How is the Behavior Change Technique Content of the NHS Diabetes Prevention Program Understood by Participants? A Qualitative Study of Fidelity, With a Focus on Receipt

Abstract Background The National Health Service (NHS) Diabetes Prevention Program (DPP) is a nationally implemented behavioral intervention for adults at high risk of developing Type 2 diabetes in England, based on a program specification that stipulates inclusion of 19 specific behavior change techniques (BCTs). Previous work has identified drift in fidelity from these NHS England specifications through providers’ program manuals, training, and delivery, especially in relation to BCTs targeting self-regulatory processes. Purpose This qualitative study investigates intervention receipt, i.e., how the self-regulatory BCT content of the NHS-DPP is understood by participants. Methods Twenty participants from eight NHS-DPP locations were interviewed; topics included participants’ understanding of self-monitoring of behavior, goal setting, feedback, problem solving, and action planning. Transcripts were analyzed thematically using the framework method. Results There was a wide variation in understanding among participants for some BCTs, as well as between BCTs. Participants described their understanding of “self-monitoring of behaviors” with ease and valued BCTs focused on outcomes (weight loss). Some participants learned how to set appropriate behavioral goals. Participants struggled to recall “action planning” or “problem solving” or found these techniques challenging to understand, unless additional support was provided (e.g., through group discussion). Conclusions Participants’ lack of understanding of some self-regulatory BCTs is consistent with the drift across fidelity domains previously identified from NHS design specifications. Behavioral interventions should build-in necessary support for participants to help them understand some BCTs such as action planning and problem solving. Alternatively, these self-regulatory BCTs may be intrinsically difficult to use for this population.

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Effects of Mobile Health Prompts on Self-Monitoring and Exercise Behaviors Following a Diabetes Prevention Program: Secondary Analysis From a Randomized Controlled Trial (Preprint)

10.2196/preprints.12956 ◽

2018 ◽

Author(s):

Megan M MacPherson ◽

Kohle J Merry ◽

Sean R Locke ◽

Mary E Jung

Keyword(s):

Mobile Health ◽

Prevention Program ◽

Diabetes Prevention ◽

Secondary Analysis ◽

Diabetes Prevention Program ◽

Exercise Behavior ◽

Moderate Intensity ◽

User Engagement ◽

Self Monitoring ◽

Exercise Behaviors

BACKGROUND A number of mobile health (mHealth) apps exist that focus specifically on promoting exercise behavior. To increase user engagement, prompts, such as text messages, emails, or push notifications, are often used. To date, little research has been done to understand whether, and for how long, these prompts influence exercise behavior. OBJECTIVE This study aimed to assess the impact of prompts on mHealth self-monitoring and self-reported exercise in the days following a prompt and whether these effects differ based on exercise modality. METHODS Of the possible 99 adults at risk for developing type II diabetes who participated in a diabetes prevention program, 69 were included in this secondary analysis. Participants were randomly assigned to 1 of the following 2 exercise conditions: high-intensity interval training or moderate-intensity continuous training. In the year following a brief, community-based diabetes prevention program involving counseling and supervised exercise sessions, all participants self-monitored their daily exercise behaviors on an mHealth app in which they were sent personalized prompts at varying frequencies. mHealth self-monitoring and self-reported exercise data from the app were averaged over 1, 3, 5, and 7 days preceding and following a prompt and subsequently compared using t tests. RESULTS In the year following the diabetes prevention program, self-monitoring (t68=6.82; P<.001; d=0.46) and self-reported exercise (t68=2.16; P=.03; d=0.38) significantly increased in the 3 days following a prompt compared with the 3 days preceding. Prompts were most effective in the first half of the year, and there were no differences in self-monitoring or self-reported exercise behaviors between exercise modalities (P values >.05). In the first half of the year, self-monitoring was significant in the 3 days following a prompt (t68=8.61; P<.001; d=0.60), and self-reported exercise was significant in the 3 days (t68=3.7; P<.001; d=0.37), 5 days (t67=2.15; P=.04; d=0.14), and 7 days (t68=2.46; P=.02; d=0.15) following a prompt, whereas no significant changes were found in the second half of the year. CONCLUSIONS This study provides preliminary evidence regarding the potential influence of prompts on mHealth self-monitoring and self-reported exercise and the duration for which prompts may be effective as exercise behavior change tools. Future studies should determine the optimal prompting frequency for influencing self-reported exercise behaviors. Optimizing prompt frequency can potentially reduce intervention costs and promote user engagement. Furthermore, it can encourage consumers to self-monitor using mHealth technology while ensuring prompts are sent when necessary and effective. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) DERR2-10.2196/11226

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A Qualitative Study on the Perspectives of Latinas Enrolled in a Diabetes Prevention Program: Is the Cost of Prevention Too High?

