Taxi ROADmAP (Realizing Optimization Around Diet And Physical Activity)

Summary

The researchers will conduct 'Taxi ROADmAP (Realizing Optimization Around Diet And Physical activity)', which also utilizes MOST, and the same 4 obesity intervention components as in SANOS, but targets the overweight/obesity crisis in another at-risk, low socioeconomic status (SES) population, taxi and for-hire vehicle (FHV) drivers (Lyft, Uber, etc.). ROADMAP also utilizes an effectiveness- implementation hybrid type 1 design. Hybrid trials, which blend effectiveness and implementation studies, can lead to more rapid translational uptake and more effective implementation. Taxi and FHV drivers are a growing, multilingual, hard-to-reach, predominantly immigrant and minority essential worker population. There are over 750,000 licensed taxi and FHV drivers in in the U.S. and over 185,000 in New York City (NYC). They have higher rates of overweight/obese range body mass index (BMI) than New Yorkers in general (77% vs 56%) and have high rates of elevated waist circumference, sedentary behavior, poor diets, and health care services underutilization. ROADmAP will test 4 evidence- and theory-based (Social Cognitive Theory \[SCT\]) behavior change intervention components. We will use MOST to identify which of the 4 components contribute most significantly and cost-effectively to weight loss among NYC drivers recruited at workplace health fairs (HFs) and virtually. Objectives are to apply MOST to design an optimized version of a scalable, lifestyle intervention for taxi/FHV drivers, and then to conduct a mixed methods multistakeholder process evaluation to facilitate widespread intervention implementation.

Eligibility

Age range

21+ years

Sex

All

Healthy volunteers

Yes

Interventions

• Behavioral
  Counseling

  In-person individual diet and physical activity (PA) counseling

• Behavioral
  Text Messages

  Thrice-weekly diet/physical activity(PA) text messages

• Behavioral
  Phone calls

  Weekly telephone support

• Behavioral
  Self-monitoring tools

  Self-monitoring tools

Location