Introduction

In recent years, police agencies have increasingly relied on high visibility hot spots policing strategies to efficiently allocate resources and reduce violent crime. Recent estimates suggest that as many as 75% of U.S. police departments use hot spots policing to control crime (Braga et al., 2019; Braga & Weisburd, 2022; Weisburd & Majmundar, 2018). These strategies focus police resources on micro locations characterized by persistent crime concentrations. Still, despite decades of evidence demonstrating the effectiveness of hot spots policing (Braga et al., 2019; Sherman & Weisburd, 1995; Turchan & Braga, 2024), there remains uncertainty about public attitudes towards these strategies. Public concerns around stigma, surveillance, and over policing continue to pose challenges for community-police relations (Boehme et al., 2022; Metcalfe & Pickett, 2018; Tyler et al., 2015a, b). Understanding these perceptions is crucial, as community support impacts the effectiveness of policing strategies through cooperation and trust (Boehme et al., 2023b; Mazerolle & Ransley, 2006) and can ultimately influence the sustainability and legitimacy of police operations.

Building on this foundation, we explore how citizens might update their views on hot spots policing when provided several descriptions. Framing theory suggests that individuals do not passively absorb information but instead interpret facts through preexisting mental models and narratives (Kühberger, 1995). In terms of policing, this means that citizens might consider quantitative information like charts, crime rates, and reduction percentages in different ways based on their prior beliefs and experiences. That is, lived experiences, identity, and/or prior experiences with police may impact the way in which such information is interpreted. For example, citizens with high baseline levels of trust in police might view quantitative evidence of crime reductions as validation that focused policing “works”, whereas those same numbers might invoke skepticism within communities that are wary of over policing. This framing lens is important to understand and has real-world implications as police departments increasingly adopt targeted strategies like hot spots policing. Community cooperation (i.e., crime reporting and acceptance of new strategies) is affected not only by police performance (Nix, 2017) but also transparent communication (Dobson et al., 2025). Even evidence-based tactics can fail when community support is unstable. On the other hand, transparent messaging that communicates not only effectiveness and results but also methods, tactics, and intentions may help community members better understand and support new strategies.

The current study addresses the existing gap in knowledge surrounding public perceptions of hot spots policing by examining how providing information on hot spots policing impacts citizen sentiment. Using a preregistered survey experiment with a large sample size (N = 2,412), we randomly assigned respondents to one of three conditions: quantitative details explaining crime reduction effectiveness, qualitative narratives emphasizing potential stigmatic impacts, or a control condition which received basic information about hot spots policing. The experimental design allows for a robust assessment of how information framing might shift public perceptions. We examine different framing techniques against a baseline to isolate the individual and combined effects of both data-driven and narrative-driven statements. Specifically, we test four preregistered hypotheses related to the impact of different informational frames and their interactions with respondent characteristics such as race and victimization status. Our findings inform how policymakers and law enforcement agencies should strategically communicate the benefits, while addressing potential pitfalls, of high visibility hot spots policing. Of note, our brief description referred to a high-visibility, deterrence-based variant of hotspots policing (i.e., lights on, frequent presence). Many successful implementations also adopt problem-oriented strategies at hot spots. Public perceptions may differ by subtype; however, this study focuses solely on messaging related to high visibility hot spots policing.

Literature Review

Framing Effects on Public Sentiment about Criminal Justice Policies

Framing is a theoretical mechanism by which changes can occur in people’s understanding of issues depending on how the issues are presented to them (Goffman, 1974; Hawk & Dabney 2014). It may also affect the solutions that people prefer to address problems. Framing effects are increasingly recognized as important for public support across a range of criminal justice policies like crime control vs. due process, punishment vs. rehabilitation, and court decision making among others (Burton et al., 2020; Boehme et al., 2024; Garnier-Dykstra & Wilson, 2021; Gottlieb, 2017; Metcalfe & Pickett, 2022; Norris & Mullinix, 2020; Suiter & Metcalfe, 2024; Wu, 2021b). Further, it can guide opinion and ultimately influence support for policy. For example, randomized survey studies have shown that providing performance data can increase support for police tactics such as discretionary traffic stops (Boehme et al., 2024). On the other hand, descriptions that highlight potential harmful effects may decrease public support by raising concerns about fairness, effectiveness, or unintended consequences. Peffley and Hurwitz (2007) found that frames emphasizing racial discrimination or wrongful convictions resulted in reduced support for capital punishment among African Americans. In contrast, many white respondents not only resisted these frames but sometimes became more supportive of punitive measures when confronted with claims of racial injustice. These results demonstrate that there is a need to identify which kinds of messages resonate with the public. Determining which “frames” affect public opinion (i.e., approval) can help practitioners and local officials tailor communication strategies while ensuring they address community concerns.

