  Many adaptive monitoring schemes adjust the required evidence toward a
hypothesis to control Type I error. This shifts focus away from determining
scientific relevance with an uncompromised degree of evidence. We propose
sequentially monitoring the Second Generation P-Value (SGPV) on repeated
intervals until establishing evidence for scientific relevance (SeqSGPV).
SeqSGPV encompasses existing strategies to monitor Region of Practical
Equivalence (ROPE) or Region of Equivalence (ROE) hypotheses. Hence, our focus
is to formalize sequential SGPV monitoring; establish a novel set of scientific
hypotheses, called PRISM, which is a ROE with a ROPE surrounding the null
hypothesis; and use monitoring frequency and a novel affirmation step to
control Type I error. Under immediate and delayed outcomes, we assess finite
and limiting SeqSGPV operating characteristics when monitoring PRISM, ROPE, and
null-bound ROE hypotheses. In extensive simulations, SeqSGPV PRISM monitoring
reduced wait time for fully sequential monitoring, average sample size, and
reversals of null hypothesis conclusions under the null. With real-world data,
we design a SeqSGPV-monitored randomized trial. SeqSGPV is method-agnostic and
easy to implement. Adjusting monitoring frequency/affirmation and monitoring a
one-sided PRISM synergistically control Type I error. PRISM monitoring and
adjusting monitoring frequency to control Type I error may have application
beyond SeqSGPV.
