METHODS: Data were collected from 10 researchers from 10 different countries (Australia, China, the UK, Brazil, Pakistan, Bangladesh, Iran, Nigeria, Trinidad and Tobago, and Turkiye) using semi-structured interviews. NVivo was employed for data analysis.
RESULTS: Based on the responses, five themes about the influence of ChatGPT on academic and research writing were generated, i.e., opportunity, human assistance, thought-provoking, time-saving, and negative attitude. Although the researchers were mostly positive about it, some feared it would degrade their writing skills and lead to plagiarism. Many of them believed that ChatGPT would redefine the concepts, parameters, and practices of creativity and plagiarism.
DISCUSSION: Creativity may no longer be restricted to the ability to write, but also to use ChatGPT or other large language models (LLMs) to write creatively. Some suggested that machine-generated text might be accepted as the new norm; however, using it without proper acknowledgment would be considered plagiarism. The researchers recommended allowing ChatGPT for academic and research writing; however, they strongly advised it to be regulated with limited use and proper acknowledgment.
METHODS: Injury mortality was estimated using the GBD mortality database, corrections for garbage coding and CODEm-the cause of death ensemble modelling tool. Morbidity estimation was based on surveys and inpatient and outpatient data sets for 30 cause-of-injury with 47 nature-of-injury categories each. The Socio-demographic Index (SDI) is a composite indicator that includes lagged income per capita, average educational attainment over age 15 years and total fertility rate.
RESULTS: For many causes of injury, age-standardised DALY rates declined with increasing SDI, although road injury, interpersonal violence and self-harm did not follow this pattern. Particularly for self-harm opposing patterns were observed in regions with similar SDI levels. For road injuries, this effect was less pronounced.
CONCLUSIONS: The overall global pattern is that of declining injury burden with increasing SDI. However, not all injuries follow this pattern, which suggests multiple underlying mechanisms influencing injury DALYs. There is a need for a detailed understanding of these patterns to help to inform national and global efforts to address injury-related health outcomes across the development spectrum.