading the app and registering for an account, 91% of participants declined this offer and downloaded the app without assistance. 61 (66%) of participants completed the 12-week study. Completion rates across all outcomes were high (Table 3 ) . Participants accepted the format of online registration, informed consent, and questionnaires, no participants needed assistance to complete the online questionnaires and no participants who withdrew from the study recorded this as a reason. Objective app usage data The total number of walks recorded in the pilot was 2,154. After the removal of outliers, where data either had little to no distance over a large time period, or little to no time period over a large distance, the total number of walks recorded over the 12-week period is 1,557. Free-text analysis Participants were asked “Please enter any suggestions to improve the app?” and “Please enter any other feedback you have.” Direct quotes are included in Table S5 . The responses have been categorised into two themes; the functionality of the app and the concept of the app. Responses relating to the functionality of the app were passed on to the app design team for consideration in future iterations of the app. Overall summary of functionality: There should be a quick start button to start recording a walk, rather than three taps Feedback questions after the walks should be shorter, more appealing Some of the design featured can be simplified More guidance for some screens People forget to finish and sometimes start their walks. They would prefer an automatic start and automatic pause button. There needs to be a differentiation between moving and elapsed time The amount of information on the screen seemed to be off-putting for some. Some mentioned to have received too many notifications Some users requested suggestions for outdoor walks Responses relating to the concept of the app were reviewed by the P-STEP study team and will be taken into consideration for future studies relating to the app. Overall summary of concept: Participants found the app motivational Participants agreed the app provided them with up-to-date air quality information. Non-routine GP visits and unexpected hospitalisations Non routine GP visits and unexpected hospitalisations are recorded in Table S3 . Of the one unexpected hospitalisation reported, this was reported to Sponsor as a potential SAE, but later withdrawn following clarification from the participant that this was an outpatient visit. Subgroup analyses The results from the 3 subgroup analyses are recorded in Table S4 . When looking at just the participants with a long-term condition (n = 33), at 6 weeks, the SUS was 56.67, one point lower than the non-diseased group. At 12 weeks, the SUS was 56.91 in the diseased group, 7 points lower than the non-diseased group. When looking at participants with experience of using a fitness tracking device (n = 22), at 6 weeks, the SUS was 56.70, two points lower than the non-experienced group. At 12 weeks, the SUS was 61.05, 1 point lower than the non-experienced group (61.96). We removed 4 users who reported on the questionnaire that they never used the app, and looked at differences between this and if they were included. At 6 weeks, the SUS was 59.40, one point higher than the original group (57.92). At 12 weeks, the SUS was 62.41, 1 point higher than the original group (61.69). These differences were similar for the bespoke usability questionnaire and the UES, but the differences were non-significant. Discussion Main findings P-STEP is a unique mobile phone application that combined air quality index (AQI) data with outdoor walking guidance and has the ability to personalise data based on the participant’s medical condition. The purpose of this study was to assess the usability and acceptability of the P-STEP app among participants with long term health conditions. The feasibility of administering the P-STEP app was assessed by participants taking part in a 12-week study. This study has provided useful information to assist in the design of a future randomised controlled trial. With regard to the usability, the mean (SD) SUS score at 12 weeks was 62 (22), which equates to a usability score of just below average. Further usability was evaluated from the bespoke usability questionnaires, the mean (SD) score being 67 ( 14 ), equating to above average usability when assessing the specific design features of the P-STEP app. With regards to acceptability, all domains of the User Engagement Scale scored 3 out of 5 which equates to medium engagement. Participants provided written feedback relating to both the functionality and concept of the app which will be used to improve future iterations of the app. Responses to the usage and general feedback were positive, with a majority (60%) of participants both stating they would recommend the app to a friend and giving the app 4–5 stars out of a possible 5. Strengths The completion rates (Table 3 ) of the questionnaires were very high in this sample, with very few participants skipping any questions. The acceptability of online registration, informed consent and questionnaires was extremely high, we were not requested to assist any participants in their completion of informed consent, baseline or follow up questionnaires in REDCap. We recorded no problems directly emailing participants from REDcap to receive questionnaires and reminders. Almost everyone (98%) who registered their interest and was eligible to take part in the study was enrolled. The 4 participants that were not enrolled was due to incorrect email address given, and the study team was unable to contact them. 93 participants received access to the app, with 66% completing the 12-week study. This equates to a dropout rate of 33% which is significantly lower than previously reported app feasibility studies( 19 ). Recruitment through the EXCEED study provided us with access to a variety of participants in terms of health status, and experience using technology. This allowed us to pilot the app in a varied group, giving us more nuanced feedback and differing perspectives, which will only help further with the future development of the app and design of a randomised controlled trial. Limitations This study did not appeal greatly to individuals in this cohort, overall interest in the study 6.5%. The original call out from the EXCEED study team went to 5,258 individuals, and the number of responses 342. There are a number of possible reasons for this. Firstly, there may be a reluctance in this cohort to take part in app studies for a number of reasons including confidence using technology and security concerns in testing an app in the investigational stages of development. The time of year of the study may have also affected take up. The study ran from September to January, where the weather and daylight timings may have discouraged individuals to take part in the study with the expectation of needing to use the app to walk outdoors. Despite the study team emphasising the fact this was an Android only study, 18 participants made it through to the final stage of being given access to the app before realising they have a non-Android phone. As a research team we reflected on this and concluded: What we thought may have been a thorough description of an Android smartphone may not have been, though this specific issue was not picked up on in the PPI meetings or reported in feedback forms. Participants may be unaware of the type of phone that they have. Extra checks in future work would need to be employed to ensure this issue is addressed in the early stages and does not waste the time of the participants or research team. Highlights the need for apps to be developed on both smartphone platforms (IOS and Android). 130 people registered their interest in the study who couldn’t take part due to this restriction, which was the largest restriction and limited the sample size, as shown in the reasons for ineligibility in Fig. 1 . 17 participants had to be withdrawn from the study due to a delay in getting the app verified by Google Fit, as shown in Fig. 1 . Not being verified meant that we were limited to 100 users. The process for app verification was out of the hands of the research team, and the process took longer than expected. By the time the verification was approved there would not have been a 12-week window for participants to test the app. Participants were understanding of this issue and no formal issues were raised. Minority ethnic groups, notably Leicester’s Asian and Asian British population, were under-represented in this study - participant ethnicity breakdown is included in Table 1 . The cohort’s age, sex and ethnicity influence the generalizability of research findings to other population groups, therefore validation in other cohorts may be required. Due to slower than expected recruitment, we relaxed the criteria of the participants needing to be diagnosed with a specific LTC. While this has benefits to the study in terms of meeting the required sample size, we moved away from the original target population. Relaxing the criteria meant that we may have ended up testing the app in a more active group where the app is specifically designed for individuals who are less active. Almost a third of our users use fitness trackers on a regular basis, and are therefore likely to be more exposed to other health and fitness apps. While testing in LTC patients would have been preferred, it would be more important in an effectiveness study, less so in a