Effectiveness of Hot Spots Policing

Strong evidence exists in support of the crime reduction effect of focused police presence in persistently high crime areas. (Braga et al., 2019; Turchan & Braga, 2024). This strategy is commonly referred to as hot spots policing. Numerous studies examining the distribution of police in high crime locations have found significant reductions in crime (Gibson et al., 2017; Groff et al., 2015; Nagin & Weisburd, 2013; Ratcliffe et al., 2011). The optimal time needed to achieve significant crime reductions is roughly 15 min per visit (Koper, 1995; Telep et al., 2014). That is, mere presence of police cars, lasting only 15 min, with their patrol lights on in high crime areas, can lead to significant decreases crime incidents in treated areas (Smith et al., 2024a; Telep et al., 2014). This potentially eliminates the need for direct engagement between police and citizens residing in these areas. Smith and colleagues (2024a) recently found that high visibility visits where officers sat in high crime locations at high crime times with their blue lights on for at least 15 min resulted in a 10.7% reduction of crime within the treated areas. The strategy possibly leading to an overall reduction in city-wide crime rates (Tregle et al., 2025b). Despite assumptions regarding hot spot policing leading to increased arrest rates, “crackdowns,” and the spatial displacement of crime, the authors also found no crime displacement to surrounding areas. Moreover, there were no increases in arrests or traffic stops in areas treated with high visibility strategies (Tregle et al., 2025a). Overall, a large body of evidence demonstrates the benefits of hot spots policing (see systematic reviews by Braga et al., 2012; Braga et al., 2014, 2019); however, there remain concerns about these strategies stigmatizing communities where these strategies are implemented.

Community Perceptions of Hot Spots

Notwithstanding the overwhelmingly positive evidence of the impact of hot spots on crime rates (Koper et al., 2024), concerns remain about the negative impact of this strategy, potentially leaving communities feeling stigmatized, targeted, and harassed (Metcalfe & Pickett, 2018; Tyler et al., 2015b). Findings examining the impact of hot spots policing on police perceptions are largely mixed. Koper and colleagues (2024) distributed a pre- and post-survey to community members in areas receiving hot spots treatment. They found no effects on community perceptions of police, with one of the studied cities showing some evidence of improved perceptions of police legitimacy and misconduct (see also Ratcliffe et al., 2015). In an earlier study, Koper et al. (2022) found nuanced effects on community perceptions based on the type of activities police engaged in at hot spots. That is, results indicated that respondents reported positive attitudes of trust and confidence, procedural justice, and legitimacy when they experienced/witnessed patrols and community-police interactions. However, support for police was lower when they witnessed heavy handed, enforcement-based activities. Scholars have expressed similar concerns over a “backfire effect” in which hot spots policing may increase fear in the public due to police presence, heighten concerns over potential victimization, or lead to stigmatization of targeted communities (Haberman et al., 2016; Geller et al., 2014; Kochel, 2011; Rosenbaum, 2006; Kochel & Weisburd, 2017; Turchan & Braga, 2024; Weisburd et al., 2011).

