bluuebunny/crossref_metadata_2025 huggingface dataset:
ATME—Needs, requirements and cross-sectoral patient journeys of patients with out-of-hospital mechanical ventilation and intensive care in outpatient settings: study protocol for an observational study
Authors: Knizia Nahne-Alina , Hirschler Josefine , Stegbauer Constance , Schwinger Antje , Büscher Andreas , Englert Nathalie , Peters Lara , Bayarassou Hakim A. , Mallmann Leonie , Willms Gerald
Published: March 2024

Introduction

An increasing number of tracheotomised and/or ventilated patients with high-cost out-of-hospital intensive care needs and, at the same time, a decreasing number of healthcare professionals inevitably lead to challenges in the care of this patient population. In addition, little is known about this population, their health restrictions, needs, patient journeys, care structures and processes. The project ‘Needs, requirements and cross-sectoral care pathways of out-of-hospital ventilated intensive care patients’ (ATME) aims to analyse these aspects and explore current care structures to inform further development of care in line with patients’ needs and requirements.

Methods and analysis

Qualitative and quantitative methods will be used. In preparation of a semistandardised survey, exploratory interviews will be conducted with tracheotomised and/or ventilated patients with out-of-hospital intensive care needs (TVPOI) (n=15), nursing care providers (n=30), outpatient medical centres, as well as outpatient medical, medical technology and therapeutic care providers (n=35). Three semistandardised survey questionnaires for TVPOI (n=2,000) will be developed and conducted with nursing care facilities (n=250) and outpatient medical centres for mechanical ventilation (n=25). Content analyses will be conducted for qualitative data; survey data will be analysed descriptively. In addition, healthcare claims data will be analysed descriptively to provide information on patient journeys. Three result workshops and one consensus conference will be carried out with representatives of the relevant target groups to analyse the suitability of care structures and to develop recommendations for action to improve TVPOI.

Ethics and dissemination

The ATME study received a positive vote from the Ethics Committee of the Osnabrück University of Applied Sciences and is registered in ‘Deutsches Register Klinischer Studien (DRKS)’ (registration number: DRKS00030891). The study results will be presented at national conferences and in relevant peer-reviewed journals. Additionally, study results will be published by the funding institution (the Innovation Committee of the Federal Joint Committee) on their website.
Impact of inconsistent ethnicity recordings on estimates of inequality in child health and education data: a data linkage study of Child and Adolescent Mental Health Services in South London
Authors: Wickersham Alice , Das-Munshi Jayati , Ford Tamsin , Jewell Amelia , Stewart Robert , Downs Johnny
Published: March 2024

Objectives

Ethnicity data are critical for identifying inequalities, but previous studies suggest that ethnicity is not consistently recorded between different administrative datasets. With researchers increasingly leveraging cross-domain data linkages, we investigated the completeness and consistency of ethnicity data in two linked health and education datasets.

Design

Cohort study.

Setting

South London and Maudsley NHS Foundation Trust deidentified electronic health records, accessed via Clinical Record Interactive Search (CRIS) and the National Pupil Database (NPD) (2007–2013).

Participants

N=30 426 children and adolescents referred to local Child and Adolescent Mental Health Services.

Primary and secondary outcome measures

Ethnicity data were compared between CRIS and the NPD. Associations between ethnicity as recorded from each source and key educational and clinical outcomes were explored with risk ratios.

Results

Ethnicity data were available for 79.3% from the NPD, 87.0% from CRIS, 97.3% from either source and 69.0% from both sources. Among those who had ethnicity data from both, the two data sources agreed on 87.0% of aggregate ethnicity categorisations overall, but with high levels of disagreement in Mixed and Other ethnic groups. Strengths of associations between ethnicity, educational attainment and neurodevelopmental disorder varied according to which data source was used to code ethnicity. For example, as compared with White pupils, a significantly higher proportion of Asian pupils achieved expected educational attainment thresholds only if ethnicity was coded from the NPD (RR=1.46, 95% CI 1.29 to 1.64), not if ethnicity was coded from CRIS (RR=1.11, 0.98 to 1.26).

Conclusions

Data linkage has the potential to minimise missing ethnicity data, and overlap in ethnicity categorisations between CRIS and the NPD was generally high. However, choosing which data source to primarily code ethnicity from can have implications for analyses of ethnicity, mental health and educational outcomes. Users of linked data should exercise caution in combining and comparing ethnicity between different data sources.
Immunosuppressant medication behaviours in solid organ transplant recipients: a cross-sectional study from south-central China during COVID-19 reopening period
Authors: Zhao Qin , Dong Lei , Wang Liang , Zhao Hongyu , Zhu Xiao , Zhang Zhihao , Liu Jia
Published: March 2024

Objective

Medication non-adherence to immunosuppressants threatens allograft survival and function maintenance among solid organ transplant (SOT) recipients. This study aimed to investigate the prevalence of immunosuppressant medication non-adherence and associated factors during the COVID-19 reopening period among Chinese SOT recipients.

Design

Cross-sectional study.

Setting

South-central China.

Population

Adult patients who received SOT with functioning graft.

