Objective: To automatically recognize self-acknowledged limitations in clinical research publications to support efforts in improving research transparency.Methods: To develop our recognition methods, we used a set of 8431 sentences from 1197 PubMed Central articles. A subset of these sentences was manually annotated for training/testing, and inter-annotator agreement was calculated. We cast the recognition problem as a binary classification task, in which we determine whether a given sentence from a publication discusses self-acknowledged limitations or not. We experimented with three methods: a rule-based approach based on document structure, supervised machine learning, and a semi-supervised method that uses self-training to expand the training set in order to improve classification performance. The machine learning algorithms used were logistic regression (LR) and support vector machines (SVM).Results: Annotators had good agreement in labeling limitation sentences (Krippendorff's α = 0.781). Of the three methods used, the rule-based method yielded the best performance with 91.5% accuracy (95% CI [90.1-92.9]), while self-training with SVM led to a small improvement over fully supervised learning (89.9%, 95% CI [88.4-91.4] vs 89.6%, 95% CI [88.1-91.1]).Conclusions: The approach presented can be incorporated into the workflows of stakeholders focusing on research transparency to improve reporting of limitations in clinical studies.
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ObjectivesOsteoarthritis (OA) of the foot-ankle complex is understudied. Understanding determinants of pain and activity limitations is necessary to improve management of foot OA. The aim of the present study was to investigate demographic, foot-specific and comorbidity-related factors associated with pain and activity limitations in patients with foot OA.MethodsThis exploratory cross-sectional study included 75 patients with OA of the foot and/or ankle joints. Demographic and clinical data were collected with questionnaires and by clinical examination. The outcome variables of pain and activity limitations were measured using the Foot Function Index (FFI). Potential determinants were categorized into demographic factors (e.g., age, sex), foot-specific factors (e.g., plantar pressure and gait parameters), and comorbidity-related factors (e.g., type and amount of comorbid diseases). Multivariable regression analyses with backward selection (p-out≥0.05) were performed in two steps, leading to a final model.ResultsOf all potential determinants, nine factors were selected in the first step. Five of these factors were retained in the second step (final model): female sex, pain located in the hindfoot, higher body mass index (BMI), neurological comorbidity, and Hospital Anxiety and Depression Scale (HADS) score were positively associated with the FFI score. The explained variance (R2) for the final model was 0.580 (adjusted R2 = 0.549).ConclusionFemale sex, pain located in the hindfoot, higher BMI, neurological comorbidity and greater psychological distress were independently associated with a higher level of foot-related pain and activity limitations. By addressing these factors in the management of foot OA, pain and activity limitations may be reduced.
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Purpose: To assess the factor structure, related constructs and internal consistency of the Child Activity Limitation Interview 21-Child version for use in Dutch-language countries.Methods: Cross-sectional validation study: After forward and back translation of the Dutch version of the Child Activity Limitation Interview 21-Child adolescents (11–21 years old) with chronic musculoskeletal pain completed an assessment. The assessment contained the Dutch Child Activity Limitation Interview, and questionnaires about demographics, pain intensity, functional disability, anxiety and depression. Internal consistency and construct validity were evaluated through exploratory factor analysis (principal axis factoring with oblique rotation) and hypotheses testing using pain intensity, activity limitations, anx- iety and depression as comparative constructs.Results: Seventy-four adolescents completed the assessment. Exploratory factor analysis resulted in a two- factor structure, explaining 50% of the variance. Internal consistency was good (Cronbach’s a 1⁄4 0.91 total scale, a 1⁄4 0.90 Factor 1, a 1⁄4 0.80 Factor 2). All nine hypotheses were confirmed.Conclusion: The Dutch version can be used to assess pain-related disability in Dutch-speaking adolescents comparable to the study sample. Scores on both subscales provide insight into the severity of the pain- related disability in both daily routine and more physically vigorous activities.
