Application of network analysis to identify interactive systems of eating disorder psychopathology.

BACKGROUND: Traditional approaches for the classification of eating disorders (EDs) attribute symptoms to an underlying, latent disease entity. The network approach is an alternative model in which mental disorders are represented as networks of interacting, self-reinforcing symptoms. This project was the first to use network analysis to identify interconnected systems of ED symptoms. METHOD: Adult participants (n = 143; 77.6% women) with a Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5) ED were recruited from the community to take part in a larger ongoing longitudinal study. The Structured Clinical Interview for DSM Disorders (SCID-I) was used to establish diagnoses. An undirected network of ED symptoms was created using items from the Eating Pathology Symptoms Inventory (EPSI) and the R package qgraph. RESULTS: Body checking emerged as the strongest and most important single symptom in the entire network by having the shortest average distance to other symptoms in the network, and by being the most frequent symptom on the path between any two other symptoms. Feeling the need to exercise every day and two symptoms assessing dietary restraint/restricting emerged as 'key players', such that their removal from the network resulted in maximal fracturing of the network into smaller components. CONCLUSIONS: Although cognitive-behavioral therapy for EDs focuses on reducing body checking to promote recovery, our data indicate that amplified efforts to address body checking may produce stronger (and more enduring) effects. Finally, results of the 'key players analysis' suggested that targeting interventions at these key nodes might prevent or slow the cascade of symptoms through the 'network' of ED psychopathology.

Phonetic priming, neighborhood activation, and PARSYN.

Perceptual identification of spoken words in noise is less accurate when the target words are preceded by spoken phonetically related primes (Goldinger, Luce, & Pisoni, 1989). The present investigation replicated and extended this finding. Subjects shadowed target words presented in the clear that were preceded by phonetically related or unrelated primes. In addition, primes were either higher or lower in frequency than the target words. Shadowing latencies were significantly longer for target words preceded by phonetically related primes, but only when the prime-target interstimulus interval was short (50 vs. 500 msec). These results demonstrate that phonetic priming does not depend on target degradation and that it affects processing time. We further demonstrated that PARSYN--a connectionist instantiation of the neighborhood activation model--accurately simulates the observed pattern of priming.

Phonotactics, neighborhood activation, and lexical access for spoken words.

Probabilistic phonotactics refers to the relative frequencies of segments and sequences of segments in spoken words. Neighborhood density refers to the number of words that are phonologically similar to a given word. Despite a positive correlation between phonotactic probability and neighborhood density, nonsense words with high probability segments and sequences are responded to more quickly than nonsense words with low probability segments and sequences, whereas real words occurring in dense similarity neighborhoods are responded to more slowly than real words occurring in sparse similarity neighborhoods. This contradiction may be resolved by hypothesizing that effects of probabilistic phonotactics have a sublexical focus and that effects of similarity neighborhood density have a lexical focus. The implications of this hypothesis for models of spoken word recognition are discussed.

The neighborhood characteristics of malapropisms.

This study examined the phonological neighborhood characteristics (frequency, density, and neighborhood frequency) of 138 malapropisms. Malapropisms are whole word substitutions that are phonologically, but not semantically, related. A statistical analysis of a speech error corpus suggests that neighborhood density and word frequency differentially affected the number of malapropisms. Specifically, a greater number of malapropisms were found among high frequency words with dense neighborhoods than with sparse neighborhoods. Exactly the opposite pattern was found among low frequency words. That is, more errors were found among low frequency words with sparse neighborhoods than with dense neighborhoods. More malapropisms resided in low frequency neighborhoods than in high. The average word frequency, average neighborhood density, and average neighborhood frequency of the malapropisms were significantly lower than the same averages computed from randomly sampled control words. Finally, more target words were replaced by error words that had relatively higher frequency than by error words that had relatively lower frequency. The implications of these findings for models of lexical representation and processing are discussed.

Phonotactics and syllable stress: implications for the processing of spoken nonsense words.

Two experiments using bisyllabic CVCCVC nonsense words that varied in phonotactic probability and stress placement were conducted to examine the influences of phonotactic and metrical information on spoken word recognition. Experiment 1 examined participants' intuitions about the phonological "goodness" of nonsense words. Experiment 2 examined processing times for the same stimuli in a speeded auditory repetition task. The results of both studies provide further evidence that the phonotactic configuration and stress placement of spoken stimuli have important implications for the representation and processing of spoken words.