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The purpose of this study is to determine the individual and combined effectiveness of two smartphone-based tools for improving physical activity. The first is an individualized and guided goal-setting module, and the second uses "points", "levels", and "badges" to provide instant positive feedback throughout the program. It is hypothesized that both components will be effective, and greater effects will be noted for those receiving both components.
The purpose of the proposed study is to test the efficacy of individual components of a smartphone application designed using theories of human behavior to promote physical activity in low-active adults. Smartphones have become commonplace: approximately two-thirds of adults own a smartphone. They allow for wireless internet connectivity and the ability to communicate via voice and text message at any time. Perhaps most importantly from the perspective of behavior change, the devices are often carried on the person at all times. In recent years researchers have attempted to use these devices to promote physical activity, but continue to encounter a number of barriers. Notably, development in the commercial sector far outpaces the standard randomized controlled trial (RCT) cycle. As a result, researchers utilizing RCT designs find it difficult to publish findings that are relevant to current technology. Additionally, this approach typically examines a full application that includes a package of features, making it difficult to draw conclusions about single intervention components. This has resulted in a commercial sector that produces a large number of physical activity applications that are not evidence based. The present study uses a factorial design to study the individual and combined efficacy of two theory-based modules: A guided goal-setting module, and a points-based feedback system. If successful, the results of this study will help to guide a fast-moving commercial sector toward the development evidence-based applications, which has the potential to yield a large public health impact.
To test these aims, adults will be recruited from Champaign-Urbana, IL, and surrounding communities to participate in a 12-week home-based and self-guided physical activity program. Eligible individuals will complete baseline questionnaires and informed consent online, and will wear an activity monitor for one week. Upon completion of questionnaires, participants will be randomly assigned to one of four conditions:
Following completion of questionnaires, all participants will attend a group-specific orientation session. During this session, trained research staff will provide an introduction to the smartphone application used in the study and all relevant features, as well as a one-on-one physical activity counseling session in which staff members will work with participants to set initial aerobic and non-aerobic physical activity goals. During this time, participants will also be introduced to the goal-directed nature of the MAPS physical activity program. Short term (i.e., weekly) goals will specify the types of aerobic and non-aerobic activities that the individual will engage in, as well as the frequency and duration with which they will engage in these activities. Each participant's initial long-term goal will reflect federal physical activity recommendations. Accordingly, each participant will work toward achieving 150 minutes of moderate intensity aerobic activity, and at least two days of full-body muscle strengthening exercises within the 12-week intervention period. Staff will work with participants to modify these long-term goals based upon the participant's current abilities and physical activity level.
The program will begin on the Sunday following the orientation session. On each Sunday of the program, a new educational module related to basic health and health behavior concepts will be released, and participants will receive a brief email containing information related to the weekly educational content with a reminder to watch the new video. With the exception of the first week, these emails will also provide specific feedback (i.e., minutes of exercise, average intensity, and average enjoyment) from the previous week, and for those with access to guided goal setting the email will also provide feedback and advice based on whether or not the previous week's goals were met. Finally, each email will prompt the participant to revisit their short and long term goals, and adjust them as necessary. At this time, participants with the guided goal setting module will be brought immediately to that module upon entering the app, and will be asked to revisit and reset their short term goals. This process will include a recommended frequency and duration based upon previous performance in the program. Participants will also be prompted to set a new long term goal in the event that they achieved their previous long term goal during the week. For those without guided goal setting, this process will be carried out using traditional printed goal setting worksheets.
During each week, participants will utilize application features to track exercises as they do them, view their feedback, review their weekly goals, and view educational content. On each Thursday, participants will receive a text message update based upon their progress during the week. For those who have not accessed the app during the week, and for those who have not yet tracked activity during the week, a brief prompt will remind them to do so. For those who have tracked activity, a brief message will provide for them an update on the number of sessions and minutes of activity for the week.
