A crisis planning and monitoring intervention to reduce compulsory hospital readmissions (FINCH study): protocol for a randomised controlled feasibility study.

BACKGROUND: Rates of compulsory (also known as involuntary) detention under mental health legislation have been rising over several decades in countries including England. Avoiding such detentions should be a high priority given their potentially traumatic nature and departure from usual ethical principles of consent and collaboration. Those who have been detained previously are at high risk of being detained again, and thus a priority group for preventive interventions. In a very sparse literature, interventions based on crisis planning emerge as having more supporting evidence than other approaches to preventing compulsory detention. METHOD: We have adapted and manualised an intervention previously trialled in Zürich Switzerland, aimed at reducing future compulsory detentions among people being discharged following a psychiatric admission that has included a period of compulsory detention. A co-production group including people with relevant lived and clinical experience has co-designed the adaptations to the intervention, drawing on evidence on crisis planning and self-management and on qualitative interviews with service users and clinicians. We will conduct a randomised controlled feasibility trial of the intervention, randomising 80 participants to either the intervention in addition to usual care, or usual care only. Feasibility and acceptability of the intervention and trial procedures will be assessed through process evaluation (including rates of randomisation, recruitment, and retention) and qualitative interviews. We will also assess and report on planned trial outcomes. The planned primary outcome for a full trial is repeat compulsory detention within one year of randomisation, and secondary outcomes include compulsory detention within 2 years, and symptoms, service satisfaction, self-rated recovery, self-management confidence, and service engagement. A health economic evaluation is also included. DISCUSSION: This feasibility study, and any subsequent full trial, will add to a currently limited literature on interventions to prevent involuntary detention, a goal valued highly by service users, carers, clinicians, and policymakers. There are significant potential impediments to recruiting and retaining this group, whose experiences of mental health care have often been negative and traumatising, and who are at high risk of disengagement. TRIAL REGISTRATION: ISRCTN, ISRCTN11627644. Registered 25th May 2022, https://www.isrctn.com/ISRCTN11627644 .

A realist interview study of a participatory public mental health project "#KindnessByPost".

BACKGROUND: #KindnessByPost (KbP) is a participatory public health initiative in which people anonymously send and receive cards containing messages of goodwill with others also taking part in the programme. Quantitative evaluations of KbP consistently find evidence of improvements to people's mental wellbeing and feelings of loneliness after participation and three months later. Our aim in the present study is to develop a programme theory of KbP, which describes for whom the KbP intervention improves mental wellbeing, other reported impacts, in which contexts it has these effects, and the mechanisms by which it works. METHODS: We use a realist interviewing methodology to develop the programme theory. We conducted a focus group with the KbP executive team, and 20 one-to-one interviews with KbP participants. During analysis, a co-production working group iteratively developed a Theory of Change model comprising context-mechanism-outcome statements [CMOs] to map out the mechanisms present in KbP. RESULTS: We developed 145 CMO statements, which we condensed and categorized into 32 overarching CMOs across nine thematic topics: access to scheme; pathways to involvement; resources; culture; giving post; receiving post; content of received post; community; long term impact. These CMOs set out pathways through which KbP benefited participants, including from doing something kind for someone else, of receiving post and appreciating the effort that went into it, and from the creative process of creating post and writing the messages inside them. Effects were sustained in part through people keeping the cards and through the social media communities that emerged around KbP. DISCUSSION: Both giving and receiving post and the sense of community benefited participants and improved their mood and feelings of connectedness with others. Connection with a stranger, rather than friends or family, was also an important feature of the initiative for participants. Our wide range of CMO pathways by which KbP produced positive outcomes may mean that the intervention is applicable or adaptable across many communities and settings. Taken together with evidence from the quantitative evaluations, KbP is potentially an effective, low-cost, and highly scalable public health intervention for reducing loneliness and improving wellbeing.

Computational Modeling of Stereotype Content in Text.

Stereotypes are encountered every day, in interpersonal communication as well as in entertainment, news stories, and on social media. In this study, we present a computational method to mine large, naturally occurring datasets of text for sentences that express perceptions of a social group of interest, and then map these sentences to the two-dimensional plane of perceived warmth and competence for comparison and interpretation. This framework is grounded in established social psychological theory, and validated against both expert annotation and crowd-sourced stereotype data. Additionally, we present two case studies of how the model might be used to answer questions using data "in-the-wild," by collecting Twitter data about women and older adults. Using the data about women, we are able to observe how sub-categories of women (e.g., Black women and white women) are described similarly and differently from each other, and from the superordinate group of women in general. Using the data about older adults, we show evidence that the terms people use to label a group (e.g., old people vs. senior citizens) are associated with different stereotype content. We propose that this model can be used by other researchers to explore questions of how stereotypes are expressed in various large text corpora.

