Journal of Speech, Language, and Hearing Research

Objective: Impaired understanding of noisy or degraded speech is a central feature of listening difficulties (LiD), but the possible causes of these symptoms are wide-ranging. Accordingly, recent research underscores the need to study these deficits using a test battery approach. Event-related potentials are useful objective metrics for studying LiD, but probing function across the speech processing hierarchy using traditional protocols is sequential and unrealistic in clinical settings. The novel chirped speech (Cheech) method combines natural speech with acoustic chirps to overcome these limitations. This study examines its utility for profiling childhood LiD. Methods: Twenty-eight children (15 typically developing, 13 with LiD), aged 8-17 years old, listened to a 17-minute Cheech story and detected a target word within the story via button press while EEG data were collected from 53 scalp sites. Results: Cheech successfully evoked responses from the auditory brainstem response through to the brain's language centers, as reflected by the N400 effect. Unlike TD children, those with LiD demonstrated N400 effects with atypical distributions that favored frontal rather than the typical parietal sites. A trend towards a delayed and reduced amplitude Wave V was also observed. Conclusions: Hierarchical examination of speech processing using Cheech primarily implicates altered language processing as a contributing factor to LiD, with the frontal topography of the N400 effect for those with LiD potentially suggesting a greater reliance on deliberate memory retrieval during the speech perception task. Significance: LiD could arise due to auditory and/or cognitive factors. The present results demonstrate the feasibility of objective, parallel measurement across this hierarchy and point to impaired language processing as a possible mechanism.

Children and adolescents with hearing loss frequently encounter reduced auditory access and delayed language development, factors that may influence the maturation of executive functions. This study examined developmental differences in planning, a core executive function, in 98 children and adolescents with hearing loss or normal hearing aged 7 to18 years using the Tower of London task. Compared to normal hearing peers, participants with hearing loss made more unnecessary moves and rule violations and initiated problem-solving more rapidly, suggesting reduced preplanning efficiency and increased impulsivity. These group differences were most pronounced in adolescents, who showed faster initiation and greater movement inefficiency than age-matched normal hearing participants. Within the hearing loss group, adolescents displayed higher accuracy and longer initiation times than children, reflecting developmental improvements despite persistent gaps relative to hearing peers. Language development age did not alter the main effects. Findings indicate that reduced early auditory and language access may contribute to differences in planning development, highlighting the need for targeted executive functions support in educational and clinical settings for youth with hearing loss.

PurposeSpeech perception is a fundamental part of everyday communication that relies on more than simple identification of words and sentences. Attention and listening engagement both contribute to speech perception, while representing distinct aspects of the listening experience. Attention is typically associated with cognitive focus, whereas listening engagement additionally involves cognitive and affective immersion in sound. Despite their importance, these states remain difficult to disentangle, behaviorally and physiologically. Both have been linked to interpersonal synchronization (the synchronization of biobehavioral signals across individuals), raising questions about what this synchronization actually reflects. MethodIn this study, we disentangled attention and listening engagement by independently manipulating both factors within a single experiment. Thirty participants listened to two simultaneously presented streams of meaningful speech and were instructed to focus on only one. Both attended and unattended stimuli were designed to be either engaging or non-engaging. Neural activity was recorded using EEG, while physiological responses were measured using heart rate and electrodermal activity. ResultsInterpersonal synchronization was computed from neural and bodily signals, alongside a self- report measure of listening engagement and auditory attention decoding (AAD), a neural measure of selective attention. Interpersonal synchronization of all three modalities significantly predicted listening engagement, whereas neural interpersonal synchronization was the only measure that significantly predicted attention. These findings suggest that attention is primarily driven by cognitive processes represented in the brain, while listening engagement additionally involves affective processes that are more strongly reflected in bodily responses. ConclusionsOverall, this study demonstrates that different forms of interpersonal synchronization reflect distinct dimensions of the listening experience and supports interpersonal synchronization as a potential objective marker of listening engagement.

