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OpenTrials
Completed

NCT Number: NCT03837366

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

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.

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Key information

Conditions

Physical Activity Promotion Behavior Habits Motor Activity

Age range

24 year–60 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

About this study

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.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Not meeting physical activity guidelines

Exclusion criteria

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

Treatment and study plan

Activity tracker and health coaching

Behavioral

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

Other names: Fitbit

Primary outcomes

  1. Steps

    Time frame: 3 months

    Average steps accumulated per day assessed via the activPAL

  2. Moderate and Vigorous Physical Activity

    Time frame: 3 months

    Average minutes per day assessed via a combination of activPAL and ActiGraph

Secondary outcomes

  1. Habit Development

    Time frame: 3 months

    Measured 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.

Sponsors and collaborators

Lead sponsor

Laura Ellingson-Sayen

Other

Registry information

Official study title

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

Important dates

Study start
2015
Primary completion
2016
Study completion
2016
First posted
Feb 12, 2019
Registry last updated
Feb 15, 2019

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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