ObjectiveThere is a growing body of research that investigates how the residential neighbourhood context relates to individual diet. However, previous studies ignore participants’ time spent in the residential environment and this may be a problem because time-use studies show that adults’ time-use pattern can significantly vary. To better understand the role of exposure duration, we designed a study to examine ‘time spent at home’ as a moderator to the residential food environment-diet association.DesignCross-sectional observational study.SettingsCity of Toronto, Ontario, Canada.Participants2411 adults aged 25–65.Primary outcome measureFrequency of vegetable and fruit intake (VFI) per day.ResultsTo examine how time spent at home may moderate the relationship between residential food environment and VFI, the full sample was split into three equal subgroups—short, medium and long duration spent at home. We detected significant associations between density of food stores in the residential food environment and VFI for subgroups that spend medium and long durations at home (ie, spending a mean of 8.0 and 12.3 h at home, respectively—not including sleep time), but no associations exist for people who spend the lowest amount of time at home (mean=4.7 h). Also, no associations were detected in analyses using the full sample.ConclusionsOur study is the first to demonstrate that time spent at home may be an important variable to identify hidden population patterns regarding VFI. Time spent at home can impact the association between the residential food environment and individual VFI.

Background News media coverage of antimask protests, COVID-19 conspiracies, and pandemic politicization has overemphasized extreme views but has done little to represent views of the general public. Investigating the public’s response to various pandemic restrictions can provide a more balanced assessment of current views, allowing policy makers to craft better public health messages in anticipation of poor reactions to controversial restrictions. Objective Using data from social media, this infoveillance study aims to understand the changes in public opinion associated with the implementation of COVID-19 restrictions (eg, business and school closures, regional lockdown differences, and additional public health restrictions, such as social distancing and masking). Methods COVID-19–related tweets in Ontario (n=1,150,362) were collected based on keywords between March 12 and October 31, 2020. Sentiment scores were calculated using the VADER (Valence Aware Dictionary and Sentiment Reasoner) algorithm for each tweet to represent its negative to positive emotion. Public health restrictions were identified using government and news media websites. Dynamic regression models with autoregressive integrated moving average errors were used to examine the association between public health restrictions and changes in public opinion over time (ie, collective attention, aggregate positive sentiment, and level of disagreement), controlling for the effects of confounders (ie, daily COVID-19 case counts, holidays, and COVID-19–related official updates). Results In addition to expected direct effects (eg, business closures led to decreased positive sentiment and increased disagreements), the impact of restrictions on public opinion was contextually driven. For example, the negative sentiment associated with business closures was reduced with higher COVID-19 case counts. While school closures and other restrictions (eg, masking, social distancing, and travel restrictions) generated increased collective attention, they did not have an effect on aggregate sentiment or the level of disagreement (ie, sentiment polarization). Partial (ie, region-targeted) lockdowns were associated with better public response (ie, higher number of tweets with net positive sentiment and lower levels of disagreement) compared to province-wide lockdowns. Conclusions Our study demonstrates the feasibility of a rapid and flexible method of evaluating the public response to pandemic restrictions using near real-time social media data. This information can help public health practitioners and policy makers anticipate public response to future pandemic restrictions and ensure adequate resources are dedicated to addressing increases in negative sentiment and levels of disagreement in the face of scientifically informed, but controversial, restrictions.

