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User-Driven Development of a Digital Behavioral Intervention for Chronic Pain:Multimethod Multiphase Study
No full textBACKGROUND: Recent research shows that chronic pain affects 27% of the adult population. For many, pain significantly impairs quality of life and everyday functioning. Behavioral interventions have shown utility, but access remains limited. Digital health solutions can increase reach, but there is a need for user-friendly, feasible, and evidence-based digital interventions. OBJECTIVE: This study aimed to clarify how a digital behavioral intervention for people with chronic pain can be developed through a user-centered approach to address the needs and preferences of the target population. METHODS: This study used a multimethod approach involving end users, namely, patients with chronic pain and therapists, to develop prototypes for a digital behavioral intervention across 3 phases. In the preparation phase (phase 0), fictional patient personas (n=3) were created to represent the diversity of the target population while emphasizing transdiagnostic features across people with chronic pain. In the design phase (phase 1), qualitative data from focus groups with patients (n=5; aged 37-51 years; 4/5, 80% women; 2/5, 40% diagnosed with Ehlers-Danlos syndrome; 3/5, 60% either undiagnosed or uncertain about their diagnosis) and therapists (n=12 licensed psychologists; aged 29-64 years; 9/12, 75% women) were collected to explore end-user preferences for the intervention design and content. In the testing phase (phase 2), the initial full prototype of the digital intervention was piloted with patients (n=11; aged 36-58 years; 9/11, 82% women; with diverse diagnoses, including migraine, arthritis, fibromyalgia, complex regional pain syndrome, hypermobile Ehlers-Danlos syndrome, herniated disc, chronic fatigue syndrome, and 1/11, 9% cases of undiagnosed pain) and therapists (n=3 licensed psychologists; aged 36-58 y; 3/3, 100% women). The Consolidated Framework for Implementation Research was used to structure analyses of end-user feedback. RESULTS: On the basis of end-user input, a 6-week digital behavioral intervention for chronic pain was created. Focus groups highlighted the importance of accessibility and adaptability of the digital intervention, emphasizing the need for tailored content, flexibility (eg, contact with the therapist via asynchronous messaging, telephone, or video calls), and user-friendly design (eg, easy navigation between modules, short microsessions, and visualizations). Average weekly ratings (scale from 1=not at all to 7=very much) by patients during pilot-testing indicated that the intervention was helpful (mean range 4.27-5.45, SD range 1.20-2.20), enjoyable (mean range 3.81-4.81, SD range 1.12-2.08), and understandable (mean range 4.45-6, SD range 1.30-1.86), suggesting initial acceptability and usability of the intervention. CONCLUSIONS: The results illustrated the utility of the patient personas when preparing, of the focus groups when designing, and of the end-user feedback when testing this new digital intervention for people with chronic pain. The findings indicated that the intervention is promising while also providing relevant end-user suggestions (eg, video content, text-to-speech function, and add-on modules) to guide further improvements
Autoimmune/Autoinflammatory Syndrome Induced by Adjuvants (ASIA Syndrome) After Polypropylene Mesh Implantation - Protocol of a Pilot Study for Diagnostics and Treatment
No full textBACKGROUND: An increasingly vocal movement of patients with systemic complaints, supposedly linked to polypropylene mesh implants, is leading to increasing numbers of patient-preferred mesh-less surgical repairs for inguinal hernia, stress urinary incontinence, and pelvic organ prolapse. However, current literature does not support any association between polypropylene implants and Autoimmune Syndrome Induced by Adjuvants (ASIA). This prospective pilot aims to examine autoimmunity in patients in whom ASIA is suspected, based on previously described criteria. We aim to demonstrate the effectiveness of mesh allergy testing and to investigate the natural evolvement of ASIA symptoms or the effect of mesh removal on ASIA complaints. METHODS: This multi-centre, prospective pilot study will include patients with symptoms of the ASIA syndrome according to Shoenfeld's Criteria. Physical examination, immunologic blood tests, and mesh allergy tests will be performed by an experienced immunologist and surgeon. Questionnaires on improvement of symptoms, psychological susceptibility, and connective tissue disease will be collected at predefined time points. When patients' wish for mesh removal is persistent, mesh implants will be removed surgically. All meshes will be assessed histopathologically. Follow-up is 12 months. DISCUSSION: Current evidence on a causal relation between polypropylene mesh and ASIA syndrome is lacking. In this study, mesh allergy testing will be evaluated as a potential first objective screening test for inflammation-like response specific to polypropylene, in patients meeting diagnostic criteria for ASIA syndrome following polypropylene implantation. This study will be performed to add to existing literature on ASIA with polypropylene adjuvants and to help reduce knowledge gaps on diagnosis and prognosis
Tiny-objective segmentation for spot signs on multi-phase CT angiography via contrastive learning with dynamic-updated positive-negative memory banks