usability and acceptability study. This outcome lead us to conclude that perhaps in a trial setting, recruitment of participants through GP referral, rather than self would help to ensure we target the most suitable participant group. Although not powered to detect change, we have reflected on the reasons why the RPAQ is declining over time. The weather may have affected outdoor physical activity, and as participants use the app and learn more about their levels of physical activity, they may have overestimated their level of physical activity at baseline. This highlights the need for a control group in similar studies, as the control group may have also had declining physical activity, but the difference in the two groups may be significant. This provides justification for a future two arm randomised controlled trial. Future work We have gained informed consent from the P-STEP® participants for the data collected in this study to be transferred to the EXCEED study team. This will enable linkage to electronic health records (EHR) and allows the EXCEED study team to analyse long term outcomes such as mortality, cardiovascular events in the future. The primary data collected in this study, together with EHR records will allow the monitoring of long-term clinical outcomes. Finding out reasons for low interest seems important and information could be collected about this by emailing a short survey asking “we recently sent you information about a new study, please let us know why you were not interested” with some options. This was beyond the scope of this study but would have been useful. Future work to convert the app to iOS would be useful as also include this participant group. Finally, a randomised control trial to assess the effectiveness of the app compared with a control group is warranted. Conclusion The purpose of this study was to assess the usability and acceptability of the P-STEP app among participants with long term conditions. The results show that the P-STEP app may be a useful tool for promoting outdoor exercise in certain patient groups. We intend to use the results from this feasibility study to make improvements to future iterations of the app and to design further research studies. Declarations Ethics approval and Informed consent to participate This study has had ethical approval from the South West Frenchay Research Ethics Committee (REC 23/SW/0060). There is no need for further approval from the Health Research Authority. Individuals gave informed consent to participate in this research. All methods were performed in accordance with the relevant guidelines and regulations (Declaration of Helsinki). Consent for publication As part of informed consent, participants will consent for the results to be published. Availability of data and material The data that support the findings of this study are available from the European Space Agency but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the corresponding author ( [email protected] ) upon reasonable request and with permission of the European Space Agency. Competing interests None Funding GA Ng is supported by a British Heart Foundation Programme Grant (RG/17/3/32,774), the Medical Research Council Biomedical Catalyst Developmental Pathway Funding Scheme (MR/S037306/1) and the British Heart Foundation Research Excellence Award (RE/24/130031). This study was supported by the National Institute for Health and Care Research (NIHR) Applied Research Collaboration East Midlands (ARC EM) and Leicester NIHR Biomedical Research Centre (BRC). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. The app was part funded by the European Space Agency (133105/20/NL/AF) and part funded by the University of Leicester. The study Sponsor is the University of Leicester (#0901). Authors' contributions HW is the lead author and wrote the manuscript. LG, SA, RH, TL and AN contributed significantly to the design and running of the study. All authors have approved the final draft. Acknowledgements None References ONS. Estimating the number of people with cardiovascular or respiratory conditions living in poverty, England: 2021 2021 [Available from: https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/healthinequalities/bullet ns/estimatingthenumberofpeoplewithcardiovascularorrespiratoryconditionslivinginpovertyengland/2 021#:~:text=On%2021%20March%202021%2C%206.6,a%20respiratory%20condition%20(6.8%25). NHS. Physical activity guidelines for adults aged 19 to 64 [Available from: https://www.nhs.uk/live-well/exercise/physical-activity-guidelines-for-adults-aged-19-to-64/#:~:text=do%20at%20least%20150%20minutes,not%20moving%20with%20some%20activity. Bull FC, Al-Ansari SS, Biddle S, Borodulin K, Buman MP, Cardon G, et al. World Health Organization 2020 guidelines on physical activity and sedentary behaviour. Br J Sports Med. 2020;54(24):1451-62. Tonga E, Worboys H, Evans RA, Singh SJ, Davies MJ, Andre Ng G, Yates T. Physical activity guidelines for adults with type 2 Diabetes: Systematic review. Diabetes Res Clin Pract. 2025;220:111982. Rist C, Karlsson N, Necander S, Da Silva CA. Physical activity end-points in trials of chronic respiratory diseases: summary of evidence. ERJ Open Res. 2022;8(1). Jagroop D, Dogra S. Physical activity among Canadian adults with obstructive respiratory diseases. Applied Physiology, Nutrition, and Metabolism. 2018;43(10):1075-82. Jordan C, Charman SJ, Batterham AM, Flynn D, Houghton D, Errington L, et al. Habitual physical activity levels of adults with heart failure: systematic review and meta-analysis. Heart. 2023;109(18):1357. Dempsey PC, Rowlands AV, Strain T, Zaccardi F, Dawkins N, Razieh C, et al. Physical activity volume, intensity, and incident cardiovascular disease. Eur Heart J. 2022;43(46):4789-800. WHO. Air quality, energy and health [Available from: https://www.who.int/teams/environment-climate-change-and-health/air-quality-energy-and-health/health-impacts#:~:text=Air%20pollution%20is%20a%20risk,(household%20air%20pollution%20only). Miller MR. The cardiovascular effects of air pollution: Prevention and reversal by pharmacological agents. Pharmacol Ther. 2022;232:107996. Laranjo L, Ding D, Heleno B, Kocaballi B, Quiroz JC, Tong HL, et al. Do smartphone applications and activity trackers increase physical activity in adults? Systematic review, meta-analysis and metaregression. British Journal of Sports Medicine. 2021;55(8):422. Gorr MW, Falvo MJ, Wold LE. Air Pollution and Other Environmental Modulators of Cardiac Function. Compr Physiol. 2017;7(4):1479-95. Worboys H, Gray L, Anthony S, Hobson R, Lucas T, Ng A. Evaluation of the usability and acceptability of the P-STEP® mobile app: feasibility study protocol. Pilot and Feasibility Studies. 2024;10(1):120. EXCEED. EXCEED Study: About Us. Brooke J. SUS: A quick and dirty usability scale. Usability Eval Ind. 1995;189. O’Brien HL, Cairns P, Hall M. A practical approach to measuring user engagement with the refined user engagement scale (UES) and new UES short form. International Journal of Human-Computer Studies. 2018;112:28-39. Huo T, Guo Y, Shenkman E, Muller K. Assessing the reliability of the short form 12 (SF-12) health survey in adults with mental health conditions: a report from the wellness incentive and navigation (WIN) study. Health Qual Life Outcomes. 2018;16(1):34. Golubic R, May AM, Benjaminsen Borch K, Overvad K, Charles MA, Diaz MJ, et al. Validity of electronically administered Recent Physical Activity Questionnaire (RPAQ) in ten European countries. PLoS One. 2014;9(3):e92829. Meyerowitz-Katz G, Ravi S, Arnolda L, Feng X, Maberly G, Astell-Burt T. Rates of Attrition and Dropout in App-Based Interventions for Chronic Disease: Systematic Review and Meta-Analysis. J Med Internet Res. 2020;22(9):e20283. Additional Declarations No competing interests reported. Supplementary Files PSTEPFeasibilityStudySupplementaryInformation19022025.docx Cite Share Download PDF Status: Published Journal Publication published 17 Oct, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 28 Apr, 2025 Reviews received at journal 27 Apr, 2025 Reviews received at journal 17 Apr, 2025 Reviewers agreed at journal 16 Apr, 2025 Reviewers agreed at journal 16 Apr, 2025 Reviewers invited by journal 16 Apr, 2025 Editor assigned by journal 16 Apr, 2025 Editor invited by journal 18 Mar, 2025 Submission checks completed at journal 17 Mar, 2025 First submitted to journal 27 Feb, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6123032","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":444685696,"identity":"5b379031-2577-476b-8229-34f042d2b690","order_by":0,"name":"Hannah Worboys","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA60lEQVRIiWNgGAWjYBACAwYG5ocfKiwY2JBFGRvwa2EzljgjAdFygEgtDBK8bRIQHlFazMXOGBhIzpOQ42M/fPjzh4p7DPztB9gkZ+DRYjk7x+BB4TYJYzaetDSJA2eKGSTOJLBJbsDnsNu5Gwwkt0kktknwmDEcbEtgYLjBwCb5gIAWCd45EvVtEvyfPxz8l8AgT5yWBokENgkeBomDDQkMBiAt+B2W/81Y4piEYRtPmpnEmWMJPIZnEpst8Xnf4HZa8sMPNTby8u2HH3+oqEmQkzt++ODNHjxaMAAPgVgZBaNgFIyCUUAMAABB/kqUHT+ixAAAAABJRU5ErkJggg==","orcid":"","institution":"University of Leicester","correspondingAuthor":true,"prefix":"","firstName":"Hannah","middleName":"","lastName":"Worboys","suffix":""},{"id":444685701,"identity":"9e4016c3-c840-4521-a23d-3f80dd042fda","order_by":1,"name":"Laura J Gray","email":"","orcid":"","institution":"University of Leicester","correspondingAuthor":false,"prefix":"","firstName":"Laura","middleName":"J","lastName":"Gray","suffix":""},{"id":444685703,"identity":"8cf261bc-18ea-4fe3-9484-9a2c744bffcb","order_by":2,"name":"Sarah