Speech and Non-Speech Measures of Audiovisual Integration are not Correlated

Many natural events generate both visual and auditory signals, and humans are remarkably adept at integrating information from those sources. However, individuals appear to differ markedly in their ability or propensity to combine what they hear with what they see. Individual differences in audiovisual integration have been established using a range of materials, including speech stimuli (seeing and hearing a talker) and simpler audiovisual stimuli (seeing flashes of light combined with tones). Although there are multiple tasks in the literature that are referred to as “measures of audiovisual integration,” the tasks themselves differ widely with respect to both the type of stimuli used (speech versus non-speech) and the nature of the tasks themselves (e.g., some tasks use conflicting auditory and visual stimuli whereas others use congruent stimuli). It is not clear whether these varied tasks are actually measuring the same underlying construct: audiovisual integration. This study tested the relationships among four commonly-used measures of audiovisual integration, two of which use speech stimuli (susceptibility to the McGurk effect and a measure of audiovisual benefit), and two of which use non-speech stimuli (the sound-induced flash illusion and audiovisual integration capacity). We replicated previous work showing large individual differences in each measure but found no significant correlations among any of the measures. These results suggest that tasks that are commonly referred to as measures of audiovisual integration may be tapping into different parts of the same process or different constructs entirely.

Understanding Speech Amid the Jingle and Jangle: Recommendations for Improving Measurement Practices in Listening Effort Research

The latent constructs psychologists study are typically not directly accessible, so researchers must design measurement instruments that are intended to provide insights about those constructs. Construct validation—assessing whether instruments measure what they intend to—is therefore critical for ensuring that the conclusions we draw actually reflect the intended phenomena. Insufficient construct validation can lead to the jingle fallacy—falsely assuming two instruments measure the same construct because the instruments share a name—and the jangle fallacy—falsely assuming two instruments measure different constructs because the instruments have different names. In this paper, we examine construct validation practices in research on listening effort and identify patterns that strongly suggest the presence of jingle and jangle in the literature. We argue that the lack of construct validation for listening effort measures has led to inconsistent findings and hindered our understanding of the construct. We also provide specific recommendations for improving construct validation of listening effort instruments, drawing on the framework laid out in a recent paper on improving measurement practices. Although this paper addresses listening effort, the issues raised and recommendations presented are widely applicable to tasks used in research on auditory perception and cognitive psychology.

Understanding Speech Amid the Jingle and Jangle: Recommendations for Improving Measurement Practices in Listening Effort Research

The latent constructs psychologists study are typically not directly accessible, so researchers must design measurement instruments that are intended to provide insights about those constructs. Construct validation—assessing whether instruments measure what they intend to—is therefore critical for ensuring that the conclusions we draw actually reflect the intended phenomena. Insufficient construct validation can lead to the jingle fallacy—falsely assuming two instruments measure the same construct because the instruments share a name—and the jangle fallacy—falsely assuming two instruments measure different constructs because the instruments have different names. In this paper, we examine construct validation practices in research on listening effort and identify patterns that strongly suggest the presence of jingle and jangle in the literature. We argue that the lack of construct validation for listening effort measures has led to inconsistent findings and hindered our understanding of the construct. We also provide specific recommendations for improving construct validation of listening effort instruments, drawing on the framework laid out in a recent paper on improving measurement practices. Although this paper addresses listening effort, the issues raised and recommendations presented are widely applicable to tasks used in research on auditory perception and cognitive psychology.

Measuring Listening Effort: Convergent Validity, Sensitivity, and Links With Cognitive and Personality Measures

Purpose: Listening effort (LE) describes the attentional or cognitive requirements for successful listening. Despite substantial theoretical and clinical interest in LE, inconsistent operationalization makes it difficult to make generalizations across studies. The aims of this large-scale validation study were to evaluate the convergent validity and sensitivity of commonly used measures of LE and assess how scores on those tasks relate to cognitive and personality variables. Method: Young adults with normal hearing (N = 111) completed 7 tasks designed to measure LE, 5 tests of cognitive ability, and 2 personality measures. Results: Scores on some behavioral LE tasks were moderately intercorrelated but were generally not correlated with subjective and physiological measures of LE, suggesting that these tasks may not be tapping into the same underlying construct. LE measures differed in their sensitivity to changes in signal-to-noise ratio and the extent to which they correlated with cognitive and personality variables. Conclusions: Given that LE measures do not show consistent, strong intercorrelations and differ in their relationships with cognitive and personality predictors, these findings suggest caution in generalizing across studies that use different measures of LE. The results also indicate that people with greater cognitive ability appear to use their resources more efficiently, thereby diminishing the detrimental effects associated with increased background noise during language processing.