Longitudinal Data Collection Research Articles

Associations between school engagement and mental well-being among Finnish parent-child dyads

Abstract Background To understand how individual differences in mental well-being emerge for children and adolescents, it is important to understand the amenable factors in the context in which the development takes place - that is, for children, primarily in the family and in school. There is a notable gap in the research exploring the positive impacts of school factors on parent-child dyads and their mental well-being, and if there are any associations between school engagement and the mental well-being of parents and their children. Methods Data from 307 parent-child dyads were included in the study, the data stemming from a Finnish l research project (CONSENSUS) encompassing longitudinal survey data collection among both children in grades 4-6 and their parents. By exploring bivariate correlations and using the Actor-Partner Interdependence Model (APIM), the present study aims to investigate actor and partner effects of school engagement and mental well-being among parents and their child in grade 4-6. Results Preliminary results show that there are statistically significant correlations between parents’ and their children’s mental well-being, but that there are no significant correlations between children’s school engagement and parental school engagement. Further, statistically significant actor effects emerge between children’s school engagement and mental well-being, and between parental school engagement and mental well-being. Conclusions By clarifying the interaction between school engagement and mental well-being in parent-child dyads, this study not only contributes to the theoretical understanding of these constructs but also offers insights that can inform future development of mental well-being promotion interventions aimed at families and educational settings in Finland and elsewhere. Key messages • This study offers an innovative exploration of the links between mental well-being and school engagement among 274 Finnish parent-child dyads. • Results show various interactions between school engagement and mental well-being among the parent-child dyads, with implications for interventions intended to support well-being in families.

One-Year Surveillance of a Patient Cohort’s Lung Ultrasonography Findings Post Mild-Moderate COVID-19 Infection

Objective: Lung involvement due to COVID-19 infection relates to patient clinical outcomes. However, little evidence exists on whether an abnormal lung sonogram, during an initial outpatient infection, may signal an abnormal immunologic response and lasting abnormalities. The aim of this study was to observe whether high-risk outpatients, previously infected with SARS CoV-2 and found to have an initial abnormal lung sonogram, had persistent diagnostic findings at a 1-year re-examination. Materials and Methods: A prospective longitudinal cohort study was performed, based on a prior study completed in January 2022 wherein 55/201 (27%) of consecutive outpatients infected with SARS-CoV-2 received therapy at an outpatient monoclonal antibody clinic and had presented with an abnormal lung ultrasound containing at least 3 apical lung B-line artifacts (LUS+). One year later, the original 55 LUS+ patients were contacted for re-examination; as a result, 14 LUS+ patients consented to a repeat LUS tospecifically recheck the apical area of the lungs for persistent B-line artifacts. The same ultrasound equipment system and imaging methodology were used for this cohort of patients. Additional data was collected regarding COVID-19 test-positive re-infection, persistent pulmonary symptoms during the past year, and COVID-19 vaccination status. Results: Of the 14 LUS+ patients, the mean cohort age was 63 ± 9 years, of which 71% were men. Over the ensuing year, 43% had persistent symptoms, 71% had updated vaccination, and 36% had a self-reported re-infection. The re-infection was reported to have occurred a median of 7 months after the initial infection. The cohort was sub-divided into those with persistent LUS+ compared to those that reverted to a normal scan. The mean age was 69 ± 10 years among those LUS+ compared to 56 ± 8 years in the normalized group. The body mass index (BMI) was 32 kg/m2 in those LUS+ compared to 27 kg/m2 in the normalized group. The cohort has 6 men and 2 women in the LUS+ group compared to 4 men and 2 women in the normalized group. One LUS+ patient out of eight reportedly had been reinfected compared to four normalized patients out of six stated being reinfected. Three LUS+ patients out of eight reported having persistent symptoms compared to three normalized patients out of six complaining of continued COVID-19 symptoms. Conclusion: Based on the 1-year repeated LUS, for this cohort, there was a high prevalence of persistent symptoms and lung abnormalities, in those who had mild-moderate outpatient COVID-19 and received monoclonal antibody therapy. The longitudinal data collection on this cohort of COVID-19 positive outpatients may suggest that individual immune responses or viral virulence factors may play a role in B-line persistence. Certainly, future LUS results may be confounded by a previous COVID-19 infection.

