scholarly journals Adults’ Preferences for Behavior Change Techniques and Engagement Features in a Mobile App to Promote 24-Hour Movement Behaviors: Cross-Sectional Survey Study (Preprint)

2019 ◽  
Author(s):  
Ann DeSmet ◽  
Ilse De Bourdeaudhuij ◽  
Sebastien Chastin ◽  
Geert Crombez ◽  
Ralph Maddison ◽  
...  
Keyword(s):  
Behavior Change ◽  
Repeated Measures ◽  
Self Regulation ◽  
Mobile App ◽  
User Preferences ◽  
Movement Behavior ◽  
Survey Study ◽  
User Engagement ◽  
Behavior Change Techniques ◽  
Self Monitoring

BACKGROUND There is a limited understanding of components that should be included in digital interventions for 24-hour movement behaviors (physical activity [PA], sleep, and sedentary behavior [SB]). For intervention effectiveness, user engagement is important. This can be enhanced by a user-centered design to, for example, explore and integrate user preferences for intervention techniques and features. OBJECTIVE This study aimed to examine adult users’ preferences for techniques and features in mobile apps for 24-hour movement behaviors. METHODS A total of 86 participants (mean age 37.4 years [SD 9.2]; 49/86, 57% female) completed a Web-based survey. Behavior change techniques (BCTs) were based on a validated taxonomy v2 by Abraham and Michie, and engagement features were based on a list extracted from the literature. Behavioral data were collected using Fitbit trackers. Correlations, (repeated measures) analysis of variance, and independent sample <italic>t</italic> tests were used to examine associations and differences between and within users by the type of health domain and users’ behavioral intention and adoption. RESULTS Preferences were generally the highest for information on the health consequences of movement behavior self-monitoring, behavioral feedback, insight into healthy lifestyles, and tips and instructions. Although the same ranking was found for techniques across behaviors, preferences were stronger for all but one BCT for PA in comparison to the other two health behaviors. Although techniques fit user preferences for addressing PA well, supplemental techniques may be able to address preferences for sleep and SB in a better manner. In addition to what is commonly included in apps, sleep apps should consider providing tips for sleep. SB apps may wish to include more self-regulation and goal-setting techniques. Few differences were found by users’ intentions or adoption to change a particular behavior. Apps should provide more self-monitoring (<italic>P</italic>=.03), information on behavior health outcome (<italic>P</italic>=.048), and feedback (<italic>P</italic>=.04) and incorporate social support (<italic>P</italic>=.048) to help those who are further removed from healthy sleep. A virtual coach (<italic>P</italic><.001) and video modeling (<italic>P</italic>=.004) may provide appreciated support to those who are physically less active. PA self-monitoring appealed more to those with an intention to change PA (<italic>P</italic>=.03). Social comparison and support features are not high on users’ agenda and may not be needed from an engagement point of view. Engagement features may not be very relevant for user engagement but should be examined in future research with a less reflective method. CONCLUSIONS The findings of this study provide guidance for the design of digital 24-hour movement behavior interventions. As 24-hour movement guidelines are increasingly being adopted in several countries, our study findings are timely to support the design of interventions to meet these guidelines.

scholarly journals Adults’ Preferences for Behavior Change Techniques and Engagement Features in a Mobile App to Promote 24-Hour Movement Behaviors: Cross-Sectional Survey Study

10.2196/15707 ◽  
2019 ◽  
Vol 7 (12) ◽  
pp. e15707 ◽  
Author(s):  
Ann DeSmet ◽  
Ilse De Bourdeaudhuij ◽  
Sebastien Chastin ◽  
Geert Crombez ◽  
Ralph Maddison ◽  
...  
Keyword(s):  
Behavior Change ◽  
Repeated Measures ◽  
Self Regulation ◽  
Mobile App ◽  
User Preferences ◽  
Movement Behavior ◽  
Survey Study ◽  
User Engagement ◽  
Behavior Change Techniques ◽  
Self Monitoring

