What matters most to patients about primary healthcare: mixed-methods patient priority setting exercises within the PREFeR (PRioritiEs For Research) project.

OBJECTIVES: To identify patient-generated priority topics for future primary care research in British Columbia (BC), Canada within a diverse patient population. DESIGN: Mixed-methods priority setting exercises framed by the dialogue model, using the nominal group technique (rank-ordered scoring) and province-wide online surveys capturing importance ratings of the top 10 primary healthcare topics from patients and primary care providers. SETTING: BC, Canada. PARTICIPANTS: Topic identification was completed by 10 patient partners (7 female, 3 male) from the BC Primary Health Care Research Network Patient Advisory; online surveys were completed by 464 patients and 173 primary care providers. RESULTS: The 10 members recruited to the patient advisory provided over 80 experiences of what stood out for them in BC primary care, which were grouped thematically into 18 topics, 10 of which were retained in province-wide surveys. Top-rated survey topics for both patients (n=464) and providers (n=173) included being unable to find a regular family doctor/other primary healthcare provider, support for living with chronic conditions, mental health resources and information sharing, including electronic medical records. However, all 10 topics were rated important, on average, by both groups. CONCLUSIONS: The current project activities demonstrate the feasibility of including patients in priority setting exercises for primary healthcare in general, rather than focusing on a condition-specific population or disease area. There was considerable overlap between patient-generated topics and topics previously identified by other stakeholders, but patients identified two additional topics (mental health resources, improve and strengthen patient-provider communication). More similarities than differences in topic importance between patients and providers emerged in the online surveys. The project activities that follow (rapid literature reviews, multistakeholder dialogue) will highlight under-researched topics and inform the development of specific research questions.

Bicycling crash circumstances vary by route type: a cross-sectional analysis.

BACKGROUND: Widely varying crash circumstances have been reported for bicycling injuries, likely because of differing bicycling populations and environments. We used data from the Bicyclists' Injuries and the Cycling Environment Study in Vancouver and Toronto, Canada, to describe the crash circumstances of people injured while cycling for utilitarian and leisure purposes. We examined the association of crash circumstances with route type. METHODS: Adult cyclists injured and treated in a hospital emergency department described their crash circumstances. These were classified into major categories (collision vs. fall, motor vehicle involved vs. not) and subcategories. The distribution of circumstances was tallied for each of 14 route types defined in an earlier analysis. Ratios of observed vs. expected were tallied for each circumstance and route type combination. RESULTS: Of 690 crashes, 683 could be characterized for this analysis. Most (74%) were collisions. Collisions included those with motor vehicles (34%), streetcar (tram) or train tracks (14%), other surface features (10%), infrastructure (10%), and pedestrians, cyclists, or animals (6%). The remainder of the crashes were falls (26%), many as a result of collision avoidance manoeuvres. Motor vehicles were involved directly or indirectly with 48% of crashes. Crash circumstances were distributed differently by route type, for example, collisions with motor vehicles, including "doorings", were overrepresented on major streets with parked cars. Collisions involving streetcar tracks were overrepresented on major streets. Collisions involving infrastructure (curbs, posts, bollards, street furniture) were overrepresented on multiuse paths and bike paths. CONCLUSIONS: These data supplement our previous analyses of relative risks by route type by indicating the types of crashes that occur on each route type. This information can guide municipal engineers and planners towards improvements that would make cycling safer.

Comparing the effects of infrastructure on bicycling injury at intersections and non-intersections using a case-crossover design.

BACKGROUND: This study examined the impact of transportation infrastructure at intersection and non-intersection locations on bicycling injury risk. METHODS: In Vancouver and Toronto, we studied adult cyclists who were injured and treated at a hospital emergency department. A case-crossover design compared the infrastructure of injury and control sites within each injured bicyclist's route. Intersection injury sites (N=210) were compared to randomly selected intersection control sites (N=272). Non-intersection injury sites (N=478) were compared to randomly selected non-intersection control sites (N=801). RESULTS: At intersections, the types of routes meeting and the intersection design influenced safety. Intersections of two local streets (no demarcated traffic lanes) had approximately one-fifth the risk (adjusted OR 0.19, 95% CI 0.05 to 0.66) of intersections of two major streets (more than two traffic lanes). Motor vehicle speeds less than 30 km/h also reduced risk (adjusted OR 0.52, 95% CI 0.29 to 0.92). Traffic circles (small roundabouts) on local streets increased the risk of these otherwise safe intersections (adjusted OR 7.98, 95% CI 1.79 to 35.6). At non-intersection locations, very low risks were found for cycle tracks (bike lanes physically separated from motor vehicle traffic; adjusted OR 0.05, 95% CI 0.01 to 0.59) and local streets with diverters that reduce motor vehicle traffic (adjusted OR 0.04, 95% CI 0.003 to 0.60). Downhill grades increased risks at both intersections and non-intersections. CONCLUSIONS: These results provide guidance for transportation planners and engineers: at local street intersections, traditional stops are safer than traffic circles, and at non-intersections, cycle tracks alongside major streets and traffic diversion from local streets are safer than no bicycle infrastructure.

