The Use of Self-Monitoring and Technology to Increase Physical Activity: A Review of the Literature

Page et al. (2020) hunted for every study that paired self-monitoring with tech to boost physical activity. They found 19 papers. Fitness trackers were the favorite tool.

The team did not pool numbers. They simply mapped what exists.

Fitness trackers rule the field. Yet no one knows which tracker-plus-plan combos give lasting change.

The review stops at description. It cannot tell you what works best.

Wang et al. (2026) adds a twist. Their meta-analysis of kids and teens with intellectual disabilities shows exercise programs without tech still raise activity and cut couch time. Page says tech is king; Aiwei shows you can win without it.

Older gadgets beat Page to the punch. Wheatley et al. (1978) used a beeping biofeedback box to raise or lower kids' movement in real time. Odom et al. (1986) slipped a sealed recorder into homes to log relaxation minutes. Both proved you can track behavior away from the clinic with simple tools.

Recent sensor papers echo Page's love for wearables. Lotfizadeh et al. (2020) used accelerometers plus machine learning to spot self-injury in autism with 94-99% accuracy. Maharaj et al. (2020) let a Kinect count repetitive moves at 92% accuracy. Gilchrist et al. (2018) and Keintz et al. (2011) showed cheap accelerometers catch hand flapping and body rocking at 80-90% accuracy. Together they prove sensors can watch many behaviors, not just steps.

You can grab a fitness band today, but you still have to test what you pair with it. Try setting a daily step goal plus a small reinforcer your client chooses. Track for one week. If steps rise, keep the package. If not, tweak the goal or the reward and measure again. Let data, not the ad, guide your pick.