Purpose: There is a long-standing perception that individuals who stutter are less intelligent, with the disfluencies unique to stuttered speech often assumed to be the overt reflection of lower intelligence, despite no supporting evidence. The purpose of the present study was to explore the validity of this assumption by examining the cognitive abilities of adults who stutter compared to the general population using the NIH Toolbox (C) Cognition Battery (NIHTB-CB). Method: Sixty-three adults who stutter completed the NIHTB-CB, which includes seven standardized measures assessing crystallized cognition (Picture Vocabulary, Oral Reading) and fluid cognition (List Sorting Memory Test, Pattern Comparison Processing Speed Test, Flanker Inhibitory Control Test, Dimensional Change Card Sort Test, Picture Sequence Memory Test). The NIHTB-CB generates t-scores adjusted for demographic variables based on a large sample of neurotypical adults. Results: Composite scores of overall cognition for adults who stutter were not statistically equivalent, rather, their scores were higher than the general population. Higher scores were driven by crystallized cognition, with significantly higher scores on Oral Reading subscale. Conclusions: Present findings demonstrate that adults who stutter possess cognitive skills that are comparable to or potentially higher, than the general population. These results challenge the misconception that stuttering reflects diminished intelligence and offer evidence to mitigate stereotype threat.

Intelligible speech disrupts selective auditory attention more than an unintelligible stream. However, low-level acoustic features of intelligible speech are relatively similar to target speech, confounding results. While controlling acoustic similarity and limiting energetic masking, we examined how masker intelligibility affects behavior and electroencephalography (EEG). Normal hearing listeners detected color words within a target stream of randomly timed words while ignoring an ongoing masker. Maskers were either spoken by the same or a different talker and comprised either isochronous sequences of intelligible words or temporally scrambled versions. Scrambled maskers either lacked broadband energy changes over time (Experiment 1) or were amplitude modulated to have the same energy profiles as intelligible, isochronous maskers (Experiment 2). In both experiments, scrambled maskers yielded better performance than intelligible maskers. For intelligible maskers, performance was better for different compared to identical talkers. EEG responses paralleled behavior: target-evoked onset responses were larger for scrambled than for intelligible maskers, particularly for identical talkers. Later target recognition responses were larger for color than other target words but unaffected by masker type or talker. Even when low-level acoustic features were carefully matched, intelligible maskers impaired auditory attention and reduced target-evoked neural responses more than scrambled maskers, implicating early sensory filtering.

Difficulties understanding speech in noise remain a common complaint even among listeners with normal hearing sensitivity, highlighting the need for objective, more effective measures of real-world listening. The goal of this study was to validate the use of a novel, chirped-speech (Cheech) stimulus - continuous, naturally-spoken speech fused with chirps designed to elicit robust auditory evoked potentials - to characterize relationships between speech recognition, listening effort, and auditory neural encoding. Twenty-five normal-hearing adults completed a sentence-recognition task using both original (unmodified) and Cheech-modified AzBio sentence lists in quiet, +3 dB, and -3 dB signal-to-noise ratio (SNR) conditions while neural responses from the brainstem through cortex were recorded simultaneously. Speech recognition remained near ceiling in quiet but declined with decreasing SNR for both original and Cheech stimuli. Compared with clean speech, Cheech-modified speech showed slightly poorer recognition performance as SNR decreased and somewhat higher perceived effort overall. Yet, Cheech was highly effective at evoking auditory responses from the brainstem (auditory brainstem response, ABR) through the cortex (including middle- and late-latency responses, MLR and LLR) even with <5 minutes listening time per condition. Neural responses showed reduced amplitudes and prolonged latencies as SNR decreased. In general, ABR latencies and wave I amplitudes were associated with speech-in-noise recognition performance, whereas cortical responses (MLR Na, Nb, and LLR P1) were associated with subjective workload. These findings show that Cheech-modified speech preserves intelligibility while yielding robust, multilevel neural recordings during sentence perception, offering a promising approach to examine hierarchical auditory processing under ecologically relevant speech-in-noise conditions.