The Present Study

To shed light on this debate, this study investigates public perceptions of these strategies and whether various framing messages affect public perceptions using a preregistered experimental survey. As the core recipients of these strategies, public perceptions are an essential consideration for police agencies before (or when) certain strategies are adopted and implemented (Doucette et al., 2021). Further, understanding whether basic information provided to the public on strategy (in)effectiveness can sway public opinion towards these strategies is important for agencies to enhance perceptions of their efforts. When the community believes in the utility of police efforts and strategies, the public may be more likely to share information, report crimes, support law enforcement initiatives, and cooperate in crime-reducing efforts (Boehme et al., 2023b; Mazerolle & Ransley, 2006). Alternatively, if the public feels that hot spots policing contributes to unwanted surveillance, privacy violations, and over policing (Boehme et al., 2022), there is the risk of damaged community-police relations and the (in)effectiveness of police strategies. Therefore, this study addresses the below preregistered hypotheses:

  • H1:Those randomly assigned the hot spots effectiveness treatment will express more positive attitudes towards the strategy (compared to those assigned the control condition).

  • H2: Those randomly assigned the hot spots stigma treatment will express less favorable attitudes towards the strategy (compared to those assigned the control condition).

  • H3: Non-White respondents will be differentially impacted by the hot spot stigma condition.

  • H4: Recent crime victims will be differentially impacted by the hot spot effectiveness treatment compared to non-crime victims.

Data and Sample

Survey Distribution

We obtained a distribution list of 903,570 emails from South Carolinian heads of households from Mailer’s Haven. Mailers Haven (2023) validates household addresses multiple times per year by using multiple data sources, including the U.S. Postal Service, mailing lists, and open source data. Addresses are excluded from the distribution list when addresses cannot be verified by Mailer’s Haven, when homes are unoccupied and therefore do not have a head of household listed, and when households actively place their address on no-contact lists. Within the distribution list of home addresses is an associated email list of the head of the household, which serves as the sampling frame for the study.Footnote 1

Invitations to participate were emailed via Qualtrics beginning August 6, 2024, with five periodic email reminders throughout, and data collection concluded on October 17, 2024. We obtained a final working sample of 2,412, indicating a response rate of < 0.1% according to the AAPOR RR2 calculator (AAPOR, 2023). During pilot testing, we distributed the survey to about 30 test subjects within the researchers’ networks, and about 20% of email invitations “landed” in their main inbox, while the other email invitations were either undelivered or landed in a junk or spam folder. Therefore, we believe that our response rate is likely higher for the emails that were actually received in the main email inbox. Previous studies have shown that a low response rate is not linked to nonresponse bias (Pickett, 2017; Pickett et al., 2018), and the experimental design with a large sample size does not preclude the ability to make a causal link between the treatment and outcomes. Additionally, and consistent with best practice, our analyses focus on potential nonresponse bias rather than overall response rate (Groves & Peytcheva, 2008).

Email invitations were sent to the full distribution list via Qualtrics. Upon clicking the survey link, respondents were first presented with three pre-experimental blocks that appeared in random order. These blocks measured willingness to obey, procedural justice, and trust and confidence in police, drawing on prior empirical literature. After completing these initial blocks, respondents entered the experimental portion of the survey.

The survey contained four embedded experiments, each focused on a different policing-related topic: (1) gunshot detection technology (GDT), (2) hot spots policing (HS), (3) door hanger interventions, and (4) police use of profanity messaging. The order of these four experimental blocks was randomized for each respondent to mitigate potential carryover and fatigue effects. Depending on randomization, respondents might complete the GDT block first, followed by re-randomization into door hanger, and so on. After completing all four experimental blocks, respondents answered socio-demographic questions and an open-ended response item at the end of the survey.

An important element of making such causal claims is whether characteristics are balanced across treatment and control groups via randomization. Table A1 in the Appendix presents a balance table across covariates with associated chi-square statistics to test if there are significant differences between the treatment and control groups. There were no significant differences in covariates between treatment and control groups, offering evidence of successful randomization via Qualtrics. Overall, comparisons between our sample and sociodemographics across the state of South Carolina showed differences in terms of race/ethnicity. There was an overrepresentation of White respondents and an underrepresentation of Black respondents, compared to the state demographic information (United States Census Bureau, 2022). However, our sample of Black respondents was representative of national estimates. Additionally, our sample primarily consisted of older respondents, over the age of 45. Regarding sex assigned at birth and political affiliation, our sample was representative of the state of South Carolina as well as the U.S. While there were some demographic differences, prior evidence indicates that our online survey technique may still produce externally valid results (Patten & Perrin, 2015). Still, we remain cautious in making claims of external validity and are committed to the core goal of obtaining a large enough sample to enhance internal validity for this study.

