{"paper_id":"594e3326-85bd-4f2d-9bfc-47fa521f69ef","body_text":"Engagement with and impact of a mobile health app for childhood obesity prevention and management: a mixed methods study protocol | 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 Study protocol Engagement with and impact of a mobile health app for childhood obesity prevention and management: a mixed methods study protocol Madison Milne-Ives, Ananya Ananthakrishnan, Sophie Homer, Jackie Andrade, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4510115/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background : Childhood obesity is a serious global health concern that affects around 20% of children worldwide. Digital health behaviour change interventions have the potential to improve behaviours that can contribute to childhood obesity, such as diet and physical activity, but often lack sufficient user engagement to achieve significant impact. The aim of this project is to develop evidence to better understand how users engage with digital interventions and how Behaviour Change Techniques can be leveraged to support engagement. Specifically, the study will examine the impact of a family-focused app for childhood obesity prevention on health behaviours, health outcomes, and communication between families and healthcare professionals. Methods : A pre-post, mixed-methods evaluation will examine the impact of the NoObesity app on families’ physical activity and dietary behaviours and on healthcare professionals’ self-efficacy at communicating with families about childhood obesity. Secondary outcomes will include well-being, usability, and users’ engagement with and perceptions of the intervention. An initial sample of 1000 families (children and young people and their parents) and 180 healthcare professionals will be recruited to participate in the study, a subset of whom will be invited to qualitative semi-structured interviews. The study implementation and follow-up period will last for 6 months, with the outcomes measured at baseline and 3- and 6-months post-baseline. Quantitative outcomes will be compared over time using repeated-measures ANOVA and qualitative data will be analysed thematically and triangulated with app use data. Discussion : Ethical approval was received from Newcastle University Faculty of Medical Science Ethics Committee (2688/41816) on 22 March, 2024. Recruitment and data collection are expected to begin in August 2024. The project’s key contributions will be to generate evidence of potential for a family-based digital intervention to support families’ health behaviour change and healthcare professionals’ confidence in their ability to support them and to improve our understanding of how particular Behaviour Change Techniques can be used to support engagement with the intervention and its target behaviours. Telemedicine Mobile Applications mHealth Paediatric Obesity Healthy Lifestyle Exercise Diet Healthy Engagement Behaviour Change Figures Figure 1 Figure 2 BACKGROUND Childhood obesity is a growing, global public health concern [ 1 , 2 ]. Certain behaviours that contribute to obesity (e.g. diet, exercise) are well-established factors in non-communicable diseases such as cancer, heart disease, stroke, and type 2 diabetes [ 3 ] and obesity is strongly associated with increased likelihood of various mental and physical health conditions [ 3 – 5 ]. The ubiquity of cell phones and internet access in the general population has made digital technology a powerful, cost-effective means of supporting key health behaviour interventions [ 6 ]. Mobile health apps have demonstrated potential to support dietary and physical activity behaviour change [ 7 – 10 ], but many do not have robust evidence of long-term positive impact [ 9 , 11 – 14 ]. A key limiting factor for impact is low engagement and adherence [ 15 , 16 ]. To achieve positive outcomes, there is a need to understand how digital tools for paediatric weight management can best support users’ engagement with the intervention and the target health behaviours to achieve positive outcomes. This study will aim to assess the impact of such an intervention on health behaviour change and explore how engagement can be best supported. The worldwide prevalence of overweight and obesity is growing rapidly in children [ 17 ], particularly in developed countries like the US and UK where around 2 in 5 children are overweight or obese by age 11 [ 18 , 19 ]. In the UK in 2015, approximately £6 billion (~ USD 9 billion) was being spent annually on obesity-related healthcare; by 2050, this is expected to increase to almost £10 billion (~ USD 15 billion) [ 20 , 21 ]. There are various determinants of childhood obesity - including factors that are difficult to modulate on an individual level, such as deprivation and genetics [ 22 – 24 ] - but behavioural factors like diet and activity can influence weight and health outcomes [ 25 – 30 ]. Healthcare professional (HCP) involvement can help support family engagement with healthier behaviours, but weight can be a difficult and sensitive topic to discuss [ 31 , 32 ]. Barriers to effective communication include fear of upsetting or offending families and losing their trust, concerns about influencing eating disorders in children, stigma and negative attitudes about obesity, and time constraints [ 31 – 34 ]. A key factor affecting all of these barriers is a lack of sufficient educating and training in the clinical skill of raising and supporting concerns about children’s weight [ 31 – 33 ]. As healthcare becomes increasingly digitised, digital tools like mobile apps have the potential to provide widely accessible behavioural support; however, long-term benefit relies on sufficient engagement [ 13 , 35 ]. As studies have linked high levels of engagement with more positive health outcomes [ 36 , 37 ], improving engagement with DBCIs could increase their potential impact [ 38 , 39 ]. Behaviour Change Techniques (BCTs) [ 40 ] incorporated in digital behaviour change interventions (DBCIs) can help support engagement and impact [ 16 , 41 ], but evidence for associations between specific BCTs and engagement with DBCIs is limited [ 42 ] and there is a lack of clarity in the literature about which BCTs are most effective, in what contexts, and in what combinations [ 43 ]. This study will build on a recent examination of barriers and facilitators to parents’ engagement with a family-focused app for childhood obesity prevention and management (“NoObesity”) [ 44 , 45 ]. In line with previous digital health research, potential impact was limited by a lack of sufficient engagement to achieve the intervention aims (“effective engagement” [ 15 ]). Our previous evaluation identified factors influencing engagement and impact related to capability, motivation, and opportunity, and generated theoretically- and empirically-based recommendations for addressing these barriers [ 44 ]. The study aims to develop evidence to better understand how users engage with DBCIs and how BCTs can be leveraged to support engagement, specifically in the context of obesity prevention and management, and to examine the impact of a family-focused app for childhood obesity prevention on health behaviours, health outcomes, and communication between families and healthcare professionals. METHODS Study Design The study will use an implementation science-centred approach to evaluate the impact of a family-focused app for childhood obesity prevention (NoObesity) on users’ engagement and behaviours and to gather feedback to enable further refinement of the intervention. A single-arm, pre-post interventional study design will examine the impact of the app on families’ physical activity and dietary behaviours and HCPs’ self-efficacy at communicating with families about childhood obesity, how participants engage with the app, and how specific BCTs may be associated with engagement and impact. The primary outcomes, family health behaviours and HCP self-efficacy will be assessed with validated questionnaires. Mixed-methods will be used to triangulate qualitative feedback from interviews with quantitative data to gather a more in-depth understanding of users’ engagement with the NoObesity app and their experiences using the app (Fig. 1 ). The Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) checklist [ 46 ] was used to ensure the comprehensiveness of this protocol (Appendix 1). Intervention The NoObesity app was originally developed by Health Education England (HEE, now the South East School of Public Health, Workforce Training and Education Directorate, NHS England) in collaboration with the Universities of Bournemouth and Southampton to support childhood obesity management and prevention [ 47 ]. The aim of the intervention was to provide health behavioural support for families via goal-setting, self-monitoring, and educational games and resources and to deliver training for HCPs on communicating with families about childhood obesity. Descriptions of the app’s features have been previously published [ 44 , 48 ]. The NoObesity app is being redesigned based on our initial evaluation [ 44 ] and the Behaviour Change Wheel [ 49 ]. The final version of the app that will be evaluated will have the same intended purpose as the original; its design and features will be detailed in the results paper. Patient and public involvement A patient and public involvement (PPI) group will be established to collaborate on the redesign of the app. Sessions will be held so that the PPI members can guide the finalisation of the app design and features, which will be incorporated in the version of the app evaluated in this study. Participants, setting, and eligibility The target population of the study will include families - children and young people (CYP) and their parents - and HCPs (Table 1 ). All eligible participants will be included. As the intervention is delivered digitally, participants can engage with it in various settings in their daily lives. Table 1 Eligibility criteria Inclusion Criteria Participant type Criteria All Willing and able to provide informed consent (16+) or assent to participate (under 16s) Able to speak English Own a mobile device capable of supporting NoObesity (iPhone) Parents/guardians Parent or guardian of at least one child under the age of 18 years Children and young people Any age (up to and including 18 years old; no lower age limit) will be set to enable parents to determine with their child whether they want to and feel capable of participating (e.g. completing questionnaires, interviews) Healthcare professionals Working with families around weight, including but not limited to: general practitioners (GPs), health visitors, school nurses, practice nurses, paediatricians, and paediatric nurses. Exclusion criteria All