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BACKGROUND: Increased rates of international travel have led to a higher demand for healthcare professionals to provide travel health services. Community-based pharmacists are capable of meeting this need. OBJECTIVE: This study evaluates the impact of pharmacists providing travel health services in a community-based pharmacy on participant understanding and satisfaction of travel education and preparation. METHOD: A trained pharmacist met with participants to review their medical history, travel itinerary, and provide education. Indicated immunizations were administered and the participant's primary care provider was contacted if prescription medications were warranted. A questionnaire was administered before and after the travel health consultation assessing participants perceived understanding of travel health information, satisfaction, and perceived monetary value of the service. Data were collected by 5-point Likert-scale responses, with 5 equivalent to strongly agree. Wilcoxon signed-rank test and descriptive statistics were used for evaluation. Participants were included if they had international travel planned within 12 weeks of the consultation. RESULTS: A total of 12 participants were included. Participant understanding significantly increased for all 5 survey items relating to travel health information with a p value < 0.05 for each item. The largest change was for how to find medical help during international travel (medians and IQR were 3(2-3), and 5(5-5) for pre-and post-consultation, respectively, p = 0.003). Participant satisfaction questions received a median response of 5. Participants' perceived monetary value of the service was a median of $50 (IQR $50-50). CONCLUSION: Pharmacist-led travel health consultations improved participant understanding of travel health information and was of perceived value.

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Predictive coding provides a compelling, unified theory of neural information processing, including for language. However, there is insufficient understanding of how predictive models adapt to changing contextual and environmental demands and the extent to which such adaptive processes differ between individuals. Here, we used electroencephalography (EEG) to track prediction error responses during a naturalistic language processing paradigm. In Experiment 1, 45 native speakers of English listened to a series of short passages. Via a speaker manipulation, we introduced changing intra-experimental adjective order probabilities for two-adjective noun phrases embedded within the passages and investigated whether prediction error responses adapt to reflect these intra-experimental predictive contingencies. To this end, we calculated a novel measure of speaker-based, intra-experimental surprisal ("speaker-based surprisal") as defined on a trial-by-trial basis and by clustering together adjectives with a similar meaning. N400 amplitude at the position of the critical second adjective was used as an outcome measure of prediction error. Results showed that N400 responses attuned to speaker-based surprisal over the course of the experiment, thus indicating that listeners rapidly adapt their predictive models to reflect local environmental contingencies (here: the probability of one type of adjective following another when uttered by a particular speaker). Strikingly, this occurs in spite of the wealth of prior linguistic experience that participants bring to the laboratory. Model adaptation effects were strongest for participants with a steep aperiodic (1/f) slope in resting EEG and low individual alpha frequency (IAF), with idea density (ID) showing a more complex pattern. These results were replicated in a separate sample of 40 participants in Experiment 2, which employed a highly similar design to Experiment 1. Overall, our results suggest that individuals with a steep aperiodic slope adapt their predictive models most strongly to context-specific probabilistic information. Steep aperiodic slope is thought to reflect low neural noise, which in turn may be associated with higher neural gain control and better cognitive control. Individuals with a steep aperiodic slope may thus be able to more effectively and dynamically reconfigure their prediction-related neural networks to meet current task demands. We conclude that predictive mechanisms in language are highly malleable and dynamic, reflecting both the affordances of the present environment as well as intrinsic information processing capabilities of the individual.

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BACKGROUND: Anecdotally, people living with Complex Regional Pain Syndrome (CRPS) often report difficulties in localising their own affected limb when it is out of view. Experimental attempts to investigate this report have used explicit tasks and yielded varied results. METHODS: Here we used a limb localisation task that interrogates implicit mechanisms because we first induce a compelling illusion called the Disappearing Hand Trick (DHT). In the DHT, participants judge their hands to be close together when, in fact, they are far apart. Sixteen volunteers with unilateral upper limb CRPS (mean age 39 ± 12 years, four males), 15 volunteers with non-CRPS persistent hand pain ('pain controls'; mean age 58 ± 13 years, two males) and 29 pain-free volunteers ('pain-free controls'; mean age 36 ± 19 years, 10 males) performed a hand-localisation task after each of three conditions: the DHT illusion and two control conditions in which no illusion was performed. The conditions were repeated twice (one for each hand). We hypothesised that (1) participants with CRPS would perform worse at hand self-localisation than both the control samples; (2) participants with non-CRPS persistent hand pain would perform worse than pain-free controls; (3) participants in both persistent pain groups would perform worse with their affected hand than with their unaffected hand. RESULTS: Our first two hypotheses were not supported. Our third hypothesis was supported -when visually and proprioceptively encoded positions of the hands were incongruent (i.e. after the DHT), relocalisation performance was worse with the affected hand than it was with the unaffected hand. The similar results in hand localisation in the control and pain groups might suggest that, when implicit processes are required, people with CRPS' ability to localise their limb is preserved.

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Artificial grammar learning (AGL) paradigms are used extensively to characterise (neuro)cognitive bases of language learning. However, despite their effectiveness in characterising the capacity to learn complex structured sequences, AGL paradigms lack ecological validity and typically do not account for cross-linguistic differences in sentence comprehension. Here, we describe a new modified miniature language paradigm - Mini Pinyin - that mimics natural language as it is based on an existing language (Mandarin Chinese) and includes both structure and meaning. Mini Pinyin contains a number of cross-linguistic elements, including varying word orders and classifier-noun rules. To evaluate the effectiveness of Mini Pinyin, 76 (mean age = 24.9; 26 female) monolingual native English speakers completed a learning phase followed by a sentence acceptability judgement task. Generalised mixed effects modelling revealed that participants attained a moderate degree of accuracy on the judgement task, with performance scores ranging from 25% to 100% accuracy depending on the word order of the sentence. Further, sentences compatible with the canonical English word order were learned more efficiently than non-canonical word orders. We controlled for inter-individual differences in statistical learning ability, which accounted for ~20% of the variance in performance on the sentence judgement task. We provide stimuli and statistical analysis scripts as open-source resources and discuss how future research can utilise this paradigm to study the neurobiological basis of language learning. Mini Pinyin affords a convenient tool for improving the future of language learning research by building on the parameters of traditional AGL or existing miniature language paradigms.

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