Sarah Denford1,2,3, Kate S Morton4, Helen Lambert1,3, Juan Zhang1, Louise E Smith5,6, G James Rubin5,6, Shenghan Cai1, Tingting Zhang1, Charlotte Robin3,7,8,9, Gemma Lasseter1,3, Mathew Hickman1,3, Isabel Oliver10, Lucy Yardley1,2,3,4. 1. Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 1UD, UK. 2. School of Psychological Science, University of Bristol, Bristol BS8 1TU, UK. 3. NIHR Health Protection Research Unit (HPRU) in Behavioural Science and Evaluation, University of Bristol in collaboration with Public Health, UK. 4. Academic Unit of Psychology, University of Southampton, Southampton SO17 1BJ, UK. 5. NIHR Health Protection Research Unit in Emergency Preparedness and Response, King's College London, London SE5 9RJ, UK. 6. Department of Psychological Medicine, King's College London, London WC2R 2LS, UK. 7. Public Health England, National Infection Service, Liverpool, UK. 8. NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, University of Liverpool, Liverpool L69 7BE, UK. 9. NIHR Health Protection Research Unit in Gastrointestinal Infections, University of Liverpool, Liverpool L69 3BX, UK. 10. Public Health England, National Infection Service, Bristol BS1 6EH, UK.
Abstract
BACKGROUND: Evidence highlights the disproportionate impact of measures that have been introduced to reduce the spread of coronavirus on individuals from Black, Asian and minority ethnic (BAME) communities, and among those on a low income. An understanding of barriers to adherence in these populations is needed. In this qualitative study, we examined the patterns of adherence to mitigation measures and reasons underpinning these behaviors. METHODS: Semi-structured interviews were conducted with 20 participants from BAME and low-income White backgrounds. The topic guide was designed to explore how individuals are adhering to social distancing and self-isolation during the pandemic and to explore the reasons underpinning this behavior. RESULTS: We identified three categories of adherence to lockdown measures: (i) caution-motivated super-adherence (ii) risk-adapted partial-adherence and (iii) necessity-driven partial-adherence. Decisions about adherence considered potential for exposure to the virus, ability to reduce risk through use of protective measures and perceived importance of/need for the behavior. CONCLUSIONS: This research highlights a need for a more nuanced understanding of adherence to lockdown measures. Provision of practical and financial support could reduce the number of people who have to engage in necessity-driven partial-adherence. More evidence is required on population level risks of people adopting risk-adapted partial-adherence.
BACKGROUND: Evidence highlights the disproportionate impact of measures that have been introduced to reduce the spread of coronavirus on individuals from Black, Asian and minority ethnic (BAME) communities, and among those on a low income. An understanding of barriers to adherence in these populations is needed. In this qualitative study, we examined the patterns of adherence to mitigation measures and reasons underpinning these behaviors. METHODS: Semi-structured interviews were conducted with 20 participants from BAME and low-income White backgrounds. The topic guide was designed to explore how individuals are adhering to social distancing and self-isolation during the pandemic and to explore the reasons underpinning this behavior. RESULTS: We identified three categories of adherence to lockdown measures: (i) caution-motivated super-adherence (ii) risk-adapted partial-adherence and (iii) necessity-driven partial-adherence. Decisions about adherence considered potential for exposure to the virus, ability to reduce risk through use of protective measures and perceived importance of/need for the behavior. CONCLUSIONS: This research highlights a need for a more nuanced understanding of adherence to lockdown measures. Provision of practical and financial support could reduce the number of people who have to engage in necessity-driven partial-adherence. More evidence is required on population level risks of people adopting risk-adapted partial-adherence.
Authors: Lisa Woodland; Ava Hodson; Rebecca K Webster; Richard Amlôt; Louise E Smith; James Rubin Journal: Int J Environ Res Public Health Date: 2022-06-14 Impact factor: 4.614
Authors: Sarah Denford; Alex F Martin; Nicola Love; Derren Ready; Isabel Oliver; Richard Amlôt; Lucy Yardley; G James Rubin Journal: Front Public Health Date: 2021-08-03
Authors: S Cai; T Zhang; C Robin; C Sawyer; W Rice; L E Smith; R Amlôt; G J Rubin; L Yardley; M Hickman; I Oliver; H Lambert Journal: Public Health Date: 2021-11-27 Impact factor: 2.427
Authors: Rachael M Hewitt; Judith Carrier; Stephen Jennings; Lilith Nagorski; Rachael Pattinson; Sally Anstey; Rhian Daniel; Chris Bundy Journal: Int J Behav Med Date: 2022-02-07
Authors: Grigoris T Gerotziafas; Mariella Catalano; Yiannis Theodorou; Patrick Van Dreden; Vincent Marechal; Alex C Spyropoulos; Charles Carter; Nusrat Jabeen; Job Harenberg; Ismail Elalamy; Anna Falanga; Jawed Fareed; Petros Agathaggelou; Darko Antic; Pier Luigi Antignani; Manuel Monreal Bosch; Benjamin Brenner; Vladimir Chekhonin; Mary-Paula Colgan; Meletios-Athanasios Dimopoulos; Jim Douketis; Essam Abo Elnazar; Katalin Farkas; Bahare Fazeli; Gerry Fowkes; Yongquan Gu; Joseph Gligorov; Mark A Ligocki; Tishya Indran; Meganathan Kannan; Bulent Kantarcioglu; Abdoul Aziz Kasse; Kostantinos Konstantinidis; Fabio Leivano; Joseph Lewis; Alexander Makatsariya; P Massamba Mbaye; Isabelle Mahé; Irina Panovska-Stavridis; Dan-Mircea Olinic; Chryssa Papageorgiou; Zsolt Pecsvarady; Sergio Pillon; Eduardo Ramacciotti; Hikmat Abdel-Razeq; Michele Sabbah; Mouna Sassi; Gerit Schernthaner; Fakiha Siddiqui; Jin Shiomura; Anny Slama-Schwok; Jean Claude Wautrecht; Alfonso Tafur; Ali Taher; Peter Klein-Wegel; Zenguo Zhai; Tazi Mezalek Zoubida Journal: Thromb Haemost Date: 2021-07-20 Impact factor: 6.681