No full textBACKGROUND AND OBJECTIVE: Presence of spot sign on CT Angiography (CTA) is associated with hematoma growth in patients with intracerebral hemorrhage. Measuring spot sign volume over time may aid to predict hematoma expansion. Due to the difficulties that imaging characteristics of spot sign are similar with vein and calcification and spot signs are tiny appeared in CTA images to detect, our aim is to develop an automated method to pick up spot signs accurately. METHODS: We proposed a novel collaborative architecture of network based on a student-teacher model by efficiently exploiting additional negative samples with contrastive learning. In particular, a set of dynamic-updated memory banks is proposed to learn more distinctive features from the extremely imbalanced positive and negative samples. Alongside, a two-steam network with an additional contextual-decoder is designed for learning more contextual information at different scales in a collaborative way. Besides, to better inhibit the false positive detection rate, a region restriction loss function is further designed to confine the spot sign segmentation within the hemorrhage. RESULTS: Quantitative evaluations using dice, volume correlation, sensitivity, specificity, area under the curve show that the proposed method is able to segment and detect spot signs accurately. Our proposed contractive learning framework obtained the best segmentation performance regarding a mean Dice of 0.638 ± 0211, a mean VC of 0.871 and a mean VDP of 0.348 ± 0.237 and detection performance regarding sensitivity of 0.956 with CI(0.895,1.000), specificity of 0.833 with CI(0.766,0.900), and AUC of 0.892 with CI(0.888,0.896), outperforming nnuNet, cascade-nnuNet, nnuNet++, SegRegNet, UNETR and SwinUNETR. CONCLUSION: This paper proposed a novel segmentation approach that leverages contrastive learning to explore additional negative samples concurrently for the automatic segmentation of spot signs on mCTA images. The experimental results demonstrate the effectiveness of our method and highlight its potential applicability in clinical settings for measuring spot sign volumes
Experiences, perceptions and attitudes on providing advice on physical activity to patients with chronic ischaemic heart disease:a qualitative study in general practitioners in Germany
No full textBACKGROUND AND OBJECTIVE: The WHO emphasises the importance of integrating advice on physical activity (PA) into primary care of patients with chronic ischaemic heart disease (IHD). Similarly, the German treatment guideline 'Chronic Coronary Heart Disease' recommends that general practitioners (GPs) provide advice on PA to IHD patients. However, the provision of PA advice seems to be inadequately implemented in general practice. One reason is the lack of medical training in providing PA advice effectively and efficiently. International guidelines recommend such training for health professionals. This study aims to explore experiences, perceptions and attitudes, including barriers and facilitators of GPs towards the routine delivery of PA advice to IHD patients. METHODS: Between March and June 2023, 12 face-to-face problem-centred interviews and six focus group discussions (n=37) with GPs were conducted. Interview and discussion guides were developed and pilot tested by the multi-professional study team. We used a purposive sampling strategy, and data were collected in an iterative process. Audio-recorded data were transcribed verbatim and analysed using a content structuring procedure (deductive and inductive approach). GPs were involved throughout the entire research process, for example, in multi-professional analysis groups. RESULTS: Although GPs are mostly aware of the health benefits of PA for patients with IHD, PA advice is not routinely provided. Conversations on PA tend to be rather unstructured, and advice is often addressed more generally than customised to the patients' needs and preferences. Priority is given to other lifestyle issues, such as smoking cessation. PA advice is perceived as time-consuming and rather ineffective with regard to the target behaviour. GPs frequently express frustration in this context. GPs express a lack of and simultaneously a need for communication strategies (structure and tools) that can be integrated into everyday GP practice to motivate patients to PA. CONCLUSION: The results provide relevant insights into the current practice of GPs with regard to their attitudes on, experiences with, and requirements for the provision of PA advice to IHD patients. These results are helpful to inform the development of appropriate GP training in the provision of very brief PA advice to IHD patients
The Risk of Mild, Moderate, and Severe Infections in IBD patients - A prospective, multicentre observational cohort study (PRIQ)
No full textBACKGROUND: In light of the growing number of treatment options, the benefit-risk balance of IBD drugs is increasingly important in clinical decision-making. Post-marketing surveillance studies are pivotal to assess infection risk, yet mainly focus on severe infections. This study aimed to assess the incidence and risk factors associated with mild, moderate, and severe infections in IBD patients. METHODS: We previously developed and validated a Patient-Reported Infections Questionnaire (PRIQ) which accurately assesses 15 infection categories with a 3-month recall period. The current prospective, multicentre, observational cohort study was performed between June 1, 2020 and July 1, 2021, enrolling consecutive IBD patients using myIBDcoach. Incidence rates (IR) were calculated for all infections and negative binomial regression was utilized to identify risk factors for infections over time. RESULTS: In total, 629 IBD patients (n=346 CD, n=283 UC, 58.3% female) were included, completing 2397 PRIQs during 573.8 person-years (PY) of follow-up. This resulted in 991 reported infections and an overall IR of 172.7 per 100PY, predominantly characterized by mild (IR 117.5 per 100PY) and moderate (IR 50.9 per 100PY) infections. Risk factors significantly associated with increased overall infection rates included female sex, higher comorbidity burden, smoking, and specific treatments, such as steroids, immunomodulators, anti-TNF agents, and JAK-inhibitors, with steroids doubling infection risk (IRR 2.02). CONCLUSION: Mild and moderate infections are common among IBD patients and are particularly associated with both patient characteristics and specific immunosuppressive treatments. These findings emphasize the need for vigilant monitoring, especially for patients at higher infection risk, and allow for more personalized advice on benefit-risk of IBD treatments