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Objective:Acknowledging study limitations in a scientific publication is a crucial element in scientific transparency and progress. However, limitation reporting is often inadequate. Natural language processing (NLP) methods could support automated reporting checks, improving research transparency. In this study, our objective was to develop a dataset and NLP methods to detect and categorize self-acknowledged limitations (e.g., sample size, blinding) reported in randomized controlled trial (RCT) publications.Methods:We created a data model of limitation types in RCT studies and annotated a corpus of 200 full-text RCT publications using this data model. We fine-tuned BERT-based sentence classification models to recognize the limitation sentences and their types. To address the small size of the annotated corpus, we experimented with data augmentation approaches, including Easy Data Augmentation (EDA) and Prompt-Based Data Augmentation (PromDA). We applied the best-performing model to a set of about 12K RCT publications to characterize self-acknowledged limitations at larger scale.Results:Our data model consists of 15 categories and 24 sub-categories (e.g., Population and its sub-category DiagnosticCriteria). We annotated 1090 instances of limitation types in 952 sentences (4.8 limitation sentences and 5.5 limitation types per article). A fine-tuned PubMedBERT model for limitation sentence classification improved upon our earlier model by about 1.5 absolute percentage points in F1 score (0.821 vs. 0.8) with statistical significance (). Our best-performing limitation type classification model, PubMedBERT fine-tuning with PromDA (Output View), achieved an F1 score of 0.7, improving upon the vanilla PubMedBERT model by 2.7 percentage points, with statistical significance ().Conclusion:The model could support automated screening tools which can be used by journals to draw the authors’ attention to reporting issues. Automatic extraction of limitations from RCT publications could benefit peer review and evidence synthesis, and support advanced methods to search and aggregate the evidence from the clinical trial literature.
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Thank you for sharing this story! However, please do so in a way that respects the copyright of this text. If you want to share or reproduce this full text, please ask permission from Innovation Origins (partners@innovationorigins.com) or become a partner of ours! You are of course free to quote this story with source citation. Would you like to share this article in another way? Then use this link to the article: https://innovationorigins.com/en/silicon-sampling-ai-powered-personas-offer-new-insights-for-market-research-but-have-limitations/ n the rapidly evolving field of marketing and communication, staying ahead means embracing technological innovations. The latest breakthrough, silicon sampling, leverages AI to revolutionize market research by creating synthetic personas that mimic human responses. This method, which utilizes large language models (LLMs) like GPT-4o, offers a cost-efficient and less time-consuming alternative to traditional market research. Roberta Vaznyte and Marieke van Vliet (Fontys University of Applied Science) have explored the promise and challenges of silicon sampling, highlighting key findings from recent experiments and the implications for the future of market research.
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This case report describes the process and outcome of an intervention where illness perceptions (IPs) were targeted in order to reduce limitations in daily activities. The patient was a 45-year-old woman diagnosed with posttraumatic secondary osteoarthritis of the lateral patella-femoral cartilage of the right knee. At baseline, the patient reported maladaptive IPs on the Brief Illness Perception Questionnaire Dutch Language Version and limitations in walking stairs, cycling and walking. Fewer limitations in daily activities are hypothesized by changing maladaptive IPs into more favourable IPs. In this case report, discussing maladaptive IPs with the patient was the main intervention. A participatory decision making model was used as a design by which the maladaptive IP were discussed. Six out of eight maladaptive IPs changed favourably and there was a clinically relevant decrease in limitations of daily activities. The Global Perceived Effect was rated as much improved
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Objectives: Decline in the performance of instrumental activities of daily living (IADL) and mobility may be preceded by symptoms the patient experiences, such as fatigue. The aim of this study is to investigate whether self-reported non-task-specific fatigue is a long-term risk factor for IADL-limitations and/or mobility performance in older adults after 10 years. Methods: A prospective study from two previously conducted cross-sectional studies with 10-year follow-up was conducted among 285 males and 249 females aged 40–79 years at baseline. Fatigue was measured by asking “Did you feel tired within the past 4 weeks?” (males) and “Do you feel tired?” (females). Self-reported IADLs were assessed at baseline and follow-up. Mobility was assessed by the 6-minute walk test. Gender-specific associations between fatigue and IADL-limitations and mobility were estimated by multivariable logistic and linear regression models. Results: A total of 18.6% of males and 28.1% of females were fatigued. After adjustment, the odds ratio for fatigued versus non-fatigued males affected by IADL-limitations was 3.3 (P=0.023). In females, the association was weaker and not statistically significant, with odds ratio being 1.7 (P=0.154). Fatigued males walked 39.1 m shorter distance than those non-fatigued (P=0.048). For fatigued females, the distance was 17.5 m shorter compared to those non-fatigued (P=0.479). Conclusion: Our data suggest that self-reported fatigue may be a long-term risk factor for IADL-limitations and mobility performance in middle-aged and elderly males but possibly not in females.