Background There is a limited understanding of components that should be included in digital interventions for 24-hour movement behaviors (physical activity [PA], sleep, and sedentary behavior [SB]). For intervention effectiveness, user engagement is important. This can be enhanced by a user-centered design to, for example, explore and integrate user preferences for intervention techniques and features. Objective This study aimed to examine adult users’ preferences for techniques and features in mobile apps for 24-hour movement behaviors. Methods A total of 86 participants (mean age 37.4 years [SD 9.2]; 49/86, 57% female) completed a Web-based survey. Behavior change techniques (BCTs) were based on a validated taxonomy v2 by Abraham and Michie, and engagement features were based on a list extracted from the literature. Behavioral data were collected using Fitbit trackers. Correlations, (repeated measures) analysis of variance, and independent sample t tests were used to examine associations and differences between and within users by the type of health domain and users’ behavioral intention and adoption. Results Preferences were generally the highest for information on the health consequences of movement behavior self-monitoring, behavioral feedback, insight into healthy lifestyles, and tips and instructions. Although the same ranking was found for techniques across behaviors, preferences were stronger for all but one BCT for PA in comparison to the other two health behaviors. Although techniques fit user preferences for addressing PA well, supplemental techniques may be able to address preferences for sleep and SB in a better manner. In addition to what is commonly included in apps, sleep apps should consider providing tips for sleep. SB apps may wish to include more self-regulation and goal-setting techniques. Few differences were found by users’ intentions or adoption to change a particular behavior. Apps should provide more self-monitoring (P=.03), information on behavior health outcome (P=.048), and feedback (P=.04) and incorporate social support (P=.048) to help those who are further removed from healthy sleep. A virtual coach (P<.001) and video modeling (P=.004) may provide appreciated support to those who are physically less active. PA self-monitoring appealed more to those with an intention to change PA (P=.03). Social comparison and support features are not high on users’ agenda and may not be needed from an engagement point of view. Engagement features may not be very relevant for user engagement but should be examined in future research with a less reflective method. Conclusions The findings of this study provide guidance for the design of digital 24-hour movement behavior interventions. As 24-hour movement guidelines are increasingly being adopted in several countries, our study findings are timely to support the design of interventions to meet these guidelines.

A systematic evaluation of primary headache management apps leveraging behavior change techniques

Cephalalgia ◽  
2021 ◽  
pp. 033310242110535
Author(s):  
Amy E Noser ◽  
Kimberly L Klages ◽  
Kaitlyn L Gamwell ◽  
Caitlin N Brammer ◽  
Kevin A Hommel ◽  
...  
Keyword(s):  
Behavior Change ◽  
Relaxation Training ◽  
Rating Scale ◽  
Mobile App ◽  
Systematic Evaluation ◽  
Evidence Based ◽  
Management Behavior ◽  
Behavior Change Techniques ◽  
Self Monitoring ◽  
Headache Management

Background Mobile health apps have the potential to promote adherence to headache management through the use of evidence-based behavior change techniques (e.g., self-monitoring). While many headache management apps exist, the extent to which these apps include behavior change techniques remains unknown. Thus, the present study systematically evaluated the content and quality of commercially available headache management apps. Methods Headache apps were identified using a systematic search in the Apple App and Google Play stores. A total of 55 apps were evaluated using the taxonomy of behavior change techniques and app quality using the Mobile App Rating Scale. Results Headache management apps included 0–14 behavior change techniques (Mean [M] = 5.89) and 0–8 headache management behavior change techniques (M = 4.29). App quality ranged from 2.84–4.67 (M = 3.73) out of 5.00. Three apps, Migraine Trainer, Easeday: Headache & Migraine, and PainScale, included the highest number of overall and headache management behavior change techniques along with good quality scores. Conclusions While randomized controlled trials are necessary to determine the efficacy of individual headache apps, most existing apps include evidence-based headache management behavior change techniques. Headache apps often focus on either self-monitoring or stress management via relaxation training, suggesting that patients’ needs should be used to inform app selection.

scholarly journals Integrating Exercise Counseling Into the Medical School Curriculum: A Workshop-Based Approach Using Behavior Change Techniques

2017 ◽  
Vol 15 (1) ◽  
pp. 84-107 ◽  
Author(s):  
Andrea M. Brennan ◽  
Katrina A. D’Urzo ◽  
Alyssa M. Fenuta ◽  
Robyn L. Houlden ◽  
Jennifer R. Tomasone
Keyword(s):  
Medical Students ◽  
Behavior Change ◽  
Repeated Measures ◽  
School Curriculum ◽  
Learning Opportunities ◽  
Subjective Norms ◽  
Social Cognitions ◽  
Behavior Change Techniques ◽  
Exercise Counseling ◽  
Perceived Behavior Control

