This study aims to evaluate existing methods for detecting insufficient effort responding (IER) in low-stakes surveys and identify the most effective approaches. The research involved two studies with 725 undergraduates responding to a personality survey online. Study 1 examined the effectiveness of four indices for detecting IER: response time, long string, psychometric antonyms, and individual reliability coefficients. Study 2 demonstrated that these indices measured the same underlying construct and improved psychometric properties after removing IER respondents. Three approaches—response time, psychometric antonyms, and individual reliability—were recommended for future use due to their high specificity and moderate sensitivity. The study highlights the importance of identifying and removing IER to ensure the quality of survey data. IER refers to responses given with low motivation, leading to inaccurate or inconsistent answers. It can manifest as random or nonrandom responses, and may result from inadvertent misinterpretation or intentional disregard of item content. Existing approaches to detect IER include infrequency, inconsistency, pattern, and response time methods. While infrequency approaches can detect random responses, they may also confound IER with impression management or faking. The study concludes that the most effective methods for detecting IER are response time, psychometric antonyms, and individual reliability, which can help researchers improve the validity of their survey data.This study aims to evaluate existing methods for detecting insufficient effort responding (IER) in low-stakes surveys and identify the most effective approaches. The research involved two studies with 725 undergraduates responding to a personality survey online. Study 1 examined the effectiveness of four indices for detecting IER: response time, long string, psychometric antonyms, and individual reliability coefficients. Study 2 demonstrated that these indices measured the same underlying construct and improved psychometric properties after removing IER respondents. Three approaches—response time, psychometric antonyms, and individual reliability—were recommended for future use due to their high specificity and moderate sensitivity. The study highlights the importance of identifying and removing IER to ensure the quality of survey data. IER refers to responses given with low motivation, leading to inaccurate or inconsistent answers. It can manifest as random or nonrandom responses, and may result from inadvertent misinterpretation or intentional disregard of item content. Existing approaches to detect IER include infrequency, inconsistency, pattern, and response time methods. While infrequency approaches can detect random responses, they may also confound IER with impression management or faking. The study concludes that the most effective methods for detecting IER are response time, psychometric antonyms, and individual reliability, which can help researchers improve the validity of their survey data.