Epidermal Carcinoma of the Conchal Bowl: Creation of a Multidisciplinary Pathway Approach.

BACKGROUND: Malignant neoplasms of the auricle make up 6% of all skin cancers. Management of cutaneous neoplasms of the conchal bowl presents a unique challenge in visualizing and defining margins that may extend into the external auditory canal (EAC). OBJECTIVES: The objective of this study was to create a multidisciplinary pathway for cutaneous carcinoma of the conchal bowl extending into the EAC. METHODS: We present a series of patients that were referred to dermatology or otolaryngology, with cutaneous neoplasms arising in the conchal bowl. A consensus approach from otolaryngology and dermatology, for evaluation and treatment, was created based on evaluation of these cases, and review of the otolaryngology and dermatology literature, in collaboration between the two specialties. RESULTS: Initial evaluation should be done by both dermatology and otolaryngology, with otomicroscopic evaluation of the canal. Imaging is recommended for lesions that approach the EAC, for bony and soft tissue spread. Excision of the tumor with Mohs micrographic surgery to achieve clearance in the conchal bowl should be performed initially. If extension into the external auditory meatus is present, otolaryngology would proceed with en bloc resection. Repair is dictated by the defect, with both specialties involved in follow-up. CONCLUSIONS: In collaboration between dermatology and otolaryngology, and following review of the literature, a pathway was created to manage skin cancer of the conchal bowl. This resulted in a stepwise approach for evaluation and management, ensuring that patients have a streamlined pathway for the treatment of these lesions.

Predicting MCI Status From Multimodal Language Data Using Cascaded Classifiers.

Recent work has indicated the potential utility of automated language analysis for the detection of mild cognitive impairment (MCI). Most studies combining language processing and machine learning for the prediction of MCI focus on a single language task; here, we consider a cascaded approach to combine data from multiple language tasks. A cohort of 26 MCI participants and 29 healthy controls completed three language tasks: picture description, reading silently, and reading aloud. Information from each task is captured through different modes (audio, text, eye-tracking, and comprehension questions). Features are extracted from each mode, and used to train a series of cascaded classifiers which output predictions at the level of features, modes, tasks, and finally at the overall session level. The best classification result is achieved through combining the data at the task level (AUC = 0.88, accuracy = 0.83). This outperforms a classifier trained on neuropsychological test scores (AUC = 0.75, accuracy = 0.65) as well as the "early fusion" approach to multimodal classification (AUC = 0.79, accuracy = 0.70). By combining the predictions from the multimodal language classifier and the neuropsychological classifier, this result can be further improved to AUC = 0.90 and accuracy = 0.84. In a correlation analysis, language classifier predictions are found to be moderately correlated (ρ = 0.42) with participant scores on the Rey Auditory Verbal Learning Test (RAVLT). The cascaded approach for multimodal classification improves both system performance and interpretability. This modular architecture can be easily generalized to incorporate different types of classifiers as well as other heterogeneous sources of data (imaging, metabolic, etc.).

Talk2Me: Automated linguistic data collection for personal assessment.

Language is one the earliest capacities affected by cognitive change. To monitor that change longitudinally, we have developed a web portal for remote linguistic data acquisition, called Talk2Me, consisting of a variety of tasks. In order to facilitate research in different aspects of language, we provide baselines including the relations between different scoring functions within and across tasks. These data can be used to augment studies that require a normative model; for example, we provide baseline classification results in identifying dementia. These data are released publicly along with a comprehensive open-source package for extracting approximately two thousand lexico-syntactic, acoustic, and semantic features. This package can be applied arbitrarily to studies that include linguistic data. To our knowledge, this is the most comprehensive publicly available software for extracting linguistic features. The software includes scoring functions for different tasks.

Automated Syntactic Analysis of Language Abilities in Persons with Mild and Subjective Cognitive Impairment.

In this work we analyze the syntactic complexity of transcribed Swedish-language picture descriptions using a variety of automated syntactic features, and investigate the features' predictive power in classifying narratives from people with subjective and mild cognitive impairment and healthy controls. Our results indicate that while there are no statistically significant differences, syntactic features can still be moderately successful at distinguishing the participant groups when used in a machine learning framework.