Objective: This study investigated whether plosive consonants carry a perceptual loudness weighting that significantly exceeds that of non-plosive consonants when judged by hearing-impaired listeners. Design: A prospective loudness matching experiment utilizing the method of adjustment. Study Sample: 19 consenting native English speakers (Mean age: 61.4, SD: 16.4) with bilateral mild to moderate high-frequency sensorineural hearing loss, indicative of presbycusis. Stimuli: 13 vowel-consonant-vowel (VCV) nonsense syllables, exclusively utilizing the flanking vowel /u/. Results: Descriptive analysis revealed a strong time-order effect influencing loudness judgments for 7 of the 13 VCV test stimuli. Statistical testing showed no significant didference (P = 0.94) between the relative amplitudes corresponding to the point of equal loudness for plosive-containing versus non-plosive-containing VCV stimuli. However, 6 individual VCV stimuli, containing consonants from 4 separate manners of articulation, produced significant loudness matching data (P < 0.01). Conclusions: The results falsify the hypothesis that plosives, analyzed collectively as a class, possess a heavier perceptual loudness weighting than non-plosive consonants. While 6 individual VCV stimuli indicated potential individual consonantal loudness weightings, these findings must be interpreted cautiously due to the restriction to a single vowel context and the presence of procedural time-order biases.

Background and Objectives: Word-finding difficulty is common in healthy aging and in neurologic disorders, including temporal lobe epilepsy (TLE) and early Alzheimer disease. Standard language measures have limited sensitivity for detecting subtle or longitudinal changes in spontaneous speech. We examined whether natural language processing and acoustic analysis of spoken biographical recall could identify lexical and temporal speech features associated with language and memory performance in TLE. Methods: We conducted a cross-sectional observational study of spoken recall during a Famous Faces biographical memory task. Adults with TLE and healthy controls (HCs) viewed 20 famous faces and spontaneously recalled biographical details. Speech was transcribed and diarized using automated tools. Lexical measures included word counts and lexical index (ratio of rare to common words). Acoustic measures included utterance and pause duration and pause frequency. Features were compared between groups and correlated with neuropsychological measures, including Montreal Cognitive Assessment (MoCA), Boston Naming Test (BNT), delayed recall, education, and biographical recall accuracy Results: Eighty-one adults participated (51 TLE, 30 HCs). Lexical measures did not differ between groups. In TLE, lexical index correlated with BNT performance (rs=0.62) and MoCA score (rs=0.35). Compared with HCs, participants with TLE produced shorter utterances (5.54 {+/-} 2.50 vs. 6.59 {+/-} 2.63; Cohen's d=0.41, 95% CI -0.05 to 0.86, p=0.041), shorter pauses (0.61 {+/-} 0.21 vs 0.67 {+/-} 0.22, Cohen's d=0.29, 95% CI -0.16 to 0.74, p=0.043), and more frequent pauses (10.81 {+/-} 3.30 vs 9.29 {+/-} 3.59, Cohen's d=-0.45, 95% CI -0.90 to 0.01, p=0.036). Higher education was associated with longer utterances, longer pauses, and lower pause frequency, without evidence of a diagnosis-by-education interaction. Faster utterance rate was associated with better biographical recall in both groups, while higher pause rate was associated with worse recall in TLE. Discussion: Speech-derived lexical and temporal features from naturalistic recall capture clinically relevant variation in language and memory-related performance. Although lexical output did not distinguish TLE from HCs, lexical richness tracked naming and global cognition in TLE, while temporal speech features related to recall performance. These findings support the potential of automated speech analysis as a digital behavioral biomarker for word-finding difficulty in neurologic populations.

Adults who stutter can speak fluently when speech is not addressed to another person, but stuttering emerges when they aim to convey information to a listener. The value of the information being conveyed to the listener also affects the likelihood of stuttering. Why should the mere absence of a listener neutralise a profound motor deficit, and why does a word's predictability affect whether it is spoken fluently? To resolve this socio-motor paradox, we develop a computational model of stuttering within an active inference architecture. The model represents the communicative context, including whether a listener is present and whether the agent is speaking or listening. It was designed around two candidate mechanisms for stuttering, a prior for silence and rigid phoneme sequencing precision. Using both, the model produced fluent private speech and more stuttering-like events during social speech. In the same parameter regime, the model also showed more stuttering-like events on words with higher information value, and produced a word-length effect, in which disfluency increased with longer words. To our knowledge, this is the first model of stuttering to generate both the private speech and the information-value effect from inferred communicative context. By representing the listener as a hidden state that makes the sensory consequences of resuming speech ambiguous, the model offers a computational link between social cognition and speech-motor instability, and suggests that speech fluency depends on whether the speaker believes anyone is present. Clinically, it may offer testable hypotheses and a route to personalising treatment, since the same overt severity can arise from different combinations of parameters.

