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 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 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 Persuasive System Design Principles and Behavior Change Techniques to Stimulate Motivation and Adherence in Electronic Health Interventions to Support Weight Loss Maintenance: Scoping Review (Preprint)

2019 ◽  
Author(s):  
Rikke Aune Asbjørnsen ◽  
Mirjam Lien Smedsrød ◽  
Lise Solberg Nes ◽  
Jobke Wentzel ◽  
Cecilie Varsi ◽  
...  
Keyword(s):  
Weight Loss ◽  
Behavior Change ◽  
Goal Setting ◽  
Weight Loss Maintenance ◽  
Behavior Change Techniques ◽  
Self Monitoring ◽  
Support Weight ◽  
And Behavior ◽  
Weight Loss Interventions

BACKGROUND Maintaining weight after weight loss is a major health challenge, and eHealth (electronic health) solutions may be a way to meet this challenge. Application of behavior change techniques (BCTs) and persuasive system design (PSD) principles in eHealth development may contribute to the design of technologies that positively influence behavior and motivation to support the sustainable health behavior change needed. OBJECTIVE This review aimed to identify BCTs and PSD principles applied in eHealth interventions to support weight loss and weight loss maintenance, as well as techniques and principles applied to stimulate motivation and adherence for long-term weight loss maintenance. METHODS A systematic literature search was conducted in PsycINFO, Ovid MEDLINE (including PubMed), EMBASE, Scopus, Web of Science, and AMED, from January 1, 2007 to June 30, 2018. Arksey and O’Malley’s scoping review methodology was applied. Publications on eHealth interventions were included if focusing on weight loss or weight loss maintenance, in combination with motivation or adherence and behavior change. RESULTS The search identified 317 publications, of which 45 met the inclusion criteria. Of the 45 publications, 11 (24%) focused on weight loss maintenance, and 34 (76%) focused on weight loss. Mobile phones were the most frequently used technology (28/45, 62%). Frequently used wearables were activity trackers (14/45, 31%), as well as other monitoring technologies such as wireless or digital scales (8/45, 18%). All included publications were anchored in behavior change theories. Feedback and monitoring and goals and planning were core behavior change technique clusters applied in the majority of included publications. Social support and associations through prompts and cues to support and maintain new habits were more frequently used in weight loss maintenance than weight loss interventions. In both types of interventions, frequently applied persuasive principles were self-monitoring, goal setting, and feedback. Tailoring, reminders, personalization, and rewards were additional principles frequently applied in weight loss maintenance interventions. Results did not reveal an ideal combination of techniques or principles to stimulate motivation, adherence, and weight loss maintenance. However, the most frequently mentioned individual techniques and principles applied to stimulate motivation were, personalization, simulation, praise, and feedback, whereas associations were frequently mentioned to stimulate adherence. eHealth interventions that found significant effects for weight loss maintenance all applied self-monitoring, feedback, goal setting, and shaping knowledge, combined with a human social support component to support healthy behaviors. CONCLUSIONS To our knowledge, this is the first review examining key BCTs and PSD principles applied in weight loss maintenance interventions compared with those of weight loss interventions. This review identified several techniques and principles applied to stimulate motivation and adherence. Future research should aim to examine which eHealth design combinations can be the most effective in support of long-term behavior change and weight loss maintenance.

scholarly journals Behavior change techniques in mobile applications for sedentary behavior

2018 ◽  
Vol 4 ◽  
pp. 205520761878579 ◽  
Author(s):  
Emily E Dunn ◽  
Heather L Gainforth ◽  
Jennifer E Robertson-Wilson
Keyword(s):  
Physical Activity ◽  
Behavior Change ◽  
Sedentary Behavior ◽  
Mobile Applications ◽  
Health Behavior Change ◽  
Behavior Change Techniques ◽  
Self Monitoring ◽  
Behavior Change Interventions ◽  
And Behavior ◽  
Keyword Searches

