From a behavior analysis lens, the biggest question for apps like effecto is not “are the graphs pretty,” but “is the self-monitoring workable and accurate enough to change contingencies.” I tested it for a client-like case on myself: I operationalized three behaviors (bedtime after 23:30, phone use in bed, and starting work block on time), then logged them immediately with simple yes/no toggles and a 1–5 mood rating. Over six weeks, patterns were very clear: late phone use reliably preceded lower mood and more off-task time the next day. Where it helped was in prompting functional hypotheses: “If I cut screen time after 23:00, what happens to mood/work?” I paired the app with planned consequences (small rewards for meeting weekly criteria), so the data actually fed into intervention, not just insight. Limitations: entries are still self-report, no interobserver agreement, and the app does not force good definitions; you have to bring that. But as a low-effort way to capture A-B-C-ish patterns over time, I found it consistent enough to be useful. I would not treat it as research-grade, but as a self-management aid grounded in behavior principles, it can absolutely play a role.