Methods

Sociodemographic questionnaire and scales to measure physical activity, depression and medication non-adherence were used to collect data. Logistic regression analysis was conducted to identify factors associated with medication non-adherence. Mediation and moderated mediation analyses were performed to examine the potential mechanisms influencing medication behaviour during the pandemic reopening period using SPSS PROCESS macro 4.3 software.

Results

A total of 1121 participants were recruited and the prevalence of medication non-adherence was 36.3% in this study. Recipients who were men, had a higher monthly income, lived alone, had received transplantation for a minimum of 3 years, had received COVID-19 vaccination and experienced depressive symptoms exhibited an increased risk of non-adherence. Contrarily, those who engaged in high-intensity physical activity exhibited a decreased risk. Physical activity was negatively associated with medication non-adherence (r=−0.124, p<0.001) with depression fully mediating this relationship (B=−0.014, 95% CI: −0.032 to –0.003). COVID-19 vaccination significantly moderated the relationship between physical activity and depression (B=−0.303, 95% CI: −0.515 to –0.090).

Conclusion

This study investigated the prevalence of medication non-adherence among SOT recipients during the COVID-19 reopening period in China, its associated factors and a potential mechanism. Depression fully mediated the association between physical activity and medication non-adherence, and COVID-19 vaccination moderated the relationship between physical activity and depression. These findings provide some insights for managing medication behaviour when confronting public health emergencies. However, relationships displayed in the moderated mediation model should be tracked after returning to normal life and other potential relationships should be explored to deeply understand medication non-adherent behaviour.
Tracking deaths of people who have experienced homelessness: a dynamic cohort study in an Australian city
Authors: Tuson Matthew , Vallesi Shannen , Wood Lisa
Published: March 2024

Objective

Life expectancy and rates of premature death are fundamental markers of health and social equity globally, and measures on which people experiencing homelessness face enormous disparities. However, unlike for other population groups with similar disparities, concerted government action to reduce homeless mortality is rare, partly due to a lack of reliable, timely data. Contemporaneous tracking of homeless deaths is required to render such deaths less invisible and measure trends over time. Drawing on multiple data sources as recommended by the US National Health Care for the Homeless Council’s seminal Homeless Mortality Data Toolkit, we routinely and contemporaneously capture, verify and report on deaths occurring among people who have experienced homelessness in the Australian city of Perth.

Design

Dynamic cohort study.

Setting

Perth, Western Australia, Australia, between 2016 and 2022, with deaths examined between 2020 and 2022.

Participants

For this study, the cohort comprised 8753 people who experienced homelessness in Perth, with ‘recruitment’ into the cohort governed by engagement with one or more local homelessness services and programmes over the period.

Outcome measures

Number and median age-at-death statistics.

Results

There were 360 deaths over the 3-year period, which is likely an undercount. The median age at death was 50 years, >3 decades below the current Australian median age at death of 82 years. Aboriginal people accounted for 30% of the deaths.

Conclusion

The ongoing poor health and premature death of people who have experienced homeless are indictments on our society. Triangulation of multiple data sources is required to identify and monitor deaths among homeless populations. Timely, verified data on homeless mortality are important for galvanising action and accountability, and targets should be set to reduce the observed three-decade life expectancy chasm.
Enhancing pain care with the American Pain Society Patient Outcome Questionnaire for use in the emergency department (APS-POQ-RED): validating a patient-reported outcome measure
Authors: Hughes James A , Hazelwood Sarah , Lyrstedt Anna-Lisa , Jones Lee , Brown Nathan J , Jarugula Rajeev , Douglas Clint , Chu Kevin
Published: March 2024

Background

In general, the quality of pain care in emergency departments (ED) is poor, despite up to 80% of all ED patients presenting with pain. This may be due to the lack of well-validated patient-reported outcome measures (PROMs) of pain care in the ED setting. The American Pain Society-Patient Outcome Questionnaire-Revised Edition (APS-POQ-R), with slight modification for ED patients, is a potentially useful PROM for the adult ED, however it is yet to be completely validated.

Methods

Adult patients, who had presented with moderate to severe acute pain, were recruited at two large inner-city EDs in Australia. A modified version of the APS-POQ-R was administered at the completion of their ED care. Responses were randomly split into three groups and underwent multiple rounds of exploratory and confirmatory factor analysis with testing for construct, convergent, divergent validity and internal consistency.

Results

A total of 646 ED patients (55.6% female), with a median age of 48.3 years, and moderate to severe pain on arrival, completed the ED-modified APS-POQ-R. Psychometric evaluation resulted in a reduced nine-question tool, which measures three constructs (pain relief and satisfaction (α=0.891), affective distress (α=0.823) and pain interference (α=0.908)) and demonstrated construct, convergent, divergent validity, and internal consistency.

Conclusions

This new tool, which we refer to as the American Pain Society-Patient Outcome Questionnaire-Revised for the ED (APS-POQ-RED), should form the basis for reporting patient-reported outcomes of ED pain care in future quality improvement and research.
Roles of gender and smoking in the associations between urinary phytoestrogens and asthma/wheeze and lung function: evidence from a cross-sectional study
Authors: Zhang Yin , Huang Tingxuan , Wang Ji , Wang Gang , Luo Fengming
Published: March 2024

Background

The role of phytoestrogens in asthma/wheeze and lung function remains controversial. Thus, we aimed to examine whether phytoestrogens have beneficial effects on asthma/wheeze, lung function for subgroups and mortality.

