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Intentional and unintentional non-adherence to social distancing measures during COVID-19: A mixed-methods analysis.

ABSTRACT: Social distancing measures implemented by governments worldwide during the COVID-19 pandemic have proven an effective intervention to control the transmission of SARS-CoV-2. There is a growing literature on predictors of adherence behaviours to social distancing measures, however, there are no comprehensive insights into the nature and types of non-adherence behaviours. To address this gap in the literature, we studied non-adherence in terms of counts of infringements and people's accounts on their behaviours in a sample of North London residents. We focused on the following social distancing rules: keeping 2 mts. distancing, meeting family and friends, and going out for non-essential reasons. A mixed-methods explanatory sequential design was used comprising an online survey (May 1-31, 2020) followed by semi-structured in-depth interviews held with a purposive sample of survey respondents (August 5 -September 21, 2020). A negative binomial regression model (quantitative) and Framework Analysis (qualitative) were undertaken.681 individuals completed the survey, and 30 individuals were interviewed. We integrated survey and interview findings following three levels of the Social Ecological model: individual, interpersonal and community levels. We identified non-adherence behaviours as unintentional (barriers beyond individual's control) and intentional (deliberate decision). Unintentional adherence was reported by interviewees as, lack of controllability in keeping 2 mts. distancing, environmental constraints, social responsibility towards the community and feeling low risk. Intentional non-adherence was statistically associated with and reported as lack of trust in Government, support from friends, and lack of knowledge about rules. In addition, interviewees reported individual risk assessment and decision making on the extent to following the rules, and perceived lack of adherence in the local area. Our findings indicate that unintentional and intentional non-adherence should be improved by Government partnerships with local communities to build trust in social distancing measures; tailored messaging to young adults emphasising the need of protecting others whilst clarifying the risk of transmission; and ensuring COVID-secured environments by working with environmental health officers.

SUBMITTER: Eraso Y

PROVIDER: S-EPMC8376044 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ObjectiveTo categorise patient-reported outcome measures (PROMs) into their propensity to detect intentional and/or unintentional non-adherence to medication, and synthesise their psychometric properties.DesignSystematic review and regression analysis.EligibilityMedication adherence levels studied at primary, secondary and tertiary care settings. Self-reported measures with scoring methods were included. Studies without proxy measures were excluded.Data sourcesUsing detailed searches with key concepts including questionnaires, reliability and validity, and restricted to English, MEDLINE, EMBASE, CINAHL, International Pharmaceutical Abstracts, and Cochrane Library were searched until 01 March 2022. Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 (PRISMA-2020) checklist was used.Data analysisRisk of bias was assessed via COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN-2018) guidelines. Narrative synthesis aided by graphical figures and statistical analyses.Outcome measuresProcess domains [behaviour (e.g., self-efficacy), barrier (e.g., impaired dexterity) or belief (e.g., perception)], and overall outcome domains of either intentional (I), unintentional (UI), or mixed non-adherence.ResultsPaper summarises evidence from 59 studies of PROMs, validated among patients aged 18-88 years in America, the United Kingdom, Europe, Middle East, and Australasia. PROMs detected outcome domains: intentional non-adherence, n=44 (I=491 criterion items), mixed intentionality, n=13 (I=79/UI=50), and unintentional, n=2 (UI=5). Process domains detected include belief (383 criterion items), barrier (192) and behaviour (165). Criterion validity assessment used proxy measures (biomarkers, e-monitors), and scoring was ordinal, dichotomised, or used Visual Analogue Scale. Heterogeneity was revealed across psychometric properties (consistency, construct, reliability, discrimination ability). Intentionality correlated positively with negative beliefs (r(57)=0.88) and barriers (r(57)=0.59). For every belief or barrier criterion-item, PROMs' aptitude to detect intentional non-adherence increased by β=0.79 and β=0.34 units, respectively (R2=0.94). Primary care versus specialised care predicted intentional non-adherence (OR 1.9; CI 1.01 to 2.66).ConclusionsTen PROMs had adequate psychometric properties. Of the ten, eight PROMs were able to detect total, and two PROMs were able to detect partial intentionality to medication default. Fortification of patients' knowledge and illness perception, as opposed to daily reminders alone, is most imperative at primary care levels.