Anthony","email":"","orcid":"","institution":"University of Leicester","correspondingAuthor":false,"prefix":"","firstName":"Sarah","middleName":"","lastName":"Anthony","suffix":""},{"id":444685705,"identity":"1463c502-cbff-4fc3-a384-85d3cbbbe99b","order_by":3,"name":"Rachel Hobson","email":"","orcid":"","institution":"University of Leicester","correspondingAuthor":false,"prefix":"","firstName":"Rachel","middleName":"","lastName":"Hobson","suffix":""},{"id":444685707,"identity":"74c31fd1-dcdb-41ae-affc-95dcff5189b3","order_by":4,"name":"Tim Lucas","email":"","orcid":"","institution":"University of Leicester","correspondingAuthor":false,"prefix":"","firstName":"Tim","middleName":"","lastName":"Lucas","suffix":""},{"id":444685710,"identity":"ba05b8a8-04ef-4938-a5fe-31da8f4485cb","order_by":5,"name":"G. André Ng","email":"","orcid":"","institution":"University of Leicester","correspondingAuthor":false,"prefix":"","firstName":"G.","middleName":"André","lastName":"Ng","suffix":""}],"badges":[],"createdAt":"2025-02-27 17:23:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6123032/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6123032/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-20314-0","type":"published","date":"2025-10-17T15:58:17+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":82135614,"identity":"05425a38-9e80-4cb2-9877-7cd391cc97cc","added_by":"auto","created_at":"2025-05-07 06:08:56","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":685707,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCONSORT flow diagram\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6123032/v1/1d72efb0f4eabd2768643317.png"},{"id":82135615,"identity":"aa4da039-efcc-403b-bfb5-603c6f4b476d","added_by":"auto","created_at":"2025-05-07 06:08:56","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":868584,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eUsage and feedback questions\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-6123032/v1/6148643460383a0df49bb27f.png"},{"id":93956196,"identity":"d341c22d-1661-4e4e-a731-dccb6e238903","added_by":"auto","created_at":"2025-10-20 16:11:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3059170,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6123032/v1/336d2897-f21a-46f3-bb07-40c0d77a5877.pdf"},{"id":82135613,"identity":"e9bd5186-0d70-412b-bfe7-eb68a56db212","added_by":"auto","created_at":"2025-05-07 06:08:56","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":47720,"visible":true,"origin":"","legend":"","description":"","filename":"PSTEPFeasibilityStudySupplementaryInformation19022025.docx","url":"https://assets-eu.researchsquare.com/files/rs-6123032/v1/7a0ed8a4653e4aacbcd9e14d.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Evaluation of the usability and acceptability of the P-STEP (Personalised Space Technology Exercise Platform) ® mobile app: Feasibility study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAs of 2021, 6.6\u0026nbsp;million in the UK live with either a cardiovascular or respiratory long term health condition(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). These conditions are associated with poorer health outcomes, reduced quality of life, hospitalisations, and premature death. Effective management through medication and lifestyle changes, particularly increased physical activity, can mitigate risk of these outcomes. Regular physical activity offers many benefits to an individual, including improved physical and mental health, improved cardiovascular outcomes and an increased risk of survival. Engaging in regular physical activity can also enhance cardiovascular fitness, which helps prevent the progression of long-term conditions (LTCs).\u003c/p\u003e \u003cp\u003ePhysical activity guidelines for the general population recommend at least 150 minutes of moderate-intensity exercise per week(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e), and often similar recommendations exist for those living with chronic conditions(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Those living with LTCs receive the same benefits from exercise as those without(\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e), despite these guidelines, many individuals fail to meet current recommended activity levels(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOne reason for reduced physical activity among individuals with LTCs could be the increased exposure to air pollution during outdoor exercise activities such as walking, cycling, or running. Air pollution can severely impact those with cardiac and respiratory diseases(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e), leading to exacerbated symptoms such as chest tightening or worsened coughing for those with asthma and COPD. This risk may discourage individuals from exercising, thus hindering their physical activity levels(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Mobile phone applications (apps) can be used to support behavioural change in those with LTCs, such as to aid increasing physical activity levels(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). However, an important factor to those living with LTC is being able to assess the air quality in the local area prior to outdoor exercising(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe Personalised Space Technology Exercise Platform (P-STEP\u0026reg;) app was designed to address this gap by integrating real-time air quality data with personalised exercise guidance, allowing individuals to plan safer outdoor activities. The P-STEP\u0026reg; app, developed with funding from the European Space Agency, brings together tailored exercise guidance, taking into account an individual\u0026rsquo;s LTCs, while also providing up-to-date information on air quality. The app allows individuals to plan exercise routes (walking routes) in order to minimise their exposure to air pollution, by using the information to avoid higher polluted areas. The app collects data on the time individuals have spent exercising, to reassess their \u0026ldquo;weekly walking target\u0026rdquo;, which is a bespoke evidence-based algorithm designed by a team of health experts that takes into account the individuals characteristics, LTC, and previous levels of exercise. The user can access a range of features in the app, including recording their walking route, planning when/where to go walking based on a 72-hour forecast, achieve walking badges/milestones, save their favourite walking routes. For such an application to be successful in real-world settings, it must be both usable and acceptable.\u003c/p\u003e \u003cp\u003eThis feasibility study is crucial as it evaluates the practical implementation of the P-STEP\u0026reg; app. By assessing usability, engagement, and feasibility outcomes, this study will inform the refinement of the app and the design of a future clinical trial. Understanding the barriers and facilitators to technology-driven behaviour change will help optimize future digital health interventions, ensuring their accessibility, relevance, and long-term sustainability while also improving the health outcomes for individuals.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eOverview\u003c/h2\u003e \u003cp\u003eThis feasibility study was a single arm 12-week pilot study based in Leicestershire, United Kingdom (UK). Questionnaire data were collected at three timepoints, baseline, 6 weeks and 12 weeks. Weekly anonymised usage data from the app were also collected. The South West Frenchay Research Ethics Committee (REC ref: 23/SW/0060) approved the study, confirming that no further Health Research Authority (HRA) approval was necessary. This study has been reported according to the CONSORT 2010 checklist for pilot or feasibility trials (\u003cb\u003eTable S6\u003c/b\u003e). The SPIRIT figure is included in the supplementary information (\u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e). The protocol for this study has been published elsewhere(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eRecruitment methods and procedure\u003c/h3\u003e\n\u003cp\u003eParticipants were recruited from the EXCEED cohort study. The EXCEED study (REC ref 13/EM/0226) is a longitudinal population-based cohort study that facilitates the investigation of genetic, environmental and lifestyle-related determinants of a broad range of diseases and multiple long-term conditions(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). EXCEED participants have consented to be contacted about participating in other research studies.\u003c/p\u003e \u003cp\u003eRecruitment was in two stages, first the criteria to mee the initial EXCEED call out, whereby participants who met the first stage of the criteria (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) were emailed by a member of the EXCEED research team informing them about the study, providing them a copy of the participant information sheet and a link to the P-STEP website. Those interested in registering for the study could fill in a registration form (via MS Forms) with questions asking the second stage of inclusion criteria, detailed below in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The MS forms were then reviewed by a member of the P-STEP study team. The MS forms had questions regarding the second stage of criteria, then additional criteria to be enrolled on the study.