Background Naturalistic audiovisual recordings of caregiver-child interactions contain rich developmental signals. However, extracting interpretable clinical measures requires resource-intensive manual coding. To address this bottleneck, we evaluated natural-language queries for retrieving specific behavioral moments from these recordings, applying multimodal embeddings as an automated evidence-selection layer. Methods We compared three embedding models (Jina Embeddings v5 Omni, LanguageBind, and Wave7B) for natural-language retrieval directly from audio and video streams, bypassing transcript text. We assessed performance across 27 behavioral targets in 277 caregiver-child recordings (14, 24, and 36 months of age) from the Early Head Start Talkbank corpus, yielding 7,479 recording-target queries. Results Jina Embeddings v5 Omni achieved the highest top-10 retrieval success (text-to-audio 38.3%; text-to-video 36.4%), ahead of LanguageBind (37.0%; 34.5%) and Wave7B (36.1%; 35.0%). Across models, retrieval was substantially more successful for common targets than for rare vocal and gestural behaviors, such as pointing and babbling. By analyzing the spoken words within the retrieved audio clips, we found that Jina accurately ranked the children by their relative vocabulary size at each age (Spearman = 0.68, 0.82, and 0.90 at 14, 24, and 36 months). However, the model severely underestimated the total number of unique words each child used throughout the full session. Conclusion Multimodal embeddings can successfully pinpoint important developmental behaviors and speech patterns within lengthy caregiver-child recordings. However, these systems still struggle to locate rare events. Additionally, while they can accurately rank children by relative vocabulary size, they fail to measure a child's complete vocabulary. We conclude that these models are currently best suited for automated evidence-selection to prioritize relevant segments for expert interpretation rather than acting as an independent replacement for manual behavioral coding or language assessment. Improving the detection of infrequent behaviors and validating these models across external datasets are essential next steps before real-world clinical deployment.

Several types of cues contribute to speech recognition in multi-talker environments. In this study, we investigated how talker head-orientation related (THOR) cues and extended high- frequency (EHF; >8kHz) cues affect speech-in-speech recognition for both female and male speech. We examined the THOR benefit associated with a non-facing masker talker head orientation (relative to a facing orientation) as a function of masker talker facing angle. The target talker always faced the listener, whereas co-located maskers were tested with eight different masker head angles, ranging from 0{degrees} (facing the listener) to facing 180{degrees} away. Two filtering conditions were tested: full- band and low-pass filtered at 8 kHz. A THOR benefit was observed at masker head angles greater than 45{degrees}, increasing from 2 dB to 8 dB between angles of 67.5{degrees} and 180{degrees}. This benefit was reduced for low-pass filtered speech. Access to EHF cues improved performance, but only for masker head angles >22.5{degrees}. There was no significant relationship between 16-kHz pure-tone thresholds and performance for young, normal-hearing listeners with good EHF hearing. These findings indicate that listeners benefit from non-facing masker talker head orientations >45{degrees} when the target talker is facing the listener, with greater benefit for larger head angles.

Connected speech is essential for everyday communication, but clinical constraints and patient fatigue limit detailed evaluation in acute stroke (<1-week post-stroke). Bedside assessments may sample discourse but rarely quantify language impairment (LI) in connected speech, leaving patient communication poorly characterized. We analyzed brief story retellings from 86 patients with left-hemisphere stroke (~4 days post-stroke; 63 classified with LI using composite clinical and naming criteria). From transcripts generated with automatic speech recognition, we derived discrete linguistic features and embeddings with Large Language Models (LLMs). An ensemble of embedding-based classifiers distinguished patients with and without LI with 90% balanced accuracy (79% sensitivity, 100% specificity), outperforming independent embedding and discrete-linguistic-based classifiers, showing distinct LLMs contributed complementary information. Adding the discrete-linguistic-based classifier to the ensemble did not improve balanced accuracy but modestly increased sensitivity at the expense of specificity. We provide proof of concept for a fast, largely automated discourse screener of acute LI.