Route infrastructure and the risk of injuries to bicyclists: a case-crossover study.

OBJECTIVES: We compared cycling injury risks of 14 route types and other route infrastructure features. METHODS: We recruited 690 city residents injured while cycling in Toronto or Vancouver, Canada. A case-crossover design compared route infrastructure at each injury site to that of a randomly selected control site from the same trip. RESULTS: Of 14 route types, cycle tracks had the lowest risk (adjusted odds ratio [OR] = 0.11; 95% confidence interval [CI] = 0.02, 0.54), about one ninth the risk of the reference: major streets with parked cars and no bike infrastructure. Risks on major streets were lower without parked cars (adjusted OR = 0.63; 95% CI = 0.41, 0.96) and with bike lanes (adjusted OR = 0.54; 95% CI = 0.29, 1.01). Local streets also had lower risks (adjusted OR = 0.51; 95% CI = 0.31, 0.84). Other infrastructure characteristics were associated with increased risks: streetcar or train tracks (adjusted OR = 3.0; 95% CI = 1.8, 5.1), downhill grades (adjusted OR = 2.3; 95% CI = 1.7, 3.1), and construction (adjusted OR = 1.9; 95% CI = 1.3, 2.9). CONCLUSIONS: The lower risks on quiet streets and with bike-specific infrastructure along busy streets support the route-design approach used in many northern European countries. Transportation infrastructure with lower bicycling injury risks merits public health support to reduce injuries and promote cycling.

Personal and trip characteristics associated with safety equipment use by injured adult bicyclists: a cross-sectional study.

BACKGROUND: The aim of this study was to estimate use of helmets, lights, and visible clothing among cyclists and to examine trip and personal characteristics associated with their use. METHODS: Using data from a study of transportation infrastructure and injuries to 690 adult cyclists in Toronto and Vancouver, Canada, we examined the proportion who used bike lights, conspicuous clothing on the torso, and helmets on their injury trip. Multiple logistic regression was used to examine associations between personal and trip characteristics and each type of safety equipment. RESULTS: Bike lights were the least frequently used (20% of all trips) although they were used on 77% of trips at night. Conspicuous clothing (white, yellow, orange, red) was worn on 33% of trips. Helmets were used on 69% of trips, 76% in Vancouver where adult helmet use is required by law and 59% in Toronto where it is not. Factors positively associated with bike light use included night, dawn and dusk trips, poor weather conditions, weekday trips, male sex, and helmet use. Factors positively associated with conspicuous clothing use included good weather conditions, older age, and more frequent cycling. Factors positively associated with helmet use included bike light use, longer trip distances, hybrid bike type, not using alcohol in the 6 hours prior to the trip, female sex, older age, higher income, and higher education. CONCLUSIONS: In two of Canada's largest cities, helmets were the most widely used safety equipment. Measures to increase use of visibility aids on both daytime and night-time cycling trips may help prevent crashes.

Safe cycling: how do risk perceptions compare with observed risk?

OBJECTIVE: Safety concerns deter cycling. The Bicyclists' Injuries and the Cycling Environment (BICE) study quantified the injury risk associated with 14 route types, from off-road paths to major streets. However, when it comes to injury risk, there may be discordance between empirical evidence and perceptions. If so, even if protective infrastructure is built people may not feel safe enough to cycle. This paper reports on the relationship between perceived and observed injury risk. METHODS: The BICE study is a case-crossover study that recruited 690 injured adult cyclists who visited emergency departments in Toronto and Vancouver. Observed risk was calculated by comparing route types at the injury sites with those at randomly selected control sites along the same route. The perceived risk was the mean response of study participants to the question "How safe do you think this site was for cyclists on that trip?", with responses scored from +1 (very safe) to -1 (very dangerous). Perceived risk scores were only calculated for non-injury control sites, to reduce bias by the injury event. RESULTS: The route type with the greatest perceived risk was major streets with shared lanes and no parked cars (mean score = -0.21, 95% confidence interval [CI]: -0.54-0.11), followed by major streets without bicycle infrastructure (-0.07, CI -0.14-0.00). The safest perceived routes were paved multi-use paths (0.66, CI 0.43-0.89), residential streets (0.44, CI 0.37-0.51), bike paths (0.42, CI 0.25-0.60) and residential streets marked as bike routes with traffic calming (0.41, CI 0.32-0.51). Most route types that were perceived as higher risk were found to be so in our injury study; similarly, most route types perceived as safer were also found to be so. Discrepancies were observed for cycle tracks (perceived as less safe than observed) and for multiuse paths (perceived as safer than observed). CONCLUSIONS: Route choices and decisions to cycle are affected by perceptions of safety, and we found that perceptions usually corresponded with observed safety. However, perceptions about certain separated route types did not align well. Education programs and social media may be ways to ensure that public perceptions of route safety reflect the evidence.