Project description:BACKGROUND:Non-adherence to medications is common and leads to suboptimal outcomes. Non-adherence can be intentional (e.g., deciding to skip dosages) or unintentional (e.g., forgetting), yet few studies have distinguished these reasons. An improved understanding of the reasons for non-adherence could inform the development of effective interventions. METHODS AND RESULTS:We analyzed data from African Americans in the Jackson Heart Study who were prescribed medications for one or more chronic conditions. Participants were grouped by patient-reported adherence with non-adherence categorized as being intentional, unintentional or both. We used modified Poisson regression models to examine the factors associated with types of non-adherence. Of 2933 participants taking medication, 2138 (72.9%) reported non-adherence with 754 (35.3%) reporting only unintentional non-adherence, 263 (12.3%) only intentional non-adherence, and 1121 (52.4%) both. Factors independently associated with intentional non-adherence included female sex and depressive symptoms while factors associated with unintentional non-adherence included younger age and separated relationship status. Unintentional and intentional non-adherence was more common among participants taking anti-arrhythmic and anti-asthmatic medications, respectively. Higher levels of global perceived stress was associated with both types of non-adherence. The adjusted models for intentional and unintentional non-adherence had c-statistics of 0.65 and 0.66, respectively, indicating modest discrimination. CONCLUSION:Specific patient factors and individual medication classes were associated with distinct patterns of intentional and unintentional non-adherence, yet the overall modest discrimination of the models suggests contributions from other unmeasured factors. These findings provide a construct for understanding reasons for non-adherence and provide rationale to assess whether personalized interventions can improve adherence.

Project description:IntroductionGovernments and public health authorities across many jurisdictions implemented social (physical) distancing measures to contain the spread of the 2019 novel coronavirus disease (COVID-19). Adherence to these measures is variable and likely influenced by various factors. This study aimed to 1) identify the individual sociodemographic, COVID-19 and social distancing related, and psychological determinants of social distancing adherence, and 2) explore regional differences in social distancing adherence in the United States (U.S.) and English-speaking Canada based on each region's discrepant response to social distancing restrictions.MethodsA web-based repeated cross-sectional survey was conducted in 4,942 English-speaking participants from the four most populous U.S. states, specifically New York, California, Texas, and Florida, and Canada (www.covid19-database.com). The study was conducted at two timepoints, from May 1 to 5, 2020 (n = 1,019, Canadian participants only) and from July 6 to 10, 2020 (n = 3,923). Separate univariate models were computed for individual sociodemographic, COVID-19 and social distancing related, and psychological determinants of social distancing adherence. To determine the total variance explained, a univariate analysis including all of the determinants was performed. Regional differences in social distancing were compared between the four U.S. states and Canada, and between the U.S. as a whole and Canada.ResultsAdherence to social distancing was higher in May (mean = 4.4/5.0±0.7) compared to July (mean = 4.3/5.0±0.7) [t (4940) = 6.96, p < 0.001], likely a reflection of relaxing restrictions. There were no regional differences in adherence. Sociodemographic, COVID-19 and social distancing related, and psychological determinants explained 10, 36, and 23% of the variance of social distancing adherence, respectively. Higher perceived seriousness of COVID-19 [β (SE) = 0.39 (0.01), p < 0.001, partial η2 = 0.22], lower risk propensity [β (SE) = -0.15 (0.01), p < 0.001, partial η2 = 0.06], germ aversion [β (SE) = 0.12 (0.01), p < 0.001, partial η2 = 0.03], age [β (SE) = 0.01 (0.00), p < 0.001, partial η2 = 0.02], and greater social support [β (SE) = 0.03 (0.00), p < 0.001, partial η2 = 0.02] had the largest effects on social distancing adherence.ConclusionPublic service initiatives to emphasize the serious consequences of infection and targeted interventions toward certain sociodemographic groups, such as younger adults and vulnerable individuals in greater need of social support, may help enhance the public's adherence to social distancing measures during subsequent waves of COVID-19 and future pandemics.