Objective Mobile applications (apps) are increasingly being utilized in health behavior change interventions. To determine the presence of underlying behavior change mechanisms, apps for physical activity have been coded for behavior change techniques (BCTs). However, apps for sedentary behavior have yet to be assessed for BCTs. Thus, the purpose of the present study was to review apps designed to decrease sedentary time and determine the presence of BCTs. Methods Systematic searches of the iTunes App and Google Play stores were completed using keyword searches. Two reviewers independently coded free ( n = 36) and paid ( n = 14) app descriptions using a taxonomy of 93 BCTs (December 2016–January 2017). A subsample ( n = 4) of free apps were trialed for one week by the reviewers and coded for the presence of BCTs (February 2017). Results In the free and paid app descriptions, only 10 of 93 BCTs were present with a mean of 2.42 BCTs (range 0–6) per app. The BCTs coded most frequently were “prompts/cues” ( n = 43), “information about health consequences” ( n = 31), and “self-monitoring of behavior” ( n = 17). For the four free apps that were trialed, three additional BCTs were coded that were not coded in the descriptions: “graded tasks,” “focus on past successes,” and “behavior substitution.” Conclusions These sedentary behavior apps have fewer BCTs compared with physical activity apps and traditional (i.e., non-app) physical activity and healthy eating interventions. The present study sheds light on the behavior change potential of sedentary behavior apps and provides practical insight about coding for BCTs in apps.

scholarly journals Key Elements of mHealth Interventions to Successfully Increase Physical Activity: Meta-Regression (Preprint)

2018 ◽  
Author(s):  
Lisa V. Eckerstorfer ◽  
Norbert K. Tanzer ◽  
Claudia Vogrincic-Haselbacher ◽  
Gayannee Kedia ◽  
Hilmar Brohmer ◽  
...  
Keyword(s):  
Physical Activity ◽  
Behavior Change ◽  
Meta Analysis ◽  
General Information ◽  
Group Differences ◽  
Behavior Change Techniques ◽  
Self Monitoring ◽  
Physical Activity Interventions ◽  
Baseline Group ◽  
Monitoring Information

BACKGROUND Mobile technology gives researchers unimagined opportunities to design new interventions to increase physical activity. Unfortunately, it is still unclear which elements are useful to initiate and maintain behavior change. OBJECTIVE In this meta-analysis, we investigated randomized controlled trials of physical activity interventions that were delivered via mobile phone. We analyzed which elements contributed to intervention success. METHODS After searching four databases and science networks for eligible studies, we entered 50 studies with N=5997 participants into a random-effects meta-analysis, controlling for baseline group differences. We also calculated meta-regressions with the most frequently used behavior change techniques (behavioral goals, general information, self-monitoring, information on where and when, and instructions on how to) as moderators. RESULTS We found a small overall effect of the Hedges g=0.29, (95% CI 0.20 to 0.37) which reduced to g=0.22 after correcting for publication bias. In the moderator analyses, behavioral goals and self-monitoring each led to more intervention success. Interventions that used neither behavioral goals nor self-monitoring had a negligible effect of g=0.01, whereas utilizing either technique increased effectiveness by Δg=0.31, but combining them did not provide additional benefits (Δg=0.36). CONCLUSIONS Overall, mHealth interventions to increase physical activity have a small to moderate effect. However, including behavioral goals or self-monitoring can lead to greater intervention success. More research is needed to look at more behavior change techniques and their interactions. Reporting interventions in trial registrations and articles need to be structured and thorough to gain accurate insights. This can be achieved by basing the design or reporting of interventions on taxonomies of behavior change.

Protection of motherhood and infancy in the USSR

1927 ◽  
Vol 23 (6-7) ◽  
pp. 751-751
Author(s):  
E. M. Lepsky
Keyword(s):  
Health Education ◽  
Infant Mortality ◽  
Infant Health ◽  
Education Organization ◽  
Maternal And Infant Health

Until recently, there were no manuals in Russian, in which all the most important questions of maternal and infant health were given with sufficient completeness; there were only works devoted to individual questions, such as infant mortality, health education, organization and work of nurseries, consultations, etc. The book by Dr. Curzon successfully fills this gap. Dr. Curzon's book successfully fills this gap.

scholarly journals Participants’ enactment of behavior change techniques: A call for increased focus on what people do to manage their motivation and behaviour

2018 ◽  
Author(s):  
Nelli Hankonen
Keyword(s):  
Behavior Change ◽  
Intervention Effectiveness ◽  
Intervention Participant ◽  
Behavior Change Techniques ◽  
Self Monitoring ◽  
Intervention Delivery ◽  
Change Behavior ◽  
Starting Point ◽  
Trial Outcomes ◽  
And Behavior