Objective. Physician physical activity (PA) counseling remains low due partly to lack of knowledge, emphasizing the importance of providing learning opportunities to develop competency, given the strong associations between PA and health. This study aimed to describe the behavior change techniques (BCTs) used in an “Exercise Expo” workshop and examine the workshop’s effectiveness for improving social cognitions to discuss exercise with patients. Methods. Second-year medical students (N = 54; Mage ± SD = 25.4 ± 2.95 years) completed questionnaires assessing attitudes, perceived behavior control (PBC), subjective norms, and intentions to provide PA counseling pre- and postworkshop. Repeated-measures analyses of variance evaluated changes in these theory of planned behavior constructs. Results. The most used BCTs included presenting information from credible sources, with opportunities for practicing the behavior and receiving feedback. Significant increases in attitudes, PBC and intentions to discuss PA were observed from pre-post Exercise Expo ( P ≤ .01). No statistically significant differences in subjective norms were observed ( P = .06). Conclusions. The Exercise Expo significantly improved social cognitions for PA counseling among medical students. Future interventions should target improvements in subjective norms to increase the likelihood the workshop improves PA counseling behavior. The evidence supports the usefulness of a workshop-based educational strategy to enhance medical students’ social cognitions for PA counseling.

scholarly journals The Effects of Gamification and Oral Self-Care on Oral Hygiene in Children: Systematic Search in App Stores and Evaluation of Apps (Preprint)

2019 ◽  
Author(s):  
Nino Fijačko ◽  
Lucija Gosak ◽  
Leona Cilar ◽  
Alenka Novšak ◽  
Ruth Masterson Creber ◽  
...  
Keyword(s):  
Public Health ◽  
Behavior Change ◽  
Oral Hygiene ◽  
Rating Scale ◽  
Self Care ◽  
Public Health Problem ◽  
Mobile App ◽  
Evidence Based ◽  
Behavior Change Techniques ◽  
Evidence Based Dentistry

BACKGROUND Poor oral hygiene is a great public health problem worldwide. Oral health care education is a public health priority as the maintenance of oral hygiene is integral to overall health. Maintaining optimal oral hygiene among children is challenging and can be supported by using relevant motivational approaches. OBJECTIVE The primary aim of this study was to identify mobile smartphone apps that include gamification features focused on motivating children to learn, perform, and maintain optimal oral hygiene. METHODS We searched six online app stores using four search terms (“oral hygiene game,” “oral hygiene gamification,” “oral hygiene brush game,” and “oral hygiene brush gamification”). We identified gamification features, identified whether apps were consistent with evidence-based dentistry, performed a quality appraisal with the Mobile App Rating Scale user version (uMARS), and quantified behavior scores (Behavior Change score, uMARS score, and Coventry, Aberdeen, and London-Refined [CALO-RE] score) using three different instruments that measure behavior change. RESULTS Of 612 potentially relevant apps included in the analysis, 17 met the inclusion criteria. On average, apps included 6.87 (SD 4.18) out of 31 possible gamification features. The most frequently used gamification features were time pressure (16/17, 94%), virtual characters (14/17, 82%), and fantasy (13/17, 76%). The most common oral hygiene evidence-based recommendation was brushing time (2-3 minutes), which was identified in 94% (16/17) of apps. The overall mean uMARS score for app quality was high (4.30, SD 0.36), with good mean subjective quality (3.79, SD 0.71) and perceived impact (3.58, SD 0.44). Sufficient behavior change techniques based on three taxonomies were detected in each app. CONCLUSIONS The majority of the analyzed oral hygiene apps included gamification features and behavior change techniques to perform and maintain oral hygiene in children. Overall, the apps contained some educational content consistent with evidence-based dentistry and high-quality background for oral self-care in children; however, there is scope for improvement.

scholarly journals Behavioral Intervention Components Associated With Cost-effectiveness: A Comparison of Six Domains

2021 ◽  
Author(s):  
E Beard ◽  
F Lorencatto ◽  
B Gardner ◽  
S Michie ◽  
L Owen ◽  
...  
Keyword(s):  
Cost Effectiveness ◽  
Behavior Change ◽  
Lower Cost ◽  
Self Regulation ◽  
Cost Effective ◽  
Cost Effectiveness Ratio ◽  
Behavior Change Techniques ◽  
Multiple Health Behaviors ◽  
Behavior Change Interventions ◽  
Multiple Health

