scholarly journals Using the Intervention Mapping and Behavioral Intervention Technology Frameworks: Development of an mHealth Intervention for Physical Activity and Sedentary Behavior Change

2017 ◽  
Vol 45 (3) ◽  
pp. 331-348 ◽  
Author(s):  
Artur Direito ◽  
Deirdre Walsh ◽  
Moohamad Hinbarji ◽  
Rami Albatal ◽  
Mark Tooley ◽  
...  
Keyword(s):  
Physical Activity ◽  
Behavior Change ◽  
Behavioral Intervention ◽  
Intervention Mapping ◽  
Health Behavior Change ◽  
Smartphone Application ◽  
Sedentary Behaviors ◽  
Mhealth Intervention ◽  
Optimal Behavior ◽  
The Individual

Few interventions to promote physical activity (PA) adapt dynamically to changes in individuals’ behavior. Interventions targeting determinants of behavior are linked with increased effectiveness and should reflect changes in behavior over time. This article describes the application of two frameworks to assist the development of an adaptive evidence-based smartphone-delivered intervention aimed at influencing PA and sedentary behaviors (SB). Intervention mapping was used to identify the determinants influencing uptake of PA and optimal behavior change techniques (BCTs). Behavioral intervention technology was used to translate and operationalize the BCTs and its modes of delivery. The intervention was based on the integrated behavior change model, focused on nine determinants, consisted of 33 BCTs, and included three main components: (1) automated capture of daily PA and SB via an existing smartphone application, (2) classification of the individual into an activity profile according to their PA and SB, and (3) behavior change content delivery in a dynamic fashion via a proof-of-concept application. This article illustrates how two complementary frameworks can be used to guide the development of a mobile health behavior change program. This approach can guide the development of future mHealth programs.

scholarly journals eHealth-Based Behavioral Intervention for Increasing Physical Activity in Persons With Multiple Sclerosis: Fidelity Protocol for a Randomized Controlled Trial (Preprint)

2018 ◽  
Author(s):  
Stephanie L Silveira ◽  
Justin McCroskey ◽  
Brooks C Wingo ◽  
Robert W Motl
Keyword(s):  
Physical Activity ◽  
Multiple Sclerosis ◽  
Behavior Change ◽  
Behavioral Intervention ◽  
Behavioral Interventions ◽  
Health Behavior Change ◽  
Phase Iii ◽  
Monitoring Plan ◽  
Randomized Controlled ◽  
Study Results

BACKGROUND The rate of physical activity is substantially lower in persons with multiple sclerosis (MS) than in the general population. This problem can be reversed through rigorous and reproducible delivery of behavioral interventions that target lifestyle physical activity in MS. These interventions are, in part, based on a series of phase II randomized controlled trials (RCTs) supporting the efficacy of an internet-delivered behavioral intervention, which is based on social cognitive theory (SCT) for increasing physical activity in MS. OBJECTIVE This paper outlines the strategies and monitoring plan developed based on the National Institutes of Health Behavior Change Consortium (NIH BCC) treatment fidelity workgroup that will be implemented in a phase III RCT. METHODS The Behavioral Intervention for Physical Activity in Multiple Sclerosis (BIPAMS) study is a phase III RCT that examines the effectiveness of an internet-delivered behavioral intervention based on SCT and is supported by video calls with a behavioral coach for increasing physical activity in MS. BIPAMS includes a 6-month treatment condition and 6-month follow-up. The BIPAMS fidelity protocol includes the five areas outlined by the NIH BCC. The study design draws on the SCT behavior-change strategy, ensures a consistent dose within groups, and plans for implementation setbacks. Provider training in theory and content will be consistent between groups with monitoring plans in place such as expert auditing of calls to ensure potential drift is addressed. Delivery of treatment will be monitored through the study website and training will focus on avoiding cross-contamination between conditions. Receipt of treatment will be monitored via coaching call notes and website monitoring. Lastly, enactment of treatment for behavioral and cognitive skills will be monitored through coaching call notes among other strategies. The specific strategies and monitoring plans will be consistent between conditions within the constraints of utilizing existing evidence-based interventions. RESULTS Enrollment began in February 2018 and will end in September 2019. The study results will be reported in late 2020. CONCLUSIONS Fidelity-reporting guidelines provided by the NIH BCC were published in 2004, but protocols are scarce. This is the first fidelity-monitoring plan involving an electronic health behavioral intervention for increasing physical activity in MS. This paper provides a model for other researchers utilizing the NIH BCC recommendations to optimize the rigor and reproducibility of behavioral interventions in MS. CLINICALTRIAL ClinicalTrials.gov NCT03490240; https://www.clinicaltrials.gov/ct2/show/NCT03490240. INTERNATIONAL REGISTERED REPOR DERR1-10.2196/12319