AVATAR therapy is an effective relational therapy for persistent distressing auditory verbal hallucinations (voices). A digital representation of the embodied persecutory voice (avatar) is created and used in a series of dialogues in which the voice hearer is supported to be more assertive and the avatar concedes power. In the first mediation analysis of AVATAR therapy examining the role of power-related constructs, we investigate whether treatment effects on total severity, frequency, and distress of voices are mediated by changes in beliefs about voices and the self, voice relationship appraisals and anxiety. Mediation effects were evaluated in relation to decomposing treatment offer and treatment receipt effects using both Intention to treat (ITT) and Complier Average Causal Effect (CACE) analyses. One hundred and fifty participants from AVATAR1, a randomised control trial (RCT) comparing AVATAR therapy to Supportive Counselling took part in this study, with their baseline and end of treatment (12 weeks) data used. As hypothesised, across both ITT and CACE analyses, reductions in perceived voice omnipotence and increased assertiveness in relation to voices emerged as consistent mediators of AVATAR therapy on reductions in overall severity, frequency and distress of auditory hallucinations compared to SC, whereas voice malevolence, perceived power differential, self-esteem and anxiety did not. Exploratory analysis also indicated that increases in acceptance and autonomy in relation to voices mediated the impact of AVATAR therapy on overall voice severity and distress. This mediation analysis refines our understanding of AVATAR therapy and highlights agency, voice omnipotence and acceptance as intervention targets.

Traditional views assume that pragmatic deficits after stroke, which compromise the interpretation of communicative intentions and non-literal meanings, follow damage to the right hemisphere (RHD), with left-hemisphere damage (LHD) primarily linked to aphasia and structural language impairment. To examine hemispheric contributions to post-stroke pragmatic profiles, we assessed 99 stroke patients (40 LHD, including 14 with aphasia of minimal-to-moderate severity; 59 RHD) and 60 healthy controls with the Assessment of Pragmatic Abilities and Cognitive Substrates (APACS). While stroke patients overall performed worse than controls, LHD and RHD profiles were largely comparable across three converging analyses: (1) permutation tests revealed no hemispheric differences except on the two tasks requiring expressive components (Interview and Figurative Language 2), which in turn lowered the composites (APACS Production and Total); (2) equivalence testing established equivalence for most measures, with only these same tasks and composites remaining inconclusive; and (3) unsupervised clustering did not group patients by lesion side. Theory of Mind was robustly associated with pragmatic performance in both groups, whereas structural language abilities related specifically to LHD performance and general cognition only to RHD. Excluding aphasic LHD patients strengthened the evidence for comparable profiles, indicating that aphasic LHD patients largely drove the residual differences. In conclusion, primary pragmatic impairment, especially in the receptive domain, emerged comparably after LHD and RHD, with the only residual LHD disadvantage limited to tasks demanding open verbal output. These findings challenge the assumption of right-hemispheric specialization for pragmatics, stressing the need for pragmatic assessment in all post-stroke patients.

Introduction Deafness is the most common human sensory deficit. Cochlear implantation is the primary intervention for severe-to-profound deafness. Currently, over 7000 people have bilateral cochlear implants (CIs) in the United Kingdom (UK), most of whom are children. Patient feedback suggests that for children with bilateral CIs, everyday communication is challenging and tiring, with extra effort required to integrate information from two ears, especially in noise, and that current rehabilitation techniques are not engaging, or appropriate to their lifestyles. To address these issues, researchers developed the Both EARS (BEARS) training package comprised of three virtual reality games to improve sound localization and listening in noise. Objectives This protocol describes the design and methodology of a multi-center phase III randomized controlled trial (RCT) to evaluate whether use of the BEARS training package alongside usual care compared to only receiving usual care improves speech-in-noise perception, hearing experiences, vocabulary and quality of life and reduces listening effort in children and young people (aged 8 -16 years (inclusive) with bilateral CIs. Methods This RCT is currently underway in 16 clinical CI departments in National Health Service or university hospitals across the UK. The intervention involves 3 months of spatial-listening training delivered via the BEARS training package in addition to any routine rehabilitation. The control is usual care (routine rehabilitation clinical care pathway). The primary outcome is the difference between the intervention groups in speech-in-noise perception score at 3 months derived from the spatial speech in noise (SSiN-VA) test. Recruitment closes at the end of the day on 31st July 2026, and end of data collection is 31st October 2026. Data analyses will be reported by 31st March 2026. Significance This is the largest known trial of children and young people with bilateral CIs. It will generate high-quality evidence on speech-in-noise outcomes and inform training interventions to improve spatial listening. Trial registration ClinicalTrials.gov registration: NCT05808543; UKs clinical study registry (ISRCTN92454702)

