We focus on a system in which a set of two-state Markov sources report status update to a common receiver over a shared wireless channel. Inspired by practical IoT networks, we consider three variations of ALOHA as medium access protocol: i) a random approach in which a source transmits regardless of its status, ii) a reactive scheme in which updates are sent only when a source changes state, and iii) a hybrid solution which blends the two possibilities. We consider different criteria to capture the ability of the receiver to maintain an accurate perception of the tracked processes: average age of incorrect information (AoII), probability of missed detection (i.e., of not detecting a source transition), and average duration of intervals over which the receiver lingers with erroneous knowledge. We provide closed form analytical expressions for all the metrics, highlighting non-trivial trade-offs and providing useful protocol design hints.