Journal of Primary Care & Community Health ◽

10.1177/2150132720945423 ◽

2020 ◽

Vol 11 ◽

pp. 215013272094542

Author(s):

Maud Joachim-Célestin ◽

Thelma Gamboa-Maldonado ◽

Hildemar Dos Santos ◽

Susanne B. Montgomery

Keyword(s):

Qualitative Study ◽

Low Income ◽

Behavior Modification ◽

Prevention Program ◽

Diabetes Prevention ◽

Diabetes Prevention Program ◽

Prevention Programs ◽

Theory Approach ◽

Preventive Behaviors ◽

Culturally Adapted

Introduction: Latinas are among the groups most affected by diabetes health disparities, yet they often benefit less from diabetes interventions even when these are culturally adapted. The purpose of this qualitative study was to explore readiness of Latinas enrolled in a diabetes prevention program to adopt recommended preventive behaviors, and to identify factors associated with the adoption and maintenance of these recommended lifestyle changes. Insights gained will be used to inform future efforts at reducing diabetes disparities and the burden of chronic diseases among Latinas. Methods: Nine focus group discussions (FGDs) and 3 key informant interviews (KIIs) were conducted after the completion of a culturally adapted diabetes prevention program led by Latino community health workers. A grounded theory approach by Charmaz informed by the transtheoretical model guided the questions. Discussions and interviews were audio-taped with participants’ permission, transcribed, coded, and themed. Results: Forty low-income Latinas contributed to FGDs and KIIs. Baseline readiness to engage in new behaviors varied. Negative personal and family health events and physician referral impacted most readiness to enroll and to adopt preventive behaviors. Built environment, financial constraints, and threat of social alienation constituted major barriers to behavior adoption and maintenance, while physician involvement, awareness of diabetes complications, and social support partially mitigated these impediments. Conclusions: Our results suggest that timing of enrollment, physician-patient dynamics, and the emotional personal/family cost of behavior modification should all be considered when planning diabetes prevention programs for low-income Latinas. Besides appropriately timing referrals to accessible culturally informed prevention programs, health educators and health care providers should be aware of the potentially negative impact of behavior modification on family dynamics and be prepared to address resulting repercussions. Future research on Latinas should also include and report data on physician involvement, family context, and social determinants of health for more consistent program comparisons.

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Women Veterans’ Experience With a Web-Based Diabetes Prevention Program: A Qualitative Study to Inform Future Practice

Journal of Medical Internet Research ◽

10.2196/jmir.4332 ◽

2015 ◽

Vol 17 (5) ◽

pp. e127 ◽

Cited By ~ 20

Author(s):

Tannaz Moin ◽

Kristyn Ertl ◽

Jessica Schneider ◽

Elena Vasti ◽

Fatima Makki ◽

...

Keyword(s):

Qualitative Study ◽

Prevention Program ◽

Diabetes Prevention ◽

Women Veterans ◽

Diabetes Prevention Program ◽

Web Based ◽

Future Practice

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BRInging the Diabetes prevention program to GEriatric populations (BRIDGE): a feasibility study

Pilot and Feasibility Studies ◽

10.1186/s40814-019-0513-7 ◽

2019 ◽

Vol 5 (1) ◽

Author(s):

Jeannette M. Beasley ◽

Lindsey Kirshner ◽

Judith Wylie-Rosett ◽

Mary Ann Sevick ◽

Laura DeLuca ◽

...