Previous involvement in development or testing of the NoObesity system Incapable of self-consent (16+) or unwilling to provide assent (under 16s) Have a pre-existing relationship with any members of the research team (e.g. friends, family members, colleagues, etc.) Children and young people Requiring specialist treatment for childhood obesity (receiving Tier 3 or 4 obesity services) Outcomes Primary outcomes To gather preliminary evidence of efficacy, the primary analysis for families will be health behaviour change, specifically related to physical activity and dietary behaviour (Table 2 ). These outcomes will be assessed using a combination of measures to enable triangulation and mitigate potential bias. This will include behavioural data captured via the app (self-report or sensor), repeated questionnaires, and qualitative feedback from semi-structured interviews (SSIs). The Family Nutrition and Physical Activity (FNPA) was selected because it examines the two main target behaviours (physical activity and healthy eating), has been validated for use with children up to 18 years old, is easy to use, and not too long [ 50 , 51 ]. Table 2 Primary and secondary outcomes and measures Outcome Participant Outcome Measure Primary outcomes Health behaviour (physical activity and healthy eating) Parents, CYP Self-reported goal progress in the app’s self-monitoring feature Linked phone or wearable sensors where captured (e.g. step counts as measured by Apple Health or Fitbit) Qualitative feedback from SSIs Family Nutrition and Physical Activity (FNPA) [ 51 ] Self-efficacy HCPs Self-efficacy questionnaire (SE-12) [ 52 ] Qualitative feedback from SSIs Secondary outcomes Engagement All App use data Uptake and dropout rates TWente Engagement with Ehealth Technologies Scale (TWEETS) [ 53 ] Digital Behaviour Change Intervention Engagement Scale (DBCI-ES) [ 54 ] Qualitative feedback from SSIs Well-being Parents, CYP Warwick-Edinburgh Mental Wellbeing Scale (WEMWBS) [ 55 ] Self-efficacy Parents Qualitative feedback from SSIs Acceptability All Qualitative feedback from SSIs (structured using the Theoretical Framework of Acceptability (TFA)) [ 56 ] Usability All mHealth App Usability Questionnaire (MAUQ) [ 57 ] All Qualitative feedback from SSIs For HCPs, the primary outcome will be the impact of the app on their perceived knowledge, skills, and confidence discussing obesity and weight-related topics with families. This will be examined using a self-efficacy questionnaire and explored in more depth in the qualitative SSIs. The self-efficacy questionnaire (SE-12) was designed and validated to assess HCP’s self-efficacy in the context of clinical communication skills training [ 52 ]. Secondary outcomes User engagement with NoObesity will be assessed using a combination of complementary measures [ 58 ], including system use data, questionnaires, and qualitative SSIs. Mixed methods approaches help to capture cognitive, behavioural, and affective components of engagement, to gain a better understanding of users’ experience engaging with the intervention and the behaviour change process [ 16 , 58 – 62 ]. Two recently developed measures of engagement with DBCIs are based on this multifaceted conceptualisation and have similar psychometric properties: the Digital Behaviour Change Intervention Engagement Scale (DBCI-ES) [ 54 ] and the TWente Engagement with Ehealth Technologies Scale (TWEETS) [ 53 ]. The scales are short (10 and 9 items, respectively), so both will be included as outcome measures to enable additional insights into user engagement [ 61 ]. We will also explore how engagement is associated with recruitment methods - whether participants found out about the study via their HCP or via online advertisement - as previous research has found a positive relationship between clinical referral and engagement [ 63 ]. Other secondary outcomes will include usability (measured using the mHealth App Usability questionnaire (MAUQ)), self-efficacy and acceptability (explored in the qualitative SSIs), and well-being. Well-being will be included as a health outcome because of its positive correlation with improvements in physical activity and healthy eating [ 64 ]. The Warwick-Edinburgh Mental Wellbeing Scale (WEMWBS) [ 55 ] has been validated in many populations, including children and teenagers over 11, so is a good measure to capture parent and CYP perspectives [ 65 , 66 ]. No weight-related measures will be captured; this is discussed further in the limitations section. Ethical approvaland considerations The study received ethical approval from the Newcastle University Faculty of Medical Sciences Ethics Committee as of 22 March 2024 (2688/41816). The study will be registered on ClinicalTrials.gov before recruitment begins. The inclusion of CYP as participants presents ethical considerations. As the app is designed for families, CYP will be invited to participate alongside their parent(s) or guardian(s) to ensure that their perspectives are captured. Children under 16 will only be included if a parent or guardian provides informed consent and the child provides assent; young people 16–18 years old will provide their own informed consent. Another consideration is the potential risk that topics arising in the interview may cause harm or distress (e.g. triggering feelings of embarrassment or low self-esteem). To mitigate this risk, interview questions will primarily focus on participants’ experience with the app, which is not expected to be a sensitive subject, and questions relating to behaviour will specifically explore the app’s influence and not the types or extent of behaviours engaged in. Sample size The target sample size was developed using a power calculation and expected dropout rates. Based on the literature, for the primary outcomes (FNPA and SE-12), a sample of 199 families and 90 healthcare professionals would achieve 80% power for an effect size of 0.2 and 0.3 (α = 0.05), respectively. High dropout is common across digital health research [ 67 – 69 ]; recent meta-analyses of mobile apps found pooled estimates of dropout rates between 40–50% [ 70 , 71 ]. As our previous study had a high rate of attrition [ 44 ], we are aiming to enrol at least 1000 families, which would enable us to achieve the target sample size with 80% attrition. We will aim to recruit at least 180 HCPs to account for 50% attrition. A subset of 20–30 participants will be selected to participate in SSIs using a stratified random sampling technique. Participants will be grouped based on demographic characteristics (e.g. gender, ethnicity, level of deprivation (assessed by postcode [ 72 ])) and randomly selected from within these groups using a computer random number generator to achieve a diverse sample. Recruitment and consenting procedure The study will be advertised using social media (Google Adwords and Instagram Ads). Upon download from the Apple App Store, the app will also display a screen during the onboarding process with a link to the study website. This will enable recruitment of people who came across the app in an app store without previously seeing recruitment materials. Recruitment posters will be distributed to local GP centres, children’s centres, schools, and other community organisations or networks. We will target centres and organisations in more disadvantaged areas using the English indices of deprivation (2019) [ 73 ], to try and increase sample diversity. This is a key target cohort to recruit, as there are strong links between obesity and deprivation [ 74 ]. The recruitment materials encourage potential HCPs to discuss the study with the families they work with and families to discuss the study with their HCPs, to increase recruitment by word of mouth. Recruitment materials will provide a brief overview of the study and link to the study website. Participant Information Sheets (PIS) designed for various participant types - parents/guardians, 16–18 year olds, 10–15 year olds, children under 10, and healthcare professionals - will be accessible on the website to provide details about the study, including the potential benefits and risks, how data will be used, anonymised, and stored, and what participation will involve. No incentives will be provided for participation in the study, as we want to evaluate users’ engagement with the app without external incentives that would not be present in a real world context. Informed consent will be collected online using the Qualtrics software; if completed, the survey will continue to collect demographic data (e.g. age, gender, ethnicity, postcode (as proxy for level of deprivation)). Participants will also be asked how they found out about the study, as previous research has indicated that clinical referral is associated with engagement. For parents, the consent and demographics survey will include a question about the age(s) of their child(ren). Depending on their response], a triggered email will be sent with the appropriate age-targeted PIS and consent (for 16–18 year olds) or assent forms (for under 10s and 10–15 year olds) so that they can discuss them as a family and email the research team with any questions they might have. Parents will complete informed consent on behalf of children under 16, but two different simplified versions of an assent form will be provided for children under 10 years old and 10–15 year olds. All informed consent and assent forms will be delivered and completed through the Qualtrics platform. Data collection Quantitative demographic data and outcome measures will be collected using an online survey platform (Qualtrics). All outcome measures will be captured at baseline, 3-months, and 6-months except for the MAUQ (captured only at 3-months). App use data will be automatically stored through the app. SSIs will be conducted with a subset of users at around 3-months (Fig. 2 ). A topic guide will provide a framework for the interviews ( Appendix 2 ). Interviews will be conducted using video or call conferencing software and recorded for transcription. If participants do not want the interview recorded, notes will be taken by hand and verified with the participant post-interview. Data management Each participant will be given a unique identifier. Data will be analysed using the unique IDs so that the overall dataset is pseudonymised. The transcription service receiving SSI recordings will only receive reference to the unique identifiers. The original audio recording will be destroyed after transcription. Records of consent will be kept for ten years after the publication of final study results. All files containing participant data will be stored in the University’s secure Microsoft OneDrive. Data analysis Repeated-measures ANOVA will be used to compare differences between the means across the three time