The effectiveness of secondary-school based interventions on the future physical activity of adolescents in Aotearoa New Zealand: a modelling study.

Secondary schools are important settings for promoting varied physical activity (PA) opportunities for adolescents to promote PA throughout life. However, research on the effect of secondary school-based interventions on future PA is limited. This study examined the potential impact of secondary school-based interventions on the determinants of future PA participation of Aotearoa New Zealand (NZ) adolescents using simulated modelling. We used data from a nationally representative sample of secondary school students (n = 5035) aged 12-17 between 2017 and 2020 in NZ. We modelled four secondary school-based interventions and their projected impact on five determinants of future PA. Modelled interventions were the technological augmentation of physical education (TAPE), a peer-led PA mentoring programme (PL), physically active learning (PAL) and the inclusion of a natural environment play area (NE). Total weekly PA increased the most from the NE intervention (+ 0.2h/week), followed by TAPE (+ 0.08h/week), PAL (+ 0.05h/week) and PL (-0.06h/week). Current number of PA settings increased the most in NE (+ 1.75 settings/week), followed by TAPE (+ 1.29 settings/week), PAL (+ 1.21 settings/week) and PL (+ 0.73 settings/week). Current number of PA types increased the most in NE (+ 1.57 types/week), followed by PL (+ 1.05 types/week), TAPE (+ 0.34 types/week) and PAL (+ 0.15 types/week). Physical literacy scores increased the most from PL (+ 3.6%), followed by PAL (+ 3.3%), TAPE (+ 0.43%) and NE (+ 0.12%). Social support scores increased the most from PAL (+ 5%), followed by PL (+ 1.9%), TAPE (+ 1.46%) and NE (+ 0.57%). On average, all interventions benefitted determinants of future PA participation to a small degree. Results show differing magnitudes of the intervention effect by determinant, indicating the complexities surrounding the promotion of PA adherence. Future interventions could be improved through detailed consultation alongside, and involving, adolescents and stakeholders within schools. Researchers should also prioritise the collection of longitudinal PA data and explore its connection with sociodemographic differences between adolescents.

127P UK real-world longitudinal data collection and analysis in adult SMA: the Adult SMA REACH Data collection study

127P UK real-world longitudinal data collection and analysis in adult SMA: the Adult SMA REACH Data collection study

A - 88 Grandparent Caregivers Interaction with Experiences of Discrimination Effect on Perceptions of Cognitive Control

Abstract Objective This study hypothesized that perceptions of cognitive ability control will differ according to grandparent caregiving status and perceptions of discrimination based on age. Control beliefs mediate the relation between discrimination and executive function. Due to the intersectional nature of grandparents who raise grandchildren and minority statuses compared to non-caregiving grandparents, it is thought that perceptions of age being the main reason of discrimination will differentially affect caregiving grandparents compared to non-caregiving grandparents perceptions of control over cognitive ability. Method Data included 92 caregiving and 407 non-caregiving grandparent participants from the third wave of a longitudinal data collection survey Midlife in the United States study (MIDUS III). MIDUS III included self-administered surveys assessing caregiver status, perceptions of main reasons of discrimination, and perceptions of cognitive control. Result A 2-way ANOVA was performed to analyze the effect of grandparent caregiver status and age discrimination perceptions on perceptions of cognitive ability control. A 2-way ANOVA revealed there was a significant interaction between the effects of grandparent caregiver status and perceptions of aging discrimination (F(1, 498) = 7047, p < 0.001). Conclusions Grandparent caregivers are more likely to have higher perceptions of control over cognitive ability when they do not perceive age as a main reason for discrimination; whereas non-caregiving grandparents have higher perceptions of control over cognitive ability when they do perceive age as a main reason for discrimination. Perceptions of why individuals are discriminated against may interact with personal factors that contribute to perceptions of control in cognitive ability.