scholarly journals Baby Steps: Using Intervention Mapping to Develop a Sustainable Perinatal Physical Activity Healthcare Intervention

2021 ◽  
Vol 18 (11) ◽  
pp. 5869
Author(s):  
Anna M. Dieberger ◽  
Mireille N. M. van Poppel ◽  
Estelle D. Watson
Keyword(s):  
Physical Activity ◽  
Behavior Change ◽  
Community Health ◽  
Community Health Workers ◽  
Health Workers ◽  
Intervention Mapping ◽  
Healthcare Intervention ◽  
Activity Levels ◽  
Major Barrier ◽  
Practical Applications

While the benefits of physical activity (PA) during and after pregnancy have been established, many women do not reach the recommended PA levels during this time. A major barrier found in the literature is a lack of counselling by healthcare providers (HCPs), which is partly caused by the limited knowledge on the topic. The aim of this study was to develop an intervention to improve the promotion of PA by HCPs. We used Intervention Mapping (IM), a theory-based framework to develop an intervention, called “Baby steps”, in a high-income (Austria) and a low-to-middle-income country (South Africa). We applied the following IM steps: (1) A needs assessment to determine the barriers and enablers of PA promotion by HCPs, including a scoping literature review and community needs assessments (qualitative interviews, questionnaires, and focus groups with midwives, obstetricians, and community health workers) to determine the desired outcomes of the intervention. (2) Performance and change objectives were formulated, describing the behaviors that need to change for the intervention to succeed. (3) Based on these objectives, theory-based behavior change techniques were selected, and practical applications were developed. (4) The applications were combined into two evidence-based interventions tailored to each country’s needs. Step (5) and (6) consist of an implementation and evaluation plan, respectively. The intervention is aimed at HCPs, such as midwives and community health workers, consisting of a two-day training course, including practical resources. Combining didactic and interactive education, it addresses both PA knowledge and the skills needed to transfer knowledge and facilitate behavior change. In the future, the intervention’s effect on women’s activity levels during and after pregnancy needs to be studied.

Translating promoting factors and behavior change principles into the blended and technology supported intervention “Foxfit” to stimulate physical activity in children with asthma: Design study (Preprint)

2021 ◽  
Author(s):  
Annette Brons ◽  
Katja Braam ◽  
Aline Broekema ◽  
Annieck Timmerman ◽  
Karel Millenaar ◽  
...  
Keyword(s):  
Physical Activity ◽  
Behavior Change ◽  
Developmental Process ◽  
Intervention Mapping ◽  
Healthcare Providers ◽  
Children With Asthma ◽  
Change Principles ◽  
And Behavior ◽  
The Impact ◽  
Functional Components