Methods

Participants in this study were individuals aged 20 years or older from the National Health and Nutrition Examination Survey. Multivariate logistic regression models were fitted to examine the associations of urinary phytoestrogens with the risk of asthma/wheeze and lung function in individuals with and without asthma/wheeze. Cox proportional hazards regression was used to examine the relationship between urinary phytoestrogens and all-cause mortality. Stratified analyses were conducted based on gender and smoking status.

Results

We included 2465 individuals in this study. Enterolactone levels in the highest quartile were associated with a lower risk of asthma than those in the lowest quartile. As compared with the lowest quartile, the highest quartile of enterodiol and enterolactone was associated with a lower risk of wheeze. Significant associations were observed between subtypes of phytoestrogens (equol and enterolactone) and lung function (forced vital capacity (FVC) and forced expiratory volume in 1 s). Besides, FVC was higher in individuals with higher levels of enterodiol. The results were consistent in subpopulations without asthma/wheeze, while the significant difference was not observed in individuals with asthma/wheeze. The stratified analyses revealed that the associations between phytoestrogens and lung function differed by gender and smoking status among subgroups. No significant association was found between urinary phytoestrogens and all-cause mortality.

Conclusion

In summary, subtypes of phytoestrogens were associated with lower risk of asthma/wheeze and beneficial for lung function improvement in individuals without asthma/wheeze. Furthermore, gender and smoking may interact in the relationship between phytoestrogens and asthma/wheeze, and lung function. Further researches are needed to confirm these associations and explain the results of stratified analyses.
Understanding parent and caregiver perceptions of paediatric vehicular hyperthermia: implications for public health messaging from a pilot study
Authors: Krase Piper , Grundstein Andrew , Stewart Alan , Williamsberg Castle , Ducre Katrina
Published: March 2024

Background

Paediatric vehicular hyperthermia (PVH) is the leading cause of non-crash vehicle-related death of children in the USA. Public health messaging is an important mitigation strategy, yet it is difficult to assess the effectiveness in reducing deaths. Here, we seek to better understand parent/caregiver perceptions on PVH to guide risk communication.

Methods

This pilot study focuses on a subset of participants (n=127) from a national survey, comprising parents/caregivers who met specific eligibility criteria (ie, those who both drive and have children ≤5 years of age). Survey participants answered questions about the perceived severity of forgetting a child in a hot car and their susceptibility to doing so, with responses recorded on a 7-point Likert scale (1=strongly disagree and 7=strongly agree).

Results

Our findings indicate that while on average (mean responses of 2.45 and 2.49) parents/caregivers did not consider themselves susceptible, they did acknowledge the severity (mean response of 6.12) of leaving a child unattended in a vehicle. The results suggest that because of this low perceived susceptibility, parents/caregivers are less likely to take protective actions aimed at preventing these incidents from happening.

Conclusions

Public health messaging on PVH should emphasise the universal risk to all parents/caregivers so as to foster greater awareness of the need to take protective actions. Furthermore, engaging secondary audiences such as teachers and healthcare professionals can amplify this message and offer concrete behavioural interventions to mitigate the risk of forgetting a child in a car.
Investigating the 2016 surge in firearm violence in Illinois, USA, through community-based organisations: a qualitative study
Authors: Dastoor Jehannaz D , Thomas Arielle , Slocum John D , Regan Sheila , Stone Levon , Richardson Joesph B , Mason Maryann , Johnson Julie K , Lin Katherine , Stey Anne
Published: March 2024

Background

Illinois experienced a historic firearm violence surge in 2016 with a decline to baseline rates in 2018. This study aimed to understand this 2016 surge through the direct accounts of violence prevention community-based organisations (CBOs) in Illinois.

Methods

We conducted semistructured interviews with 20 representatives from 13 CBOs from the south and west sides of greater Chicago metropolitan area. Interviews were audio recorded, coded and analysed thematically.

Results

We identified lack of government-derived infrastructure and systemic poverty as the central themes of Illinois’s 2016 firearm violence surge. Participants highlighted the Illinois Budget Impasse halted funding for violence prevention efforts, leading to 2016’s violence. This occurred in the context of a strained relationship with the criminal justice system, where disengagement from police and mistrust in the justice system led victims and families to seek justice outside of the judicial system. Participants emphasised that systemic poverty and the obliteration of community support structures led to overwhelming desperation, which, in turn, increased risky behaviours perceived as necessary for survival. Participants disproportionately identified that this impacted the young people in their communities.