Abstract Background To help implement behavior change interventions (BCIs) it is important to be able to characterize their key components and determine their effectiveness. Purpose This study assessed and compared the components of BCIs in terms of intervention functions identified using the Behaviour Change Wheel Framework (BCW) and in terms of their specific behavior change techniques (BCTs) identified using the BCT TaxonomyV1, across six behavioral domains and the association of these with cost-effectiveness. Methods BCIs in 251 studies targeting smoking, diet, exercise, sexual health, alcohol and multiple health behaviors, were specified in terms of their intervention functions and their BCTs, grouped into 16 categories. Associations with cost-effectiveness measured in terms of incremental cost-effectiveness ratio (ICER) upper and lower estimates were determined using regression analysis. Results The most prevalent functions were increasing knowledge through education (72.1%) and imparting skills through training (74.9%). The most prevalent BCT groupings were shaping knowledge (86.5%), changing behavioral antecedents (53.0%), supporting self-regulation (47.7%), and providing social support (44.6%). Intervention functions associated with better cost-effectiveness were those based on training (βlow = −15044.3; p = .002), persuasion (βlow = −19384.9; p = .001; βupp = −25947.6; p &lt; .001) and restriction (βupp = −32286.1; p = .019), and with lower cost-effectiveness were those based on environmental restructuring (β = 15023.9low; p = .033). BCT groupings associated with better cost-effectiveness were goals and planning (βlow = −8537.3; p = .019 and βupp = −12416.9; p = .037) and comparison of behavior (βlow = −13561.9, p = .047 and βupp = −30650.2; p = .006). Those associated with lower cost-effectiveness were natural consequences (βlow = 7729.4; p = .033) and reward and threat (βlow = 20106.7; p = .004). Conclusions BCIs that focused on training, persuasion and restriction may be more cost-effective, as may those that encourage goal setting and comparison of behaviors with others.

Content analysis of behavior change techniques in maternal and infant health apps

2020 ◽  
Author(s):  
Rizwana Biviji ◽  
Joshua R Vest ◽  
Brian E Dixon ◽  
Theresa Cullen ◽  
Christopher A Harle
Keyword(s):  
Decision Making ◽  
Health Education ◽  
Behavior Change ◽  
Infant Health ◽  
Behavior Change Techniques ◽  
Self Monitoring ◽  
Final Sample ◽  
Maternal And Infant Health ◽  
Health Expert ◽  
App Design

Abstract Maternal and infant health (MIH) mobile applications (apps) are increasingly popular and frequently used for health education and decision making. Interventions grounded in theory-based behavior change techniques (BCTs) are shown to be effective in promoting healthy behavior changes. MIH apps have the potential to be useful tools, yet the extent to which they incorporate BCTs is still unknown. The objective of this study was to assess the presence of BCTs in popular MIH apps available in the Apple App and Google Play stores. Twenty-nine popular MIH apps were coded for the presence of 16 BCTs using the mHealth app taxonomy. Popular MIH apps whose purpose was to provide health education or decision-making support to pregnant women or parents/caregivers of infants were included in the final sample. On an average, the reviewed apps included seven BCTs (range 2–16). Techniques such as personalization, review of general or specific goals, macro tailoring, self-monitoring of goals, and health behavior linkages were most frequently present. No differences in the presence of BCTs between paid and free apps were observed. Popular MIH apps typically included only a minority of BCTs found to be useful for health promotion. However, apps developed by healthcare developers incorporated a higher number of BCTs within the app content. Therefore, app developers and policymakers may consider strategies to increase health expert involvement in app design and content delivery.

scholarly journals Gamification and Behavior Change Techniques in Diabetes Self-Management Apps

2019 ◽  
Vol 13 (5) ◽  
pp. 954-958 ◽  
Author(s):  
Lilli Priesterroth ◽  
Jennifer Grammes ◽  
Kimberly Holtz ◽  
Anna Reinwarth ◽  
Thomas Kubiak
Keyword(s):  
Behavior Change ◽  
Diabetes Management ◽  
Self Management ◽  
Systematic Research ◽  
User Engagement ◽  
Inclusion Criteria ◽  
Behavior Change Techniques ◽  
Positive Effects ◽  
And Behavior ◽  
App Design