points (baseline, 3 months, and 6 months) for primary and secondary quantitative outcomes (health behaviour, self-efficacy, and well-being). This primary analysis will be conducted on the sample of participants who complete the outcome measures at each time point. Descriptive statistics will be used to evaluate the other quantitative outcomes (e.g. usability scores, app usage data). SSIs will be coded by two investigators using thematic analysis [ 75 ]. Triangulation of the quantitative questionnaire and system use data and qualitative semi-structured interview data will be conducted to validate the findings. DISCUSSION Dissemination Recruitment is expected to begin in August 2024, with data collection running from August 2024 to February 2025. Academic dissemination will include publication of results in a peer-reviewed journal and conference presentations. Public dissemination will be planned in collaboration with PPI representatives, but will include a summary of results being distributed to participants. Limitations Although the aim of the intervention is to support the prevention and management of childhood obesity, the study will focus on evaluating behaviour change, rather than weight-related outcomes. This is a limitation, as we will not capture evidence of clinical impact or determine if the app is associated with weight change. There were two main reasons for this decision: first, our aim is to evaluate impact on engagement, HCP self-efficacy, and family behaviour, in line with the app’s intended purpose. Although the overall aim of this behaviour change is to mitigate childhood obesity, several participants in our previous evaluation reported feeling uncomfortable with weight measurements, especially for their children [ 44 ]. Based on this finding, we also expect that participants may be less likely to provide that data or participate if this measurement was required. Second, there is a logistical challenge in collecting high quality data, as participants would have to self-report measurements, which introduces potential bias or inaccuracy if there are differences in scale calibration or performance of measurements. However, this limitation should be addressed in future, large-scale studies if the evaluation provides good evidence of the impact of the app on health behaviours. Technical limitations of the app will affect generalisability. At present, patients without access to an iPhone will not be able to use the system, and are therefore not eligible for inclusion in the study. Also, as the app is currently only available in English, non-English speaking patients will be excluded from the study, also limiting the representativeness of the sample. There is also potential bias in the qualitative analysis from two sources: the influence of the interviewer on how participants respond (e.g. social desirability bias) and the interpretation of participant responses. The first potential bias will be assessed by examining the balance of positive and negative feedback and by comparing the qualitative and quantitative data about NoObesity’s usability, acceptability, and impact. The second will be addressed by having multiple researchers conduct the thematic analysis, to challenge individual perspectives and preconceived ideas. Conclusions There is an urgent need to address the issue of childhood obesity. Family-based interventions have previously demonstrated positive impact on behavioural and health outcomes, particularly when involving HCP support [ 76 ], but this can be difficult to deliver on a large scale. This study will build on a previous evaluation of the NoObesity app by incorporating feedback and theory to improve the intervention and will assess its ability to positively impact families’ health behaviours and HCPs’ confidence in supporting them. We predict that engagement with the app will lead to improved physical activity, dietary behaviour, and well-being for families and improved self-efficacy for HCPs. More broadly, we anticipate that this evaluation will provide useful insights into how users engage with DBCIs and how particular BCTs can support affective, cognitive, and behavioural engagement with the intervention and health behaviours, which will help inform future development of various DBCIs. Declarations Ethics approval and consent to participate The study received ethical approval from the Newcastle University Faculty of Medical Sciences Ethics Committee as of 22 March, 2024 (2688/41816). Newcastle University is the study sponsor but had no role in study design or the writing and decision to submit for publication. Informed consent will be collected from all participants 16 years and older. For participants younger than 16 years, a parent or guardian will be asked to provide informed consent on their behalf and the participant will be asked to provide their own assent to participate, they will only be included if both are provided. Consent for publication Not applicable. Availability of data and materials Not applicable. Competing interests The authors declare that they have no competing interests. Funding This work was supported by the former Health Education England, which is now the South East School of Public Health, Workforce Training and Education Directorate, NHS England [grant reference number: AM1000393]. MMI, AA, and EM are supported by the NIHR Newcastle BRC. The views expressed in this publication are those of the author (s) and not necessarily those of the South East School of Public Health NHS England or any of the authors’ affiliated universities or BRCs. The funding body was not involved in the study design or the writing and decision to submit the article for publication. Authors' contributions MMI and EM conceived of the study topic and designed and drafted the protocol. SH and JA contributed to the drafting and revision of the protocol. Final revision was conducted by MMI, AA, and EM. Acknowledgements Not applicable. 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Meinert E, Rahman E, Potter A, Lawrence W, Van Velthoven M. Acceptability and Usability of the Mobile Digital Health App NoObesity for Families and Health Care Professionals: Protocol for a Feasibility Study. JMIR Res Protoc. 2020,9:e18068. Michie S, Atkins L, West R. The Behaviour Change Wheel: A Guide to Designing Interventions. London: Silverback Publishing, 2014. Rendina D, Campanozzi A, De Filippo G, the SINU Working Group on Nutritional Surveillance in Adolescents. Methodological approach to the assessment of the obesogenic environment in children and adolescents: A review of the literature. Nutr Metab Cardiovasc Dis. 2019,29:561–71. Ihmels MA, Welk GJ, Eisenmann JC, Nusser SM. Development and preliminary validation of a Family Nutrition and Physical Activity (FNPA) screening tool. Int J Behav Nutr Phys Act. 2009,6:1–10. Axboe MK, Christensen KS, Kofoed P-E, Ammentorp J. Development and validation of a self-efficacy questionnaire (SE-12) measuring the clinical communication skills of health care professionals. BMC Med Educ. 2016,16:272. Kelders SM, Kip H, Greeff J. Psychometric Evaluation of the TWente Engagement with Ehealth Technologies Scale (TWEETS): Evaluation Study. J Med Internet Res. 2020,22:e17757. Perski O, Blandford A, Garnett C, Crane D, West R, Michie S. A self-report measure of engagement with digital behavior change interventions (DBCIs): development and psychometric evaluation of the “DBCI Engagement Scale.” Transl Behav Med. 2019,10:267–77. Tennant R, Hiller L, Fishwick R, Platt S, Joseph S, Weich S, et al. The Warwick-Edinburgh Mental Well-being Scale (WEMWBS): development and UK validation. Health Qual Life Outcomes. 2007,5:63. Sekhon M, Cartwright M, Francis JJ. Acceptability of healthcare interventions: an overview of reviews and development of a theoretical framework. BMC Health Serv Res. 2017,17:1–13. Zhou L, Bao J, Made Agus Setiawan I, Saptono A, Parmanto B. The mHealth App Usability Questionnaire (MAUQ): Development and Validation Study. JMIR mHealth and uHealth. 2019,7:e11500. Torous J, Michalak EE, O’Brien HL. Digital Health and Engagement—Looking Behind the Measures and Methods. JAMA Network Open. 2020,3:e2010918. Kelders SM, van Zyl LE, Ludden GDS. The Concept and Components of Engagement in Different Domains Applied to eHealth: A Systematic Scoping Review. Front Psychol. 2020,0. O’Brien H. Theoretical Perspectives on User Engagement. In: Why Engagement Matters. Cham: Springer International Publishing, 2016. p. 1–26. Milne-Ives M, Homer S, Andrade J, Meinert E. The conceptualisation and measurement of engagement in digital health. Internet interventions. 2024,36. Short CE, DeSmet A, Woods C, Williams SL, Maher C, Middelweerd A, et al. Measuring Engagement in eHealth and mHealth Behavior Change Interventions: Viewpoint of Methodologies. J Med Internet Res. 2018,20:e9397. Pratap A, Neto EC, Snyder P, Stepnowsky C, Elhadad N, Grant D, et al. Indicators of retention in remote digital health studies: a cross-study evaluation of 100,000 participants. npj Digital Medicine. 2020,3:1–10. Gireesh A, Das S, Viner RM. Impact of health behaviours and deprivation on well-being in a national sample of English young people. BMJ Paediatrics Open. 2018,2:e000335. Melendez-Torres GJ, Hewitt G, Hallingberg B, Anthony R, Collishaw S, Hall J, et al. Measurement invariance properties and external construct validity of the short Warwick-Edinburgh mental wellbeing scale in a large national sample of secondary school students in Wales. Health Qual Life Outcomes. 2019,17:1–9. Clarke A, Friede T, Putz R, Ashdown J, Martin S, Blake A, et al. Warwick-Edinburgh Mental Well-being Scale (WEMWBS): Validated for teenage school students in England and Scotland. A mixed methods assessment. BMC Public Health. 2011,11:1–9. 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:e20283. Torous J, Lipschitz J, Ng M, Firth J. Dropout rates in clinical trials of smartphone apps for depressive symptoms: A systematic review and meta-analysis. J Affect Disord. 2020,263:413–9. Pratap A, Neto EC, Snyder P, Stepnowsky C, Elhadad N, Grant D, et al. Indicators of retention in remote digital health studies: a cross-study evaluation of 100,000 participants. npj Digital Medicine. 2020,3:1–10. 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:e20283. Torous J, Lipschitz J, Ng M, Firth J. Dropout rates in clinical trials of smartphone apps for depressive symptoms: A systematic review and meta-analysis. J Affect Disord. 2020,263:413–9. English indices of deprivation 2019. Ministries of Housing, Communities, & Local Government. 2019. https://imd-by-postcode.opendatacommunities.org/imd/2019. Accessed 10 Sep 2022. English indices of deprivation 2019: mapping resources. GOV.UK. https://www.gov.uk/guidance/english-indices-of-deprivation-2019-mapping-resources. Accessed 17 Mar 2023. Part 4: Deprivation. NHS Digital. 