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInclusion criteria for P-STEP study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"1\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirst stage of inclusion criteria:\u003c/p\u003e \u003cp\u003e\u0026bull; Part of the EXCEED cohort study\u003c/p\u003e \u003cp\u003e\u0026bull; Adult\u0026thinsp;\u0026ge;\u0026thinsp;18 years\u003c/p\u003e \u003cp\u003e\u0026bull; Lives in Leicestershire\u003c/p\u003e \u003cp\u003e\u0026bull; Does not have dementia, learning disability, severe mental health disorders (other than depression or anxiety), cancer or epilepsy.\u003c/p\u003e \u003cp\u003e\u0026bull; Are not receiving palliative care\u003c/p\u003e \u003cp\u003e\u0026bull; Diagnosed with at least one of the following conditions; asthma, chronic obstructive pulmonary disease (COPD), interstitial lung disease (ILD), coronary heart disease (CHD), heart failure (HF), type 2 diabetes\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecond stage of inclusion criteria:\u003c/p\u003e \u003cp\u003eDoes:\u003c/p\u003e \u003cp\u003e\u0026bull; Can walk for a minimum of 5 minutes outside\u003c/p\u003e \u003cp\u003e\u0026bull; Have an Android smartphone\u003c/p\u003e \u003cp\u003e\u0026bull; Have access to the internet on smartphone\u003c/p\u003e \u003cp\u003e\u0026bull; Have ability to give informed consent\u003c/p\u003e \u003cp\u003eDoes not:\u003c/p\u003e \u003cp\u003e\u0026bull; Have chest pain at rest\u003c/p\u003e \u003cp\u003e\u0026bull; Feel unsteady when standing or walking, which has led to a fall\u003c/p\u003e \u003cp\u003e\u0026bull; Are pregnant\u003c/p\u003e \u003cp\u003e\u0026bull; Are a current cancer patient\u003c/p\u003e \u003cp\u003e\u0026bull; Are receiving palliative care\u003c/p\u003e \u003cp\u003e\u0026bull; Have access to an iOS smartphone only\u003c/p\u003e \u003cp\u003e\u0026bull; Have been advised not to take part in exercise in the past 12 months\u003c/p\u003e \u003cp\u003e\u0026bull; Were part of the P-STEP User engagement group and provided PPI input.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eData collection methods and procedure\u003c/h3\u003e\n\u003cp\u003e Participants who met the inclusion criteria were invited to complete an electronic consent form via REDCap, and enrolled onto the study. Participants then filled in the baseline questionnaire for the study, once completed they were then given access to the P-STEP\u0026reg; app. The baseline questionnaire asked demographic questions, about current experience using technology, the Recent Physical Activity Questionnaire (RPAQ) and the SF-12 quality of life questionnaire.\u003c/p\u003e \u003cp\u003eEach participant had access to the app for 12 weeks. Follow-up questionnaires were sent via REDCap to participants for completion at 6- and 12-weeks. The follow-up questionnaires included the System Usability Scale (SUS), bespoke usability questions, the user engagement scale short form, RPAQ, SF-12, about non-routine GP visits or unexpected hospitalisations and general usage and feedback questions about the app. Two free text box feedback questions allowed for collection of free-text data.\u003c/p\u003e \u003cp\u003eThe questionnaires were designed through a process of iteration with our Patient and Public Involvement and Engagement (PPIE) members. Questionnaire data was collected in REDCap and the quantitative data analysed in Stata. Free text responses were summarised.\u003c/p\u003e\n\u003ch3\u003eOutcomes\u003c/h3\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eSystem Usability Scale (SUS)\u003c/h2\u003e \u003cp\u003eThe primary outcome measure for this study was the SUS at 12 weeks. The SUS is a validated and popular instrument for measuring perceived usability(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). There are 10 items in total, 5 with a positive tone and 5 with a negative tone. The responses range from strongly disagree to strongly agree. The original questionnaire asks about the \u0026ldquo;system\u0026rdquo; however it is acceptable practice to replace system with a relevant term such as website, or app, therefore this study replaces the word system with app. For scoring, the negative SUS responses are reversed and the scores were then transformed onto a 0-100 scale. A SUS score of 68 and above considers the usability score to be above average and anything less below average(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eBespoke Usability Questions (P-STEP\u0026reg; specific)\u003c/h2\u003e \u003cp\u003eNine additional usability questions (\u003cb\u003eTable S2\u003c/b\u003e) that relate specifically to the features of the P-STEP\u0026reg; app, were asked at 6 and 12 weeks. These questions were formulated with input from the PPIE group, and through a process of iteration, finalised with nine questions on a Likert scale of strongly agree to strongly disagree.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eUser Engagement Scale Short Form (UES-SF)\u003c/h3\u003e\n\u003cp\u003eThe User Engagement Scale - Short Form (UES-SF) contains twelve items that measure user engagement(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). There are 12 items which are categorised into; focused attention, perceived usability, aesthetic appeal, and reward. Focused attention refers to feeling absorbed in the interaction and losing track of time. Perceived usability refers to the experience of the interaction and the degree of control and effort expended. Aesthetic appeal refers to the attractiveness and visual appeal of the interface. Reward is the extent to which the experience was rewarding. An overall user engagement was calculated by converting the score to a numeric value of 1\u0026ndash;5 (strongly disagree equals 1, strongly agree equals 5) and taking the mean(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eQuality of Life\u003c/h3\u003e\n\u003cp\u003eThis study was not powered to detect statistical differences over 12 weeks. Despite this, we used the SF-12 in this study to give an indication of change and assess the feasibility of the questionnaire in this sample. The Short Form 12-Item Health Survey (SF-12) is a health-related quality of life tool that measures functional health and well-being from the participant\u0026rsquo;s perspective(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). It assesses eight domains including physical functioning, physical role, pain, general health, vitality, social functioning, social role and mental health. The 8 domains are then categorised into two summary scores; physical component score (PCS) and mental component score (MCS). Scores for the PCS and MCS range from 0-100, and a higher score indicates a higher quality of life.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eRecent Physical Activity Questionnaire (RPAQ)\u003c/h2\u003e \u003cp\u003eThe RPAQ was used and enables assessment of the daily physical activity and sedentary behaviours of adults(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). It includes questions on physical leisure and sports activities (frequency and duration), and activities performed in the home (television, computer, climbing stairs, etc.) and at work (quantity and type of work, home-work journeys, etc.). The analysis takes into account the duration and frequency of each activity, and its intensity. This study was not powered to detect statistical differences over 12 weeks. Despite this, we used the RPAQ in this study to give an indication of change and assess the feasibility of the questionnaire in this sample.\u003c/p\u003e \u003cp\u003eAs well as the RPAQ, two additional questions on self-perceived walking pace were collected at 6 and 12 weeks.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eFeasibility outcomes\u003c/h2\u003e \u003cp\u003eAnonymous usage data were extracted weekly. These data gave information on the features that were used in the app, which were used to inform the feasibility outcomes. The data extracted are a summary of all participants - the information is anonymous and therefore cannot be linked back to participants. These outcomes assess the feasibility of using certain study design features and outcome measures which will help plan a future trial for effectiveness. One of the main feasibility outcomes is the acceptability of the questionnaires within this sample group.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eBaseline characteristics are summarised using mean and standard deviation (SD) or median and interquartile range (IQR) for continuous variables and count and percentage/proportion for categorical. The mean and standard deviation of the SUS, usability and user engagement scores is reported at 6 and 12 weeks. A breakdown of responses to the SUS questionnaire are included both as a frequency table and bar graph. The SF-12 and RPAQ were collected at baseline, 6 and 12 weeks. An indication of changes over time are reported using a fixed effects model. Feasibility outcomes are reported as mean and standard deviations or count and percentages where appropriate.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eSubgroup analyses\u003c/h2\u003e \u003cp\u003eWe conducted three subgroup analyses for the usability outcomes based on i) whether participants had one of the LTCs or not, ii) whether participants had experience using a fitness tracking device, and iii) removing users who enrolled but reported not using the app.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eObjective app usage data\u003c/h2\u003e \u003cp\u003eWalking data were exported from the app to completement the questionnaire data. Input from health professionals provided guidance on the thresholds to remove outliers. Outliers were removed under the assumptions that:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eParticipants may have forgotten to pause and got into a moving vehicle and as a result, the distance for these walks would be high while the associated steps low.