研究数据管理发展基金（2023）

The project will benefit from a clear research data management plan. We aim to enhance the existing transcripts and improve the accuracy of the tagging of parts of speech of the child and adult utterances. Improvement of accuracy in tagging will greatly enhance the overall quality of the corpus.

The data will allow us to determine the developmental milestones for the children under investigation at different developmental stages and address important theoretical and empirical research questions and assess a number of factors that contribute to bilingual and trilingual development including the role of parental input, language dominance, degrees of balance in the target languages and crosslinguistic influence.

Specifically, I will use China and US export and import data to investigate how does firms’ financial reporting quality affect their export and import value and the number of trading partners. First, I will use survey data from executives to measure accounting quality and conduct country-sector-level analyses. Second, I will use firm-level international trade data to conduct more detailed analyses.

International trade is crucial for the global economy. The evidence provided in this project extends the understanding of the real economic effects of high quality financial disclosure. Moreover, there are important policy implications for developing countries that heavily rely on international trade for economic growth and at the same time have low financial reporting quality.

Through this innovative methodology, we aim to establish the first crime map in China that provides an accurate footprint for each individual crime instance. This proves invaluable for scholars, as it provides deeper insights into the spatial distribution of crimes, instead of just looking at the number of incidents. By analyzing the geographical patterns and clusters of criminal activities, we can uncover concealed trends and correlations that illuminate the dynamics of criminal behavior.

Through the creation of such crime map, we aim to equip policymakers, researchers, and communities with the knowledge necessary to develop effective crime prevention strategies and enhance urban safety in China.

A systematic and self-explanatory database will be established and the data will be deposited at the CUHK Research Data Repository (https://researchdata.cuhk.edu.hk). The database will be accessible to approved researchers and students undertaking research into a wide range of age-related topics and will contribute to improve our understanding of healthy ageing. We are open to various collaborations. Further information on this cohort and the database can be found in our website (http://www.jococ.org/zh-hk/mros-msos.php).

Research Objectives: This study aims to investigate what factors may affect specialist outpatient participation in medical decision-making in Hong Kong.

Methods: This study includes two phases. In Phase I, in-depth reviews (n = 15) will be conducted to explore patients’ experiences and their perceived barriers and facilitators of SDM in specialist outpatient settings. In Phase II, a cross-sectional survey (n = 600) will be conducted among specialist outpatient attendees. Informed by the insights from Phase I and the literature, the survey will gather quantitative data on patient demographics, preferred and actual involvement in medical decision-making, and factors influencing patient involvement in SDM. Additionally, the questionnaire will incorporate a subset of open-ended questions to investigate factors affecting patients’ experiences related to SDM.

Conclusion: This will be the first study combining qualitative and quantitative methods to explore factors influencing patient involvement in decision-making in Hong Kong. The outcomes of this research can inform healthcare practices, enhance patient-centered care, and contribute to the implementation of SDM in specialist outpatient settings.

Here, we share three processed and validated magnetic resonance imaging (MRI) datasets acquired from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN), the Harvard Aging Brain Study (HABS) and the Hong Kong SuperAgers study (ClinicalTrials.gov ID: NCT05728801), including high-resolution T1-weighted structural MRI and resting-state functional MRI (rs-fMRI) at 3 Tesla. These three datasets contain structural and resting-state functional MRI (rs-fMRI) neuroimaging data that has been acquired from 643 English healthy participants, 220 American participants and 488 Chinese old adults. Alongside, we share large-scale gradients estimated from each modality and constructed radiomic models. Our processed datasets will facilitate future research examining the coupling between brain macrostructure, mesostructure, connectivity, and cognitive function.

In this proposed 6-month project, we aim to set up the common practice guidelines for storing these sequencing data into the CUHK Research Data Repository. We will first invite a group of students and researchers to input different kinds of data to the system, and via discussing and interviewing the participants, we will formulate a protocol based on the feedback. One workshop will then be carried out in the School of Life Sciences to train the students and researchers, and necessary modifications to the protocol will be made if deemed appropriate. Another workshop will be made to everyone in the University, and the established protocol will be made publicly available at the CUHK Research Data Repository website.

The project aims to contribute to the understanding of how different learning strategies impact the acquisition of sign language, which could have implications for educational practices, particularly in the context of teaching the hearing-impaired. By making the database accessible to researchers and educators, the project supports the principles of open science and collaborative research. The findings from this study have the potential to inform educational strategies and contribute to the broader field of cognitive neuroscience and language acquisition.

To test our hypothesized relationships, we plan to conduct a cross-lagged panel study that observes 600 older employees (i.e., age 50+) living in Hong Kong over the time frame of one year and two experimental studies. The findings will highlight the relevance of older employees’ digital self-efficacy for their work continuance motivation and reveal factors that help to build and maintain digital self-efficacy in older age. Moreover, the results will provide new insights into the role of the organizational context (i.e., digitization of an organization and ageism in the workplace) and how it shapes whether digital self-efficacy translates into motivation to continue working.