2021. https://digital.nhs.uk/data-and-information/publications/statistical/national-child-measurement-programme/2020-21-school-year/deprivation. Accessed 25 Nov 2022. Braun V, Clarke V. Using thematic analysis in psychology. Qual Res Psychol. 2006,3:77–101. Varagiannis P, Magriplis E, Risvas G, Vamvouka K, Nisianaki A, Papageorgiou A, et al. Effects of Three Different Family-Based Interventions in Overweight and Obese Children: The “4 Your Family” Randomized Controlled Trial. Nutrients. 2021,13. Additional Declarations No competing interests reported. Supplementary Files APPENDICES.docx Cite Share Download PDF Status: Posted Version 1 posted 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-4510115\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Study protocol\",\"associatedPublications\":[],\"authors\":[{\"id\":315755184,\"identity\":\"3f09d537-4628-4429-a1e2-a331cdbe300c\",\"order_by\":0,\"name\":\"Madison Milne-Ives\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Newcastle University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Madison\",\"middleName\":\"\",\"lastName\":\"Milne-Ives\",\"suffix\":\"\"},{\"id\":315755186,\"identity\":\"eff8d397-f3be-474b-9893-5d694d60ba00\",\"order_by\":1,\"name\":\"Ananya Ananthakrishnan\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Newcastle University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Ananya\",\"middleName\":\"\",\"lastName\":\"Ananthakrishnan\",\"suffix\":\"\"},{\"id\":315755187,\"identity\":\"fb13a804-f74e-4aa5-9446-ab2f6b9aa838\",\"order_by\":2,\"name\":\"Sophie Homer\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Plymouth\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Sophie\",\"middleName\":\"\",\"lastName\":\"Homer\",\"suffix\":\"\"},{\"id\":315755189,\"identity\":\"de152125-f84f-490b-a4ec-ed718e2da7b2\",\"order_by\":3,\"name\":\"Jackie Andrade\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Plymouth\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Jackie\",\"middleName\":\"\",\"lastName\":\"Andrade\",\"suffix\":\"\"},{\"id\":315755192,\"identity\":\"b938ca25-7d9f-4c28-94fb-39b211067e43\",\"order_by\":4,\"name\":\"Edward Meinert\",\"email\":\"data:image/png;base64,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\",\"orcid\":\"\",\"institution\":\"Imperial College London\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Edward\",\"middleName\":\"\",\"lastName\":\"Meinert\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2024-05-31 16:06:04\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-4510115/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-4510115/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":59217103,\"identity\":\"eb8597d2-90a5-4522-9e9b-c423aac1f2fd\",\"added_by\":\"auto\",\"created_at\":\"2024-06-27 19:10:46\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":352044,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eStudy logic diagram\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure1.Studylogicdiagram.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4510115/v1/9c0b83c4d7d726c8d7692e60.png\"},{\"id\":59217383,\"identity\":\"ae629f43-b32f-4dbb-a318-54ca617b2f13\",\"added_by\":\"auto\",\"created_at\":\"2024-06-27 19:18:45\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":217558,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eParticipant flow diagram\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure2.Participantflowdiagram.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4510115/v1/745652069ac5e957c6948b89.png\"},{\"id\":73295606,\"identity\":\"12bbb00a-c433-4be8-937e-4092cc679914\",\"added_by\":\"auto\",\"created_at\":\"2025-01-08 15:08:54\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":835000,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4510115/v1/e1cf92c5-bcef-4f7d-a1c4-0e19302259b4.pdf\"},{\"id\":59217102,\"identity\":\"4bd0e2de-7d83-4b82-a7ac-83d77089738b\",\"added_by\":\"auto\",\"created_at\":\"2024-06-27 19:10:46\",\"extension\":\"docx\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":29733,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"APPENDICES.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4510115/v1/e44010e3373c894d2b7ca0bd.docx\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Engagement with and impact of a mobile health app for childhood obesity prevention and management: a mixed methods study protocol\",\"fulltext\":[{\"header\":\"BACKGROUND\",\"content\":\"\\u003cp\\u003eChildhood obesity is a growing, global public health concern [\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e]. Certain behaviours that contribute to obesity (e.g. diet, exercise) are well-established factors in non-communicable diseases such as cancer, heart disease, stroke, and type 2 diabetes [\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e] and obesity is strongly associated with increased likelihood of various mental and physical health conditions [\\u003cspan additionalcitationids=\\\"CR4\\\" citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e]. The ubiquity of cell phones and internet access in the general population has made digital technology a powerful, cost-effective means of supporting key health behaviour interventions [\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e]. Mobile health apps have demonstrated potential to support dietary and physical activity behaviour change [\\u003cspan additionalcitationids=\\\"CR8 CR9\\\" citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e], but many do not have robust evidence of long-term positive impact [\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e, \\u003cspan additionalcitationids=\\\"CR12 CR13\\\" citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e]. A key limiting factor for impact is low engagement and adherence [\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e]. To achieve positive outcomes, there is a need to understand how digital tools for paediatric weight management can best support users\\u0026rsquo; engagement with the intervention and the target health behaviours to achieve positive outcomes. This study will aim to assess the impact of such an intervention on health behaviour change and explore how engagement can be best supported.\\u003c/p\\u003e \\u003cp\\u003eThe worldwide prevalence of overweight and obesity is growing rapidly in children [\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e], particularly in developed countries like the US and UK where around 2 in 5 children are overweight or obese by age 11 [\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e]. In the UK in 2015, approximately \\u0026pound;6\\u0026nbsp;billion (~\\u0026thinsp;USD 9\\u0026nbsp;billion) was being spent annually on obesity-related healthcare; by 2050, this is expected to increase to almost \\u0026pound;10\\u0026nbsp;billion (~\\u0026thinsp;USD 15\\u0026nbsp;billion) [\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e]. There are various determinants of childhood obesity - including factors that are difficult to modulate on an individual level, such as deprivation and genetics [\\u003cspan additionalcitationids=\\\"CR23\\\" citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e] - but behavioural factors like diet and activity can influence weight and health outcomes [\\u003cspan additionalcitationids=\\\"CR26 CR27 CR28 CR29\\\" citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e]. Healthcare professional (HCP) involvement can help support family engagement with healthier behaviours, but weight can be a difficult and sensitive topic to discuss [\\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e]. Barriers to effective communication include fear of upsetting or offending families and losing their trust, concerns about influencing eating disorders in children, stigma and negative attitudes about obesity, and time constraints [\\u003cspan additionalcitationids=\\\"CR32 CR33\\\" citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e]. A key factor affecting all of these barriers is a lack of sufficient educating and training in the clinical skill of raising and supporting concerns about children\\u0026rsquo;s weight [\\u003cspan additionalcitationids=\\\"CR32\\\" citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eAs healthcare becomes increasingly digitised, digital tools like mobile apps have the potential to provide widely accessible behavioural support; however, long-term benefit relies on sufficient engagement [\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e]. As studies have linked high levels of engagement with more positive health outcomes [\\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e], improving engagement with DBCIs could increase their potential impact [\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e]. Behaviour Change Techniques (BCTs) [\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e] incorporated in digital behaviour change interventions (DBCIs) can help support engagement and impact [\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e41\\u003c/span\\u003e], but evidence for associations between specific BCTs and engagement with DBCIs is limited [\\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e] and there is a lack of clarity in the literature about which BCTs are most effective, in what contexts, and in what combinations [\\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e43\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eThis study will build on a recent examination of barriers and facilitators to parents\\u0026rsquo; engagement with a family-focused app for childhood obesity prevention and management (\\u0026ldquo;NoObesity\\u0026rdquo;) [\\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR45\\\" class=\\\"CitationRef\\\"\\u003e45\\u003c/span\\u003e]. In line with previous digital health research, potential impact was limited by a lack of sufficient engagement to achieve the intervention aims (\\u0026ldquo;effective engagement\\u0026rdquo; [\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e]). Our previous evaluation identified factors influencing engagement and impact related to capability, motivation, and opportunity, and generated theoretically- and empirically-based recommendations for addressing these barriers [\\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e]. The study aims to develop evidence to better understand how users engage with DBCIs and how BCTs can be leveraged to support engagement, specifically in the context of obesity prevention and management, and to examine the impact of a family-focused app for childhood obesity prevention on health behaviours, health outcomes, and communication between families and healthcare professionals.