Feasibility of Measuring Smartphone Accelerometry Data During a Weekly Instrumented Timed Up-and-Go Test After Emergency Department Discharge: Prospective Observational Cohort Study.

Older adults discharged from the emergency department (ED) face elevated risk of falls and functional decline. Smartphones might enable remote monitoring of mobility after ED discharge, yet their application in this context remains underexplored. This study aimed to assess the feasibility of having older adults provide weekly accelerometer data from an instrumented Timed Up-and-Go (TUG) test over an 11-week period after ED discharge. This single-center, prospective, observational, cohort study recruited patients aged 60 years and older from an academic ED. Participants downloaded the GaitMate app to their iPhones that recorded accelerometer data during 11 weekly at-home TUG tests. We measured adherence to TUG test completion, quality of transmitted accelerometer data, and participants' perceptions of the app's usability and safety. Of the 617 approached patients, 149 (24.1%) consented to participate, and of these 149 participants, 9 (6%) dropped out. Overall, participants completed 55.6% (912/1639) of TUG tests. Data quality was optimal in 31.1% (508/1639) of TUG tests. At 3-month follow-up, 83.2% (99/119) of respondents found the app easy to use, and 95% (114/120) felt safe performing the tasks at home. Barriers to adherence included the need for assistance, technical issues with the app, and forgetfulness. The study demonstrates moderate adherence yet high usability and safety for the use of smartphone TUG tests to monitor mobility among older adults after ED discharge. Incomplete TUG test data were common, reflecting challenges in the collection of high-quality longitudinal mobility data in older adults. Identified barriers highlight the need for improvements in user engagement and technology design.

Study protocol for a randomized controlled trial of neurofeedback mindfulness in chronic migraines

Chronic migraine is a debilitating headache disorder that is associated with excessive analgesic use. As the long-term use of analgesics could cause additional headaches due to medication overuse, there is a need to probe efficient nonprophylactic alternatives and migraineurs’ long-term adherence to such possible treatments. This protocol investigates the integration of neurofeedback and mindfulness which are the two common nonpharmacological therapies for migraines. We offer the use of portable EEG headbands for easy home-based data collection and consistent data access from researchers. In order to evaluate the efficacy of this recommended intervention, this is a protocol for a randomized control trial with a waitlisted group and an intervention group consisting of a daily attention task. The protocol presents important criteria which should be checked for consistency in longitudinal data collection from adults with chronic migraine.

The relational nature of citizen science

Abstract Most citizen science research inherently separates the observer (citizen science participant) from the observation (e.g. data point), placing artificial boundaries around what matters and how it comes to matter. We apply three elements of the philosophical framework of agential realism to reveal a more complex picture of how data arise within citizen science programmes, and its meaning to both the practice of science and the citizen science participant: ‘intra‐action’ (all entities have agency and are entangled with one another); ‘material becoming’ (what comes to matter); and ‘responsibility’ (accountability for what comes to matter and what is excluded from mattering). We draw on a case study of FrogID—an Australia‐wide citizen science program focused on calling frogs, with over 42,000 participants and over 1 million frog records. We conducted semi‐structured interviews with 30 FrogID users, completing two rounds of thematic and relational coding. Our findings reveal that as a consequence of their recording behaviours, FrogID participants become increasingly entangled with the nocturnal environment, with sound and with their own self. Expanding and reciprocal relationships and experiences shape the nature and frequency of their recordings. Second, meaning influences what comes to matter (i.e. what is recorded and submitted) for FrogID participants. We reveal meaning related to feedback (recognition and thus reciprocity), others (social networks and participation with family and friends) and the self (physical and mental well‐being and identity formation/becoming). These different forms of meaning influenced engagement with app use. Third, participants communicated responsibilities related to their involvement in citizen science, including responsibilities to create knowledge (e.g. longitudinal data collection), to conserve (e.g. actively conserving frog, formally committing areas to conservation) and to educate self and others (e.g. skills and competencies required for environmental action). Synthesis and applications: By recognizing a more comprehensive set of intra‐actions, beyond the observer and the observation, agential realism can reveal when, why and how citizen science observations are made; what observations come to matter and why; and how people can create a more just world. Agential realism can shape how citizen science participation, retention and biodiversity data generation are founded. We propose three opportunities for citizen science programs based on these findings. Read the free Plain Language Summary for this article on the Journal blog.