Research and Survey Design

Information provision and framing experiments are commonly used in the research literature to assess whether respondents update prior notions after having been provided with various criminal justice information (Boehme et al., 2023a; Mullinix et al., 2021; Norris & Mullinix, 2020; Wu, 2021a). After consenting to take the survey, and before the experimental portion of the survey, respondents were asked about their trust and confidence in police, perceptions of police procedural justice, and their willingness to obey the law. Next, respondents proceeded to the experimental portion of the survey where they received only one of the three experimental conditions. If assigned a treatment condition, they were presented with the entirety of the treatment information on a single page. After clicking the “next” button to move to the next page, the respondent was then provided the same treatment information above the Likert-scale questions.

Regardless of experimental condition, all respondents were assigned the same baseline statement about the strategy. This information provided context for the Likert-scale questions. The baseline statement read as follows: Hot spots policing is a strategy used by some police agencies, in which agencies dedicate more resources to a small number of areas that are responsible for a large number of violent crimes. Respondents assigned to the control received only the above statement, followed by six Likert-scale questions. The questions consisted of the dependent variables (detailed below). If randomly assigned the hot spots effectiveness treatment, they were presented with the baseline statement as above with added information and data about crime reductions derived from an empirical evaluation discussed below. If randomly assigned the hot spots stigma treatment, they were presented the baseline statement with added information about qualitative community concerns expressed by advocates and community members over stigma and targeting due to hot spots policing (detailed below). No empirical data referencing effectiveness was displayed to respondents who received the stigma treatment.

The effectiveness treatment was based on a recent evaluation of a high visibility hot spots intervention in four large U.S. cities. The evaluation found significant crime reduction effects on the targeted street segments and citywide (Smith et al., 2024b, c, d; Tregle et al., 2025a, b). The hot spots stigma treatment was derived from a synthesis of research on community concerns about hot spots policing strategies (Kochel, 2011; Metcalfe & Pickett, 2018). Therefore, results from this survey contrast a quantitative data message framing with a qualitative community sentiment framing to explore each’s impact on public perceptions of high visibility hot spots police strategies.

Variables

The dependent variable consisted of a mean scale combining respondents’ answers to the six posttreatment Likert-scale questions which asked how much they agreed or disagreed with the following statements about the relevant topic (alpha = 0.851).Footnote 2 Some responses were reverse-coded such that higher scores on the mean scale indicated more positive attitudes toward hot spots policing. The items measuring police harassment, erodes trust in police, and unnecessary stops were reverse-coded when creating the combined mean scale, such that higher values on the composite measure reflected more positive attitudes toward high-visibility hot spots policing. For the analyses of individual items, however, these variables were left in their original direction (i.e., not reverse-coded). Below are the statements all respondents were asked to rate their level of agreement/disagreement related to hot spots policing:

  • This is an effective strategy to reduce crime in those communities.

  • This strategy will lead to police harassment of residents in those communities (reverse coded).

  • This strategy will improve community safety.

  • This strategy will erode trust in the police (reverse coded).

  • This strategy will take violent offenders off the street.

  • This strategy will lead to unnecessary stops of residents by police (reverse coded).

Independent Variables

The key predictors were treatment variables coded 1 if the respondent was assigned one of the treatments/controls and 0 if not. The control condition served as the reference category. Experimental conditions can be found in Appendix Table A2, and covariate measures are located in Appendix Table A3. We created three combined mean scales of pre-experimental perceptions: trust/confidence in police, perceptions of police procedural justice, and perceptions of willingness to obey the law. These items were presented before the experimental portion of the survey to measure pre-experimental and overall perceptions of police. Additionally, we included post randomization sociodemographic variables of sex assigned at birth (male/female), race/ethnicity (Black, Other race, and White), age, political ideology (liberal, moderate, or conservative), education attainment, marital status, employment status, crime victim in the past year, and police contactFootnote 3 in the past year.

