Defy The Odds: Exercise Forecasting and Motivation Strategies for Prolonged-Sitting Jobs

N/AActive Not RecruitingNCT07475130

University of Wisconsin, Madison20 enrolled

Overview

This study aims to see if a new approach called "Exercise Forecasting" can help people with jobs with a lot of sitting get more active. It also tests if using this method in personal motivational messages makes it easier for them to exercise. The main questions it aims to answer are: * Can "Exercise Forecasting" be used effectively for people in jobs requiring long periods of sitting? * Do these tailored, proactive messages encourage people to exercise more and sit less? Participants will: * Wear the provided smartwatch and answer two questions per day * Receive customized motivational messages

Study Type

INTERVENTIONAL

Allocation

NON_RANDOMIZED

Purpose

PREVENTION

Masking

NONE

Enrollment

Conditions

Prolonged Sitting

Interventions

Eligibility

Sex: ALLMin age: 40 YearsHealthy volunteers:

Medical Language ↔ Plain English

Inclusion Criteria: * Can communicate in English * Currently participate in less than 30 minutes of regular physical activity per week. * Healthy male/female, age \>=40 * Currently working in a prolonged sitting job (e.g., truck driver or office worker). * Have been working in this industry/business for at least one year. Exclusion Criteria: * Have had a heart attack within the past three months * Surgery in the past three months * Recent stroke, mini-stroke/TIA in the past three months * Recent seizure disorder or epilepsy in the past three months * Had an aortic aneurysm before * Have a medical condition or physical limitation that makes physical activity unsafe * Currently meeting or exceeding physical activity guidelines (≥150 minutes/week of moderate-intensity activity or equivalent). * Cannot wear a smartwatch for 30 days. * Do not want to install a study APP in smart phone for 30 days. * Cannot respond to the study APP notification for 30 days.

Outcomes

Primary Outcomes

Correlation between biometric data and self-reported exercise

Biometric data will be collected through the smartwatch. Participants are also asked to self-report what type of exercise they did. These will be correlated to learn whether probability of daily activity can be predicted.

Time frame: 20 days

Acceptability of customized messages

Acceptability will be qualitatively evaluated using one-on-one interviews, with semi-structured interview guides. Acceptability will be analyzed using thematic analyses.

Time frame: 30 days

Feasibility - retention rate

Retention rate will be measured by the number of participants who complete the study.

Time frame: 30 days

Change in level of physical activity when receiving custom motivational messages

Using data collected from the smartwatch, level of physical activity will be compared between pre-motivational messaging and post-motivational messaging.

Time frame: Baseline to 30 days

Change in System Usability Scale (SUS) Score

SUS is a 10-item questionnaire about system usability. It is scored on a 5-point Likert scale, where 1 = strongly disagree and 5 = strongly agree. Scores range from 0-100 (due to reverse scoring and 2.5 multiplication). Higher scores indicate greater usability.