Implementing human factors in clinical practice

OBJECTIVES: To understand whether aviation-derived human factors training is acceptable and useful to healthcare professionals. To understand whether and how healthcare professionals have been able to implement human factors approaches to patient safety in their own area of clinical practice. METHODS: Qualitative, longitudinal study using semi-structured interviews and focus groups, of a multiprofessional group of UK NHS staff (from the emergency department and operating theatres) who have received aviation-derived human factors training. RESULTS: The human factors training was evaluated positively, and thought to be both acceptable and relevant to practice. However, the staff found it harder to implement what they had learned in their own clinical areas, and this was principally attributed to features of the informal organisational cultures. CONCLUSIONS: In order to successfully apply human factors approaches in hospital, careful consideration needs to be given to the local context and informal culture of clinical practice

CLIMB: Curriculum Learning for Infant-inspired Model Building

We describe our team's contribution to the STRICT-SMALL track of the BabyLM Challenge. The challenge requires training a language model from scratch using only a relatively small training dataset of ten million words. We experiment with three variants of cognitively-motivated curriculum learning and analyze their effect on the performance of the model on linguistic evaluation tasks. In the vocabulary curriculum, we analyze methods for constraining the vocabulary in the early stages of training to simulate cognitively more plausible learning curves. In the data curriculum experiments, we vary the order of the training instances based on i) infant-inspired expectations and ii) the learning behavior of the model. In the objective curriculum, we explore different variations of combining the conventional masked language modeling task with a more coarse-grained word class prediction task to reinforce linguistic generalization capabilities. Our results did not yield consistent improvements over our own non-curriculum learning baseline across a range of linguistic benchmarks; however, we do find marginal gains on select tasks. Our analysis highlights key takeaways for specific combinations of tasks and settings which benefit from our proposed curricula. We moreover determine that careful selection of model architecture, and training hyper-parameters yield substantial improvements over the default baselines provided by the BabyLM challenge

Tracking cortical entrainment in neural activity: auditory processes in human temporal cortex.

A primary objective for cognitive neuroscience is to identify how features of the sensory environment are encoded in neural activity. Current auditory models of loudness perception can be used to make detailed predictions about the neural activity of the cortex as an individual listens to speech. We used two such models (loudness-sones and loudness-phons), varying in their psychophysiological realism, to predict the instantaneous loudness contours produced by 480 isolated words. These two sets of 480 contours were used to search for electrophysiological evidence of loudness processing in whole-brain recordings of electro- and magneto-encephalographic (EMEG) activity, recorded while subjects listened to the words. The technique identified a bilateral sequence of loudness processes, predicted by the more realistic loudness-sones model, that begin in auditory cortex at ~80 ms and subsequently reappear, tracking progressively down the superior temporal sulcus (STS) at lags from 230 to 330 ms. The technique was then extended to search for regions sensitive to the fundamental frequency (F0) of the voiced parts of the speech. It identified a bilateral F0 process in auditory cortex at a lag of ~90 ms, which was not followed by activity in STS. The results suggest that loudness information is being used to guide the analysis of the speech stream as it proceeds beyond auditory cortex down STS toward the temporal pole.This work was supported by an EPSRC grant to William D. Marslen-Wilson and Paula Buttery (EP/F030061/1), an ERC Advanced Grant (Neurolex) to William D. Marslen-Wilson, and by MRC Cognition and Brain Sciences Unit (CBU) funding to William D. Marslen-Wilson (U.1055.04.002.00001.01). Computing resources were provided by the MRC-CBU and the University of Cambridge High Performance Computing Service (http://www.hpc.cam.ac.uk/). Andrew Liu and Phil Woodland helped with the HTK speech recogniser and Russell Thompson with the Matlab code. We thank Asaf Bachrach, Cai Wingfield, Isma Zulfiqar, Alex Woolgar, Jonathan Peelle, Li Su, Caroline Whiting, Olaf Hauk, Matt Davis, Niko Kriegeskorte, Paul Wright, Lorraine Tyler, Rhodri Cusack, Brian Moore, Brian Glasberg, Rik Henson, Howard Bowman, Hideki Kawahara, and Matti Stenroos for invaluable support and suggestions.This is the final published version. The article was originally published in Frontiers in Computational Neuroscience, 10 February 2015 | doi: 10.3389/fncom.2015.0000

CLIMB: Curriculum Learning for Infant-inspired Model Building

We describe our team's contribution to the STRICT-SMALL track of the BabyLM Challenge. The challenge requires training a language model from scratch using only a relatively small training dataset of ten million words. We experiment with three variants of cognitively-motivated curriculum learning and analyze their effect on the performance of the model on linguistic evaluation tasks. In the vocabulary curriculum, we analyze methods for constraining the vocabulary in the early stages of training to simulate cognitively more plausible learning curves. In the data curriculum experiments, we vary the order of the training instances based on i) infant-inspired expectations and ii) the learning behavior of the model. In the objective curriculum, we explore different variations of combining the conventional masked language modeling task with a more coarse-grained word class prediction task to reinforce linguistic generalization capabilities. Our results did not yield consistent improvements over our own non-curriculum learning baseline across a range of linguistic benchmarks; however, we do find marginal gains on select tasks. Our analysis highlights key takeaways for specific combinations of tasks and settings which benefit from our proposed curricula. We moreover determine that careful selection of model architecture, and training hyper-parameters yield substantial improvements over the default baselines provided by the BabyLM challenge

The cross-linguistic performance of word segmentation models over time.

