Application of theoretical domains framework to explore the enablers and barriers to physical activity among university staff and students: a qualitative study

Background Physical inactivity is one of the major risk factors for developing several chronic illnesses. However, despite strong evidence indicating the health benefits of physical activity, many university staff and students tend to be physically inactive. University settings provide a stable environment where behaviour change interventions can be implemented across multiple levels of change. The aim of this study is to examine the perceived barriers and enablers to physical activity among staff and students in a university setting, using the Theoretical Domains Framework (TDF), a precursor of COM-B behaviour model. Methods This was a qualitative study carried out at a Midlands University in the United Kingdom. Eight group interviews were conducted with the sample (n = 40) consisting of 6 male and 15 female university staff (mean age = 40.5 ± 10.6 years) with different job roles (e.g., academic, administrative, cleaning and catering staff), and 12 male and 7 female students (mean age = 28.6 ± 4.7 years) at different stages of study (e.g., undergraduate, postgraduate, and international students). Interviews were audio recorded, transcribed verbatim and imported into NVivo12 software, responses were mapped using the TDF where theory-driven deductive content analysis was used for data analysis. Results Six prominent domains were identified from the group interviews as enablers and/or barriers to physical activity among university staff and students: Environmental context and resources; intentions; social influences; knowledge; beliefs about capabilities; and social/professional role and identity. The themes emerging from the group interviews fit into all 14 domains of the TDF; however, 71% of the themes fit into the six most prominent domains. Conclusions These findings suggest that several enablers and barriers influence university staff and students’ capability, opportunity, and motivation to engage in physical activity. This study, therefore, provides a theoretical foundation to inform the development of bespoke interventions to increase physical activity among inactive university staff and students

Addressing the Public Health Misinformation Challenge with Real-Time Data Fusion

Misinformation is at an all-time peak across the globe, it wouldn‘t be considered an exaggeration if we describe ‘misinformation’ as a billion-dollar industry where bad actors profit off the chaos generated by misinformation. The public health industry has been at the receiving end of this challenge for way too long, leading to a high mortality rate in the public health industry. The number of resources invested into misinformation has made this phenomenon complex through its adoption of new and sophisticated deception techniques. The impact of misinformation on democracy and human rights can be damning and have severe consequences, also counter-misinformation will prove to be counter-productive, further denting the integrity of democracy and human rights; the COVID-19 pandemic illustrates what the war of misinformation looks like, an unending wave of misinformation and impeding crack on democracy as we know it. On numerous levels, effective responses to tackle disinformation are required, some of which will include laws and regulations, civil actions, and corporate measures among other practices. The early months of 2020 undeniably altered humanity\u27s lifestyle in several ways, some of which humans could not have imagined. Of all the changes brought upon humanity by the 2020 COVID- 19 pandemic, the fusion of aggregated data using technological solutions is paramount. The adoption of AI in several fields was fast-tracked by the occurrence which is the COVID-19 pandemic; AI was already in the works, but the pandemic accelerated its wide-scale adoption by compressing digital transformation that would have taken two years into a few months. Here we review the misinformation challenge encountered by the public health sector and identify major gaps in research, we also propose asolution that leverages the IT techniques in AI, deep learning, and semantic technologies. The place of IT techniques in addressing the public health misinformation challenge with realtime data fusion will be explored in this paper