Analytic Strategy

We employed a multiphased analytical approach beginning with summary statistics of both the entire sample and by experimental condition to assess the impact on the dependent variables. We rely on the unadjusted models as the main analyses, as experimental methodologists suggest relying on the uncontrolled models, particularly in large samples (Berk et al., 2013; Freedman, 2008; Lin, 2013). We also estimated interactions between treatments to measure the heterogeneity of our treatments across certain subgroups. All models were estimated using OLS regression models with robust standard errors on our continuous dependent variable.

Descriptive Results

Table 1 Collapsed binary means of dependent variables by experimental
Full size table

Table 1 presents summary statistics of the collapsed single items of our dependent variables. These results show the percentage of the sample that indicated they either “strongly agree” or “agree” with the outcome statements. Here, we direct the reader to the control condition as a proxy for baseline perceptions of high visibility hot spots policing. Respondents in the control condition showed high agreement (e.g., strongly agreed/agreed) with perceived benefits and comparatively low agreement with perceived harms. That is, in the control group, 76% agreed that hot spots policing reduces crime; 76% said hot spots improve community safety, and 63% agreed that hot spots would remove violent offenders from the street. By contrast, only 25% agreed that this strategy would lead to police harassment, 21% agree that it would erode trust in police, and 30% agreed that it would lead to unnecessary stops. These results serve as the baseline against which we interpret experimental effects.

T-tests assessing the mean responses to the combined mean scale and single items are presented in Appendix Table A4. In comparison to the control condition, respondents assigned the effectiveness treatment expressed significantly more positive attitudes toward hot spots policing (combined mean scale) and the crime prevention related single items, while expressing less positive attitudes toward the stigma related single items. Respondents assigned the stigma treatment did not report significantly different perceptions than respondents in the control condition, with one exception. Those assigned the stigma treatment had significantly higher average scores that hot spots policing will erode trust in the police.

Experimental Results

The uncontrolled model, which only includes the two treatment variables (compared to the control condition), is regressed on the combined mean scale (Table 2). We found differential effects for the two experimental conditions relative to the control condition. Specifically, respondents assigned to the hot spots effectiveness treatment expressed significantly more positive attitudes towards hot spots policing. On average, the effectiveness treatment increased respondents’ positive attitudes towards hot spots strategies by roughly 15%, compared to those in the control condition (AME = 0.148, S.E. = 0.036, p < 0.001). These results indicate that providing citizens with information about the crime reductions associated with hot spots policing may have a significant, positive effect on perceptions of the strategy.

The hot spots stigma treatment did not yield statistically significant changes in attitudes. The treatment was associated with a modest, nonsignificant negative effect (AME = −0.055, S.E. = 0.040, p = 0.166). These results suggest that the stigmatizing framing did not significantly alter respondents’ overall perceptions of hot spots policing relative to the control condition when no covariates were added to the model. The uncontrolled model provides initial evidence that framing the strategy in terms of its effectiveness has a significant positive impact on public attitudes towards hot spots policing, whereas the stigma framing does not produce a comparable effect.

Of note, the framing effects associated with the stigma condition are modest, especially given the large sample size. The unadjusted effect is small and non-significant. Given the already high endorsements seen in the control condition, these effects amount to small updates in opinion rather than whole attitudinal changes.Footnote 4

Table 2 Uncontrolled OLS regression on the combined mean dependent variable
Full size table

Robustness Checks

We estimated several robustness checks using different model specifications. Appendix Table A5 reports unadjusted OLS regression results on single item outcomes. Findings demonstrated that those assigned the effectiveness treatment (compared to the control condition) expressed positive attitudes that hot spots will reduce crime and improve community safety. The effectiveness treatment also decreased perceptions that hot spots will lead to more police harassment, erode trust in police, will remove violent offenders from the streets, and result in unnecessary stops. The stigma treatment increased agreement that hot spots will erode trust in police.

Table A6 reports the unadjusted logistic regression results on single items. The effectiveness treatment aligned with the OLS results. The stigma treatment again increased agreement that hot spots will erode trust in police and result in unnecessary stops. Overall, these results show robustness in the effectiveness treatment’s association with positive attitudes towards hot spots policing.