Second language (L2) processing engages both language-specific and domain-general control systems, yet how these systems vary with L2 proficiency remains unclear. We used functional magnetic resonance imaging (fMRI) to examine neural activity during L2 English processing in Korean-English (K-E) bilinguals across three proficiency levels (beginner, intermediate, advanced). Participants performed rhyme and spelling judgement tasks manipulating orthographic-phonological conflict. Behaviourally, conflict conditions reduced accuracy, with proficiency effects observed selectively in the rhyme task. fMRI results showed that conflict processing recruited frontoparietal control regions, including inferior frontal and parietal cortices, accompanied by deactivation in default mode network regions. Critically, proficiency-related effects differed by task. During rhyme judgement, advanced bilinguals showed greater activation in the left supramarginal gyrus (SMG) and cerebellum, whereas intermediate bilinguals exhibited greater recruitment of the left middle orbital gyrus and dorsomedial prefrontal cortex. During spelling judgement, advanced bilinguals showed greater thalamic activation alongside greater deactivation of the right dorsolateral prefrontal cortex. Activity in the left SMG and cerebellum was positively associated with L2 reading score, and cerebellar activity was also associated with rhyme-task performance, whereas right DLPFC activity was negatively associated with the scores. These findings suggest that increasing L2 proficiency is associated less with altered recruitment of core reading regions than with task-specific shifts in the balance between phonological-specialized, subcortical attentional, and domain-general control systems supporting L2 processing.

Language comprehension requires the continuous transformation of speech into a hierarchy of linguistic units, from phonemes to syllables to words. Because speech unfolds rapidly, listeners are thought to predict upcoming content to keep pace. Previous research has provided empirical evidence for predictive processes operating at multiple linguistic levels during naturalistic listening, including words and phonemes. However, it remains unclear whether prediction also operates concurrently at other levels, such as syllabic and phrasal representation. Here we use Mandarin Chinese to examine the neural signatures of predictive processing across multiple levels of linguistic granularity during natural speech comprehension. Mandarin comprises four representational levels: phoneme, sub-syllabic, character and word, and its lexical identity is largely constrained at the sub-syllabic level, potentially redistributing predictive weight across linguistic representations. We recorded magnetoencephalography (MEG) data while 34 native Mandarin speakers (21 females) listened to a naturalistic audiobook and applied linear regression modeling to examine how linguistic features modulated neural activity. We found that the brain activity of listeners segmented speech into hierarchical units, and that surprisal modulated responses simultaneously across sub-syllabic, character and word levels. In contrast to findings from Indo-European languages, however, we did not observe unique surprisal effects at the lowest, phonemic level. Furthermore, the surprisal of lexical tone in Mandarin modulated brain activity only when integrated with its phonological components. These findings suggest that predictive processing during Mandarin speech comprehension operates concurrently across multiple (though not necessarily all) levels of linguistic granularity, with its implementation shaped by language-specific structural properties. Significance statementLanguage comprehension involves segmenting a continuous acoustic stream into multiple linguistic units, from phonemes to words, and generating predictions at these levels. However, direct neural evidence remains limited regarding how segmentation and prediction operate simultaneously across levels of linguistic granularity, particularly outside Indo-European languages. Using temporal response function analysis of magnetoencephalography data recorded during naturalistic Mandarin listening, we show that predictive processing occurs across multiple levels of linguistic granularity. Specifically, we find evidence for prediction-related neural responses at sub-syllabic, character, and word levels, but not a reliable unique effect at the phonemic level. These results indicate that predictive processing also operates during Mandarin speech comprehension, and its neural implementation is shaped by language-specific structural properties.