Conclusions

Lack of government-derived infrastructure and systemic poverty were the central themes of the 2016 firearm violence surge. The insights gained from the 2016 surge are applicable to understanding both current and future surges. CBOs focused on violence prevention offer insights into the context and conditions fuelling surges in the epidemic of violence.
Emerging and under-recognised patterns of colorectal carcinoma morphologies: a comprehensive review
Authors: Ono Yuho , Yilmaz Osman
Published: March 2024

While the overwhelming majority of colorectal carcinomas (CRC) are diagnosed as adenocarcinoma not otherwise specified, there are numerous under-recognised morphologic patterns of CRC. These patterns are recognised by the WHO, appear in reporting manuals for the American Joint Committee of Cancer, and/or are listed on synoptic reports, while many other variants have either fallen out of favour or are emerging as future bona fide patterns. Herein, we discuss 13 variants: serrated adenocarcinoma, micropapillary adenocarcinoma, medullary carcinoma, neuroendocrine carcinoma, mucinous adenocarcinoma, signet-ring cell carcinoma, adenosquamous carcinoma, adenoma-like adenocarcinoma, lymphoglandular complex-like CRC, carcinoma with sarcomatoid components, cribriform-comedo-type adenocarcinoma, undifferentiated carcinoma and low-grade tubuloglandular adenocarcinoma. The purpose of this review is to scrutinise these variants by assessing their clinical characteristics, morphologic cues, as well as pitfalls, and address their prognostic significance. Our analysis aims to bring clarity and updated understanding to these variants, offering valuable insights for pathologists. This contributes to more nuanced CRC diagnosis and treatment strategies, highlighting the importance of recognising a broad spectrum of morphologic patterns in CRC.
Clinical outcomes and safety of immune checkpoint inhibitors in patients with solid tumors and paraneoplastic syndromes
Authors: Nassar Amin H , El Zarif Talal , Khalid Ahmed Bilal , Rahme Serena , Zhong Caiwei , Kwak Lucia , Salame Marita , Farhat Elias Bou , Freeman Dory , El-Am Edward , Ravishankar Arjun , Ahmad Bachar , Nana Frank Aboubakar , Kaldas David , Naqash Abdul Rafeh , Sharon Elad , LeBoeuf Nicole R , Cortellini Alessio , Malgeri Andrea , Gupta Shruti , Al-Hader Ahmad , Sparks Jeffrey A , Linnoila Jenny , Hamnvik Ole-Petter R , Mouhieddine Tarek H , Marron Thomas , Parikh Kaushal , McKay Rana R , Dilling Thomas , Choueiri Toni K , Adib Elio , Najem Elie , Kim So Yeon , Sonpavde Guru
Published: March 2024

Background

Patients with paraneoplastic syndromes (PNS) are excluded from clinical trials involving immune checkpoint inhibitors (ICIs) due to safety concerns. Moreover, real-world data on efficacy and safety is scarce.

Methods

In this retrospective study, data were collected on patients with PNS and solid tumors receiving ICI between 2015 and 2022 at nine institutions. Patients were classified into: Cohort 1 (pre-existing PNS before ICI initiation), cohort 2 (PNS during ICI treatment), and cohort 3 (PNS after ICI discontinuation). Patients with metastatic non-small cell lung cancer (NSCLC) (mNSCLC) from cohort 1 were matched to patients who were PNS-free at each institution up to a 1:3 ratio for age, sex, type of ICI, use of concurrent chemotherapy, and number of lines of systemic therapy prior to ICI initiation. Kaplan-Meier method was used to assess overall survival (OS) and time-to-next treatment (TTNT).

Results

Among 109 patients with PNS treated with ICIs, median age at ICI initiation was 67 years (IQR: 58–74). The most represented cancer type was NSCLC (n=39, 36%). In cohort 1 (n=55), PNS exacerbations occurred in 16 (29%) patients with median time to exacerbation after ICI of 1.1 months (IQR: 0.7–3.3). Exacerbation or de novo PNS prompted temporary/permanent interruption of ICIs in 14 (13%) patients. For cohort 2 (n=16), median time between ICI initiation and de novo PNS was 1.2 months (IQR: 0.4–3.5). Treatment-related adverse events (trAEs) occurred in 43 (39%) patients. Grade ≥3 trAEs occurred in 18 (17%) patients. PNS-directed immunosuppressive therapy was required in 55 (50%) patients. We matched 18 patients with mNSCLC and PNS (cohort 1) to 40 without PNS, treated with ICIs. There was no significant difference in OS or TTNT between patients with mNSCLC with and without PNS, although a trend was seen towards worse outcomes in patients with PNS. TrAEs occurred in 6/18 (33%) and 14/40 (35%), respectively. Grade ≥3 trAEs occurred in 4 (22%) patients with PNS and 7 (18%) patients without PNS.

Conclusions

Exacerbations of pre-existing PNS occurred in 29% of patients treated with ICIs and both exacerbations and de novo PNS occur early in the ICI course. TrAE from ICIs were similar between patients with and without PNS. Our data suggest that pre-existing PNS should not preclude consideration of ICI therapy although patients may not derive the same clinical benefit compared with patients without PNS.
Tobacco packaging littering behaviours among Australian adults who smoke: findings from cross-sectional and observational studies to inform the implementation of cigarette pack inserts
Authors: Gascoyne Claudia , Li Rain , Scollo Michelle , Wakefield Melanie A , Brennan Emily
Published: March 2024

Background

Cigarette pack inserts are small cards that highlight the benefits of quitting and promote use of smoking cessation support. With evidence from Canada that they increase self-efficacy to quit, quit attempts and sustained cessation, inserts are set to be introduced into tobacco packs sold in Australia. Some people have expressed concern that the introduction of inserts may create more litter if incorrectly disposed of on pack-opening.