Discussion

The findings from our preregistered survey experiment demonstrate that presenting the public with specific messages about policing strategies, like high visibility, deterrence-based hot spots policing, can shape perceptions. Results discussed here are derived from the preregistered, unadjusted analyses Our findings are largely consistent with prior surveys exploring hot spots implementations. When participants were exposed to information communicating hot spots effectiveness, they expressed increased acceptance of concentrating resources in high crime micro locations. The straightforward takeaway is that sharing positive results with the public influences perceptions of hot spots policing in a positive direction, while discussions related to negative stigmas associated with the interventions may influence attitudes in the opposite direction. We discuss the implications of the nuanced findings below.

Across the entire sample, respondents generally expressed positive attitudes towards crime outcome measures. They expressed less favorable attitudes toward stigma related outcomes. That is, those in the stigma treatment did not express significantly different perceptions of hot spots policing relative to the control condition. However, when including covariates into the model, the stigma condition became significant in a negative direction, which indicates negative attitudes towards hot spots strategies. These results highlight the importance of communication and information sharing in policing. The way agencies, stakeholders, and even the local media represent and justify police strategies can either foster or erode broader community support.

Similarly, the positive and significant coefficients for trust and confidence, procedural justice, and willingness to obey reinforce prior findings on police legitimacy (Sunshine & Tyler, 2003; Tyler, 1990). That is, when the community views the police as procedurally fair and just, they are more willing to endorse evidence-based crime control tactics, even when those tactics include proactive enforcement tactics like concentrated police patrol in specific places (National Academies of Sciences et al., 2018; Sunshine & Tyler, 2003). Experimental evidence also shows that procedural justice training can change officer behavior and improve community attitudes at hot spots (Weisburd et al., 2022). Additionally, prior research demonstrates that legitimacy may function as a mechanism to increase public cooperation (Tyler et al., 2015a). Police departments can use these findings to their advantage when implementing hot spots policing. Indeed, our findings lend support to the idea that hot spots strategies can integrate officer deployment with procedural-justice oriented engagement (Weisburd et al., 2022).

We estimated preregistered subgroup tests to explore whether responses varied by race or recent victimization. There were only two notable differences. First, non-White respondents, regardless of condition, who received the stigma message expressed somewhat more negative attitudes toward hot spots policing. This pattern aligns with prior literature exploring nonwhite support of police (Boehme et al., 2022) and suggests that concerns about how policing strategies are applied in specific communities can shape reactions to information about those strategies. Second, recent crime victims, who were assigned the effectiveness treatment, expressed negative attitudes toward the strategy. This indicates that that prior victimization may negatively influence how respondents interpreted the treatment messages.

The specific design and execution of high-visibility hotspot policing may ultimately mitigate potential unintended consequences in treatment areas. The mechanism of crime reduction is deterrence-based and focuses on conspicuous presence rather than heavy handed, intensive enforcement. Again, Tregle and colleagues (2025) recently found that high visibility treatments achieved significant crime reductions without increasing arrests. In other words, officers can serve as a visible deterrent rather than a punitive presence. This model may provide public safety benefits to minority communities while avoiding the cycle of over policing, which may lead to cynicism (especially when coupled with enforcement tactics) (MacDonald et al., 2016; Sherman & Eck, 2003).

Our results reinforce these findings. Respondents who received the effectiveness treatment believed that hot spots policing would make neighborhoods safer. At the same time, they felt it would not lead to more arrests on the street. This indicates that the public may have some confidence in a “prevention through presence,” deterrence-based approach. Moving forward, these results provide an opportunity to change how the public thinks about policing. If the public witnesses crime reduction firsthand, in the absence of increased arrests, they may be more likely to endorse police strategies. Police agencies can use this insight to couple light footprint strategies with positive messaging surrounding the intended strategies and achieved results. High visibility hot spots patrols may offer a “sweet spot” or “just right” policing (Sherman, 2022), whereby police are present “enough” without exerting too much presence and excessive contact to the community which may erode trust in police.