Background: Diabetes management apps may have positive effects on diabetes self-management. It remains unclear, however, which app features are particularly effective and encourage sustained app usage. Behavior change techniques (BCTs) and gamification are promising approaches to improve user engagement. However, little is known about the frequency BCTs and gamification techniques (GTs) are actually used. This app review aims to provide an overview of BCTs and GTs in current diabetes management apps. Methods: Google’s Play Store was searched for applications using a broad search strategy (keyword: “diabetes”). We limited our research to freely available apps. A total of 56 apps matched the inclusion criteria and were reviewed in terms of the features they offer to support self-management. We used a taxonomy comprising 29 BCTs and 17 GTs to evaluate the applications. Two independent raters tested and evaluated each app. Results: Interrater agreement was high (ICC = .75 for BCTs; ICC = .90 for GTs). An average of 7.4 BCTs (SD = 3.1) and an average of 1.4 out of 17 GTs (SD = 1.6) were implemented in each app. Five out of 29 BCTs accounted for 55.8% of the BCTs identified in total. The GT most often identified was “feedback” and accounted for 50% of the GTs. Conclusions: The potential of BCTs and GTs in diabetes management apps has not been fully exploited yet. Only very restricted sets of BCTs and gamification features were implemented. Systematic research on the efficacy of specific BCTs and GTs is needed to provide further guidance for app design.

scholarly journals Behavior Change Techniques in Wrist-Worn Wearables to Promote Physical Activity: Content Analysis (Preprint)

2020 ◽  
Author(s):  
Peter Düking ◽  
Marie Tafler ◽  
Birgit Wallmann-Sperlich ◽  
Billy Sperlich ◽  
Sonja Kleih
Keyword(s):  
Physical Activity ◽  
Content Analysis ◽  
Behavior Change ◽  
Goal Setting ◽  
Wearable Sensors ◽  
Action Planning ◽  
Noncommunicable Diseases ◽  
Behavior Change Techniques ◽  
Self Monitoring ◽  
Current Behavior

BACKGROUND Decreasing levels of physical activity (PA) increase the incidences of noncommunicable diseases, obesity, and mortality. To counteract these developments, interventions aiming to increase PA are urgently needed. Mobile health (mHealth) solutions such as wearable sensors (wearables) may assist with an improvement in PA. OBJECTIVE The aim of this study is to examine which behavior change techniques (BCTs) are incorporated in currently available commercial high-end wearables that target users’ PA behavior. METHODS The BCTs incorporated in 5 different high-end wearables (Apple Watch Series 3, Garmin Vívoactive 3, Fitbit Versa, Xiaomi Amazfit Stratos 2, and Polar M600) were assessed by 2 researchers using the BCT Taxonomy version 1 (BCTTv1). Effectiveness of the incorporated BCTs in promoting PA behavior was assessed by a content analysis of the existing literature. RESULTS The most common BCTs were goal setting (behavior), action planning, review behavior goal(s), discrepancy between current behavior and goal, feedback on behavior, self-monitoring of behavior, and biofeedback. Fitbit Versa, Garmin Vívoactive 3, Apple Watch Series 3, Polar M600, and Xiaomi Amazfit Stratos 2 incorporated 17, 16, 12, 11, and 11 BCTs, respectively, which are proven to effectively promote PA. CONCLUSIONS Wearables employ different numbers and combinations of BCTs, which might impact their effectiveness in improving PA. To promote PA by employing wearables, we encourage researchers to develop a taxonomy specifically designed to assess BCTs incorporated in wearables. We also encourage manufacturers to customize BCTs based on the targeted populations.

scholarly journals Baby Buddy App for Breastfeeding and Behavior Change: Retrospective Study of the App Using the Behavior Change Wheel (Preprint)

2020 ◽  
Author(s):  
Loretta M Musgrave ◽  
Alison Baum ◽  
Nilushka Perera ◽  
Caroline SE Homer ◽  
Adrienne Gordon
Keyword(s):  
Behavior Change ◽  
Self Efficacy ◽  
Mobile App ◽  
World Health ◽  
Future Research ◽  
Potential Health ◽  
Behavior Change Techniques ◽  
Barriers And Enablers ◽  
Behavior Change Wheel ◽  
The Uk