White Matter Disruption and Connected Speech in Non-Fluent and Semantic Variants of Primary Progressive Aphasia.

Differential patterns of white matter disruption have recently been reported in the non-fluent (nfvPPA) and semantic (svPPA) variants of primary progressive aphasia (PPA). No single measure is sufficient to distinguish between the PPA variants, but connected speech allows for the quantification of multiple measures. The aim of the present study was to further investigate the white matter correlates associated with connected speech features in PPA. We examined the relationship between white matter metrics and connected speech deficits using an automated analysis of transcriptions of connected speech and diffusion tensor imaging in language-related tracts. Syntactic, lexical, and semantic features were automatically extracted from transcriptions of topic-directed interviews conducted with groups of individuals with nfvPPA or svPPA as well as with a group of healthy controls. A principal component analysis was performed in order to reduce the number of language measures and yielded a five-factor solution. The results indicated that nfvPPA patients differed from healthy controls on a syntactic factor, and svPPA patients differed from controls on two semantic factors. However, the patient groups did not differ on any factor. Moreover, a correlational analysis revealed that the lexical richness factor was significantly correlated with radial diffusivity in the left inferior longitudinal fasciculus, which suggests that semantic deficits in connected speech reflect a disruption of this ventral pathway, and which is largely consistent with the results of previous studies. Using an automated approach for the analysis of connected speech combined with probabilistic tractography, the present findings demonstrate that nfvPPA patients are impaired relative to healthy controls on syntactic measures and have increased radial diffusivity in the left superior longitudinal fasciculus, whereas the svPPA group was impaired on lexico-semantic measures relative to controls and showed increased radial diffusivity in the uncinate and inferior longitudinal fasciculus bilaterally.

Linguistic Features Identify Alzheimer's Disease in Narrative Speech.

BACKGROUND: Although memory impairment is the main symptom of Alzheimer's disease (AD), language impairment can be an important marker. Relatively few studies of language in AD quantify the impairments in connected speech using computational techniques. OBJECTIVE: We aim to demonstrate state-of-the-art accuracy in automatically identifying Alzheimer's disease from short narrative samples elicited with a picture description task, and to uncover the salient linguistic factors with a statistical factor analysis. METHODS: Data are derived from the DementiaBank corpus, from which 167 patients diagnosed with "possible" or "probable" AD provide 240 narrative samples, and 97 controls provide an additional 233. We compute a number of linguistic variables from the transcripts, and acoustic variables from the associated audio files, and use these variables to train a machine learning classifier to distinguish between participants with AD and healthy controls. To examine the degree of heterogeneity of linguistic impairments in AD, we follow an exploratory factor analysis on these measures of speech and language with an oblique promax rotation, and provide interpretation for the resulting factors. RESULTS: We obtain state-of-the-art classification accuracies of over 81% in distinguishing individuals with AD from those without based on short samples of their language on a picture description task. Four clear factors emerge: semantic impairment, acoustic abnormality, syntactic impairment, and information impairment. CONCLUSION: Modern machine learning and linguistic analysis will be increasingly useful in assessment and clustering of suspected AD.

Polysensitization in recurrent lip dermatitis.

BACKGROUND: In allergic contact dermatitis (ACD), polysensitization consists of positive patch test reactions to three or more unrelated allergens. OBJECTIVE: The purpose of this case report is to document a 27-year-old female with recurrent lip dermatitis, polysensitization, and reactions to a number of clinically relevant exposures. METHODS: Patch testing results revealed positive reactions to tixocortol-21-pivalate (3+), lanolin (3+), neomycin (3+), nickel (1+), hydroxyethyl methylacrylate (3+), bacitracin (3+), and abitol (3+). RESULTS: The patient had seven positive reactions, meeting the criteria for polysensitization. Of known clinical relevance, the patient had applied lanolin-containing lip balms and hydrocortisone- and bacitracin-containing products to the lips, all of which she was strongly reactive to on patch testing. CONCLUSION: Polysensitization occurs when three or more unrelated allergens are positive on patch testing. This case highlights the importance of considering polysensitization in ACD as numerous allergens that were positive on patch testing were clinically relevant.

Flow cytometric analysis of regulatory T cells during hyposensitization of acquired allergic contact dermatitis.