Methods

We used a cross-sectional survey to assess self-reported pack-opening location and waste disposal behaviours of people who smoke to determine the potential for littering to occur when tobacco packs are first opened. We also visited a sample of supermarkets, convenience stores and tobacconists located throughout Melbourne, Australia, to discreetly collect observational data regarding pack-opening and waste disposal behaviours at the point of purchase.

Results

Among participants in the cross-sectional study (N=369), the majority reported that they opened their most recent tobacco pack at home (70.9%) where there is little potential for littering, and this proportion was higher among those who smoke daily (78.6%) and men (74.3%). Self-reported behaviours that could result in littering were rare; 1.0% reported that they left tobacco packaging where they believed it would be collected for disposal. Of the 128 individuals observed at the point of purchase across 46 stores, 96.9% did not open the tobacco product immediately after purchase. One incident of littering was observed (0.8%).

Conclusion

The introduction of cigarette pack inserts in Australia is unlikely to create a substantial amount of additional litter.
Building capacity for ATLS trauma education: role of nurse practitioners and physician assistants
Authors: Dunn Julie A , Wiley Alysia , McFann Kim , Baumgartner Craig , Chernock Brad , Capella Jeannette , Wilson Catherine , Hallman Melanie , Taylor Dennis , Sutyak John , Campo Theresa , Thorton Tim , Polk Travis
Published: March 2024

Objectives

Advanced Trauma Life Support (ATLS) focuses on care of injured patients in the first hour of resuscitation. Expanded demand for courses has led to a concurrent need for new instructors. Nurse practitioners and physician assistants (NPs/PAs) work on trauma services and duties include patient, staff, and outreach education. The goal of this project was to assess NP/PA self-reported knowledge and skills pertinent to ATLS and identify potential barriers to becoming instructors.

Materials

This was a voluntary 91-question survey emailed to NP/PA lists obtained from professional societies and online social media channels. NPs/PAs completed a survey reflecting self-reported knowledge, experience, comfort level, and barriers to teaching ATLS interactive discussions and skills. Responses were recorded using a Likert scale and results were documented as percentages. Number of years of experience versus perceived knowledge and comfort teaching were compared using a χ2test of independence.

Results

There were 1696 completed surveys. Most NPs/PAs thought they had adequate knowledge and experience to teach interactive discussions and skills. Those with more years of experience and those who completed more ATLS courses had higher percentages. The number 1 barrier to teaching was lack of formal teaching experience followed by perceived hierarchy concerns. Experience and comfort with skills that fell below 50% were pediatric airway (49.5%), needle and surgical cricothyrotomy (49.8% and 44.8%), diagnostic peritoneal lavage (21.6%), and venous cutdown (20.8%).

Conclusion

NPs/PAs with experience in trauma reported having the knowledge and skill to teach ATLS. A majority are comfortable teaching interactive discussions and skills for which they are knowledgeable. The primary barrier to teaching was lack of formal teaching experience, which is covered in the ATLS Instructor course. Training NPs/PAs to become instructors would increase the instructor base and allow for increased promulgation of ATLS and trauma education.

Level of evidence

IV.
Co-Designing Sensory Feedback for Wearables to Support Physical Activity through Body Sensations
Authors: Ley-Flores Judith , Vidal Laia Turmo , Segura Elena Márquez , Singh Aneesha , Bevilacqua Frederic , Cuadrado Francisco , Durán Joaquín Roberto Díaz , Valdiviezo-Hernández Omar , Sánchez-Martin Milagrosa , Tajadura-Jiménez Ana
Published: March 2024

Many technologies for promoting physical activity (PA) give limited importance to critical variables for engagement in PA, such as negative body perceptions. Here, we aim to address this gap by incorporating barriers and experienced body sensations into the design process for wearables and body-based devices thus expanding the design space for such technologies. We first report four co-design workshops with physically inactive participants (n=9); in these workshops, we explored tangible tools (i) to sensitize people to body sensations experienced when facing barriers to PA and (ii) to ideate how haptic and auditory feedback could transform body sensations to increase body-awareness and engagement in PA; results show several interactive sensorial patterns with potential to inform the design of body transformation wearables. These were validated through a follow-up workshop (n=13 participants) and reflections based on insights from a literature review. Our findings are significant for the design of ubiquitous technology to support and initiate PA in everyday contexts through a novel approach of transforming body perceptions/ sensations related to PA barriers. We contribute design inspirations and cards for identifying barriers to PA and to empower designers and researchers to integrate them early in the design process.
exHAR
Authors: Kianpisheh Mohammad , Mariakakis Alex , Truong Khai N.
Published: March 2024

Human activity recognition (HAR) is crucial for ubiquitous computing systems. While HAR systems are able to recognize a predefined set of activities established during the development process, they often fail to handle users' unique ways of completing these activities and changes in their behavior over time, as well as different activities. Knowledge-based HAR models have been proposed to help individuals create new activity definitions based on common-sense rules, but little research has been done to understand how users approach this task. To investigate this process, we developed and studied how people interact with an explainable knowledge-based HAR development tool called exHAR. Our tool empowers users to define their activities as a set of factual propositions. Users can debug these definitions by soliciting explanations for model predictions (why and why-not) and candidate corrections for faulty predictions (what-if and how-to). After conducting a study to evaluate the effectiveness of exHAR in helping users design accurate HAR systems, we conducted a think-aloud study to better understand people's approach to debugging and personalizing HAR systems and the challenges they may encounter. Our findings revealed why some participants had inaccurate mental models of knowledge-based HAR systems and inefficient approaches to the debugging process.
Capturing the College Experience
Authors: Nepal Subigya , Liu Wenjun , Pillai Arvind , Wang Weichen , Vojdanovski Vlado , Huckins Jeremy F. , Rogers Courtney , Meyer Meghan L. , Campbell Andrew T.
Published: March 2024