Open Network for Digital Commerce in India: Past, Present, and Future

Abstract The primary objective of this article is to provide a comprehensive analysis of the open network for digital commerce (ONDC), an innovative initiative by the Indian government. The study aims to explore the potential impact of ONDC on India’s digital commerce sector, focusing on how it seeks to democratize digital commerce and create an environment characterized by fair competition, innovation, and inclusivity. Our methodology involves an extensive review and thematic analysis of relevant literature. This approach includes a detailed examination of ONDC’s core objectives, its technological underpinnings, and the role of the government in facilitating its growth and adoption. The study is designed to provide a holistic view of ONDC, considering various aspects such as technology, policy, and market dynamics. The analysis suggests that ONDC could revolutionize India’s digital commerce ecosystem. Key findings indicate that ONDC can enhance interoperability, empower small businesses and local retailers, and diversify consumer choices. The initiative’s reliance on existing digital frameworks like the Unified Payments Interface and the Data Empowerment and Protection Architecture is crucial in streamlining transactions and bolstering data security. However, the realization of ONDC’s full potential is contingent upon its effective implementation and widespread acceptance among stakeholders. This study contributes to the existing body of knowledge by comprehensively analysing ONDC, a relatively new and underexplored area in digital commerce research. It offers original insights into the initiative’s potential to transform India’s digital commerce landscape. The article also identifies gaps in current research, such as the limited scope of existing studies, the absence of primary data, and the influence of external variables. It suggests avenues for future research, including longitudinal studies, international comparisons, and primary data collection, to understand ONDC better and its long-term impact on India’s digital commerce sector.

What Radio Waves Tell Us about Sleep!

The ability to assess sleep at home, capture sleep stages, and detect the occurrence of apnea (without on-body sensors) simply by analyzing the radio waves bouncing off people's bodies while they sleep is quite powerful. Such a capability would allow for longitudinal data collection in patients' homes, informing our understanding of sleep and its interaction with various diseases and their therapeutic responses, both in clinical trials and routine care. In this article, we develop an advanced machine learning algorithm for passively monitoring sleep and nocturnal breathing from radio waves reflected off people while asleep. Validation results in comparison with the gold standard (i.e., polysomnography) (n=880) demonstrate that the model captures the sleep hypnogram (with an accuracy of 80.5% for 30-second epochs categorized into Wake, Light Sleep, Deep Sleep, or REM), detects sleep apnea (AUROC = 0.89), and measures the patient's Apnea-Hypopnea Index (ICC=0.90; 95% CI = [0.88, 0.91]). Notably, the model exhibits equitable performance across race, sex, and age. Moreover, the model uncovers informative interactions between sleep stages and a range of diseases including neurological, psychiatric, cardiovascular, and immunological disorders. These findings not only hold promise for clinical practice and interventional trials but also underscore the significance of sleep as a fundamental component in understanding and managing various diseases.