BACKGROUND Children with asthma can decrease the impact of their disease by improving their physical activity (PA). However, healthcare providers lack in interventions for children with asthma that effectively increase their PA levels and achieve behavior change regarding PA. A technology supported approach can positively influence PA and physical functioning in children. OBJECTIVE The aim of this study was to develop a technology supported intervention that facilitates healthcare providers in promoting PA for children with asthma and to systematically describe this developmental process. METHODS Intervention mapping (IM) was applied to develop a blended and technology supported intervention in co-creation with children with asthma, their parents, and healthcare providers. According to the IM framework, the following steps were performed: 1) conduct a needs assessment; 2) define the intervention outcome, performance objectives, and change objectives; 3) select theory based intervention methods and strategies; 4) create components of the intervention and conduct pilot tests; 5) create an implementation plan; and 6) create an evaluation plan. RESULTS We developed the blended intervention “Foxfit” that consists of an app with a physical activity monitor (PAM) for children with asthma, and a web-based dashboard for their healthcare provider. The intervention focusses on PA in everyday life to improve social participation. Foxfit contains components based on behavior change principles and gamification: goal setting, rewards, action planning, (self-)monitoring, shaping knowledge, a gamified story, personal coaching and feedback, and a tailored approach. CONCLUSIONS The IM framework was very useful to systematically develop a technology supported intervention and to describe the translational process from scientific evidence, the needs and wishes of future users, and behavior change principles into this intervention. This has led to the technology supported intervention Foxfit that facilitates healthcare providers in promoting PA in children with asthma. The structured description of the development process and functional components shows the way behavior change techniques are incorporated in the intervention. CLINICALTRIAL Dutch Trial Register: NTR6658

scholarly journals Fear of Cancer Recurrence: A Model Examination of Physical Symptoms, Emotional Distress, and Health Behavior Change

2019 ◽  
Vol 15 (9) ◽  
pp. e787-e797 ◽  
Author(s):  
Daniel L. Hall ◽  
Rachel B. Jimenez ◽  
Giselle K. Perez ◽  
Julia Rabin ◽  
Katharine Quain ◽  
...  
Keyword(s):  
Physical Activity ◽  
Health Behavior ◽  
Behavior Change ◽  
Health Behaviors ◽  
Emotional Distress ◽  
Cancer Recurrence ◽  
Health Behavior Change ◽  
Physical Symptoms ◽  
Fear Of Cancer Recurrence ◽  
Fear Of Cancer

PURPOSE: Fear of cancer recurrence is highly prevalent among adult survivors of cancer. The role of fear of recurrence in the emotional distress of survivors of cancer, as well as health behaviors that may directly affect their health, remains unclear. To advance oncology practice, this study sought to examine the extent to which fear of recurrence stemming from physical symptoms accounts for emotional distress in a large sample of adult survivors of cancer and to extend the model to explain postdiagnosis self-reported health behavior change. METHODS: In 2016, 258 survivors of cancer at an academic hospital completed a survey of psychosocial needs. Items assessed physical symptoms (checklist), fear of cancer recurrence (Assessment of Survivor Concerns), emotional distress (anxiety and depressed mood), and health behaviors (current alcohol use, physical activity, diet, and sunscreen use, as well as changes after cancer diagnosis) informed by National Comprehensive Cancer Network survivorship guidelines. Indirect effects regression models accounting for relevant covariates (age and treatment history) used 5,000-iteration bootstrapping. RESULTS: Higher fear of cancer recurrence was associated with greater number of physical symptoms ( P < .001), greater emotional distress ( P < .05), lower moderate or vigorous physical activity ( P < .05), higher sunscreen use ( P < .05), and postdiagnosis increases in alcohol use ( P < .01) and reductions in physical activity ( P < .01). Fear of cancer recurrence models accounted for almost half of the variance in distress of survivors of cancer ( R2 = 0.44, P < .001) and, to a lesser yet significant extent, changes in alcohol consumption ( R2 = 0.09, P < .001) and physical activity ( R2 = 0.06, P = .003). CONCLUSION: Fear of cancer recurrence plays a central role in the emotional distress and key health behaviors of survivors of cancer. These findings support fear of cancer recurrence as a potential target for emotional health and health behavior change interventions.

scholarly journals Promoting Healthy Eating and Physical Activity Behaviors: A Systematic Review of Multiple Health Behavior Change Interventions Among Cancer Survivors

2016 ◽  
Vol 12 (3) ◽  
pp. 184-199 ◽  
Author(s):  
Steve Amireault ◽  
Angela J. Fong ◽  
Catherine M. Sabiston
Keyword(s):  
Physical Activity ◽  
Health Behavior ◽  
Behavior Change ◽  
Cancer Survivors ◽  
Healthy Eating ◽  
Health Behavior Change ◽  
Cochrane Library ◽  
Multiple Health Behavior Change ◽  
The Impact ◽  
Multiple Health