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eParticipants may have forgotten to pause when getting back from a walk and as a result, the duration for these walks would be high while the associated distance and steps low.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eNon-routine GP visits and unexpected hospitalisations\u003c/h2\u003e \u003cp\u003eAs the app is not an investigational medicinal product nor a medical device, no adverse effects are expected. Data on non-routine GP visits and unexpected hospitalisations, related or unrelated to the participant's chronic condition(s) were collected at 6 and 12 weeks, instead of adverse events. Any unexpected hospitalisations reported were treated as a potential serious adverse event (SAE) as per University of Leicester Sponsor SAE reporting policy, and followed up directly with participants to obtain further information.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003ePatient and public involvement and engagement (PPIE)\u003c/h2\u003e \u003cp\u003eMembers from the University Hospitals of Leicester NHS Trust Lifestyle PPIE group, and members from the Extended Cohort for E-health, Environment and DNA (EXCEED) study were involved in the design of this study. This included designing and reviewing the study documents such as the register your interest form, participant information sheet, informed consent form, baseline and follow-up questionnaires. PPIE members were also included in reviewing the participant pathway to identify ways to minimise participant burden.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec19\"\u003e\n \u003ch2\u003eRecruitment and enrolment\u003c/h2\u003e\n \u003cp\u003eRecruitment to the study was open from August – October 2023. Recruitment was reviewed every two weeks by the study team and mitigation strategies were employed if the study team identified recruitment to be slower than expected.\u003c/p\u003e\n \u003cp\u003eMitigation strategies for recruitment included relaxing the inclusion criteria of a participant being diagnosed with one of the six long-term conditions. This is justified as while the app may be designed for those with cardiovascular or respiratory diseases, everyone can and would benefit from a reduction in exposure to air pollution. Another justification for this is that the primary outcome is the usability of the app and not its effectiveness in these condition groups. Logistically this mitigation strategy means the EXCEED research team would send out a second wave of invitations irrespective of long-term condition as long as all the other inclusion and exclusion criteria were met.\u003c/p\u003e\n \u003cp\u003eThe CONSORT flow diagram for the participants in this study is reported in Fig. 1. 342 people registered their interest in the study, of which 182 (53%) were eligible. All but 4 of the 182 were enrolled on the study, however 85 were lost at some point between enrolment and being given access to the app. Of these, 43 (51%) did not respond to emails moving them onto the next stage and 21 (25%) were non-Android users. 17 participants had to be withdrawn from the study due to a delay in getting the app verified by Google Fit.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec20\"\u003e\n \u003ch2\u003eBaseline, demographics and technology self-efficacy\u003c/h2\u003e\n \u003cp\u003e93 participants were given access to the app and all were included in the final analysis. The baseline demographics of the participants are included in Table 2. Of the final sample, 33 (35%) were diagnosed with one of the 6 long term conditions originally part of the inclusion criteria. A further breakdown for the conditions is included in Table 2.\u003c/p\u003e\n \u003cp\u003ePrevious experience and current usage of technology are recorded in \u003cstrong\u003eTable S1\u003c/strong\u003e. All participants have experience using a smartphone at least once a week, with the majority (98%) using every day. Most (80%) participants have regular use of a computer and experience using weather apps (85%). However, none reported experience using pollution tracking apps. A third (35%) of participants have experience using health apps and half (49%) reported experience using exercise tracking apps.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv\u003e\n \u003cdiv align=\"char\"\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003cstrong\u003e: Baseline characteristics experience\u0026nbsp;\u003c/strong\u003e\u003c/div\u003e\n \u003ctable id=\"Taba\" border=\"1\"\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStd. dev\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMin\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMax\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e48.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e78.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFreq\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex, Female\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEthnicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMixed/multiple ethnic groups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAsian/Asian British\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBlack/African/Caribbean/Black British\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrefer not to say\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLong term condition(s)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAsthma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eType 2 Diabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChronic obstructive pulmonary disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInterstitial lung disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCoronary heart disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeart failure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAt least one LTC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEnglish first language\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHas previously attended an exercise rehabilitation programme\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec21\"\u003e\n \u003ch2\u003eUsability and acceptability of the app\u003c/h2\u003e\n \u003cdiv id=\"Sec22\"\u003e\n \u003ch2\u003eSystem usability scale\u003c/h2\u003e\n \u003cp\u003eTable 3 reports a mean (SD) SUS at 12 weeks of 61.62 (22.09). 34 (56%) reported a SUS score of less than 68, representing somewhat below average usability. Itemised responses at 12 weeks from the SUS are included in \u003cstrong\u003eTable S2\u003c/strong\u003e, 50% of participants agreed they would use the app frequently, found it easy to use, 64% felt confident using the app, 66% of participants agreed “most people would learn to use the app quickly”, 76% disagreed additional assistance would be needed to use the app, and 57% disagreed it was awkward to use.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec23\"\u003e\n \u003ch2\u003eAdditional usability and user engagement\u003c/h2\u003e\n \u003cp\u003eTable 3 reports a mean (SD) overall score at 12 weeks of the bespoke usability questions of 66.82 (14.75), out of a possible 100. These results indicate a good usability in the user specific functions of the P-STEP app. Itemised responses at 12 weeks are included in \u003cstrong\u003eTable S2\u003c/strong\u003e, 82% agreed the app provided them with up-to-date air quality information, 56% felt it was suitable for their age group, 61% agreed the app allowed them to track their own progress, 52% felt reassured the app would keep their data secure, 33% agreed the app provided guidance specific to their needs, 38% disagreed that the app allowed them to plan their walking routes, and 39 agreed the walking guidance recommended matches their walking ability.\u003c/p\u003e\n \u003cp\u003eTable 3 reports a mean (SD) overall score from the UES-SF of 3.08 (0.79) out of a possible 5, indicating avergae4 user engagement. Itemised responses at 12 weeks are included in \u003cstrong\u003eTable S2\u003c/strong\u003e, 54% disagreed they felt absorbed or lost their selves in the experience of using P-STEP, 60% did not find P-STEP confusing to use, 69% did not find it physically or mentally demanding, 56%, 54% neither agreed or disagreed P-STEP was an attractive app or visually appealing, and 61% agreed they found the app interesting.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 3\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eOutcome Scores\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBaseline, mean (SD) (n = 93)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e6 weeks, mean (SD) (n = 72)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e12 weeks, mean (SD) (n = 61)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEffect size mean change over time (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSystem Usability Score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57.92 (20.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61.68 (22.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBespoke Usability Questions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65.62 (15.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66.815 (14.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUES-SF Overall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.06 (0.