Keyword(s):

Physical Activity ◽

Older Adults ◽

Focus Group ◽

Prevention Program ◽

Behavioral Interventions ◽

Diabetes Prevention ◽

Diabetes Prevention Program ◽

Senior Center ◽

Attendance Rates ◽

Activity Trackers

Abstract Background The purpose of this 6-week intervention was to test the feasibility and acceptability of implementing a telehealth-adapted Diabetes Prevention Program (DPP) at a senior center. Methods Older adults (n = 16) attended weekly interactive webinars. At each measurement time point, participants completed questionnaires covering lifestyle, physical activity, quality of life, and food records and wore physical activity trackers. Qualitative data were gathered from 2 focus groups inviting all 16 participants with 13 and 10 participants attending, respectively. Results Over 2000 senior center members were contacted, approximately 2% (n = 39) responded to the recruitment email, and 16 were recruited into the study. Retention was 75%, and attendance rates averaged 80% across the six intervention sessions. The focus group participants provided positive opinions for most program components, especially the webinar group interaction and using physical activity trackers. Suggestions for improvement included a greater focus on specific needs of older adults (i.e., adapting activities) and placing a greater emphasis on dietary strategies to prevent diabetes. Mean weight loss was 2.9% (2.7 kg [95% CI 1.6, 3.7]; p value = 0.001). Conclusion The feasibility of providing DPP via webinar appears to be high based on the retention and attendance rates. Similar to other behavioral interventions engaging older adults, recruitment rates were low. Acceptability was evidenced by high attendance at the intervention sessions and feedback from participants during focus group sessions. The intervention efficacy should be evaluated based on CDC criteria for program recognition in a larger scale randomized trial. Trial registration NCT03524404. Registered 14 May 2018—retrospectively registered. Trial protocol will be provided by the corresponding author upon request.

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PDB89 PREDICTIVE MODEL FOR BEHAVIOR CHANGE IN A MODIFIED TELEHEALTH DIABETES PREVENTION PROGRAM

Value in Health ◽

10.1016/j.jval.2019.04.637 ◽

2019 ◽

Vol 22 ◽

pp. S155

Author(s):

Y.H. Li ◽

E. Mullette ◽

P.J. Coon

Keyword(s):

Behavior Change ◽

Predictive Model ◽

Prevention Program ◽

Diabetes Prevention ◽

Diabetes Prevention Program

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Drivers of weight loss in a CDC-recognized digital diabetes prevention program

BMJ Open Diabetes Research & Care ◽

10.1136/bmjdrc-2019-001132 ◽

2020 ◽

Vol 8 (1) ◽

pp. e001132 ◽

Cited By ~ 1

Author(s):

Stefanie L Painter ◽

Wei Lu ◽

Jennifer Schneider ◽

Roberta James ◽

Bimal Shah

Keyword(s):

Weight Loss ◽

Regression Analysis ◽

Prevention Program ◽

Diabetes Prevention ◽

Diabetes Prevention Program ◽

Self Monitoring ◽

Using Data ◽

Predictors Of Weight Loss ◽

Design And Methods ◽

The Impact

IntroductionTo investigate the impact of the digital Livongo Diabetes Prevention Program (DPP) on weight at 12 months, understand participants’ self-monitoring behaviors associated with greater weight loss, and evaluate the impact of coaching interactions on more frequent self-monitoring behaviors.Research design and methodsA retrospective analysis was performed using data from 2037 participants enrolled in the Livongo DPP who completed lesson 1 and recorded a starting weight during 2016–2017. Self-monitoring behaviors, including weigh-ins, food logging, activity, and coach–participant interactions, were analyzed at 6 and 12 months. Subgroup analysis was conducted based on those who were highly engaged versus those minimally engaged. Multiple regression analysis was performed using demographic, self-monitoring, and lesson attendance data to determine predictors of weight loss at 12 months and coaching impact on self-monitoring.ResultsParticipants had a mean age of 50 years (SD ±12), with a starting weight of 94 kg (SD ±21), were college-educated (78%), and were female (74%). Overall, participants lost on average 5.1% of their starting weight. Highly engaged participants lost 6.6% of starting body weight, with 25% losing ≥10% at 12 months. Logistic regression analysis showed each submitted food log was associated with 0.23 kg (p<0.05) weight loss, each lesson completed was associated with 0.14 kg (p<0.05) weight loss, and a week of 150 active minutes was associated with 0.1 kg (p<0.01) weight loss. One additional coach–participant message each week was associated with 1.4 more food logs per week, 1.6% increase in weeks with four or more weigh-ins, and a 2.7% increase in weeks with 150 min of activity.ConclusionsFood logging had the largest impact on weight loss, followed by lesson engagement and physical activity. Future studies should examine further opportunities to deliver nutrition-based content to increase and sustain weight loss for DPP.