Understanding the dynamics of mental health among undergraduate students across the college years is of critical importance, particularly during a global pandemic. In our study, we track two cohorts of first-year students at Dartmouth College for four years, both on and off campus, creating the longest longitudinal mobile sensing study to date. Using passive sensor data, surveys, and interviews, we capture changing behaviors before, during, and after the COVID-19 pandemic subsides. Our findings reveal the pandemic's impact on students' mental health, gender based behavioral differences, impact of changing living conditions and evidence of persistent behavioral patterns as the pandemic subsides. We observe that while some behaviors return to normal, others remain elevated. Tracking over 200 undergraduate students from high school to graduation, our study provides invaluable insights into changing behaviors, resilience and mental health in college life. Conducting a long-term study with frequent phone OS updates poses significant challenges for mobile sensing apps, data completeness and compliance. Our results offer new insights for Human-Computer Interaction researchers, educators and administrators regarding college life pressures. We also detail the public release of the de-identified College Experience Study dataset used in this paper and discuss a number of open research questions that could be studied using the public dataset.
Multi-Subject 3D Human Mesh Construction Using Commodity WiFi
Authors: Wang Yichao , Ren Yili , Yang Jie
Published: March 2024

This paper introduces MultiMesh, a multi-subject 3D human mesh construction system based on commodity WiFi. Our system can reuse commodity WiFi devices in the environment and is capable of working in non-line-of-sight (NLoS) conditions compared with the traditional computer vision-based approach. Specifically, we leverage an L-shaped antenna array to generate the two-dimensional angle of arrival (2D AoA) of reflected signals for subject separation in the physical space. We further leverage the angle of departure and time of flight of the signal to enhance the resolvability for precise separation of close subjects. Then we exploit information from various signal dimensions to mitigate the interference of indirect reflections according to different signal propagation paths. Moreover, we employ the continuity of human movement in the spatial-temporal domain to track weak reflected signals of faraway subjects. Finally, we utilize a deep learning model to digitize 2D AoA images of each subject into the 3D human mesh. We conducted extensive experiments in real-world multi-subject scenarios under various environments to evaluate the performance of our system. For example, we conduct experiments with occlusion and perform human mesh construction for different distances between two subjects and different distances between subjects and WiFi devices. The results show that MultiMesh can accurately construct 3D human meshes for multiple users with an average vertex error of 4cm. The evaluations also demonstrate that our system could achieve comparable performance for unseen environments and people. Moreover, we also evaluate the accuracy of spatial information extraction and the performance of subject detection. These evaluations demonstrate the robustness and effectiveness of our system.
Sasha
Authors: King Evan , Yu Haoxiang , Lee Sangsu , Julien Christine
Published: March 2024

Smart home assistants function best when user commands are direct and well-specified---e.g., "turn on the kitchen light"---or when a hard-coded routine specifies the response. In more natural communication, however, human speech is unconstrained, often describing goals (e.g., "make it cozy in here" or "help me save energy") rather than indicating specific target devices and actions to take on those devices. Current systems fail to understand these under-specified commands since they cannot reason about devices and settings as they relate to human situations. We introduce large language models (LLMs) to this problem space, exploring their use for controlling devices and creating automation routines in response to under-specified user commands in smart homes. We empirically study the baseline quality and failure modes of LLM-created action plans with a survey of age-diverse users. We find that LLMs can reason creatively to achieve challenging goals, but they experience patterns of failure that diminish their usefulness. We address these gaps with Sasha, a smarter smart home assistant. Sasha responds to loosely-constrained commands like "make it cozy" or "help me sleep better" by executing plans to achieve user goals---e.g., setting a mood with available devices, or devising automation routines. We implement and evaluate Sasha in a hands-on user study, showing the capabilities and limitations of LLM-driven smart homes when faced with unconstrained user-generated scenarios.
Transportation Mode Detection Technology to Predict Wheelchair Users' Life Satisfaction in Seoul, South Korea
Authors: Hwang Sungjin , Heo Jiwoong , Cho Youngwug , Moon Jucheol , Lee Yushin , Kim Hansung , Cha Jaehyuk , Kim Kwanguk
Published: March 2024