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.083 (0.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFocused Attention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.57 (0.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.519 (0.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePerceived Usability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.37 (0.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.55 (0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAesthetic Appeal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.06 (0.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.077 (0.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReward\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.23 (1.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.224 (1.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSF-12 Physical Component Score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.57 (6.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50.30 (6.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.53 (7.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.066 (-0.656 to 0.523)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.826\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSF-12 Mental Component Score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54.18 (6.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53.72 (5.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54.03 (6.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.433 (-0.978 to 0.113)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.120\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSedentary (RPAQ)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.56 (2.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.29 (2.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.39 (2.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.075 (-0.331 to 0.182)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.568\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLight (RPAQ)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.08 (1.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.81 (1.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.687 (1.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.117 (-0.220 -0.014)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate (RPAQ)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.96 (1.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.56 (1.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.88 (1.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.430 (-0.639 to 0.222)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVigorous (RPAQ)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.02 (0.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.88 (0.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.72 (0.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.136 (-0.156 to 0.117)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCompleteness of questionnaires\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSUS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99.86%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBespoke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99.84%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUES-SF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99.84%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSF-12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99.73%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99.31%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96.45%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRPAQ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99.33%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e93%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e88.28%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFreq (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChange in perceived walking pace\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22 (24%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec24\"\u003e\n \u003ch2\u003eSF-12\u003c/h2\u003e\n \u003cp\u003eThere was no indication of change in quality of life over the 12-week period (Table 3\u003cstrong\u003e)\u003c/strong\u003e. The SF-12 had a very high completion rate across all 3 time periods (Table 3\u003cstrong\u003e)\u003c/strong\u003e.\u003c/p\u003e\n \u003cdiv id=\"Sec25\"\u003e\n \u003ch2\u003eRPAQ\u003c/h2\u003e\n \u003cp\u003eThere was no indication of change in the sedentary domain, while light, moderate and vigorous domains all indicated a negative change in physical activity over the 12 weeks (Table 3\u003cstrong\u003e)\u003c/strong\u003e.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec26\"\u003e\n \u003ch2\u003eSelf-perceived walking pace\u003c/h2\u003e\n \u003cp\u003eAt 12 weeks, 24% of participants agreed that their walking pace had positively changed as a result of using P-STEP (Table S2).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec27\"\u003e\n \u003ch2\u003eUsage and feedback\u003c/h2\u003e\n \u003cp\u003eFigure 2 presents graphically responses on usage and feedback of the app. Participants were asked on average how many times they used the app per week. 80% reported using the app at least once every week, almost 20% reported using the app every day. 60% of participants reported they would be likely to recommend the app to a friend or family member, and 60% rated the app 4–5 stars.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec28\"\u003e\n \u003ch2\u003eFeasibility outcomes\u003c/h2\u003e\n \u003cp\u003e6.5% of those originally emailed about the study registered their interest. The proportion of interested individuals who met the eligibility criteria was 53%, and reasons for ineligibility are recorded in Fig. 1. 98% of eligible participants enrolled on the study. We offered participants the opportunity to receive a phone call to assist with downloading the app and registering for an account, 91% of participants declined this offer and downloaded the app without assistance. 61 (66%) of participants completed the 12-week study. Completion rates across all outcomes were high (Table 3\u003cstrong\u003e)\u003c/strong\u003e. Participants accepted the format of online registration, informed consent, and questionnaires, no participants needed assistance to complete the online questionnaires and no participants who withdrew from the study recorded this as a reason.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec29\"\u003e\n \u003ch2\u003eObjective app usage data\u003c/h2\u003e\n \u003cp\u003eThe total number of walks recorded in the pilot was 2,154. After the removal of outliers, where data either had little to no distance over a large time period, or little to no time period over a large distance, the total number of walks recorded over the 12-week period is 1,557.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eFree-text analysis\u003c/h3\u003e\n\u003cp\u003eParticipants were asked “Please enter any suggestions to improve the app?” and “Please enter any other feedback you have.” Direct quotes are included in \u003cstrong\u003eTable S5\u003c/strong\u003e. The responses have been categorised into two themes; the functionality of the app and the concept of the app.\u003c/p\u003e\n\u003cp\u003eResponses relating to the functionality of the app were passed on to the app design team for consideration in future iterations of the app.\u003c/p\u003e\n\u003cp\u003eOverall summary of functionality:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eThere should be a quick start button to start recording a walk, rather than three taps\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eFeedback questions after the walks should be shorter, more appealing\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eSome of the design featured can be simplified\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eMore guidance for some screens\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003ePeople forget to finish and sometimes start their walks. They would prefer an automatic start and automatic pause button. There needs to be a differentiation between moving and elapsed time\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eThe amount of information on the screen seemed to be off-putting for some.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eSome mentioned to have received too many notifications\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eSome users requested suggestions for outdoor walks\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eResponses relating to the concept of the app were reviewed by the P-STEP study team and will be taken into consideration for future studies relating to the app.\u003c/p\u003e\n\u003cdiv id=\"Sec31\"\u003e\n \u003ch2\u003eOverall summary of concept:\u003c/h2\u003e\n \u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eParticipants found the app motivational\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eParticipants agreed the app provided them with up-to-date air quality information.\u003c/p\u003e\n \u003c/li\u003e\n \u003c/ul\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec32\"\u003e\n \u003ch2\u003eNon-routine GP visits and unexpected hospitalisations\u003c/h2\u003e\n \u003cp\u003eNon routine GP visits and unexpected hospitalisations are recorded in \u003cstrong\u003eTable S3\u003c/strong\u003e. Of the one unexpected hospitalisation reported, this was reported to Sponsor as a potential SAE, but later withdrawn following clarification from the participant that this was an outpatient visit.