Mobile Check-In Completion as an Early Indicator of Case Outcomes in Pretrial Supervision

Pretrial supervision has a short window to keep someone on track to resolve their case without going back to jail, and most of what agencies use to decide how closely to supervise a person is set at booking. Published pretrial research has found that static factors like criminal history and prior failures to appear predict better than dynamic ones (Bechtel, Lowenkamp, & Holsinger, 2011), and what we found may challenge that. We wanted to know whether one thing RePath records from day one, the share of scheduled app check-ins a participant completes in their first 30 days, says anything about how the case ends. We looked at Missouri pretrial cases that closed successfully or unsuccessfully between October 1, 2025, and September 30, 2026, and were open at least 30 days (4,833 closures across 65 agencies). Of those, 1,504 cases had check-ins scheduled in the first month. Participants whose cases closed successfully had completed 68.9% of them, and participants whose cases closed unsuccessfully had completed 47.3%, a gap of 21.6 points (95% CI 17.2 to 26.0; Cohen's d = 0.67). People who completed fewer than half closed unsuccessfully 32.9% of the time, compared with 14.2% for everyone else (risk ratio 2.31). Unsuccessful closure was most common among people who completed little or none of their first month check-ins (39.5% at zero) and least common among those who completed nearly all of them (7.9% at 90 to 99%; none of 26 at 100%). Completion in the first month separated the two outcomes with an AUC of .69 (95% CI .66 to .72). That's within the range reported for two validated pretrial risk tools, the Public Safety Assessment (.55 to .68) and the federal Pretrial Risk Assessment (.67 to .73), though the populations, outcomes and timing aren't the same. The gap held up across minimum case lengths, inside individual agencies, with excluded closures recoded either way, and after dropping closures recorded on agency batch days. The study has real limits. It's one state over one year, the outcomes are whatever agency staff entered, technical revocations and new arrests can't be told apart, and the data warehouse didn't have its own quality checks yet when we ran the analysis. With those limits in mind, check-in completion in the first month works as an early indicator that gives agencies something useful to act on, and it doesn't add any new assessment.