Advancing high quality longitudinal data collection: Implications for the HEALthy Brain and Child Development (HBCD) Study design and recruitment

The HEALthy Brain and Child Development (HBCD) Study, a multi-site prospective longitudinal cohort study, will examine human brain, cognitive, behavioral, social, and emotional development beginning prenatally and planned through early childhood. The HBCD Study aims to reflect the sociodemographic diversity of pregnant individuals in the U.S. The study will also oversample individuals who use substances during pregnancy and enroll similar individuals who do not use to allow for generalizable inferences of the impact of prenatal substance use on trajectories of child development. Without probability sampling or a randomization-based design, the study requires innovation during enrollment, close monitoring of group differences, and rigorous evaluation of external and internal validity across the enrollment period. In this article, we discuss the HBCD Study recruitment and enrollment data collection processes and potential analytic strategies to account for sources of heterogeneity and potential bias. First, we introduce the adaptive design and enrollment monitoring indices to assess and enhance external and internal validity. Second, we describe the visit schedule for in-person and remote data collection where dyads are randomly assigned to visit windows based on a jittered design to optimize longitudinal trajectory estimation. Lastly, we provide an overview of analytic procedures planned for estimating trajectories.

Compliance and response consistency in a lengthy intensive longitudinal data protocol.

Research on real-world patterns of substance use increasingly involves intensive longitudinal data (ILD) collection, requiring long assessment windows. The present study extends limited prior research examining event- and person-level influences on compliance and response consistency by investigating how these behaviors are sustained over time in an ILD study of alcohol and cannabis co-use in college students. Participants (n = 316) completed two 28-day bursts of ILD comprising five daily surveys, which included a morning survey of prior-day drinking. We used linear mixed effects models in a multilevel interrupted time series framework to evaluate the associations of time and measurement burst with (a) noncompliance (count of missed surveys) and (b) response consistency (difference between same-day report of drinking and morning report of prior-day drinking). We observed that time was positively associated with noncompliance, with no discontinuity associated with measurement burst. The slope of time was more positive in the second burst. Neither time nor measurement burst were significantly associated with consistent reporting. However, survey nonresponse and consistency of responding appeared to be impacted by the same-day use of substances. Overall, compliance decreased while consistency was stable across the duration of a lengthy ILD protocol. Shorter assessment windows or adaptive prompting strategies may improve overall study compliance. Further work examining daily burden and context is needed to inform future ILD design. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Burden and Inattentive Responding in a 12-Month Intensive Longitudinal Study: Interview Study Among Young Adults.

Intensive longitudinal data (ILD) collection methods have gained popularity in social and behavioral research as a tool to better understand behavior and experiences over time with reduced recall bias. Engaging participants in these studies over multiple months and ensuring high data quality are crucial but challenging due to the potential burden of repeated measurements. It is suspected that participants may engage in inattentive responding (IR) behavior to combat burden, but the processes underlying this behavior are unclear as previous studies have focused on the barriers to compliance rather than the barriers to providing high-quality data. This study aims to broaden researchers' knowledge about IR during ILD studies using qualitative analysis and uncover the underlying IR processes to aid future hypothesis generation. We explored the process of IR by conducting semistructured qualitative exit interviews with 31 young adult participants (aged 18-29 years) who completed a 12-month ILD health behavior study with daily evening smartphone-based ecological momentary assessment (EMA) surveys and 4-day waves of hourly EMA surveys. The interviews assessed participants' motivations, the impact of time-varying contexts, changes in motivation and response patterns over time, and perceptions of attention check questions (ACQs) to understand participants' response patterns and potential factors leading to IR. Thematic analysis revealed 5 overarching themes on factors that influence participant engagement: (1) friends and family also had to tolerate the frequent surveys, (2) participants tried to respond to surveys quickly, (3) the repetitive nature of surveys led to neutral responses, (4) ACQs within the surveys helped to combat overly consistent response patterns, and (5) different motivations for answering the surveys may have led to different levels of data quality. This study aimed to examine participants' perceptions of the quality of data provided in an ILD study to contribute to the field's understanding of engagement. These findings provide insights into the complex process of IR and participant engagement in ILD studies with EMA. The study identified 5 factors influencing IR that could guide future research to improve EMA survey design. The identified themes offer practical implications for researchers and study designers, including the importance of considering social context, the consideration of dynamic motivations, and the potential benefit of including ACQs as a technique to reduce IR and leveraging the intrinsic motivators of participants. By incorporating these insights, researchers might maximize the scientific value of their multimonth ILD studies through better data collection protocols. RR2-10.2196/36666.