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In this article, we investigate how small museums running on volunteers deal with the challenge of innovation given that the future is becoming more digital. From the literature, little is known about the strategies and practices for designing innovative visitor experiences in small museums and about the skills needed for doing so. In particular, we were interested in understanding how professionals working in small museums design experiences that mainly appeal to and engage a younger public and how digital innovation can play a role in both attracting and keeping such audiences engaged with the museum. Our most important conclusion is that the question of “how to innovate” is misplaced and that small museums rather need to capitalize on the strong tie with the community they serve. Only in this way can they lower the threshold to access and connect to a broader public that is younger and more diverse.
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As multimedia gradually becomes more and more an integrated part of video conferencing systems, the use of multimedia integrated desktop video conferencing technology (MIDVCT) will open up new educational possibilities for synchronous learning. However, the possibilities and limitations of this technology must be clearly understood so that it can be used to maximize possible pedagogical benefits and reduce possible pedagogical limitations. This paper analyses the process of integrating MIDVCT in a first-year English language course, and offers insights into theoretical underpinnings of multimedia learning from two perspectives: the generative theory of multimedia learning and the cognitive overload theory. The data discussed in this paper have been drawn from a study which took place in a cross institutional setting at Fontys University of Applied Sciences, The Netherlands. The data were collected and analyzed according to a qualitative approach.
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Background: Follow-up of stroke survivors is important to objectify activity limitations and/or participations restrictions. Responsive measurement tools are needed with a low burden for professional and patient. Aim: To examine the concurrent validity, floor and ceiling effects and responsiveness of both domains of the Late-Life Function and Disability Index Computerized Adaptive Test (LLFDI-CAT) in first-ever stroke survivors discharged to their home setting. Design: Longitudinal study. Setting: Community. Population: First ever stroke survivors. Methods: Participants were visited within three weeks after discharge and six months later. Stroke Impact Scale (SIS 3.0) and Five-Meter Walk Test (5MWT) outcomes were used to investigate concurrent validity of both domains, activity limitations, and participation restriction, of the LLFDI-CAT. Scores at three weeks and six months were used to examine floor and ceiling effects and change scores were used for responsiveness. Responsiveness was assessed using predefined hypotheses. Hypotheses regarding the correlations with change scores of related measures, unrelated measures, and differences between groups were formulated. Results: The study included 105 participants. Concurrent validity (R) of the LLFDI-CAT activity limitations domain compared with the physical function domain of the SIS 3.0 and with the 5MWT was 0.79 and -0.46 respectively. R of the LLFDI-CAT participation restriction domain compared with the participation domain of the SIS 3.0 and with the 5MWT was 0.79 and -0.41 respectively. A ceiling effect (15%) for the participation restriction domain was found at six months. Both domains, activity limitations and participation restrictions, of the LLFDI-CAT, scored well on responsiveness: 100% (12/12) and 91% (12/11) respectively of the predefined hypotheses were confirmed. Conclusions: The LLFDI-CAT seems to be a valid instrument and both domains are able to detect change over time. Therefore, the LLFDI-CAT is a promising tool to use both in practice and in research. Clinical rehabilitation impact: The LLFDI-CAT can be used in research and clinical practice.
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