Background: Adverse drug withdrawal events (ADWEs) are a key safety concern during deprescribing but remain poorly explored in pharmacovigilance systems. Objectives: To identify and compare ADWE signals across drug classes, different drugs within drug classes, and across patient characteristics, countries, and over time. Methods: A case/non-case disproportionality analysis was conducted in FDA-FAERS and EMA-EudraVigilance pharmacovigilance databases, with stratification by age (adults: 18-64, older adults: [&ge;]65), sex (male/female), reporting time (2004-2023 in 5-year intervals), and country (for EMA data). Disproportionality analysis (quantitative signal detection) was used to detect signals between ADWEs and drugs using the proportional reporting rate (PRR[&ge;]2), reporting odds ratio (ROR>1), and information component (IC>0) with case count [&ge;]5. Results: Overall, 158,501 reports (FDA-FAERS 145,514; EMA-EudraVigilance 12,987) included drug-event pairs related to ADWEs. In FDA-FAERS, clobetasone (IC=5.58; PRR=79.18; ROR=176.90) showed the strongest ADWE signals, followed by hydromorphone (4.85; 29.94; 37.37), hydrocodone, and paroxetine. In EMA-EudraVigilance, ethyl loflazepate (IC=6.01; PRR=119.80; ROR=197.53), clobetasone (5.39; 102.73; 155.10), veralipride, and levomethadone had the strongest signals. Most drugs maintained positive ADWE signals in analysis stratified into adults and older adults. However, among the top 10 drugs (based on highest IC values), buprenorphine/naloxone, desvenlafaxine, and baclofen in FDA-FAERS (ICs 4.95-6.05) showed stronger signals in older adults. A sex-based difference was observed, with paroxetine, venlafaxine, and buprenorphine/naloxone showing a stronger positive signal in females in both databases, whereas several opioids had stronger signals in males versus females across both databases. Conclusion: This study suggests ADWE signals for some medications differ by age and sex, potentially indicating different risks for withdrawal effects.

Self-repairs, in-utterance revisions in which a speaker abandons and reformulates their speech, are a promising interpretable marker for speech-based cognitive screening. Detecting them automatically is difficult because a self-repair is defined by its relationship to surrounding speech rather than by fixed lexical cues. On the DementiaBank ADReSS corpus, we compared the capability of generative LLMs under a five-condition prompt ablation against a fine-tuned DistilBERT token classifier at detecting self-repairs. GPT-5 performed best (test F1 = 0.73) and was largely insensitive to prompt design, whereas the LLaMA (open-weight alternative) was both weaker and far more prompt-sensitive (test F1 = 0.47). DistilBERT, nearly 100 times smaller, matched the open-weight LLM at a fraction of the computational cost. These results suggest that a locally deployable encoder, given sufficient in-domain annotation, is a more plausible route to clinical self-repair detection than scaling model size or prompt complexity.

Abstract: Objective: Post-traumatic epilepsy (PTE) is a common sequela of traumatic brain injury (TBI). Research indicates that individuals with PTE tend to experience greater cognitive difficulties compared to those with TBI alone. However, it is plausible that a distinct cognitive profile exists that distinguishes between TBI cases with and without PTE. We aimed to identify longitudinal changes in cognitive measures among TBI patients to better assess the changes associated with developing PTE. Setting: Outpatient. Participants: Prospective subjects who had suffered TBI within 6 months post-injury (TBI-6M, n=32), retrospective subjects with pre-existing PTE diagnoses (PTE, n=20), and healthy control subjects (HC, n=41). Design: We examined cognitive performance for TBI patients within 6 months post-injury, then again within 12 months (TBI-12M, n=26), and within 18-months (TBI-18M, n=25), and compared this with cognitive performance among HC and PTE. Main Measures: Cognitive tests administered yielded 15 test components for analysis. We utilized linear mixed effects modeling to examine cohort-level differences cognitive function. Results: 11/15 tests showed a significant performance deficit in the PTE subjects compared to HC. TBI-6M was not significantly different from the PTE subjects; with time, 9/15 tests showed some degree of recovery in TBI subjects. Tests for information processing speed/working memory and executive function showed strong recovery (TBI-6M vs. TBI-18M, SDMT written: p<0.0001, SDMT oral and COWAT: p<0.001). Tests for visual attention/working memory also showed a smaller but significant recovery (TBI-18M vs. PTE, p<0.05). By contrast, tests for verbal memory [HVLT-R Delayed Recall] showed chronic impairment in TBI (TBI-18M vs HC, p<0.0001). TBI subjects generally trend towards recovery in cognitive performance post-TBI. Conclusions: Information processing speed/working memory are strong indicators for TBI recovery, while auditory learning/memory shows chronic impairment. The stagnation of recovery in cognitive domains typically characterized by robust recovery may correlate with an elevated risk of developing PTE.