Beyond age and intensive exposure: Initial proficiency effects on adolescents’ second language proficiency in an international school

This study investigates the effects of biological age and intensive exposure on L2 learning in an International School context as regards variability in learning rate and L2 development among pre- versus mid-adolescent learners. Longitudinal data collection at three time-points over one year involved semi-guided interviews and written productions among 28 L1-French learners of English in two age groups, either 11 years or 15 years of age. The data were investigated using quantitative measures of accuracy, fluency and holistic proficiency, and analysed with robust repeated measures ANOVAs and ANCOVAs. The findings suggest that the one-year intensive experience of English learning in the International School promoted significant gains in accuracy and holistic proficiency, but only one aspect of fluency, i.e., speech rate. When initial proficiency as Time 1 performance was controlled, the 15-year-old learners performed better than their younger peers only in written proficiency, while the 11-year-olds showed a faster learning rate in some aspects of oral accuracy and fluency. However, initial proficiency eclipsed age and exposure effects on L2 proficiency development during the one-year intensive experience. These results suggest that, for the introduction of short intensive programs in instructed contexts, learners’ initial proficiency and biological age should be considered.

Modelling the nicotine pharmacokinetic profile for e-cigarettes using real time monitoring of consumers’ physiological measurements and mouth level exposure

Pharmacokinetic (PK) studies can provide essential information on abuse liability of nicotine and tobacco products but are intrusive and must be conducted in a clinical environment. The objective of the study was to explore whether changes in plasma nicotine levels following use of an e-cigarette can be predicted from real time monitoring of physiological parameters and mouth level exposure (MLE) to nicotine before, during, and after e-cigarette vaping, using wearable devices. Such an approach would allow an -effective pre-screening process, reducing the number of clinical studies, reducing the number of products to be tested and the number of blood draws required in a clinical PK study Establishing such a prediction model might facilitate the longitudinal collection of data on product use and nicotine expression among consumers using nicotine products in their normal environments, thereby reducing the need for intrusive clinical studies while generating PK data related to product use in the real world.An exploratory machine learning model was developed to predict changes in plasma nicotine levels following the use of an e-cigarette; from real time monitoring of physiological parameters and MLE to nicotine before, during, and after e-cigarette vaping. This preliminary study identified key parameters, such as heart rate (HR), heart rate variability (HRV), and physiological stress (PS) that may act as predictors for an individual’s plasma nicotine response (PK curve). Relative to baseline measurements (per participant), HR showed a significant increase for nicotine containing e-liquids and was consistent across sessions (intra-participant). Imputing missing values and training the model on all data resulted in 57% improvement from the original’learning’ data and achieved a median validation R2 of 0.70.The study is in its exploratory phase, with limitations including a small and non-diverse sample size and reliance on data from a single e-cigarette product. These findings necessitate further research for validation and to enhance the model's generalisability and applicability in real-world settings. This study serves as a foundational step towards developing non-intrusive PK models for nicotine product use.

A Prospective Observational Cohort Study for Newly Diagnosed Osteosarcoma Patients in the UK: ICONIC Study Initial Results.