Project description:BackgroundOn March 23, 2020, the government of the United Kingdom told the British people to stay home, an unprecedented request designed to limit the spread of the COVID-19 virus and stop the National Health Service from being overwhelmed.MethodsThis study undertook a cross-sectional design to survey a convenience sample of 681 residents of North London on their social distancing (SD) behaviours, demographics, housing situation, politics, psychology and social support using an online questionnaire. Logistic regression was used to measure the associations between these explanatory factors and non-adherence to all SD rules and intentional non-adherence to SD rules.ResultsThe vast majority (92.8%) of participants did not adhere to all SD rules and nearly half (48.6%) engaged in intentional non-adherence of rules. The odds of not adhering to all SD rules increased if a participant was not identified as highly vulnerable to COVID-19 [OR = 4.5], had lower control over others' distancing [OR = .724], had lower control over responsibilities for which coming into contact with others was unavoidable [OR = .642], and if SD behaviours were reported after lockdown was first relaxed [OR = .261]. The odds of intentionally not adhering to SD rules increased if a participant had a lower intention to socially distance [OR = .468], had lower control over others' distancing [OR = .829], had a doctoral degree compared to a master's degree [OR = .332], a professional qualification [OR = .307], a bachelor's degree [OR = .361] or work-related qualification [OR = .174], voted for the UK Government compared to not voting for the Government [OR = .461], perceived higher normative pressure from neighbours [OR = 1.121] and had greater support from friends [OR = 1.465].ConclusionsNon-adherence to all SD rules had a stronger association with vulnerability to COVID-19 and control over SD, whereas intentional non-adherence had a stronger association with intention and anti-social psychological factors. It is recommended that people living in high-risk environments, such as those living in houses of multiple occupancy, should be specially supported when asked to stay at home, and public health messaging should emphasise shared responsibility and public consciousness.

Project description:Social distancing measures are effective in reducing overall community transmission but much remains unknown about how they have impacted finer-scale dynamics. In particular, much is unknown about how changes of contact patterns and other behaviors including adherence to social distancing, induced by these measures, may have impacted finer-scale transmission dynamics among different age groups. In this paper, we build a stochastic age-specific transmission model to systematically characterize the degree and variation of age-specific transmission dynamics, before and after lifting the lockdown in Georgia, USA. We perform Bayesian (missing-)data-augmentation model inference, leveraging reported age-specific case, seroprevalence and mortality data. We estimate that overall population-level transmissibility was reduced to 41.2% with 95% CI [39%, 43.8%] of the pre-lockdown level in about a week of the announcement of the shelter-in-place order. Although it subsequently increased after the lockdown was lifted, it only bounced back to 62% [58%, 67.2%] of the pre-lockdown level after about a month. We also find that during the lockdown susceptibility to infection increases with age. Specifically, relative to the oldest age group (> 65+), susceptibility for the youngest age group (0-17 years) is 0.13 [0.09, 0.18], and it increases to 0.53 [0.49, 0.59] for 18-44 and 0.75 [0.68, 0.82] for 45-64. More importantly, our results reveal clear changes of age-specific susceptibility (defined as average risk of getting infected during an infectious contact incorporating age-dependent behavioral factors) after the lockdown was lifted, with a trend largely consistent with reported age-specific adherence levels to social distancing and preventive measures. Specifically, the older groups (> 45) (with the highest levels of adherence) appear to have the most significant reductions of susceptibility (e.g., post-lockdown susceptibility reduced to 31.6% [29.3%, 34%] of the estimate before lifting the lockdown for the 6+ group). Finally, we find heterogeneity in case reporting among different age groups, with the lowest rate occurring among the 0-17 group (9.7% [6.4%, 19%]). Our results provide a more fundamental understanding of the impacts of stringent lockdown measures, and finer evidence that other social distancing and preventive measures may be effective in reducing SARS-CoV-2 transmission. These results may be exploited to guide more effective implementations of these measures in many current settings (with low vaccination rate globally and emerging variants) and in future potential outbreaks of novel pathogens.

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Intentional and unintentional non-adherence to social distancing measures during COVID-19: A mixed-methods analysis.

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