BACKGROUND: We previously demonstrated that repeated intradermal steroid injections administered at weekly intervals into positive patch-test sites induce hyposensitization and desensitization. OBJECTIVE: To examine changes in CD4CD25CD127lo/ regulatory T cells during the attenuation of the patch-test response. METHODS: Ten patients with known allergic contact dermatitis were patch tested weekly for 10 weeks. The patch-test site was injected intradermally with 2 mg triamcinolone. At weeks 1 and 7, a biopsy was performed on the patch-test site in 6 patients, and flow cytometry was performed assessing CD4CD25CD127lo/ regulatory T cells. Secondary outcomes were clinical score, reaction size, erythema, and temperature. Statistical analysis included regression, correlation, and repeated-measures analysis of variance. RESULTS: The percentage of CD4CD25CD127lo/ regulatory T cells, measured by flow cytometry, increased from week 1 to week 7 by an average of 19.2%. The average grade of patch-test reaction decreased from +++ (vesicular reaction) to ++ (palpable erythema). The mean drop in temperature following treatment was 0.28°C per week. The mean area decreased 8.6 mm/wk over 10 weeks. CONCLUSIONS: Intradermal steroid injections of weekly patch-test reactions resulted in hyposensitization of the allergic contact dermatitis reaction. CD4CD25CD127lo/ regulatory T cells showed a tendency to increase; however, further studies are needed to determine if this is significant.

Automated classification of primary progressive aphasia subtypes from narrative speech transcripts.

In the early stages of neurodegenerative disorders, individuals may exhibit a decline in language abilities that is difficult to quantify with standardized tests. Careful analysis of connected speech can provide valuable information about a patient's language capacities. To date, this type of analysis has been limited by its time-consuming nature. In this study, we present a method for evaluating and classifying connected speech in primary progressive aphasia using computational techniques. Syntactic and semantic features were automatically extracted from transcriptions of narrative speech for three groups: semantic dementia (SD), progressive nonfluent aphasia (PNFA), and healthy controls. Features that varied significantly between the groups were used to train machine learning classifiers, which were then tested on held-out data. We achieved accuracies well above baseline on the three binary classification tasks. An analysis of the influential features showed that in contrast with controls, both patient groups tended to use words which were higher in frequency (especially nouns for SD, and verbs for PNFA). The SD patients also tended to use words (especially nouns) that were higher in familiarity, and they produced fewer nouns, but more demonstratives and adverbs, than controls. The speech of the PNFA group tended to be slower and incorporate shorter words than controls. The patient groups were distinguished from each other by the SD patients' relatively increased use of words which are high in frequency and/or familiarity.

Chronic urticaria and autoimmunity.

Chronic urticaria is defined as hives, typically occurring daily, for greater than 6 weeks duration. Chronic idiopathic urticaria, which has no discernable external cause, comprises the majority of cases of chronic urticaria. Over half of all cases of chronic idiopathic urticaria are thought to occur by an autoimmune mechanism, primarily autoantibodies against the high affinity immunoglobulin E (IgE) receptor (FcεRI). Chronic urticaria is hypothesized to occur because of a predilection in the patient to develop reactions to self. Supporting this hypothesis, a strong association has been found between chronic urticaria and additional autoimmune diseases, such as thyroid disease, rheumatoid arthritis, systemic lupus erythematosus, Sjögren's syndrome, celiac disease and type 1 diabetes, among others. Herein, we review the associations between chronic urticaria, thyroid disease, and other autoimmune disorders, as well as the implications that these correlations hold for therapeutic intervention in chronic urticaria.

Too young for attention deficit disorder? Views from preschool.

A review of public-school administrative records and interviews with early-childhood directors from special and regular programs were used to collect information about factors associated with outcomes for young children with attention-deficit disorder with or without hyperactivity (AD/HD) in preschool. Special-education preschool administrators and community-based child care and preschool directors differed in their fundamental view of "what works" with preschool AD/HD children, but they agreed in principle on other issues (e.g., public-school providers attested to faith in adult-directed programming; community providers cited child-centered approaches as effective with AD/HD). The records review and interviews indicate that intrinsic program structure, gentle and constant adult help, acceptance of the child, family integrity, gross motor facilities, and attention to comorbidities were seen as positively related to child success. Multiple caregivers, poor understanding of development, failure to foster self-soothing and other personal mastery skills, expectations of perfection, and delegated parenting were identified as negatively related to good outcomes over time for children with AD/HD or similar profiles.