Transportation mode detection (TMD) has been proposed as a computational technology to obtain mobility information. However, previous TMD studies mainly focused on improving detection performance and have not investigated the social implications of mobility information. This is the first study to use TMD to predict the life satisfaction of wheelchair users. Our goal is to develop TMD for wheelchair users (wTMD) utilizing smartphone location data and apply it to determine how transportation behaviors affect the life satisfaction of wheelchair users. First, we propose a wTMD technology by collecting a new dataset from wheelchair and non-wheelchair users. Second, we conduct regression analyses on existing in-the-wild dataset of wheelchair users. The result shows that the portion of subways in an individual's travel time is directly connected to wheelchair users' life satisfaction in Seoul, South Korea. We hope our findings are a good example for future social science studies and ultimately help to design wheelchair-friendly urban planning and accessibility.
TagSleep3D
Authors: Liu Chen , Dong Zixuan , Huang Li , Yan Wenlong , Wang Xin , Fang Dingyi , Chen Xiaojiang
Published: March 2024

Sleep posture plays a crucial role in maintaining good morpheus quality and overall health. As a result, long-term monitoring of 3D sleep postures is significant for sleep analysis and chronic disease prevention. To recognize sleep postures, traditional methods either use cameras to record image data or require the user to wear wearable devices or sleep on pressure mattresses. However, these methods could raise privacy concerns and cause discomfort during sleep. Accordingly, the RF (Radio Frequency) based method has emerged as a promising alternative. Despite most of these methods achieving high precision in classifying sleep postures, they struggle to retrieve 3D sleep postures due to difficulties in capturing 3D positions of static body joints. In this work, we propose TagSleep3D to resolve all the above issues. Specifically, inspired by the concept of RFID tag sheets, we explore the possibility of recognizing 3D sleep posture by deploying an RFID tag array under the bedsheet. When a user sleeps in bed, the signals of some tags could be blocked or reflected by the sleep posture, which can produce a body imprint. We then propose a novel deep learning model composed of the attention mechanism, convolutional neural network, and together with two data augmentation methods to retrieve the 3D sleep postures by analyzing these body imprints. We evaluate TagSleep3D with 43 users and we totally collect 27,300 sleep posture samples. Our extensive experiments demonstrate that TagSleep3D can recognize each joint on the human skeleton with a median MPJPE (Mean Per Joint Position Error) of 4.76 cm for seen users and 7.58 cm for unseen users.
MAPLE
Authors: Khaokaew Yonchanok , Xue Hao , Salim Flora D.
Published: March 2024

In recent years, predicting mobile app usage has become increasingly important for areas like app recommendation, user behaviour analysis, and mobile resource management. Existing models, however, struggle with the heterogeneous nature of contextual data and the user cold start problem. This study introduces a novel prediction model, Mobile App Prediction Leveraging Large Language Model Embeddings (MAPLE), which employs Large Language Models (LLMs) and installed app similarity to overcome these challenges. MAPLE utilises the power of LLMs to process contextual data and discern intricate relationships within it effectively. Additionally, we explore the use of installed app similarity to address the cold start problem, facilitating the modelling of user preferences and habits, even for new users with limited historical data. In essence, our research presents MAPLE as a novel, potent, and practical approach to app usage prediction, making significant strides in resolving issues faced by existing models. MAPLE stands out as a comprehensive and effective solution, setting a new benchmark for more precise and personalised app usage predictions. In tests on two real-world datasets, MAPLE surpasses contemporary models in both standard and cold start scenarios. These outcomes validate MAPLE's capacity for precise app usage predictions and its resilience against the cold start problem. This enhanced performance stems from the model's proficiency in capturing complex temporal patterns and leveraging contextual information. As a result, MAPLE can potentially improve personalised mobile app usage predictions and user experiences markedly.
IOTeeth
Authors: Hu Zhizhang , Radmehr Amirmohammad , Zhang Yue , Pan Shijia , Nguyen Phuc
Published: March 2024

While occlusal diseases - the main cause of tooth loss -- significantly impact patients' teeth and well-being, they are the most underdiagnosed dental diseases nowadays. Experiencing occlusal diseases could result in difficulties in eating, speaking, and chronicle headaches, ultimately impacting patients' quality of life. Although attempts have been made to develop sensing systems for teeth activity monitoring, solutions that support sufficient sensing resolution for occlusal monitoring are missing. To fill that gap, this paper presents IOTeeth, a cost-effective and automated intra-oral sensing system for continuous and fine-grained monitoring of occlusal diseases. The IOTeeth system includes an intra-oral piezoelectric-based sensing array integrated into a dental retainer platform to support reliable occlusal disease recognition. IOTeeth focuses on biting and grinding activities from the canines and front teeth, which contain essential information of occlusion. IOTeeth's intra-oral wearable collects signals from the sensors and fetches them into a lightweight and robust deep learning model called Physioaware Attention Network (PAN Net) for occlusal disease recognition. We evaluate IOTeeth with 12 articulator teeth models from dental clinic patients. Evaluation results show an F1 score of 0.97 for activity recognition with leave-one-out validation and an average F1 score of 0.92 for dental disease recognition for different activities with leave-one-out validation.
Planning the Future in a Longer Perspective
Authors: Tateyama Naoki , Yokomura Ryota , Ban Yuki , Warisawa Shin'ichi , Fukui Rui
Published: March 2024