BACKGROUND Breastfeeding plays a major role in the health of mothers and babies and has the potential to positively shape an individual’s life both in the short and long term. In the United Kingdom (UK), although 81% of women initiate breastfeeding, only 1% of women breastfeed exclusively to 6 months as recommended by the World Health Organization. In the UK, women who are socially disadvantaged and younger are less likely to breastfeed at 6 to 8 weeks postpartum. One strategy that aims to improve these statistics is the Baby Buddy app, which has been designed and implemented by the UK charity Best Beginnings to be a universal intervention to help reduce health inequalities, including those in breastfeeding. OBJECTIVE This study aimed to retrospectively examine the development of Baby Buddy by applying the Behavior Change Wheel (BCW) framework to understand how it might increase breastfeeding self-efficacy, knowledge, and confidence. METHODS Retrospective application of the BCW was completed after the app was developed and embedded into maternity services. A three-stage process evaluation used triangulation methods and formalized tools to gain an understanding of the potential mechanisms and behaviors used in apps that are needed to improve breastfeeding rates in the UK. First, we generated a behavioral analysis by mapping breastfeeding barriers and enablers onto the Capability, Opportunity, and Motivation-Behavior (COM-B) system using documents provided by Best Beginnings. Second, we identified the intervention functions and policy categories used. Third, we linked these with the behavior change techniques identified in the app breastfeeding content using the Behavior Change Techniques Taxonomy (BCTTv1). RESULTS Baby Buddy is a well-designed platform that could be used to change breastfeeding behaviors. Findings from stage one showed that Best Beginnings had defined breastfeeding as a key behavior requiring support and demonstrated a thorough understanding of the context in which breastfeeding occurs, the barriers and enablers of breastfeeding, and the target actions needed to support breastfeeding. In stage two, Best Beginnings had used intervention and policy functions to address the barriers and enablers of breastfeeding. In stage three, Baby Buddy had been assessed for acceptability, practicability, effectiveness, affordability, safety, and equity. Several behavior change techniques that could assist women with decision making around breastfeeding (eg, information about health consequences and credible sources) and possibly affect attitudes and self-efficacy were identified. Of the 39 videos in the app, 19 (49%) addressed physical capabilities related to breastfeeding and demonstrated positive breastfeeding behaviors. CONCLUSIONS Applying a theoretical framework retrospectively to a mobile app is possible and results in useful information to understand potential health benefits and to inform future development. Future research should assess which components and behavioral techniques in the app are most effective in changing behavior and supporting breastfeeding.

scholarly journals A Smartphone-Based Technique to Detect Dynamic User Preferences for Tailoring Behavioral Interventions: Observational Utility Study of Ecological Daily Needs Assessment (Preprint)

2020 ◽  
Author(s):  
Ginger E Nicol ◽  
Amanda R Ricchio ◽  
Christopher L Metts ◽  
Michael D Yingling ◽  
Alex T Ramsey ◽  
...  
Keyword(s):  
Young Adults ◽  
Health Behavior ◽  
Behavior Change ◽  
Needs Assessment ◽  
Mobile Health ◽  
Health Behavior Change ◽  
Mobile App ◽  
User Needs ◽  
Self Monitoring ◽  
Psychiatric Conditions

BACKGROUND Mobile health apps are promising vehicles for delivering scalable health behavior change interventions to populations that are otherwise difficult to reach and engage, such as young adults with psychiatric conditions. To improve uptake and sustain consumer engagement, mobile health interventions need to be responsive to individuals’ needs and preferences, which may change over time. We previously created an ecological daily needs assessment to capture microprocesses influencing user needs and preferences for mobile health treatment adaptation. OBJECTIVE The objective of our study was to test the utility of a needs assessment anchored within a mobile app to capture individualized, contextually relevant user needs and preferences within the framework of a weight management mobile health app. METHODS Participants with an iOS device could download the study app via the study website or links from social media. In this fully remote study, we screened, obtained informed consent from, and enrolled participants through the mobile app. The mobile health framework included daily health goal setting and self-monitoring, with up to 6 daily prompts to determine in-the-moment needs and preferences for mobile health–assisted health behavior change. RESULTS A total of 24 participants downloaded the app and provided e-consent (22 female; 2 male), with 23 participants responding to at least one prompt over 2 weeks. The mean length of engagement was 5.6 (SD 4.7) days, with a mean of 2.8 (1.1) responses per day. We observed individually dynamic needs and preferences, illustrating daily variability within and between individuals. Qualitative feedback indicated preferences for self-adapting features, simplified self-monitoring, and the ability to personalize app-generated message timing and content. CONCLUSIONS The technique provided an individually dynamic and contextually relevant alternative and complement to traditional needs assessment for assessing individually dynamic user needs and preferences during treatment development or adaptation. The results of this utility study suggest the importance of personalization and learning algorithms for sustaining app engagement in young adults with psychiatric conditions. Further study in broader user populations is needed.

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