\u003c/p\u003e\n \u003cdiv id=\"Sec33\"\u003e\n \u003ch2\u003eSubgroup analyses\u003c/h2\u003e\n \u003cp\u003eThe results from the 3 subgroup analyses are recorded in \u003cstrong\u003eTable S4\u003c/strong\u003e.\u003c/p\u003e\n \u003cp\u003eWhen looking at just the participants with a long-term condition (n = 33), at 6 weeks, the SUS was 56.67, one point lower than the non-diseased group. At 12 weeks, the SUS was 56.91 in the diseased group, 7 points lower than the non-diseased group.\u003c/p\u003e\n \u003cp\u003eWhen looking at participants with experience of using a fitness tracking device (n = 22), at 6 weeks, the SUS was 56.70, two points lower than the non-experienced group. At 12 weeks, the SUS was 61.05, 1 point lower than the non-experienced group (61.96).\u003c/p\u003e\n \u003cp\u003eWe removed 4 users who reported on the questionnaire that they never used the app, and looked at differences between this and if they were included. At 6 weeks, the SUS was 59.40, one point higher than the original group (57.92). At 12 weeks, the SUS was 62.41, 1 point higher than the original group (61.69). These differences were similar for the bespoke usability questionnaire and the UES, but the differences were non-significant.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec35\" class=\"Section2\"\u003e \u003ch2\u003eMain findings\u003c/h2\u003e \u003cp\u003eP-STEP is a unique mobile phone application that combined air quality index (AQI) data with outdoor walking guidance and has the ability to personalise data based on the participant\u0026rsquo;s medical condition. The purpose of this study was to assess the usability and acceptability of the P-STEP app among participants with long term health conditions. The feasibility of administering the P-STEP app was assessed by participants taking part in a 12-week study. This study has provided useful information to assist in the design of a future randomised controlled trial. With regard to the usability, the mean (SD) SUS score at 12 weeks was 62 (22), which equates to a usability score of just below average. Further usability was evaluated from the bespoke usability questionnaires, the mean (SD) score being 67 (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), equating to above average usability when assessing the specific design features of the P-STEP app. With regards to acceptability, all domains of the User Engagement Scale scored 3 out of 5 which equates to medium engagement. Participants provided written feedback relating to both the functionality and concept of the app which will be used to improve future iterations of the app. Responses to the usage and general feedback were positive, with a majority (60%) of participants both stating they would recommend the app to a friend and giving the app 4\u0026ndash;5 stars out of a possible 5.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStrengths\u003c/h3\u003e\n\u003cp\u003eThe completion rates (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) of the questionnaires were very high in this sample, with very few participants skipping any questions. The acceptability of online registration, informed consent and questionnaires was extremely high, we were not requested to assist any participants in their completion of informed consent, baseline or follow up questionnaires in REDCap. We recorded no problems directly emailing participants from REDcap to receive questionnaires and reminders. Almost everyone (98%) who registered their interest and was eligible to take part in the study was enrolled. The 4 participants that were not enrolled was due to incorrect email address given, and the study team was unable to contact them. 93 participants received access to the app, with 66% completing the 12-week study. This equates to a dropout rate of 33% which is significantly lower than previously reported app feasibility studies(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Recruitment through the EXCEED study provided us with access to a variety of participants in terms of health status, and experience using technology. This allowed us to pilot the app in a varied group, giving us more nuanced feedback and differing perspectives, which will only help further with the future development of the app and design of a randomised controlled trial.\u003c/p\u003e \u003cdiv id=\"Sec37\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThis study did not appeal greatly to individuals in this cohort, overall interest in the study 6.5%. The original call out from the EXCEED study team went to 5,258 individuals, and the number of responses 342. There are a number of possible reasons for this. Firstly, there may be a reluctance in this cohort to take part in app studies for a number of reasons including confidence using technology and security concerns in testing an app in the investigational stages of development. The time of year of the study may have also affected take up. The study ran from September to January, where the weather and daylight timings may have discouraged individuals to take part in the study with the expectation of needing to use the app to walk outdoors.\u003c/p\u003e \u003cp\u003eDespite the study team emphasising the fact this was an Android only study, 18 participants made it through to the final stage of being given access to the app before realising they have a non-Android phone. As a research team we reflected on this and concluded:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eWhat we thought may have been a thorough description of an Android smartphone may not have been, though this specific issue was not picked up on in the PPI meetings or reported in feedback forms.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eParticipants may be unaware of the type of phone that they have.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eExtra checks in future work would need to be employed to ensure this issue is addressed in the early stages and does not waste the time of the participants or research team.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eHighlights the need for apps to be developed on both smartphone platforms (IOS and Android).\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e130 people registered their interest in the study who couldn\u0026rsquo;t take part due to this restriction, which was the largest restriction and limited the sample size, as shown in the reasons for ineligibility in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e17 participants had to be withdrawn from the study due to a delay in getting the app verified by Google Fit, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Not being verified meant that we were limited to 100 users. The process for app verification was out of the hands of the research team, and the process took longer than expected. By the time the verification was approved there would not have been a 12-week window for participants to test the app. Participants were understanding of this issue and no formal issues were raised.\u003c/p\u003e \u003cp\u003eMinority ethnic groups, notably Leicester\u0026rsquo;s Asian and Asian British population, were under-represented in this study - participant ethnicity breakdown is included in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The cohort\u0026rsquo;s age, sex and ethnicity influence the generalizability of research findings to other population groups, therefore validation in other cohorts may be required.\u003c/p\u003e \u003cp\u003eDue to slower than expected recruitment, we relaxed the criteria of the participants needing to be diagnosed with a specific LTC. While this has benefits to the study in terms of meeting the required sample size, we moved away from the original target population. Relaxing the criteria meant that we may have ended up testing the app in a more active group where the app is specifically designed for individuals who are less active. Almost a third of our users use fitness trackers on a regular basis, and are therefore likely to be more exposed to other health and fitness apps. While testing in LTC patients would have been preferred, it would be more important in an effectiveness study, less so in a usability and acceptability study. This outcome lead us to conclude that perhaps in a trial setting, recruitment of participants through GP referral, rather than self would help to ensure we target the most suitable participant group.\u003c/p\u003e \u003cp\u003eAlthough not powered to detect change, we have reflected on the reasons why the RPAQ is declining over time. The weather may have affected outdoor physical activity, and as participants use the app and learn more about their levels of physical activity, they may have overestimated their level of physical activity at baseline. This highlights the need for a control group in similar studies, as the control group may have also had declining physical activity, but the difference in the two groups may be significant. This provides justification for a future two arm randomised controlled trial.\u003c/p\u003e \u003cdiv id=\"Sec38\" class=\"Section3\"\u003e \u003ch2\u003eFuture work\u003c/h2\u003e \u003cp\u003eWe have gained informed consent from the P-STEP\u0026reg; participants for the data collected in this study to be transferred to the EXCEED study team. This will enable linkage to electronic health records (EHR) and allows the EXCEED study team to analyse long term outcomes such as mortality, cardiovascular events in the future. The primary data collected in this study, together with EHR records will allow the monitoring of long-term clinical outcomes.