This study builds upon earlier studies of the degree of interchangeability between volunteers and paid staff in nonprofit organizations. While these earlier studies were from an organization perspective, this study is from the perspective of volunteers, and looks at individual and organizational characteristics in all types of organizations—nonprofits, for-profits, government agencies, and others. The findings indicate that 10.8% of volunteers reported replacing a paid staff member, 3.1% permanently. Volunteers also reported being replaced by paid staff: 7.6% reported being replaced, 2.1% permanently. The study suggests that organizations utilize a co-production model and appear to interchange their paid staff and volunteers when needed in tasks requiring higher-level skills. RÉSUMÉ Cette étude se fonde sur des études antérieures qui portaient sur le niveau d’interchangeabilité entre Cette étude se fonde sur des études antérieures qui portaient sur le niveau d’interchangeabilité entre bénévoles et salariés dans des organismes à but non lucratif. Tandis que ces études antérieures adoptaient une perspective organisationnelle, cette étude-ci adopte celle des bénévoles et examine les caractéristiques individuelles et organisationnelles de toutes sortes d’organisations—à but non lucratif, à but lucratif, gouvernementaux et coopératifs. Elle se fonde sur deux sous-échantillons provenant d’une enquête aléatoire par téléphone avec 768 individus provenant de partout au Canada. Les résultats indiquent que 10,8% des bénévoles disent avoir remplacé un salarié, 3,1% en permanence. Les bénévoles disent d’autre part que des salariés les ont remplacés : 7,6% ont ainsi été remplacés par des salariés, 2,1% en permanence. L’étude semble montrer que les organisations utilisent un modèle de co-production et paraissent échanger leurs salariés et bénévoles au besoin pour des tâches requérant des habiletés de haut niveau.

There is a growing public discourse that volunteering increases the likelihood of finding a better job because it improves social and human capital. While previous studies have largely treated volunteers' motivations as individualistically determined, contextual determinants of volunteers' motivations are relatively neglected. The purpose of this study is to understand the individual and contextual characteristics in which individuals are more likely to volunteer as a means of improving their employability. Using a random sample of 768 volunteers across Canada, we estimate the independent effects of a) municipal‐level material insecurity, b) urbanicity, and c) individual characteristics on the odds of “volunteering to improve employability.” Our findings show that living in municipalities with high economic insecurity and in urban settings independently increases the odds of volunteering to improve employability. Our study points to evidence of model misspecification, by omission of unobserved geographical covariates, in previous studies of volunteers' motivations.

BACKGROUND News media coverage of anti-mask protests, COVID-19 conspiracies, and pandemic politicization has overemphasized extreme views, but does little to represent views of the general public. Investigating the public’s response to various pandemic restrictions can provide a more balanced assessment of current views, allowing policymakers to craft better public health messages in anticipation of poor reactions to controversial restrictions. OBJECTIVE Using data from social media, this study aims to understand the changes in public opinion associated with the implementation of COVID-19 restrictions (e.g. business and school closure, regional lockdown differences, additional public health restrictions such as social distancing and masking). METHODS COVID-related tweets in Ontario (n=1,150,362) were collected based on keywords between March 12 to Oct 31 2020. Sentiment scores were calculated using the VADER algorithm for each tweet to represent its negative to positive emotion. Public health restrictions were identified using government and news media websites, and dynamic regression models with ARIMA errors were used to examine the association between public health restrictions and changes in public opinion over time (i.e. collective attention, aggregate positive sentiment, and level of disagreement) controlling for the effects of confounders (i.e. daily COVID-19 case counts, holidays, COVID-related official updates). RESULTS In addition to expected direct effects (e.g. business closure led to decreased positive sentiment and increased disagreements), the impact of restriction on public opinion is contextually driven. For example, the negative sentiment associated with business closures was reduced with higher COVID-19 case counts. While school closure and other restrictions (e.g. masking, social distancing, and travel restrictions) generated increased collective attention, they did not have an effect on aggregate sentiment or the level of disagreement (i.e. sentiment polarization). Partial (region-targeted) lockdowns were associated with better public response (i.e. higher number of tweets with net positive sentiment and lower levels of disagreement) compared to province-wide lockdowns. CONCLUSIONS Our study demonstrates the feasibility of a rapid and flexible method of evaluating the public response to pandemic restrictions using near real-time social media data. This information can help public health practitioners and policymakers anticipate public response to future pandemic restrictions, and ensure adequate resources are dedicated to addressing increases in negative sentiment and levels of disagreement in the face of scientifically informed, but controversial, restrictions.