Intervention effectiveness does not only depend on fidelity of intervention delivery, but also the enactment, or use, of behavior change techniques (BCTs) by the participants. For example, it is not sufficient that intervention provider prompts an intervention participant to self-monitor their physical activity, but crucially, the participant enacts self-monitoring. Theoretical and conceptual work integrating various strands of research into ‘what a person can do for oneself’ to change behavior is needed. This paper argues how this would aid in designing for, assessing, and promoting the use individuals’ self-management techniques, and ultimately, our understanding of sustained behavior change. The recently published, integrative compendium of self-enactable techniques to change and self-manage motivation and behavior can act as a useful starting point for this work. An increased focus on the enactment of BCTs would help clarify intervention processes, help explain trial outcomes, and potentially enhance intervention effectiveness.

scholarly journals Evaluación de aplicaciones para la deshabituación tabáquica con elementos de gamificación: elaboración y aplicación de un check-list = Evaluation of gamification apps in smoking cessation: development and application of a check-list

2018 ◽  
Vol 9 (2) ◽  
pp. 152
Author(s):  
Rubén Andújar-Espinosa ◽  
Lourdes Salinero-González ◽  
Manuel Castilla-Martínez ◽  
Carlos Castillo-Quintanilla ◽  
Rocío Ibañez-Meléndez ◽  
...  
Keyword(s):  
Smoking Cessation ◽  
Behavior Change ◽  
Check List ◽  
Tobacco Use Cessation ◽  
Behavior Change Techniques ◽  
Self Monitoring ◽  
Pubmed Search ◽  
And Behavior ◽  
Access Policies

Resumen: Introducción. El uso de la gamificación en salud es una herramienta útil para incrementar la motivación cuan­do se aplica a salud. Los objetivos fueron realizar una revisión sobre evidencias científicas de aplicaciones con elementos de gamificación en salud, identificar características de calidad, elaborar un check-list y aplicarlo a apli­caciones para la deshabituación tabáquica con elementos de gamificación. Métodos. Se realizó una búsqueda bibliográfica en Pubmed sobre gamificación en salud y una búsqueda de apps de cese tabáquico con elementos de gamificación. Se elaboró un check-list para evaluar la calidad, elementos de gamificación y técnicas de cambio de comportamiento utilizados, posteriormente se aplicó a las apps seleccionadas. Resultados. Se incluyeron 14 apps sobre gamificación en deshabituación tabáquica. Solo 4 (28,6%) identificaron fuentes de información fiables y solo 2 (14,3%) informaron sobre políticas de acceso y tratamiento de datos. Las técnicas de cambio de comportamiento identificadas fueron retroalimentación en todas las apps, automonitorización en 12 (85,7%) y cambios basados en los éxitos pasados en 13 (92,9%). Conclusiones. Existen pocos estudios sobre aplica­ciones para la deshabituación tabáquica con elementos de gamificación, con gran variabilidad en metodología, variables medidas y escasas evidencias. La creación de un check-list sobre calidad de las aplicaciones podría disminuir esta variabilidad y mejorar la calidad de los estudios futuros. Son necesarios nuevos estudios.Palabras clave: Deshabituación tabáquica; Aplicaciones móviles; Terapia de comportamiento; Cese tabáquico.Abstract: Introduction. The use of health gamification has proven to be a useful tool to increase motivation and com­mitment when applied to health. The objectives were to review the scientific evidences of health gamification applications, to identify the quality characteristics, to develop a check list to evaluate it and to apply it to the appli­cations in smoking cessation. Methodology. PubMed search on health gamification and a search for smoking cessation apps with gamification elements in the most important application stores. A checklist was developed to evaluate the quality, gamification elements and behavior change techniques used, and was applied to the selected apps. Results. We included 14 apps on gamification in smoking cessation. Only 4 (28.6%) identified reliable sou­rces of information and only 2 (14.3%) reported on access policies and data processing. Behavior change techni­ques identified were feedback in all apps, self-monitoring in 12 (85.7%) and changes based on past successes 13 (92.9%). Conclusions. There are few studies on gamification applications in smoking cessation, with a high variabi­lity in the methodology, measured variables and with little evidence. Creating a checklist on the quality of smoking cessation apps could decrease this variability and improve the quality of future studies. Further studies are needed.Keywords: Tobacco Use Cessation; Mobile Applications; Behavior Therapy; Smoking Cessation.

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.

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