Use of the scale-up methods in injury prevention research: An empirical assessment to the case of choking in children

The scale-up method estimates the size of hard to count subpopulations. This method is based on the idea that the proportion of subjects in a subpopulation E known to each member of the general population T is the same as the proportion of members of E belonging to general population T.     

Mobilized by Direct Democracy: Short‐Term Versus Long‐Term Effects and the Geography of Turnout in Ballot Measure Elections*

Objectives. A number of recent studies find that direct democracy increases voter turnout. In this article, we ask: Who does direct democracy mobilize to vote and how are they mobilized? We distinguish between long‐term and short‐term effects on voter turnout, noting that much of the current literature has focused on participatory theory. Methods. Our research design harnesses the power of geographic information systems and examines turnout in special initiative‐only elections using registered voter lists. Our model draws on individual and Census tract data, incorporated using a hierarchical generalized linear model. Results. The findings demonstrate how partisan context mitigates the potential for direct democracy to mobilize from the middle, and clarifies the dominance of short‐term as opposed to long‐term effects in increasing voter participation in ballot initiative elections. Conclusion. Mobilization via direct legislation occurs mostly because voters are actively mobilized by partisan campaigns, not because of an increase in participatory fervor.     

Large Risks,Limited Liability,and Dynamic Moral Hazard

We study a continuous‐time principal–agent model in which a risk‐neutral agent with limited liability must exert unobservable effort to reduce the likelihood of large but relatively infrequent losses. Firm size can be decreased at no cost or increased subject to adjustment costs. In the optimal contract, investment takes place only if a long enough period of time elapses with no losses occurring. Then, if good performance continues, the agent is paid. As soon as a loss occurs, payments to the agent are suspended, and so is investment if further losses occur. Accumulated bad performance leads to downsizing. We derive explicit formulae for the dynamics of firm size and its asymptotic growth rate, and we provide conditions under which firm size eventually goes to zero or grows without bounds.     

On Recalling ANT

This paper explores one after the other the four difficulties of actor-network theory, that is the words 'actor', 'network' and 'theory'—without forgetting the hyphen. It tries to refocus the originality of what is more a method to deploy the actor's own world building activities than an alternative social theory. Finally, it sketches some of its remaining potential.     

Risk Target: An Interactive Context Factor in Risk Perception

The effect of specification of the target on risk evaluation was examined. A whole set of hazards, covering most of the domains, were considered: common individual hazards, outdoor activities, medical care, public transportation, energy production, pollutants, sex, deviance, and addictions. Three human targets were introduced: personal health risk (including personal risk of death), health risk for people in the country, and health risk for people in the world. The basic design was a between-subjects design. The first hypothesis was that risk judgments made in the "world" condition should be higher than risk judgments made in the "country" condition, and risk judgments made in this condition should be higher than risk judgments made in the "personal" condition. This is what was observed. The second hypothesis was that the target effect should differ as a function of the kind of hazards considered. This also is what was observed. In two domains--pollutants, and deviance, sex, and addictions--the target effect was important. It corresponded to about one-tenth of the response scale. In the four remaining domains, the target effect was unimportant or absent.     

Motivation as a limit to pricing

A monetary reward offered by a principal tends to crowd out an agent's willingness to perform the task for its own sake (i.e. based on intrinsic motivation) if the agent's sense of recognition, fairness, or self-determination are thereby negatively affected. The crowding-out effect of pricing may also spill over into sectors where no pricing is applied (spillover effect) if the persons affected find it costly to dinstinguish their motivations according to sectors. Motivation crowding-out and spillover narrow the scope for successfully applying monetary rewards. These theoretical claims are supported by real-life observations for environmental policy and blood donations.     

Health and the Quality of Life

The aim of this investigation was to explain theimpact of peoples self-reported health on theirlevels of satisfaction with their health, and theimpact of these things plus satisfaction with otherspecific domains of their lives on the perceivedquality of their lives. The latter was operationalized as general happiness, satisfactionwith life as a whole and overall satisfaction with thequality of life. Seven hundred and twenty-three (723)usable questionnaires returned from a mailout randomsample of 2500 households of Prince George, BritishColumbia in November 1998 formed the working data-setfor our analyses. Among other things, mean respondentscores on the SF-36 health profile were found to belower than published norms from the UK, USA,Netherlands and Sweden, but higher than scores fromAberdeen, Scotland. Mean scores on the CES-Ddepression scale also indicated that our respondentstended to have more depressive symptoms thancomparison groups in Winnipeg and the USA. A review oftrends in mean scores on 17 quality of life items(e.g., satisfaction with family life, financialsecurity, recreation, etc.) from 1994, 1997 and 1998revealed that there were only 7 statisticallysignificant changes across the four year period andthey were all negative. Multivariate regressionanalysis showed that health status measured with avariety of indicators could explain 56% of thevariation in respondents reported satisfaction withtheir health. A combination of health status plusdomain satisfaction indicators could explain 53% ofthe variation in respondents reported happiness, 68%of reported life satisfaction and 63% of reportedsatisfaction with the overall quality of life. Sixtypercent of the explained variation in happiness scoreswas attributable to self-reported health scores, whileonly 18% of the explained variation in satisfactionwith life and with the overall quality of life scoreswas attributable self-reported health scores.     

Healthy Days,Health Satisfaction and Satisfaction with the Overall Quality of Life

In this note we report results of 6 surveysusing the United States Centers for DiseaseControl and Prevention indicators of healthstatus, taken from the Behavioral Risk FactorSurveillance System. Generally speaking, wefound that the CDC healthy days variables couldplay a useful role in survey research aimed atassessing the impact of measured health statuson people's satisfaction with their own healthand with the overall quality of their lives.More precisely, using stepwise regressions wefound: (1) The three healthy days variablesexplained from 16 to 27 percent of the variancein General Health scores. The limited activitydays variable remained as a significantpredictor in only one of the six regressionsand the not good physical health days variablewas most influential in every sample. (2) Thethree healthy days variables explained from 19to 32 percent of the variance in healthsatisfaction scores, and the not good physicalhealth days variable was again most influentialin every sample. (3) The three healthy daysvariables explained from 12 to 39 percent ofthe variance in quality-of-life satisfactionscores, with the not good mental healthvariable most influential in every sample. (4)The four CDC variables together explained from40 to 55 percent of the variance in healthsatisfaction scores, with the General Healthvariable always dominating the set ofpredictors by a fairly wide margin. (5) Thefour CDC variables together explained from 17to 28 percent of the variance inquality-of-life satisfaction scores, with theGeneral Health variable most influential inthree samples and the not good mental healthvariable most influential in the other three.(6) When the four CDC variables plus the healthsatisfaction variable were used as potentialpredictors, we were able to explain from 29 to40 percent of the variance in quality-of-lifesatisfaction scores. In every sample, theGeneral Health and limited activity daysvariables had no significant impact. (7) Usingstructural equation modeling, we found GeneralHealth does not have a direct effect onsatisfaction with the overall quality of lifebut rather only an indirect effect throughhealth satisfaction. The General Health, notgood physical health, and not good mentalhealth days variables account for 51% of thevariation in health satisfaction, and healthsatisfaction, not good physical health and notgood mental health days variables account for30% of the variation in satisfaction with theoverall quality of life.