\\u003c/p\\u003e\"},{\"header\":\"METHODS\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eStudy Design\\u003c/h2\\u003e \\u003cp\\u003eThe study will use an implementation science-centred approach to evaluate the impact of a family-focused app for childhood obesity prevention (NoObesity) on users\\u0026rsquo; engagement and behaviours and to gather feedback to enable further refinement of the intervention. A single-arm, pre-post interventional study design will examine the impact of the app on families\\u0026rsquo; physical activity and dietary behaviours and HCPs\\u0026rsquo; self-efficacy at communicating with families about childhood obesity, how participants engage with the app, and how specific BCTs may be associated with engagement and impact. The primary outcomes, family health behaviours and HCP self-efficacy will be assessed with validated questionnaires. Mixed-methods will be used to triangulate qualitative feedback from interviews with quantitative data to gather a more in-depth understanding of users\\u0026rsquo; engagement with the NoObesity app and their experiences using the app (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). The Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) checklist [\\u003cspan citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e46\\u003c/span\\u003e] was used to ensure the comprehensiveness of this protocol (Appendix 1).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec4\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eIntervention\\u003c/h2\\u003e \\u003cp\\u003eThe NoObesity app was originally developed by Health Education England (HEE, now the South East School of Public Health, Workforce Training and Education Directorate, NHS England) in collaboration with the Universities of Bournemouth and Southampton to support childhood obesity management and prevention [\\u003cspan citationid=\\\"CR47\\\" class=\\\"CitationRef\\\"\\u003e47\\u003c/span\\u003e]. The aim of the intervention was to provide health behavioural support for families via goal-setting, self-monitoring, and educational games and resources and to deliver training for HCPs on communicating with families about childhood obesity. Descriptions of the app\\u0026rsquo;s features have been previously published [\\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR48\\\" class=\\\"CitationRef\\\"\\u003e48\\u003c/span\\u003e]. The NoObesity app is being redesigned based on our initial evaluation [\\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e] and the Behaviour Change Wheel [\\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e49\\u003c/span\\u003e]. The final version of the app that will be evaluated will have the same intended purpose as the original; its design and features will be detailed in the results paper.\\u003c/p\\u003e \\u003cdiv id=\\\"Sec5\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003ePatient and public involvement\\u003c/h2\\u003e \\u003cp\\u003eA patient and public involvement (PPI) group will be established to collaborate on the redesign of the app. Sessions will be held so that the PPI members can guide the finalisation of the app design and features, which will be incorporated in the version of the app evaluated in this study.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec6\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eParticipants, setting, and eligibility\\u003c/h2\\u003e \\u003cp\\u003eThe target population of the study will include families - children and young people (CYP) and their parents - and HCPs (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). All eligible participants will be included. As the intervention is delivered digitally, participants can engage with it in various settings in their daily lives.\\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\\u003eEligibility criteria\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"3\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"6\\\" rowspan=\\\"7\\\"\\u003e \\u003cp\\u003eInclusion Criteria\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eParticipant type\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eCriteria\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e \\u003cp\\u003eAll\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eWilling and able to provide informed consent (16+) or assent to participate (under 16s)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eAble to speak English\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eOwn a mobile device capable of supporting NoObesity (iPhone)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eParents/guardians\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eParent or guardian of at least one child under the age of 18 years\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eChildren and young people\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eAny age (up to and including 18 years old; no lower age limit) will be set to enable parents to determine with their child whether they want to and feel capable of participating (e.g. completing questionnaires, interviews)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eHealthcare professionals\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eWorking with families around weight, including but not limited to: general practitioners (GPs), health visitors, school nurses, practice nurses, paediatricians, and paediatric nurses.\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"3\\\" rowspan=\\\"4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eExclusion criteria\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e \\u003cp\\u003eAll\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003ePrevious involvement in development or testing of the NoObesity system\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eIncapable of self-consent (16+) or unwilling to provide assent (under 16s)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eHave a pre-existing relationship with any members of the research team (e.g. friends, family members, colleagues, etc.)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eChildren and young people\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eRequiring specialist treatment for childhood obesity (receiving Tier 3 or 4 obesity services)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec7\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eOutcomes\\u003c/h2\\u003e \\u003cdiv id=\\\"Sec8\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003ePrimary outcomes\\u003c/h2\\u003e \\u003cp\\u003eTo gather preliminary evidence of efficacy, the primary analysis for families will be health behaviour change, specifically related to physical activity and dietary behaviour (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). These outcomes will be assessed using a combination of measures to enable triangulation and mitigate potential bias. This will include behavioural data captured via the app (self-report or sensor), repeated questionnaires, and qualitative feedback from semi-structured interviews (SSIs). The Family Nutrition and Physical Activity (FNPA) was selected because it examines the two main target behaviours (physical activity and healthy eating), has been validated for use with children up to 18 years old, is easy to use, and not too long [\\u003cspan citationid=\\\"CR50\\\" class=\\\"CitationRef\\\"\\u003e50\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR51\\\" class=\\\"CitationRef\\\"\\u003e51\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003ePrimary and secondary outcomes and measures\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"3\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eOutcome\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eParticipant\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eOutcome Measure\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"3\\\" nameend=\\\"c3\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003ePrimary outcomes\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"3\\\" rowspan=\\\"4\\\"\\u003e \\u003cp\\u003eHealth behaviour (physical activity and healthy eating)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\" morerows=\\\"3\\\" rowspan=\\\"4\\\"\\u003e \\u003cp\\u003eParents, CYP\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eSelf-reported goal progress in the app\\u0026rsquo;s self-monitoring feature\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eLinked phone or wearable sensors where captured (e.g. step counts as measured by Apple Health or Fitbit)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eQualitative feedback from SSIs\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eFamily Nutrition and Physical Activity (FNPA) [\\u003cspan citationid=\\\"CR51\\\" class=\\\"CitationRef\\\"\\u003e51\\u003c/span\\u003e]\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eSelf-efficacy\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eHCPs\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eSelf-efficacy questionnaire (SE-12) [\\u003cspan citationid=\\\"CR52\\\" class=\\\"CitationRef\\\"\\u003e52\\u003c/span\\u003e]\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eQualitative feedback from SSIs\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"3\\\" nameend=\\\"c3\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eSecondary outcomes\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"4\\\" rowspan=\\\"5\\\"\\u003e \\u003cp\\u003eEngagement\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\" morerows=\\\"4\\\" rowspan=\\\"5\\\"\\u003e \\u003cp\\u003eAll\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eApp use data\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eUptake and dropout rates\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eTWente Engagement with Ehealth Technologies Scale (TWEETS) [\\u003cspan citationid=\\\"CR53\\\" class=\\\"CitationRef\\\"\\u003e53\\u003c/span\\u003e]\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eDigital Behaviour Change Intervention Engagement Scale (DBCI-ES) [\\u003cspan citationid=\\\"CR54\\\" class=\\\"CitationRef\\\"\\u003e54\\u003c/span\\u003e]\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eQualitative feedback from SSIs\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eWell-being\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eParents, CYP\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eWarwick-Edinburgh Mental Wellbeing Scale (WEMWBS) [\\u003cspan citationid=\\\"CR55\\\" class=\\\"CitationRef\\\"\\u003e55\\u003c/span\\u003e]\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSelf-efficacy\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eParents\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eQualitative feedback from SSIs\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAcceptability\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eAll\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eQualitative feedback from SSIs (structured using the Theoretical Framework of Acceptability (TFA)) [\\u003cspan citationid=\\\"CR56\\\" class=\\\"CitationRef\\\"\\u003e56\\u003c/span\\u003e]\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eUsability\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eAll\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003emHealth App Usability Questionnaire (MAUQ) [\\u003cspan citationid=\\\"CR57\\\" class=\\\"CitationRef\\\"\\u003e57\\u003c/span\\u003e]\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eAll\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eQualitative feedback from SSIs\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003eFor HCPs, the primary outcome will be the impact of the app on their perceived knowledge, skills, and confidence discussing obesity and weight-related topics with families. This will be examined using a self-efficacy questionnaire and explored in more depth in the qualitative SSIs. The self-efficacy questionnaire (SE-12) was designed and validated to assess HCP\\u0026rsquo;s self-efficacy in the context of clinical communication skills training [\\u003cspan citationid=\\\"CR52\\\" class=\\\"CitationRef\\\"\\u003e52\\u003c/span\\u003e].