Correcting Beliefs About Job Opportunities and Wages: A Field Experiment on Education Choices
No full textWe run a field experiment in which we provide information to students about job opportunities and hourly wages of occupations they are interested in. The experiment takes place within a widely-used career orientation program in the Netherlands, and involves 28,186 pre-vocational secondary education students in 243 schools over two years. The information improves the accuracy of students’ beliefs and leads them to change their preferred occupation to one with better labor market prospects. Administrative data that covers up to four years after the experiment shows that students choose (and remain in) post-secondary education programs with better job opportunities and higher hourly wages as a result of the information treatment
Evaluating multiple large language models on orbital diseases
No full textThe avoidance of mistakes by humans is achieved through continuous learning, error correction, and experience accumulation. This process is known to be both time-consuming and laborious, often involving numerous detours. In order to assist humans in their learning endeavors, ChatGPT (Generative Pre-trained Transformer) has been developed as a collection of large language models (LLMs) capable of generating responses that resemble human-like answers to a wide range of problems. In this study, we sought to assess the potential of LLMs as assistants in addressing queries related to orbital diseases. To accomplish this, we gathered a dataset consisting of 100 orbital questions, along with their corresponding answers, sourced from examinations administered to ophthalmologist residents and medical students. Five language models (LLMs) were utilized for testing and comparison purposes, namely, GPT-4, GPT-3.5, PaLM2, Claude 2, and SenseNova. Subsequently, the LLM exhibiting the most exemplary performance was selected for comparison against ophthalmologists and medical students. Notably, GPT-4 and PaLM2 demonstrated a superior average correlation when compared to the other LLMs. Furthermore, GPT-4 exhibited a broader spectrum of accurate responses and attained the highest average score among all the LLMs. Additionally, GPT-4 demonstrated the highest level of confidence during the test. The performance of GPT-4 surpassed that of medical students, albeit falling short of that exhibited by ophthalmologists. In contrast, the findings of the study indicate that GPT-4 exhibited superior performance within the orbital domain of ophthalmology. Given further refinement through training, LLMs possess considerable potential to be utilized as comprehensive instruments alongside medical students and ophthalmologists
Positron emission tomography imaging biomarker and artificial intelligence for the characterization of solitary pulmonary nodule
No full textBackground The characterization of solitary pulmonary nodules (SPNs) as malignant or benign remains a diagnostic challenge using conventional imaging parameters. The literature suggests using combined Positron Emission Tomography (PET) and Computed Tomography (CT) to characterise a SPN. Radiomics and machine learning are other promising technologies which can be utilised to characterise the SPN.Purpose This study explores the potential of PET radiomics signatures and machine learning algorithms to characterise the SPN.Methods This retrospective study aimed to characterize solitary pulmonary nodules (SPNs) using PET radiomics. A total of 163 patients who underwent PET/CT imaging were included in this study. A total of 1,098 features were extracted from PET images using PyRadiomics. To optimize model performance two strategies i.e., (a) feature selection and (b) feature reduction techniques were employed, including hierarchical clustering, RFE in feature selection, and PCA in feature reduction. To address outcome class imbalance, the dataset was statistically resampled (SMOTE). A random forest models was developed using original training set (RF-Model-O & RF-PCA-Model-O) and balanced training dataset (RF-Model-B & RF-PCA-Model-B) and validated on the test datasets. Additionally, 5-fold cross-validation and bootstrap validation was also performed. The model's performance was assessed using various metrics, such as accuracy, AUC, precision, recall, and F1-score.Results Of the 163 patients (aged 36-76 years, mean age 58 +/- 7), 117 had malignant disease and 46 had granulomatous or benign conditions. In Strategy (a), five radiomic features were identified as optimal using hierarchical clustering and RFE. In Strategy (b), five principal components were deemed optimal using PCA. The model accuracy of RF-Model-O and RF-Model-B in the train-test validation, 5-fold cross-validation and bootstrap validation were found to be 0.8, 0.80 +/- 0.07, 0.84 +/- 1.11 and 0.8, 0.83 +/- 0.10, 0.80 +/- 0.07 in Strategy (a). Similarly, the model accuracy of RF-PCA-Model-O and RF-PCA-Model-B in the train-test validation, 5-fold cross-validation and bootstrap validation were found to be 0.84, 0.80 +/- 0.07, 0.84 +/- 07 and 0.74, 0.80 +/- 0.08, 0.75 +/- 0.08 in Strategy (b).Conclusion The PET radiomics demonstrated excellent performance in characterizing SPNs as benign or malignant