Multiple health behavior change (MHBC) interventions have great potential for enhancing health and well-being following cancer diagnosis and treatment. However, the characteristics and effects of MHBC interventions remain elusive for cancer survivors. The main purpose of this study was to evaluate the effectiveness of MHBC interventions on healthy eating and physical activity behaviors among cancer survivors. A secondary aim was to examine the effect of using a simultaneous and sequential design approach to MHBC (ie, changing both behaviors at the same time or one after the other). Randomized controlled trials reporting the impact of a MHBC intervention on both healthy eating and physical activity behaviors among cancer survivors were retrieved from MEDLINE, Cochrane Library, and PsycINFO. A total of 27 MHBC interventions were identified; most (92.6%) were designed to promote simultaneous change in both behaviors and assessed end-of-treatment effect among breast cancer survivors. MHBC interventions led by nurses or multidisciplinary teams showed the most compelling evidence for small to moderate improvement in both behaviors, with interventions that lasted ≥17 weeks more likely to improve both behaviors. This study identifies research priorities and provides preliminary evidence for clinical decision making and advancements in MHBC intervention design and delivery for clinical oncology.

scholarly journals Evaluating Motivational Interviewing and Habit Formation to Enhance the Effect of Activity Trackers on Healthy Adults’ Activity Levels: Randomized Intervention (Preprint)

2018 ◽  
Author(s):  
Laura D Ellingson ◽  
Jeni E Lansing ◽  
Kathryn J DeShaw ◽  
Karissa L Peyer ◽  
Yang Bai ◽  
...  
Keyword(s):  
Physical Activity ◽  
Behavior Change ◽  
Motivational Interviewing ◽  
Vigorous Physical Activity ◽  
Healthy Adults ◽  
Activity Levels ◽  
Regression Analyses ◽  
Sedentary Behaviors ◽  
Wear Time ◽  
Activity Trackers

BACKGROUND While widely used and endorsed, there is limited evidence supporting the benefits of activity trackers for increasing physical activity; these devices may be more effective when combined with additional strategies that promote sustained behavior change like motivational interviewing (MI) and habit development. OBJECTIVE This study aims to determine the utility of wearable activity trackers alone or in combination with these behavior change strategies for promoting improvements in active and sedentary behaviors. METHODS A sample of 91 adults (48/91 female, 53%) was randomized to receive a Fitbit Charge alone or in combination with MI and habit education for 12 weeks. Active and sedentary behaviors were assessed pre and post using research-grade activity monitors (ActiGraph and activPAL), and the development of habits surrounding the use of the trackers was assessed postintervention with the Self-Reported Habit Index. During the intervention, Fitbit wear time and activity levels were monitored with the activity trackers. Linear regression analyses were used to determine the influence of the trial on outcomes of physical activity and sedentary time. The influence of habits was examined using correlation coefficients relating habits of tracker use (wearing the tracker and checking data on the tracker and associated app) to Fitbit wear time and activity levels during the intervention and at follow-up. RESULTS Regression analyses revealed no significant differences by group in any of the primary outcomes (all P>.05). However, personal characteristics, including lower baseline activity levels (beta=–.49, P=.01) and lack of previous experience with pedometers (beta=–.23, P=.03) were predictive of greater improvements in moderate and vigorous physical activity. Furthermore, for individuals with higher activity levels at the baseline, MI and habit education were more effective for maintaining these activity levels when compared with receiving a Fitbit alone (eg, small increase of ~48 steps/day, d=0.01, vs large decrease of ~1830 steps/day, d=0.95). Finally, habit development was significantly related to steps/day during (r=.30, P=.004) and following the intervention (r=.27, P=.03). CONCLUSIONS This study suggests that activity trackers may have beneficial effects on physical activity in healthy adults, but benefits vary based on individual factors. Furthermore, this study highlights the importance of habit development surrounding the wear and use of activity trackers and the associated software to promote increases in physical activity. CLINICALTRIAL ClinicalTrials.gov NCT03837366; https://clinicaltrials.gov/ct2/show/NCT03837366

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