\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec9\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003eSecondary outcomes\\u003c/h2\\u003e \\u003cp\\u003eUser engagement with NoObesity will be assessed using a combination of complementary measures [\\u003cspan citationid=\\\"CR58\\\" class=\\\"CitationRef\\\"\\u003e58\\u003c/span\\u003e], including system use data, questionnaires, and qualitative SSIs. Mixed methods approaches help to capture cognitive, behavioural, and affective components of engagement, to gain a better understanding of users\\u0026rsquo; experience engaging with the intervention and the behaviour change process [\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e, \\u003cspan additionalcitationids=\\\"CR59 CR60 CR61\\\" citationid=\\\"CR58\\\" class=\\\"CitationRef\\\"\\u003e58\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR62\\\" class=\\\"CitationRef\\\"\\u003e62\\u003c/span\\u003e]. Two recently developed measures of engagement with DBCIs are based on this multifaceted conceptualisation and have similar psychometric properties: the Digital Behaviour Change Intervention Engagement Scale (DBCI-ES) [\\u003cspan citationid=\\\"CR54\\\" class=\\\"CitationRef\\\"\\u003e54\\u003c/span\\u003e] and the TWente Engagement with Ehealth Technologies Scale (TWEETS) [\\u003cspan citationid=\\\"CR53\\\" class=\\\"CitationRef\\\"\\u003e53\\u003c/span\\u003e]. The scales are short (10 and 9 items, respectively), so both will be included as outcome measures to enable additional insights into user engagement [\\u003cspan citationid=\\\"CR61\\\" class=\\\"CitationRef\\\"\\u003e61\\u003c/span\\u003e]. We will also explore how engagement is associated with recruitment methods - whether participants found out about the study via their HCP or via online advertisement - as previous research has found a positive relationship between clinical referral and engagement [\\u003cspan citationid=\\\"CR63\\\" class=\\\"CitationRef\\\"\\u003e63\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eOther secondary outcomes will include usability (measured using the mHealth App Usability questionnaire (MAUQ)), self-efficacy and acceptability (explored in the qualitative SSIs), and well-being. Well-being will be included as a health outcome because of its positive correlation with improvements in physical activity and healthy eating [\\u003cspan citationid=\\\"CR64\\\" class=\\\"CitationRef\\\"\\u003e64\\u003c/span\\u003e]. The Warwick-Edinburgh Mental Wellbeing Scale (WEMWBS) [\\u003cspan citationid=\\\"CR55\\\" class=\\\"CitationRef\\\"\\u003e55\\u003c/span\\u003e] has been validated in many populations, including children and teenagers over 11, so is a good measure to capture parent and CYP perspectives [\\u003cspan citationid=\\\"CR65\\\" class=\\\"CitationRef\\\"\\u003e65\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR66\\\" class=\\\"CitationRef\\\"\\u003e66\\u003c/span\\u003e]. No weight-related measures will be captured; this is discussed further in the \\u003cspan refid=\\\"Sec17\\\" class=\\\"InternalRef\\\"\\u003elimitations\\u003c/span\\u003e section.\\u003c/p\\u003e \\u003cp\\u003e \\u003cstrong\\u003eEthical approvaland considerations\\u003c/strong\\u003e \\u003c/p\\u003e\\u003cp\\u003e The study received ethical approval from the Newcastle University Faculty of Medical Sciences Ethics Committee as of 22 March 2024 (2688/41816). The study will be registered on ClinicalTrials.gov before recruitment begins.\\u003c/p\\u003e \\u003cp\\u003eThe inclusion of CYP as participants presents ethical considerations. As the app is designed for families, CYP will be invited to participate alongside their parent(s) or guardian(s) to ensure that their perspectives are captured. Children under 16 will only be included if a parent or guardian provides informed consent \\u003cem\\u003eand\\u003c/em\\u003e the child provides assent; young people 16\\u0026ndash;18 years old will provide their own informed consent. Another consideration is the potential risk that topics arising in the interview may cause harm or distress (e.g. triggering feelings of embarrassment or low self-esteem). To mitigate this risk, interview questions will primarily focus on participants\\u0026rsquo; experience with the app, which is not expected to be a sensitive subject, and questions relating to behaviour will specifically explore the app\\u0026rsquo;s influence and not the types or extent of behaviours engaged in.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec10\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eSample size\\u003c/h2\\u003e \\u003cp\\u003eThe target sample size was developed using a power calculation and expected dropout rates. Based on the literature, for the primary outcomes (FNPA and SE-12), a sample of 199 families and 90 healthcare professionals would achieve 80% power for an effect size of 0.2 and 0.3 (α\\u0026thinsp;=\\u0026thinsp;0.05), respectively. High dropout is common across digital health research [\\u003cspan additionalcitationids=\\\"CR68\\\" citationid=\\\"CR67\\\" class=\\\"CitationRef\\\"\\u003e67\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR69\\\" class=\\\"CitationRef\\\"\\u003e69\\u003c/span\\u003e]; recent meta-analyses of mobile apps found pooled estimates of dropout rates between 40\\u0026ndash;50% [\\u003cspan citationid=\\\"CR70\\\" class=\\\"CitationRef\\\"\\u003e70\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR71\\\" class=\\\"CitationRef\\\"\\u003e71\\u003c/span\\u003e]. As our previous study had a high rate of attrition [\\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e], we are aiming to enrol at least 1000 families, which would enable us to achieve the target sample size with 80% attrition. We will aim to recruit at least 180 HCPs to account for 50% attrition.\\u003c/p\\u003e \\u003cp\\u003eA subset of 20\\u0026ndash;30 participants will be selected to participate in SSIs using a stratified random sampling technique. Participants will be grouped based on demographic characteristics (e.g. gender, ethnicity, level of deprivation (assessed by postcode [\\u003cspan citationid=\\\"CR72\\\" class=\\\"CitationRef\\\"\\u003e72\\u003c/span\\u003e])) and randomly selected from within these groups using a computer random number generator to achieve a diverse sample.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eRecruitment and consenting procedure\\u003c/h2\\u003e \\u003cp\\u003eThe study will be advertised using social media (Google Adwords and Instagram Ads). Upon download from the Apple App Store, the app will also display a screen during the onboarding process with a link to the study website. This will enable recruitment of people who came across the app in an app store without previously seeing recruitment materials.\\u003c/p\\u003e \\u003cp\\u003eRecruitment posters will be distributed to local GP centres, children\\u0026rsquo;s centres, schools, and other community organisations or networks. We will target centres and organisations in more disadvantaged areas using the English indices of deprivation (2019) [\\u003cspan citationid=\\\"CR73\\\" class=\\\"CitationRef\\\"\\u003e73\\u003c/span\\u003e], to try and increase sample diversity. This is a key target cohort to recruit, as there are strong links between obesity and deprivation [\\u003cspan citationid=\\\"CR74\\\" class=\\\"CitationRef\\\"\\u003e74\\u003c/span\\u003e]. The recruitment materials encourage potential HCPs to discuss the study with the families they work with and families to discuss the study with their HCPs, to increase recruitment by word of mouth.\\u003c/p\\u003e \\u003cp\\u003eRecruitment materials will provide a brief overview of the study and link to the study website. Participant Information Sheets (PIS) designed for various participant types - parents/guardians, 16\\u0026ndash;18 year olds, 10\\u0026ndash;15 year olds, children under 10, and healthcare professionals - will be accessible on the website to provide details about the study, including the potential benefits and risks, how data will be used, anonymised, and stored, and what participation will involve. No incentives will be provided for participation in the study, as we want to evaluate users\\u0026rsquo; engagement with the app without external incentives that would not be present in a real world context.\\u003c/p\\u003e \\u003cp\\u003e \\u003cstrong\\u003eInformed consent\\u003c/strong\\u003e \\u003cp\\u003ewill be collected online using the Qualtrics software; if completed, the survey will continue to collect demographic data (e.g. age, gender, ethnicity, postcode (as proxy for level of deprivation)). Participants will also be asked how they found out about the study, as previous research has indicated that clinical referral is associated with engagement. For parents, the consent and demographics survey will include a question about the age(s) of their child(ren). Depending on their response], a triggered email will be sent with the appropriate age-targeted PIS and consent (for 16\\u0026ndash;18 year olds) or assent forms (for under 10s and 10\\u0026ndash;15 year olds) so that they can discuss them as a family and email the research team with any questions they might have. Parents will complete informed consent on behalf of children under 16, but two different simplified versions of an assent form will be provided for children under 10 years old and 10\\u0026ndash;15 year olds. All informed consent and assent forms will be delivered and completed through the Qualtrics platform.