There has been little change to the standard treatment for osteosarcoma (OS) over the last 25 years and there is an unmet need to identify new biomarkers and novel therapeutic approaches if outcomes are to improve. Furthermore, there is limited evidence on the impact of OS treatment on patient-reported outcomes (PROs). ICONIC (Improving Outcomes through Collaboration in Osteosarcoma; NCT04132895) is a prospective observational cohort study recruiting newly diagnosed OS patients across the United Kingdom (UK) with matched longitudinal collection of clinical, biological, and PRO data. During Stage 1, which assessed the feasibility of recruitment and data collection, 102 patients were recruited at 22 sites with representation from patient groups frequently excluded in OS studies, including patients over 50 years and those with less common primary sites. The feasibility of collecting clinical and biological samples, in addition to PRO data, has been established and there is ongoing analysis of these data as part of Stage 2. ICONIC will provide a unique, prospective cohort of newly diagnosed OS patients representative of the UK patient population, with fully annotated clinical outcomes linked to molecularly characterised biospecimens, allowing for comprehensive analyses to better understand biology and develop new biomarkers and novel therapeutic approaches.

Self-Assessment of Cochlear Health by New Cochlear Implant Recipients: Daily Impedance, Electrically Evoked Compound Action Potential and Electrocochleography Measurements Over the First Three Postoperative Months.

In newly implanted cochlear implant (CI) users, electrically evoked compound action (eCAPs) and electrocochleography (ECochGs) will remain stable over time. Electrode impedances will increase immediately postimplantation due to the initial inflammatory response, before decreasing after CI switch-on and stabilizing thereafter. The study of cochlear health (CH) has several applications, including explaining variation in CI outcomes, informing CI programming strategies, and evaluating the safety and efficacy of novel biological treatments for hearing loss. Very early postoperative CH patterns have not previously been intensively explored through longitudinal daily testing. Thanks to technological advances, electrode impedances, eCAPs, and ECochGs can be independently performed by CI users at home to monitor CH over time. A group of newly implanted CI users performed daily impedances, eCAPs, and ECochGs for 3 months at home, starting from the first day postsurgery (N = 7) using the Active Insertion Monitoring system by Advanced Bionics. Measurement validity of 93.5, 93.0, and 81.6% for impedances, eCAPs, and ECochGs, respectively, revealed high participant compliance. Impedances increased postsurgery before dropping and stabilizing after switch-on. eCAPs showed good stability, though statistical analyses revealed a very small but significant increase in thresholds over time. Most ECochG thresholds did not reach the liberal signal-to-noise criterion of 2:1, with low threshold stability over time. Newly implanted CI recipients can confidently and successfully perform CH recordings at home, highlighting the valuable role of patients in longitudinal data collection. Electrode impedances and eCAPs are promising objective measurements for evaluating CH in newly implanted CI users.

Major Problems in Clinical Psychological Science and How to Address them. Introducing a Multimodal Dynamical Network Approach

Abstract Background Despite impressive dissemination programs of best-practice therapies, clinical psychology faces obstacles in developing more efficacious treatments for mental disorders. In contrast to other medical disciplines, psychotherapy has made only slow progress in improving treatment outcomes. Improvements in the classification of mental disorders could enhance the tailoring of treatments to improve effectiveness. We introduce a multimodal dynamical network approach, to address some of the challenges faced by clinical research. These challenges include the absence of a comprehensive meta-theory, comorbidity, substantial diagnostic heterogeneity, violations of ergodicity assumptions, and a limited understanding of causal processes. Methods Through the application of multimodal dynamical network analysis, we describe how to advance clinical research by addressing central problems in the field. By utilizing dynamic network analysis techniques (e.g., Group Iterative Multiple Model Estimation, multivariate Granger causality), multimodal measurements (i.e., psychological, psychopathological, and neurobiological data), intensive longitudinal data collection (e.g., Ecological Momentary Assessment), and causal inference methods (e.g., GIMME), our approach could improve the comprehension and treatment of mental disorders. Under the umbrella of the systems approach and utilizing e.g., graph theory and control theory, we aim to integrate data from longitudinal, multimodal measurements. Results The multimodal dynamical network approach enables a comprehensive understanding of mental disorders as dynamic networks of interconnected symptoms. It dismantles artificial diagnostic boundaries, facilitating a transdiagnostic view of psychopathology. The integration of longitudinal data and causal inference techniques enhances our ability to identify influential nodes, prioritize interventions, and predict the impact of therapeutic strategies. Conclusion The proposed approach could improve psychological treatment by providing individualized models of psychopathology and by suggesting individual treatment angles.