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Effects of Mobile Health Prompts on Self-Monitoring and Exercise Behaviors Following a Diabetes Prevention Program: Secondary Analysis From a Randomized Controlled Trial

JMIR mhealth and uhealth ◽

10.2196/12956 ◽

2019 ◽

Vol 7 (9) ◽

pp. e12956 ◽

Cited By ~ 3

Author(s):

Megan M MacPherson ◽

Kohle J Merry ◽

Sean R Locke ◽

Mary E Jung

Keyword(s):

Mobile Health ◽

Prevention Program ◽

Diabetes Prevention ◽

Secondary Analysis ◽

Diabetes Prevention Program ◽

Exercise Behavior ◽

Moderate Intensity ◽

User Engagement ◽

Self Monitoring ◽

Exercise Behaviors

Background A number of mobile health (mHealth) apps exist that focus specifically on promoting exercise behavior. To increase user engagement, prompts, such as text messages, emails, or push notifications, are often used. To date, little research has been done to understand whether, and for how long, these prompts influence exercise behavior. Objective This study aimed to assess the impact of prompts on mHealth self-monitoring and self-reported exercise in the days following a prompt and whether these effects differ based on exercise modality. Methods Of the possible 99 adults at risk for developing type II diabetes who participated in a diabetes prevention program, 69 were included in this secondary analysis. Participants were randomly assigned to 1 of the following 2 exercise conditions: high-intensity interval training or moderate-intensity continuous training. In the year following a brief, community-based diabetes prevention program involving counseling and supervised exercise sessions, all participants self-monitored their daily exercise behaviors on an mHealth app in which they were sent personalized prompts at varying frequencies. mHealth self-monitoring and self-reported exercise data from the app were averaged over 1, 3, 5, and 7 days preceding and following a prompt and subsequently compared using t tests. Results In the year following the diabetes prevention program, self-monitoring (t68=6.82; P<.001; d=0.46) and self-reported exercise (t68=2.16; P=.03; d=0.38) significantly increased in the 3 days following a prompt compared with the 3 days preceding. Prompts were most effective in the first half of the year, and there were no differences in self-monitoring or self-reported exercise behaviors between exercise modalities (P values >.05). In the first half of the year, self-monitoring was significant in the 3 days following a prompt (t68=8.61; P<.001; d=0.60), and self-reported exercise was significant in the 3 days (t68=3.7; P<.001; d=0.37), 5 days (t67=2.15; P=.04; d=0.14), and 7 days (t68=2.46; P=.02; d=0.15) following a prompt, whereas no significant changes were found in the second half of the year. Conclusions This study provides preliminary evidence regarding the potential influence of prompts on mHealth self-monitoring and self-reported exercise and the duration for which prompts may be effective as exercise behavior change tools. Future studies should determine the optimal prompting frequency for influencing self-reported exercise behaviors. Optimizing prompt frequency can potentially reduce intervention costs and promote user engagement. Furthermore, it can encourage consumers to self-monitor using mHealth technology while ensuring prompts are sent when necessary and effective. International Registered Report Identifier (IRRID) DERR2-10.2196/11226

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Using the behavior change wheel to develop text messages to promote diet and physical activity adherence following a diabetes prevention program

Translational Behavioral Medicine ◽

10.1093/tbm/ibab058 ◽

2021 ◽

Author(s):

Megan M MacPherson ◽

Kaela D Cranston ◽

Sean R Locke ◽

Jessica E Bourne ◽

Mary E Jung

Keyword(s):

Physical Activity ◽

Behavior Change ◽

Prevention Program ◽

Text Messaging ◽

Diabetes Prevention ◽

Diabetes Prevention Program ◽

Text Messages ◽

Behavior Change Wheel ◽

Diet And Physical Activity ◽

Physical Activity Adherence

Lay Summary Making changes to one’s physical activity and diet can reduce future risk of developing type 2 diabetes. That being said, making life-long changes to complex behaviors such as diet or physical activity is easier said than done. Text messages can be used to improve long-term diet and physical activity changes; however, it can be difficult to identify what should be said in a text message to nudge those behaviors. To improve utility and reduce cost of sending unnecessary messages, theory should be used in developing text messaging content. The current study used the Behavior Change Wheel to develop a library of text messages that can be used to improve diet and physical activity in individuals who have taken part in an effective community-based diabetes prevention program. The Behavior Change Wheel guides researchers to develop real-world interventions based on evidence and theory. Overall, we created a library of 124 theory-based messages which can be further tested following a diabetes prevention program.

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