\\u003c/p\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eData collection\\u003c/h2\\u003e \\u003cp\\u003eQuantitative demographic data and outcome measures will be collected using an online survey platform (Qualtrics). All outcome measures will be captured at baseline, 3-months, and 6-months except for the MAUQ (captured only at 3-months). App use data will be automatically stored through the app. SSIs will be conducted with a subset of users at around 3-months (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). A topic guide will provide a framework for the interviews (\\u003cspan refid=\\\"Sec20\\\" class=\\\"InternalRef\\\"\\u003eAppendix 2\\u003c/span\\u003e). Interviews will be conducted using video or call conferencing software and recorded for transcription. If participants do not want the interview recorded, notes will be taken by hand and verified with the participant post-interview.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec13\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eData management\\u003c/h2\\u003e \\u003cp\\u003eEach participant will be given a unique identifier. Data will be analysed using the unique IDs so that the overall dataset is pseudonymised. The transcription service receiving SSI recordings will only receive reference to the unique identifiers. The original audio recording will be destroyed after transcription. Records of consent will be kept for ten years after the publication of final study results. All files containing participant data will be stored in the University\\u0026rsquo;s secure Microsoft OneDrive.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec14\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eData analysis\\u003c/h2\\u003e \\u003cp\\u003eRepeated-measures ANOVA will be used to compare differences between the means across the three time points (baseline, 3 months, and 6 months) for primary and secondary quantitative outcomes (health behaviour, self-efficacy, and well-being). This primary analysis will be conducted on the sample of participants who complete the outcome measures at each time point. Descriptive statistics will be used to evaluate the other quantitative outcomes (e.g. usability scores, app usage data). SSIs will be coded by two investigators using thematic analysis [\\u003cspan citationid=\\\"CR75\\\" class=\\\"CitationRef\\\"\\u003e75\\u003c/span\\u003e]. Triangulation of the quantitative questionnaire and system use data and qualitative semi-structured interview data will be conducted to validate the findings.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"DISCUSSION\",\"content\":\"\\u003cdiv id=\\\"Sec16\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eDissemination\\u003c/h2\\u003e \\u003cp\\u003eRecruitment is expected to begin in August 2024, with data collection running from August 2024 to February 2025. Academic dissemination will include publication of results in a peer-reviewed journal and conference presentations. Public dissemination will be planned in collaboration with PPI representatives, but will include a summary of results being distributed to participants.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec17\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eLimitations\\u003c/h2\\u003e \\u003cp\\u003eAlthough the aim of the intervention is to support the prevention and management of childhood obesity, the study will focus on evaluating behaviour change, rather than weight-related outcomes. This is a limitation, as we will not capture evidence of clinical impact or determine if the app is associated with weight change. There were two main reasons for this decision: first, our aim is to evaluate impact on engagement, HCP self-efficacy, and family behaviour, in line with the app\\u0026rsquo;s intended purpose. Although the overall aim of this behaviour change is to mitigate childhood obesity, several participants in our previous evaluation reported feeling uncomfortable with weight measurements, especially for their children [\\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e]. Based on this finding, we also expect that participants may be less likely to provide that data or participate if this measurement was required. Second, there is a logistical challenge in collecting high quality data, as participants would have to self-report measurements, which introduces potential bias or inaccuracy if there are differences in scale calibration or performance of measurements. However, this limitation should be addressed in future, large-scale studies if the evaluation provides good evidence of the impact of the app on health behaviours.\\u003c/p\\u003e \\u003cp\\u003eTechnical limitations of the app will affect generalisability. At present, patients without access to an iPhone will not be able to use the system, and are therefore not eligible for inclusion in the study. Also, as the app is currently only available in English, non-English speaking patients will be excluded from the study, also limiting the representativeness of the sample.\\u003c/p\\u003e \\u003cp\\u003eThere is also potential bias in the qualitative analysis from two sources: the influence of the interviewer on how participants respond (e.g. social desirability bias) and the interpretation of participant responses. The first potential bias will be assessed by examining the balance of positive and negative feedback and by comparing the qualitative and quantitative data about NoObesity\\u0026rsquo;s usability, acceptability, and impact. The second will be addressed by having multiple researchers conduct the thematic analysis, to challenge individual perspectives and preconceived ideas.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Conclusions\",\"content\":\"\\u003cp\\u003eThere is an urgent need to address the issue of childhood obesity. Family-based interventions have previously demonstrated positive impact on behavioural and health outcomes, particularly when involving HCP support [\\u003cspan citationid=\\\"CR76\\\" class=\\\"CitationRef\\\"\\u003e76\\u003c/span\\u003e], but this can be difficult to deliver on a large scale. This study will build on a previous evaluation of the NoObesity app by incorporating feedback and theory to improve the intervention and will assess its ability to positively impact families\\u0026rsquo; health behaviours and HCPs\\u0026rsquo; confidence in supporting them. We predict that engagement with the app will lead to improved physical activity, dietary behaviour, and well-being for families and improved self-efficacy for HCPs. More broadly, we anticipate that this evaluation will provide useful insights into how users engage with DBCIs and how particular BCTs can support affective, cognitive, and behavioural engagement with the intervention and health behaviours, which will help inform future development of various DBCIs.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003eEthics approval and consent to participate\\u003c/p\\u003e\\n\\u003cp\\u003eThe study received ethical approval from the Newcastle University Faculty of Medical Sciences Ethics Committee as of 22 March, 2024 (2688/41816). Newcastle University is the study sponsor but had no role in study design or the writing and decision to submit for publication. Informed consent will be collected from all participants 16 years and older. For participants younger than 16 years, a parent or guardian will be asked to provide informed consent on their behalf and the participant will be asked to provide their own assent to participate, they will only be included if both are provided. \\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eConsent for publication\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eAvailability of data and materials\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eCompeting interests\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors declare that they have no competing interests.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eFunding\\u003c/p\\u003e\\n\\u003cp\\u003eThis work was supported by the former Health Education England, which is now the South East School of Public Health, Workforce Training and Education Directorate, NHS England [grant reference number: AM1000393]. MMI, AA, and EM are supported by the NIHR Newcastle BRC. The views expressed in this publication are those of the author (s) and not necessarily those of the South East School of Public Health NHS England or any of the authors\\u0026rsquo; affiliated universities or BRCs. The funding body was not involved in the study design or the writing and decision to submit the article for publication.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eAuthors\\u0026apos; contributions\\u003c/p\\u003e\\n\\u003cp\\u003eMMI and EM conceived of the study topic and designed and drafted the protocol. SH and JA contributed to the drafting and revision of the protocol. Final revision was conducted by MMI, AA, and EM.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eAcknowledgements\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable. \\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eObesity. 2019. https://www.nuffieldtrust.org.uk/resource/obesity. 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Am J Public Health. 2012,102:401\\u0026ndash;5.\\u003c/li\\u003e\\n\\u003cli\\u003eMichie S, Richardson M, Johnston M, Abraham C, Francis J, Hardeman W, et al. The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: building an international consensus for the reporting of behavior change interventions. Ann Behav Med. 2013,46:81\\u0026ndash;95.\\u003c/li\\u003e\\n\\u003cli\\u003eKlonoff DC. Behavioral Theory: The Missing Ingredient for Digital Health Tools to Change Behavior and Increase Adherence. J Diabetes Sci Technol. 2019,13:276\\u0026ndash;81.\\u003c/li\\u003e\\n\\u003cli\\u003eMilne-Ives M, Homer SR, Andrade J, Meinert E. Potential associations between behavior change techniques and engagement with mobile health apps: a systematic review. Front Psychol. 2023,14.\\u003c/li\\u003e\\n\\u003cli\\u003eMichie S, West R, Sheals K, Godinho CA. Evaluating the effectiveness of behavior change techniques in health-related behavior: a scoping review of methods used. Transl Behav Med. 2018,8:212\\u0026ndash;24.\\u003c/li\\u003e\\n\\u003cli\\u003eMilne-Ives M, Rahman E, Bradwell H, Baines R, Boey T, Potter A, et al. Barriers and facilitators to parents\\u0026rsquo; engagement with and perceived impact of a childhood obesity app: A mixed-methods study. PLOS Digital Health. 2024,3.\\u003c/li\\u003e\\n\\u003cli\\u003eMeinert E, Rahman E, Potter A, Lawrence W, Van Velthoven M. Acceptability and Usability of the Mobile Digital Health App NoObesity for Families and Health Care Professionals: Protocol for a Feasibility Study. JMIR Res Protoc. 