\u003c/p\u003e \u003cp\u003eFinding out reasons for low interest seems important and information could be collected about this by emailing a short survey asking \u0026ldquo;we recently sent you information about a new study, please let us know why you were not interested\u0026rdquo; with some options. This was beyond the scope of this study but would have been useful. Future work to convert the app to iOS would be useful as also include this participant group. Finally, a randomised control trial to assess the effectiveness of the app compared with a control group is warranted.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe purpose of this study was to assess the usability and acceptability of the P-STEP app among participants with long term conditions. The results show that the P-STEP app may be a useful tool for promoting outdoor exercise in certain patient groups. We intend to use the results from this feasibility study to make improvements to future iterations of the app and to design further research studies.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and Informed consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study has had ethical approval from the South West Frenchay Research Ethics Committee (REC 23/SW/0060). There is no need for further approval from the Health Research Authority. Individuals gave informed consent to participate in this research. All methods were performed in accordance with the relevant guidelines and regulations (Declaration of Helsinki).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs part of informed consent, participants will consent for the results to be published.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the European Space Agency but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the corresponding author ([email protected]) upon reasonable request and with permission of the European Space Agency.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGA Ng is supported by a British Heart Foundation Programme Grant (RG/17/3/32,774), the Medical Research Council Biomedical Catalyst Developmental Pathway Funding Scheme (MR/S037306/1) and the British Heart Foundation Research Excellence Award (RE/24/130031). This study was supported by the National Institute for Health and Care Research (NIHR) Applied Research Collaboration East Midlands (ARC EM) and Leicester NIHR Biomedical Research Centre (BRC). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. The app was part funded by the European Space Agency (133105/20/NL/AF) and part funded by the University of Leicester. The study Sponsor is the University of Leicester (#0901).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHW is the lead author and wrote the manuscript. LG, SA, RH, TL and AN\u003c/p\u003e\n\u003cp\u003econtributed significantly to the design and running of the study. All authors have approved\u003c/p\u003e\n\u003cp\u003ethe final draft.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eONS. Estimating the number of people with cardiovascular or respiratory conditions living in poverty, England: 2021 2021 [Available from: https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/healthinequalities/bullet\u003cbr\u003ens/estimatingthenumberofpeoplewithcardiovascularorrespiratoryconditionslivinginpovertyengland/2\u003cbr\u003e021#:~:text=On%2021%20March%202021%2C%206.6,a%20respiratory%20condition%20(6.8%25).\u003c/li\u003e\n\u003cli\u003eNHS. Physical activity guidelines for adults aged 19 to 64 [Available from: https://www.nhs.uk/live-well/exercise/physical-activity-guidelines-for-adults-aged-19-to-64/#:~:text=do%20at%20least%20150%20minutes,not%20moving%20with%20some%20activity.\u003c/li\u003e\n\u003cli\u003eBull FC, Al-Ansari SS, Biddle S, Borodulin K, Buman MP, Cardon G, et al. World Health Organization 2020 guidelines on physical activity and sedentary behaviour. Br J Sports Med. 2020;54(24):1451-62.\u003c/li\u003e\n\u003cli\u003eTonga E, Worboys H, Evans RA, Singh SJ, Davies MJ, Andre Ng G, Yates T. Physical activity guidelines for adults with type 2 Diabetes: Systematic review. Diabetes Res Clin Pract. 2025;220:111982.\u003c/li\u003e\n\u003cli\u003eRist C, Karlsson N, Necander S, Da Silva CA. Physical activity end-points in trials of chronic respiratory diseases: summary of evidence. ERJ Open Res. 2022;8(1).\u003c/li\u003e\n\u003cli\u003eJagroop D, Dogra S. Physical activity among Canadian adults with obstructive respiratory diseases. Applied Physiology, Nutrition, and Metabolism. 2018;43(10):1075-82.\u003c/li\u003e\n\u003cli\u003eJordan C, Charman SJ, Batterham AM, Flynn D, Houghton D, Errington L, et al. Habitual physical activity levels of adults with heart failure: systematic review and meta-analysis. Heart. 2023;109(18):1357.\u003c/li\u003e\n\u003cli\u003eDempsey PC, Rowlands AV, Strain T, Zaccardi F, Dawkins N, Razieh C, et al. 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Compr Physiol. 2017;7(4):1479-95.\u003c/li\u003e\n\u003cli\u003eWorboys H, Gray L, Anthony S, Hobson R, Lucas T, Ng A. Evaluation of the usability and acceptability of the P-STEP\u0026reg; mobile app: feasibility study protocol. Pilot and Feasibility Studies. 2024;10(1):120.\u003c/li\u003e\n\u003cli\u003eEXCEED. EXCEED Study: About Us.\u003c/li\u003e\n\u003cli\u003eBrooke J. SUS: A quick and dirty usability scale. Usability Eval Ind. 1995;189.\u003c/li\u003e\n\u003cli\u003eO\u0026rsquo;Brien HL, Cairns P, Hall M. A practical approach to measuring user engagement with the refined user engagement scale (UES) and new UES short form. International Journal of Human-Computer Studies. 2018;112:28-39.\u003c/li\u003e\n\u003cli\u003eHuo T, Guo Y, Shenkman E, Muller K. Assessing the reliability of the short form 12 (SF-12) health survey in adults with mental health conditions: a report from the wellness incentive and navigation (WIN) study. Health Qual Life Outcomes. 2018;16(1):34.\u003c/li\u003e\n\u003cli\u003eGolubic R, May AM, Benjaminsen Borch K, Overvad K, Charles MA, Diaz MJ, et al. Validity of electronically administered Recent Physical Activity Questionnaire (RPAQ) in ten European countries. PLoS One. 2014;9(3):e92829.\u003c/li\u003e\n\u003cli\u003eMeyerowitz-Katz G, Ravi S, Arnolda L, Feng X, Maberly G, Astell-Burt T. Rates of Attrition and Dropout in App-Based Interventions for Chronic Disease: Systematic Review and Meta-Analysis. J Med Internet Res. 2020;22(9):e20283.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6123032/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6123032/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe P-STEP® (Personalised Space Technology Exercise Platform) app is designed to bring together tailored exercise guidance and up-to-date air quality information for patients with long term health conditions. The app allows individuals to plan outdoor exercise walking routes while minimising their exposure to air pollution. Individuals with chronic long-term conditions, particularly respiratory and cardiovascular conditions, can use the app to minimise the risk of their symptoms being worsened by pollution, while gaining the benefits of outdoor exercise.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study measured the usability and acceptability of the P-STEP® app. The study was a single-arm 12-week pilot study based in Leicestershire, United Kingdom (UK). We recruited 93 participants from an existing cohort study to evaluate the app for 12 weeks. Questionnaire data were collected at three timepoints; baseline, 6 weeks and 12 weeks. The primary outcome was the System Usability Scale at 12 weeks. Secondary outcomes included the User Engagement Scale Short Form, SF-12, Recent Physical Activity Questionnaire, bespoke app-specific usability questions and feasibility outcomes. Additional data collected include participant demographic information,\u003c/p\u003e\n\u003cp\u003etechnology self-efficacy, and adverse events. Weekly anonymised app usage data were collected and analysed separately to complement the questionnaire data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e342 individuals were assessed for eligibility, of whom 182 (53%) were eligible. 93 (51%) eligible participants were enrolled and given access to the app for 12 weeks. 61 (66%) participants completed the study. At 12 weeks, the mean (SD) System Usability Score was 61.68 (22.9), Bespoke usability score was 66.82 (14.75) and User Engagement Score was 3.08 (0.79). Completion rates across all questionnaires were high. Participants accepted the format of online questionnaires, with no participants requiring help to complete and no participants withdrawing from the study for this reason.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiscussion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study helps to understand the feasibility and acceptability of administering this app in the community. The results will help inform the design of a future randomised controlled trial.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics and dissemination\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study has received ethical approval from the South West Frenchay Research Ethics (23/SW/0060) Committee. There is no need for further approval from the Health Research Authority as the study is not taking place in the NHS. 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