We select three word segmentation models with psycholinguistic foundations - transitional probabilities, the diphone-based segmenter, and PUDDLE - which track phoneme co-occurrence and positional frequencies in input strings, and in the case of PUDDLE build lexical and diphone inventories. The models are evaluated on caregiver utterances in 132 CHILDES corpora representing 28 languages and 11.9 m words. PUDDLE shows the best performance overall, albeit with wide cross-linguistic variation. We explore the reasons for this variation, fitting regression models to performance scores with linguistic properties which capture lexico-phonological characteristics of the input: word length, utterance length, diversity in the lexicon, the frequency of one-word utterances, the regularity of phoneme patterns at word boundaries, and the distribution of diphones in each language. These properties together explain four-tenths of the observed variation in segmentation performance, a strong outcome and a solid foundation for studying further variables which make the segmentation task difficult

Haemophilus influenzae type b reemergence after combination immunization

An increase in Haemophilus influenzae type b (Hib) in British children has been linked to the widespread use of a diphtheria/tetanus/acellular pertussis combination vaccine (DTaP-Hib). We measured anti-polyribosyl-ribitol phos- phate antibody concentration and avidity before and after a Hib booster in 176 children 2–4 years of age who had received 3 doses of DTP-Hib (either DT whole cell pertus- sis-Hib or DTaP-Hib) combination vaccine in infancy. We also measured pharyngeal carriage of Hib. Antibody con- centrations before and avidity indices after vaccination were low (geometric mean concentration 0.46μg/mL, 95% confidence interval [CI] 0.36–0.58; geometric mean avidity index 0.16, 95% CI 0.14–0.18) and inversely related to the number of previous doses of DTaP-Hib (p = 0.02 and p<0.001, respectively). Hib was found in 2.1% (95% CI 0.7%–6.0%) of study participants. Our data support an association between DTaP-Hib vaccine combinations and clinical Hib disease through an effect on antibody concen- tration and avidit

T Regulatory Cells Control Susceptibility to Invasive Pneumococcal Pneumonia in Mice

Streptococcus pneumoniae is an important human pathogen responsible for a spectrum of diseases including pneumonia. Immunological and pro-inflammatory processes induced in the lung during pneumococcal infection are well documented, but little is known about the role played by immunoregulatory cells and cytokines in the control of such responses. We demonstrate considerable differences in the immunomodulatory cytokine transforming growth factor (TGF)-β between the pneumococcal pneumonia resistant BALB/c and susceptible CBA/Ca mouse strains. Immunohistochemistry and flow cytometry reveal higher levels of TGF-β protein in BALB/c lungs during pneumococcal pneumonia that correlates with a rapid rise in lung Foxp3+Helios+ T regulatory cells. These cells have protective functions during pneumococcal pneumonia, because blocking their induction with an inhibitor of TGF-β impairs BALB/c resistance to infection and aids bacterial dissemination from lungs. Conversely, adoptive transfer of T regulatory cells to CBA/Ca mice, prior to infection, prolongs survival and decreases bacterial dissemination from lungs to blood. Importantly, strong T regulatory cell responses also correlate with disease-resistance in outbred MF1 mice, confirming the importance of immunoregulatory cells in controlling protective responses to the pneumococcus. This study provides exciting new evidence for the importance of immunomodulation during pulmonary pneumococcal infection and suggests that TGF-β signalling is a potential target for immunotherapy or drug design

Sex-dependent immune responses to infant vaccination: an individual participant data meta-analysis of antibody and memory B cells.

BACKGROUND: Biological sex can be an important source of variation in infection and immunity and sex-dependent differences in immune response to vaccination have been reported in some studies. METHODS: We conducted an individual participant data meta-analysis of vaccine trials from one research centre, in which vaccines were administered to children under three years of age and immunological parameters measured. Log-transformed antigen-specific antibody and memory B cell results were meta-analysed and differences between girls and boys reported as geometric mean ratios. RESULTS: Antibody and memory B cell data were available from nine trials and 2378 children. Statistically significant differences between girls and boys were observed for diphtheria toxoid, capsular group A, W, and Y meningococcal, and pneumococcal vaccines. No sex-differences were observed for responses to Haemophilus influenzae type b, capsular group C meningococcal or tetanus toxoid vaccines. CONCLUSIONS: In young children, immune responses to vaccines were consistently higher or equivalent in girls compared with boys. In no instance were responses in boys significantly higher than girls. While these data do not indicate differences in protection conferred by immunisation in boys and girls, they do support further consideration of biological sex in planning of clinical trials of vaccines