Skip to content

Evaluating Motivational Interviewing and Habit Formation to Enhance the Effect of Activity Trackers on Physical Activity

Evaluating Motivational Interviewing and Habit Formation to Enhance the Effect of Activity Trackers on Healthy Adults' Activity Levels: A Randomized Intervention

Status
Completed
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT03837366
Enrollment
91
Registered
2019-02-12
Start date
2015-06-11
Completion date
2016-03-03
Last updated
2019-02-15

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Physical Activity Promotion

Keywords

Activity tracker, Physical Activity, mHealth, habit, Motivational Interviewing

Brief summary

Wearable fitness monitors are increasingly popular but the actual utility of these devices for promoting physical activity behavior is unknown. The purpose is to examine the efficacy of the Fitbit monitor for previously inactive individuals when used alone or following brief training in behavior change strategies and techniques. Psychosocial factors will be assessed and changes in physical activity will be monitored over three months to determine the efficacy of this intervention and to better understand individual differences in effectiveness.

Detailed description

The objective for this pilot study is to determine the efficacy of the Fitbit Charge wearable fitness monitor alone or in combination with additional behavior change strategies for increasing physical activity in inactive adults. A secondary objective is to assess the influence of psychosocial factors (e.g. self-efficacy, self-regulation, habit formation) on the effectiveness of this type of behavior change intervention. The central hypothesis is that use of the Fitbit will increase physical activity from baseline and that adding additional strategies will enhance this effect. This hypothesis is based on previous research demonstrating that continuous self- monitoring (using wearable technology) is effective in promotion of weight-loss in overweight and obese adults. This objective will be addressed through pursuing the following specific aims. Aim 1: To determine the efficacy of using the Fitbit to increase physical activity behaviors and improve health markers in inactive adults. The working hypothesis is that wearing a Fitbit for 3 months will increase physical activity and improve health markers from baseline to follow-up in inactive adults. Aim 2: To compare the efficacy of the Fitbit alone to the Fitbit in combination with behavior change strategies for increasing physical activity and improving psychosocial factors in inactive adults. The working hypothesis is that using the Fitbit along with behavior change strategies will lead to greater improvements in physical activity and psychosocial factors (self- motivation, self-regulation, self-efficacy, and social support) than using the Fitbit alone. Aim 3: To assess the influence of individual differences in psychosocial variables on changes in physical activity over the intervention. The working hypothesis is that higher levels of self- motivation, self-regulation, self-efficacy, and social support at baseline will be predictive of greater improvements in physical activity over the intervention, regardless of group assignment.

Interventions

BEHAVIORALActivity tracker and health coaching

Use of an activity tracker alone or in combination with health coaching on physical activity behaviors.

Sponsors

Laura Ellingson-Sayen
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
PREVENTION
Masking
SINGLE (Outcomes Assessor)

Masking description

Individuals processing outcome data are blinded to experimental condition.

Intervention model description

Participants are randomized to one of two groups. One group received an activity tracker and the other received an activity tracker in combination with Health Coaching.

Eligibility

Sex/Gender
ALL
Age
24 Years to 60 Years
Healthy volunteers
Yes

Inclusion criteria

* Not meeting physical activity guidelines

Exclusion criteria

* Meeting physical activity guidelines * Injury or condition that limits mobility

Design outcomes

Primary

MeasureTime frameDescription
Steps3 monthsAverage steps accumulated per day assessed via the activPAL
Moderate and Vigorous Physical Activity3 monthsAverage minutes per day assessed via a combination of activPAL and ActiGraph

Secondary

MeasureTime frameDescription
Habit Development3 monthsMeasured via the Automaticity Index of the Self-Reported Habit Index. The Self-Reported Habit Index consists of 12 items and the Automaticity Subscale includes 4 of these 12. Each item is scored on a 5-point (0-4) Likert scale with anchors ranging from strongly disagree (0) to strongly agree (4). As such, scores for the Automaticity Index range from 0-16 with higher scores indicating stronger habits.

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 22, 2026