We also observed some “spillover” effects. That is, the effectiveness frame decreased agreement with items about potential harms, and the stigma frame sometimes reduced agreement with effectiveness items that were not directly targeted. One plausible explanation is coherence shifting. After receiving new information, respondents may update a global evaluation and then align related beliefs for internal consistency (Holyoak & Simon, 1999). Assimilation dynamics can produce similar patterns, whereby a cue about one attribute (e.g., crime reduction) colors judgments on related attributes (e.g., trust or harassment) (Sherif & Hovland, 1961). Our design cannot identify the precise mechanism at work. Future research should measure mediators such as perceived mechanisms, perceived fairness and procedural justice, or trust/confidence cues, as these items may account for movements across these domains.

While our study offered a high degree of internal validity, some limitations warrant discussion. First, although the survey was well powered to execute the designed experiment, our findings may not extend to all populations. That is, our sample was over representative of White and highly educated respondents, whereby extrapolating our findings across various context should be cautioned. The statewide, email-based sample was over representative of White and older adults and does not include neighborhood descriptors (e.g., hot spot treated residence). Therefore, future studies should build on this work to allow for generalizing to residents in different areas. Future studies should also oversample in high crime street segments or recruit directly within treated hot spots to assess local reactions. We also note that, although most of our sample has not experienced hot spots policing in their neighborhood, which is common even in randomized field experiments, where many residents living near treated locations are unaware that the strategy has been implemented (Weisburd et al., 2011). In fact, this may actually increase the importance of framing given that citizens often rely on indirect information rather than personal observation of policing tactics.

Second, our survey did not include direct measures of respondents’ fear of crime, perceived local disorder, or views about under- or over-policing in their own neighborhoods. These attitudes could shape how people evaluate concentrated patrol strategies and how they receive different frames. Future studies should build on this study by including measures of fear/disorder to examine these mechanisms directly. That said, our study offers general public perceptions of hot spots strategies. This is a key component of broader public perceptions within jurisdictions as public messaging that police are “doing something” to address crime problems may be more palatable to the public. Of note, survey-based research often encounters challenges regarding sampling frames and participant self-selection. Future research should replicate this study in different regions and jurisdictions to bolster generalizability. Third, we were unable to assess prolonged exposure to hot spots policing or interactions between different messaging types. The stigma associated with hot spots policing might overcome any effects associated with positive messaging surrounding its crime control benefits. Conversely, some populations may be willing to tolerate stigmatizing conditions if they know that the strategy is capable of achieving large crime reductions. Future research could expand on this study by determining whether prolonged exposure to either effectiveness or stigma messaging, rather than a single brief statement, would induce stronger or more stable changes in attitudes. Likewise, qualitative methods could help understand how individuals weigh benefits such as crime reduction against possible disadvantages like intrusive surveillance or community labeling. Fourth, we surveyed the public, most of whom have most likely never experienced hot spots policing. Therefore, surveying those that have experienced hot spots policing strategies in their neighborhoods may produce differing results. Finally, this survey measured perceived benefits and harms of hot spots policing. Future experiments should include an overall perceptions item along with qualitative measures to gain a richer understanding of the public’s understanding and attitudes towards hot spots policing.

Implications and Conclusion

From a policy perspective, it appears that police agencies and policymakers could benefit from transparent communication about the data driven results associated with high visibility, deterrence based hot spots policing. Taking an extra step to emphasize documented reductions in violent crime could increase community acceptance, especially if the information is presented in ways that address existing concerns around over policing or harassment. At the same time, it is important for law enforcement to engage community members in ways that mitigate concerns about stigmas associated with hot spots policing. Regardless of any benefits, the need remains to ensure that increased visibility does not alienate the very neighborhoods the strategy seeks to protect. One possibility is that police agencies can build avenues for community feedback and use procedural justice strategies (Mazerolle & Ransley, 2006) to build trust and support among residents who may feel disproportionately targeted by police presence in historically marginalized areas. As for the potential for stigma messaging affecting perceptions of hot spots policing, agencies should be particularly cautious yet cognizant of how crime prevention strategies may affect public perceived benefits and harms of the police, particularly for non-White residents. Reciprocal discussions with the targeted communities through police outreach are vital to reduce crime while also managing (or mitigating) public concerns. Researchers and agencies should consider public perceptions of community members in which hot spots policing is implemented in the form of surveys and interviews to better address concerns that are brought about before, during, and after the intervention.