Recruiting study participants with programming skill is essential for researchers. As programming is not a common skill, recruiting programmers as participants in large numbers is challenging. Platforms like Amazon MTurk or Qualtrics offer to recruit participants with programming knowledge. As this is self-reported, participants without programming experience could still take part, either due to a misunderstanding or to obtain the study compensation. If these participants are not detected, the data quality will suffer. To tackle this, Danilova et al.~\cite{danilova2021you} developed and tested screening tasks to detect non-programmers. Unfortunately, the most reliable screeners were also those that took the most time. Since screeners should take as little time as possible, we examine whether the introduction of time limits allows us to create more efficient (i.e. quicker but still reliable) screeners. Our results show that this is possible and we extend the pool of screeners and make recommendations on how to improve the process.