British Axial Spondyloarthritis Inception Cohort (BAxSIC): a protocol for a multicentre real-world observational cohort study of early axial spondyloarthritis.

Timely diagnosis remains a challenge in axial SpA (axSpA). In addition, data are scarce on the impact of diagnostic delay and disease progression in affected individuals. The British Axial Spondyloarthritis Inception Cohort (BAxSIC) study aims to investigate the impact of newly diagnosed axSpA, the natural history of the disease and the effect of diagnostic delay on disease outcomes. BAxSIC is a prospective, multicentre, observational study. Eligible participants are adults (≥16 years of age), with a physician-confirmed diagnosis of axSpA in the 6 months prior to study entry, recruited from secondary and tertiary rheumatology centres in the UK. Participants will be followed up for 3 years, with in-person visits at baseline and 24 months. In addition, patient self-reported assessments will be recorded remotely via the online electronic case report form (eCRF) at 6, 12, 18, 30 and 36 months. The first patient was enrolled in BAxSIC in June 2023. Recruitment is currently ongoing and is planned to end in June 2026. Initial results will be available in 2027. Since opening, the trial has undergone two protocol amendments. The BAxSIC study is the first inception cohort designed to investigate the impact of diagnostic delay on clinical presentation and long-term functional outcomes in patients with axSpA in the UK. With an innovative, patient-led virtual longitudinal data collection model, data generated from this study will help inform and improve the care of people newly diagnosed with axSpA. ClinicalTrials.gov (http://clinicaltrials.gov), NCT05676775.

Performance characteristics of a tissue-agnostic genome-wide methylome enrichment MRD assay for head and neck malignancies.

3009 Background: Plasma cell-free DNA (cfDNA) tests have emerged as a promising approach for cancer management. cfDNA methylome approaches are well-suited for molecular residual disease (MRD) detection. Here we present data using a tissue-agnostic, genome-wide methylome enrichment platform based on cell-free methylated DNA immunoprecipitation and high throughput sequencing (cfMEDIP-seq) in head and neck cancer (HNC) to predict relapse for purposes of guiding adjuvant therapy after completion of curative-intent treatment and to detect early relapse. Methods: The cohort is comprised of biobanked samples from individuals diagnosed with stage I-IVB human papillomavirus (HPV)-negative and HPV-positive HNC with longitudinal data collection and sampling. The full cohort includes 325 unique patients with 1,155 samples. Samples were split into distinct sets to train and test a classifier consisting of differentially methylated regions. Blood collection time points include at diagnosis, and approximately 3 (landmark), 12 and 24 months after curative intent treatment. 5-10 ng of cfDNA isolated from each plasma sample was used for cfMEDIP-seq. MRD signals were quantified from average normalized counts across informative methylated regions and binarized into a positive (above the threshold) and negative groups. Recurrence-free survival (RFS) was compared for patients who tested positive to those who tested negative at 3 months post-curative treatment (i.e., landmark timepoint) and longitudinally. Results: A total of 196 post-treatment samples from 80 unique patients [stage I (35%), II (15%), III (24%), IV (26%)] were analyzed and correlated with recurrence, in this interim training result. At the landmark timepoint, patients who tested positive showed significantly worse RFS than those who tested negative (Hazard ratio (HR) 9.69; 95% CI, 4.39-21.4, P<0.001). Incorporating serial longitudinal samples, recurrence-free survival was worse in patients who tested positive compared to those that tested negative (HR 14.52; 95% CI, 5.78-36.46, P<0.001). Conclusions: Interim analysis demonstrates that MRD detection with a tissue-agnostic, genome-wide methylome enrichment platform in HNC patients after curative intent treatment correlates strongly with RFS with hazard ratios consistent with tumor-informed assays previously described. Updated analyses from the cohort will be presented at the meeting.