2020,9:e18068.\\u003c/li\\u003e\\n\\u003cli\\u003eChan A-W, Tetzlaff JM, Altman DG, Laupacis A, G\\u0026oslash;tzsche PC, Krleža-Jerić K, et al. SPIRIT 2013 Statement: Defining Standard Protocol Items for Clinical Trials. Ann Intern Med. 2013.\\u003c/li\\u003e\\n\\u003cli\\u003eKing D, Rahman E, Potter A. NoObesity Apps \\u0026ndash; From Approach to Finished App. Proceedings of the Future Technologies Conference (FTC) 2018. 2019,:1145\\u0026ndash;57.\\u003c/li\\u003e\\n\\u003cli\\u003eMeinert E, Rahman E, Potter A, Lawrence W, Van Velthoven M. Acceptability and Usability of the Mobile Digital Health App NoObesity for Families and Health Care Professionals: Protocol for a Feasibility Study. JMIR Res Protoc. 2020,9:e18068.\\u003c/li\\u003e\\n\\u003cli\\u003eMichie S, Atkins L, West R. The Behaviour Change Wheel: A Guide to Designing Interventions. London: Silverback Publishing, 2014.\\u003c/li\\u003e\\n\\u003cli\\u003eRendina D, Campanozzi A, De Filippo G, the SINU Working Group on Nutritional Surveillance in Adolescents. Methodological approach to the assessment of the obesogenic environment in children and adolescents: A review of the literature. Nutr Metab Cardiovasc Dis. 2019,29:561\\u0026ndash;71.\\u003c/li\\u003e\\n\\u003cli\\u003eIhmels MA, Welk GJ, Eisenmann JC, Nusser SM. Development and preliminary validation of a Family Nutrition and Physical Activity (FNPA) screening tool. Int J Behav Nutr Phys Act. 2009,6:1\\u0026ndash;10.\\u003c/li\\u003e\\n\\u003cli\\u003eAxboe MK, Christensen KS, Kofoed P-E, Ammentorp J. Development and validation of a self-efficacy questionnaire (SE-12) measuring the clinical communication skills of health care professionals. BMC Med Educ. 2016,16:272.\\u003c/li\\u003e\\n\\u003cli\\u003eKelders SM, Kip H, Greeff J. Psychometric Evaluation of the TWente Engagement with Ehealth Technologies Scale (TWEETS): Evaluation Study. J Med Internet Res. 2020,22:e17757.\\u003c/li\\u003e\\n\\u003cli\\u003ePerski O, Blandford A, Garnett C, Crane D, West R, Michie S. A self-report measure of engagement with digital behavior change interventions (DBCIs): development and psychometric evaluation of the \\u0026ldquo;DBCI Engagement Scale.\\u0026rdquo; Transl Behav Med. 2019,10:267\\u0026ndash;77.\\u003c/li\\u003e\\n\\u003cli\\u003eTennant R, Hiller L, Fishwick R, Platt S, Joseph S, Weich S, et al. The Warwick-Edinburgh Mental Well-being Scale (WEMWBS): development and UK validation. Health Qual Life Outcomes. 2007,5:63.\\u003c/li\\u003e\\n\\u003cli\\u003eSekhon M, Cartwright M, Francis JJ. Acceptability of healthcare interventions: an overview of reviews and development of a theoretical framework. BMC Health Serv Res. 2017,17:1\\u0026ndash;13.\\u003c/li\\u003e\\n\\u003cli\\u003eZhou L, Bao J, Made Agus Setiawan I, Saptono A, Parmanto B. The mHealth App Usability Questionnaire (MAUQ): Development and Validation Study. JMIR mHealth and uHealth. 2019,7:e11500.\\u003c/li\\u003e\\n\\u003cli\\u003eTorous J, Michalak EE, O\\u0026rsquo;Brien HL. Digital Health and Engagement\\u0026mdash;Looking Behind the Measures and Methods. JAMA Network Open. 2020,3:e2010918.\\u003c/li\\u003e\\n\\u003cli\\u003eKelders SM, van Zyl LE, Ludden GDS. The Concept and Components of Engagement in Different Domains Applied to eHealth: A Systematic Scoping Review. Front Psychol. 2020,0.\\u003c/li\\u003e\\n\\u003cli\\u003eO\\u0026rsquo;Brien H. Theoretical Perspectives on User Engagement. In: Why Engagement Matters. Cham: Springer International Publishing, 2016. p. 1\\u0026ndash;26.\\u003c/li\\u003e\\n\\u003cli\\u003eMilne-Ives M, Homer S, Andrade J, Meinert E. The conceptualisation and measurement of engagement in digital health. Internet interventions. 2024,36.\\u003c/li\\u003e\\n\\u003cli\\u003eShort CE, DeSmet A, Woods C, Williams SL, Maher C, Middelweerd A, et al. Measuring Engagement in eHealth and mHealth Behavior Change Interventions: Viewpoint of Methodologies. J Med Internet Res. 2018,20:e9397.\\u003c/li\\u003e\\n\\u003cli\\u003ePratap A, Neto EC, Snyder P, Stepnowsky C, Elhadad N, Grant D, et al. Indicators of retention in remote digital health studies: a cross-study evaluation of 100,000 participants. npj Digital Medicine. 2020,3:1\\u0026ndash;10.\\u003c/li\\u003e\\n\\u003cli\\u003eGireesh A, Das S, Viner RM. Impact of health behaviours and deprivation on well-being in a national sample of English young people. BMJ Paediatrics Open. 2018,2:e000335.\\u003c/li\\u003e\\n\\u003cli\\u003eMelendez-Torres GJ, Hewitt G, Hallingberg B, Anthony R, Collishaw S, Hall J, et al. Measurement invariance properties and external construct validity of the short Warwick-Edinburgh mental wellbeing scale in a large national sample of secondary school students in Wales. Health Qual Life Outcomes. 2019,17:1\\u0026ndash;9.\\u003c/li\\u003e\\n\\u003cli\\u003eClarke A, Friede T, Putz R, Ashdown J, Martin S, Blake A, et al. Warwick-Edinburgh Mental Well-being Scale (WEMWBS): Validated for teenage school students in England and Scotland. A mixed methods assessment. BMC Public Health. 2011,11:1\\u0026ndash;9.\\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:e20283.\\u003c/li\\u003e\\n\\u003cli\\u003eTorous J, Lipschitz J, Ng M, Firth J. Dropout rates in clinical trials of smartphone apps for depressive symptoms: A systematic review and meta-analysis. J Affect Disord. 2020,263:413\\u0026ndash;9.\\u003c/li\\u003e\\n\\u003cli\\u003ePratap A, Neto EC, Snyder P, Stepnowsky C, Elhadad N, Grant D, et al. Indicators of retention in remote digital health studies: a cross-study evaluation of 100,000 participants. npj Digital Medicine. 2020,3:1\\u0026ndash;10.\\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:e20283.\\u003c/li\\u003e\\n\\u003cli\\u003eTorous J, Lipschitz J, Ng M, Firth J. Dropout rates in clinical trials of smartphone apps for depressive symptoms: A systematic review and meta-analysis. J Affect Disord. 2020,263:413\\u0026ndash;9.\\u003c/li\\u003e\\n\\u003cli\\u003eEnglish indices of deprivation 2019. Ministries of Housing, Communities, \\u0026amp; Local Government. 2019. https://imd-by-postcode.opendatacommunities.org/imd/2019. Accessed 10 Sep 2022.\\u003c/li\\u003e\\n\\u003cli\\u003eEnglish indices of deprivation 2019: mapping resources. GOV.UK. https://www.gov.uk/guidance/english-indices-of-deprivation-2019-mapping-resources. Accessed 17 Mar 2023.\\u003c/li\\u003e\\n\\u003cli\\u003ePart 4: Deprivation. NHS Digital. 2021. https://digital.nhs.uk/data-and-information/publications/statistical/national-child-measurement-programme/2020-21-school-year/deprivation. Accessed 25 Nov 2022.\\u003c/li\\u003e\\n\\u003cli\\u003eBraun V, Clarke V. Using thematic analysis in psychology. Qual Res Psychol. 2006,3:77\\u0026ndash;101.\\u003c/li\\u003e\\n\\u003cli\\u003eVaragiannis P, Magriplis E, Risvas G, Vamvouka K, Nisianaki A, Papageorgiou A, et al. Effects of Three Different Family-Based Interventions in Overweight and Obese Children: The \\u0026ldquo;4 Your Family\\u0026rdquo; Randomized Controlled Trial. Nutrients. 2021,13.\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":true,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true},\"keywords\":\"Telemedicine, Mobile Applications, mHealth, Paediatric Obesity, Healthy Lifestyle, Exercise, Diet, Healthy, Engagement, Behaviour Change\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-4510115/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-4510115/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003e\\u003cstrong\\u003eBackground\\u003c/strong\\u003e: Childhood obesity is a serious global health concern that affects around 20% of children worldwide. Digital health behaviour change interventions have the potential to improve behaviours that can contribute to childhood obesity, such as diet and physical activity, but often lack sufficient user engagement to achieve significant impact. The aim of this project is to develop evidence to better understand how users engage with digital interventions and how Behaviour Change Techniques can be leveraged to support engagement. Specifically, the study will examine the impact of a family-focused app for childhood obesity prevention on health behaviours, health outcomes, and communication between families and healthcare professionals.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eMethods\\u003c/strong\\u003e: A pre-post, mixed-methods evaluation will examine the impact of the NoObesity app on families’ physical activity and dietary behaviours and on healthcare professionals’ self-efficacy at communicating with families about childhood obesity. Secondary outcomes will include well-being, usability, and users’ engagement with and perceptions of the intervention. An initial sample of 1000 families (children and young people and their parents) and 180 healthcare professionals will be recruited to participate in the study, a subset of whom will be invited to qualitative semi-structured interviews. The study implementation and follow-up period will last for 6 months, with the outcomes measured at baseline and 3- and 6-months post-baseline. Quantitative outcomes will be compared over time using repeated-measures ANOVA and qualitative data will be analysed thematically and triangulated with app use data.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eDiscussion\\u003c/strong\\u003e: Ethical approval was received from Newcastle University Faculty of Medical Science Ethics Committee (2688/41816) on 22 March, 2024. Recruitment and data collection are expected to begin in August 2024. The project’s key contributions will be to generate evidence of potential for a family-based digital intervention to support families’ health behaviour change and healthcare professionals’ confidence in their ability to support them and to improve our understanding of how particular Behaviour Change Techniques can be used to support engagement with the intervention and its target behaviours.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Engagement with and impact of a mobile health app for childhood obesity prevention and management: a mixed methods study protocol\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2024-06-27 19:10:40\",\"doi\":\"10.21203/rs.3.rs-4510115/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"65283576-5991-4d1c-9b9a-e1e1fbc84478\",\"owner\":[],\"postedDate\":\"June 27th, 2024\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2025-01-08T15:08:15+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2024-06-27 19:10:40\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-4510115\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-4510115\",\"identity\":\"rs-4510115\",\"version\":[\"v1\"]},\"buildId\":\"qtupq5eGEP_6zYnWcrvyt\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}