During the final week of the program, participants will once again receive the activity monitor via mail and will be asked to wear it for one week. On completion of the 12-week program, participants will receive an email informing them that the program has completed. This email will also provide a link to follow-up questionnaires. At this time, research staff will also contact the participant to schedule a follow-up appointment, which will take no more than 60 minutes. During this appointment, participants will return the activity monitor and will complete a post-study survey assessing their experiences with the MAPS program and with the MAPS research staff.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Group A | Experimental |
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| Group B | Experimental |
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| Group C | Experimental |
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| Group D | Active Comparator |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Group A | Behavioral | This condition receives three study components:
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| Measure | Description | Time Frame |
|---|---|---|
| Change in accelerometer-measured physical activity from baseline to month three | In the week prior to the start of the program and in the twelfth week of the program, participants will wear an actigraph brand accelerometer on their hip during waking hours for seven consecutive days. | Baseline and Three Months |
| Measure | Description | Time Frame |
|---|---|---|
| Change in psychosocial outcomes from baseline to month three as assessed by psychosocial questionnaires. | In the week prior to the start of the program and in the twelfth week of the program, participants will complete a short battery of online psychosocial questionnaires. The investigators will then examined whether study group placement influences levels on any of these variables. | Baseline and Three Months |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Edward McAuley, PhD | University of Illinois at Urbana-Champaign | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University of Illinois at Urbana-Champaign | Urbana | Illinois | 61801 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 1583674 | Background | McAuley E. The role of efficacy cognitions in the prediction of exercise behavior in middle-aged adults. J Behav Med. 1992 Feb;15(1):65-88. doi: 10.1007/BF00848378. | |
| 8315239 | Background | McAuley E, Lox C, Duncan TE. Long-term maintenance of exercise, self-efficacy, and physiological change in older adults. J Gerontol. 1993 Jul;48(4):P218-24. doi: 10.1093/geronj/48.4.p218. |
| Label | URL |
|---|---|
| Exercise Psychology Lab at the University of Illinois Urbana-Champaign | View source |
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| ID | Term |
|---|---|
| D015438 | Health Behavior |
| D057185 | Sedentary Behavior |
| D009043 | Motor Activity |
| ID | Term |
|---|---|
| D001519 | Behavior |
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| Group B | Behavioral | This condition receives two study components:
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| Group C | Behavioral | This condition receives two study components:
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| Group D | Behavioral | This condition receives only the base-level smartphone app. This contains health-related educational content (i.e., weekly videos, additional resources, brief quiz questions), behavioral tracking, and instantaneous graphical feedback. As the intervention is goal drive, these participants will also receive printed goal setting worksheets. |
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| Number of days of program use per participant over the course of the intervention as assessed via program log-in. | The investigators will monitor participant application use by assessing the number of day in which each participant logs into the application over the course of the study period. The investigators will then examine whether study group placement influences the length of time that an individual uses the application. | Three Months |
| Program usability and acceptability | To assess usability and acceptability of the study application, participants will complete a brief program evaluation upon completion of the study. This will assess the ease of use and level of enjoyment associated with the three month program. | Month 3 |
| 19528360 | Background | McAuley E, Hall KS, Motl RW, White SM, Wojcicki TR, Hu L, Doerksen SE. Trajectory of declines in physical activity in community-dwelling older women: social cognitive influences. J Gerontol B Psychol Sci Soc Sci. 2009 Sep;64(5):543-50. doi: 10.1093/geronb/gbp049. Epub 2009 Jun 15. |
| 15990910 | Background | Rogers LQ, Shah P, Dunnington G, Greive A, Shanmugham A, Dawson B, Courneya KS. Social cognitive theory and physical activity during breast cancer treatment. Oncol Nurs Forum. 2005 Jul 1;32(4):807-15. doi: 10.1188/05.ONF.807-815. |
| 19181688 | Background | Wojcicki TR, White SM, McAuley E. Assessing outcome expectations in older adults: the multidimensional outcome expectations for exercise scale. J Gerontol B Psychol Sci Soc Sci. 2009 Jan;64(1):33-40. doi: 10.1093/geronb/gbn032. Epub 2009 Jan 29. |
| 12054320 | Background | Rovniak LS, Anderson ES, Winett RA, Stephens RS. Social cognitive determinants of physical activity in young adults: a prospective structural equation analysis. Ann Behav Med. 2002 Spring;24(2):149-56. doi: 10.1207/S15324796ABM2402_12. |
| 2782727 | Background | Bandura A. Human agency in social cognitive theory. Am Psychol. 1989 Sep;44(9):1175-84. doi: 10.1037/0003-066x.44.9.1175. |
| 25092122 | Background | Collins LM, Dziak JJ, Kugler KC, Trail JB. Factorial experiments: efficient tools for evaluation of intervention components. Am J Prev Med. 2014 Oct;47(4):498-504. doi: 10.1016/j.amepre.2014.06.021. Epub 2014 Aug 1. |
| 17466815 | Background | Collins LM, Murphy SA, Strecher V. The multiphase optimization strategy (MOST) and the sequential multiple assignment randomized trial (SMART): new methods for more potent eHealth interventions. Am J Prev Med. 2007 May;32(5 Suppl):S112-8. doi: 10.1016/j.amepre.2007.01.022. |
| 28255750 | Derived | Fanning J, Roberts S, Hillman CH, Mullen SP, Ritterband L, McAuley E. A smartphone "app"-delivered randomized factorial trial targeting physical activity in adults. J Behav Med. 2017 Oct;40(5):712-729. doi: 10.1007/s10865-017-9838-y. Epub 2017 Mar 2. |