A long-term perspective toward the future enables a more comprehensive approach to decision-making, considering a variety of potential scenarios. The forecasting of mental health was anticipated to promote proactive planning, however, it faces challenges such as a short forecasting period and a lack of intuitive understanding of the relationship between actions and the forecast. This study presents a novel mental health indicator that incorporates a long-term perspective by considering past actions. A four-week experiment was conducted with 105 participants to evaluate the effects of a one-week forecast. Qualitative analysis reveals the effects of the one-week forecast on behavioral planning, emotional states, and reasons for disregarding the forecasts. Findings indicate that conventional mood indicators prompt participants to prioritize pre-existing schedules and perceive the forecast as infeasible, whereas the proposed indicator enhances the ability to plan work schedules in advance. Our results offer valuable insights into the presentation of forecasts for effectively managing mental health, considering the time constraints of everyday life.
Mental-LLM
Authors: Xu Xuhai , Yao Bingsheng , Dong Yuanzhe , Gabriel Saadia , Yu Hong , Hendler James , Ghassemi Marzyeh , Dey Anind K. , Wang Dakuo
Published: March 2024

Advances in large language models (LLMs) have empowered a variety of applications. However, there is still a significant gap in research when it comes to understanding and enhancing the capabilities of LLMs in the field of mental health. In this work, we present a comprehensive evaluation of multiple LLMs on various mental health prediction tasks via online text data, including Alpaca, Alpaca-LoRA, FLAN-T5, GPT-3.5, and GPT-4. We conduct a broad range of experiments, covering zero-shot prompting, few-shot prompting, and instruction fine-tuning. The results indicate a promising yet limited performance of LLMs with zero-shot and few-shot prompt designs for mental health tasks. More importantly, our experiments show that instruction finetuning can significantly boost the performance of LLMs for all tasks simultaneously. Our best-finetuned models, Mental-Alpaca and Mental-FLAN-T5, outperform the best prompt design of GPT-3.5 (25 and 15 times bigger) by 10.9% on balanced accuracy and the best of GPT-4 (250 and 150 times bigger) by 4.8%. They further perform on par with the state-of-the-art task-specific language model. We also conduct an exploratory case study on LLMs' capability on mental health reasoning tasks, illustrating the promising capability of certain models such as GPT-4. We summarize our findings into a set of action guidelines for potential methods to enhance LLMs' capability for mental health tasks. Meanwhile, we also emphasize the important limitations before achieving deployability in real-world mental health settings, such as known racial and gender bias. We highlight the important ethical risks accompanying this line of research.
XRF55
Authors: Wang Fei , Lv Yizhe , Zhu Mengdie , Ding Han , Han Jinsong
Published: March 2024

Radio frequency (RF) devices such as Wi-Fi transceivers, radio frequency identification tags, and millimeter-wave radars have appeared in large numbers in daily lives. The presence and movement of humans can affect the propagation of RF signals, further, this phenomenon is exploited for human action recognition. Compared to camera solutions, RF approaches exhibit greater resilience to occlusions and lighting conditions, while also raising fewer privacy concerns in indoor scenarios. However, current works have many limitations, including the unavailability of datasets, insufficient training samples, and simple or limited action categories for specific applications, which seriously hinder the growth of RF solutions, presenting a significant obstacle in transitioning RF sensing research from the laboratory to a wide range of everyday life applications. To facilitate the transitioning, in this paper, we introduce and release a large-scale multiple radio frequency dataset, named XRF55, for indoor human action analysis. XRF55 encompasses 42.9K RF samples and 55 action classes of human-object interactions, human-human interactions, fitness, body motions, and human-computer interactions, collected from 39 subjects within 100 days. These actions were meticulously selected from 19 RF sensing papers and 16 video action recognition datasets. Each action is chosen to support various applications with high practical value, such as elderly fall detection, fatigue monitoring, domestic violence detection, etc. Moreover, XRF55 contains 23 RFID tags at 922.38MHz, 9 Wi-Fi links at 5.64GHz, one mmWave radar at 60-64GHz, and one Azure Kinect with RGB+D+IR sensors, covering frequency across decimeter wave, centimeter wave, and millimeter wave. In addition, we apply a mutual learning strategy over XRF55 for the task of action recognition. Unlike simple modality fusion, under mutual learning, three RF modalities are trained collaboratively and then work solely. We find these three RF modalities will promote each other. It is worth mentioning that, with synchronized Kinect, XRF55 also supports the exploration of action detection, action segmentation, pose estimation, human parsing, mesh reconstruction, etc., with RF-only or RF-Vision approaches.
A Multi-sensory Kiosk Interface to Familiarize Users with New Foods
Authors: Choi Eunsol Sol , Kang Younah
Published: March 2024

Familiarity significantly impacts public willingness to try new foods, making novel foods unlikely to be consumed. However, exposing eaters to various sensory modalities---encompassing vision, smell, sound, and touch---prior to eating may enhance their willingness to try these foods. Although multisensory methodologies have already been developed to transmit the sensory cues of food digitally, existing technology is limited to replication, and novel technologies remain relatively scarce in traditional food practices. Through a sensory design activity, multisensory interactions were incorporated into a self-ordering kiosk used for daily food selection. Subsequently, we conducted an experiment to observe how participants perceived a novel food on a multisensory interface, and found them to exhibit a significantly increased willingness to try the food regardless of level of fear. We also observed the multisensory interface to yield statistically significant results in food familiarity and overall satisfaction. These findings suggest that technology that integrates sensory exposure into daily life can effectively educate and familiarize people with novel food products.