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. Author manuscript; available in PMC: 2024 Oct 1.
Published in final edited form as: J Anxiety Disord. 2023 Aug 15;99:102764. doi: 10.1016/j.janxdis.2023.102764

Heightened threat perceptions and reduced stability in anxiety and fear among U.S. adults who carry handguns

Craig J Bryan 1, Samantha E Daruwala 1, Jeffrey V Tabares 1, Jonathan E Butner 2, Emil F Coccaro 1, Stephanie M Gorka 1
PMCID: PMC10543589  NIHMSID: NIHMS1927899  PMID: 37597342

Abstract

Firearm carrying is often motivated to provide safety and is correlated with increased anxiety related to elevated perceptions of the world as a dangerous place. No studies have investigated affective states among firearm owners as they occur in their natural environments. This study used ecological momentary assessment (EMA) to examine cognitive-affective states among firearm owners who carry handguns outside their home (n=35), firearm owners who do not carry (n=47), and non-firearm owners (n=62). Participants completed a self-report questionnaire at baseline followed by EMA surveys of mood state with the Positive and Negative Affect Scale (PANAS) 8 times per day for 28 consecutive days. Carry handgun owners reported significantly higher threat perceptions, measured with the negative cognitions about the world subscale of the shortened Posttraumatic Cognitions Inventory (PTCI), than no-carry handgun owners (Mdiff=2.0, 95% CI=0.8-2.0, d=0.45, p=.001) and non-owners (Mdiff=1.8, 95% CI=0.6-2.9, d=0.42, p=.003). Groups did not significantly differ in mean momentary mood ratings assessed via EMA but stability in high-arousal negative arousal was significantly reduced among carry handgun owners (F(2,145)=3.5, p=.031). Results suggest firearm owners who carry handguns view the world as especially dangerous, are more likely to experience shifts in anxiety and fear, and take longer to recover from periods of elevated anxiety and fear.

Keywords: firearms, negative affect, anxiety, threat perceptions

Approximately 40-45% of U.S. adults report living in a household with a firearm and approximately 30% report personally owning one (Bryan, Bryan, et al., 2019; Schaeffer, 2021; Smith & Son, 2015). Self-protection is the most commonly reported motive for firearm acquisition and ownership among U.S. firearm owners, increasing from 46% of firearm owners in 1994 to 65% of firearm owners in 2019 (Carlson, 2005; Miller, Zhang, Rowhani-Rahbar, et al., 2022; Wright et al., 2017). The number of firearm owners who report carrying a firearm outside the home—lawfully or otherwise—has also increased during this timeframe (Cook & Ludwig, 1996; Miller, Zhang, & Azrael, 2022), likely because self-protection is also the primary motive for carrying firearms outside the home (Kleck & Gertz, 1998; Rowhani-Rahbar et al., 2022). While firearms are often acquired for safety and protection, research shows that firearm acquisition actually increases the likelihood of harm for firearm owners and others, but does little to deter crime (Hemenway, 2011).

Though the experience of violent crime and other forms of victimization has been shown to increase the likelihood that someone will acquire a firearm (Oliphant et al., 2019), firearm acquisition is motivated to a greater degree by diffuse anxiety associated with heightened threat perceptions (e.g., “The world is dangerous”) (Stroebe et al., 2017). Consistent with this pattern, self-protection motives among firearm owners are correlated with heightened threat perceptions (Stroebe et al., 2017) and multiple cross-sectional studies have found heightened threat perceptions among those who intend to acquire their first firearm (Anestis & Bryan, 2021; Bryan, Bryan, et al., 2020; Stroebe et al., 2017). Longitudinal studies further show that anxiety about possible future victimization predicts later firearm acquisition (Hauser & Kleck, 2013).

Individuals who are sensitive to threat likely experience sustained hypervigilance and arousal, particularly when stressors or threats are uncertain or unpredictable. Carrying a firearm outside the home may be one potential strategy to manage arousal in response to uncertainty given that, for some, firearm carrying facilitates feelings of preparedness and controllability (Kleck & Gertz, 1998; Warner & Thrash, 2020). Firearm carrying may paradoxically sustain anxiety, however, through increased threat attention and hypervigilance (Buttrick, 2020). Supporting this possibility is research showing that holding a firearm increases attention towards changing environmental conditions (Taylor et al., 2017) and biases individuals to misperceive threat cues (Taylor & Witt, 2014; Witt & Brockmole, 2012). From this perspective, firearm carrying may function as a maladaptive safety behavior (Telch & Lancaster, 2012) because it is enacted even when there is no actual threat, paradoxically generating and sustaining distress rather than ameliorating it (Helbig-Lang & Petermann, 2010).

Firearm possession may also contribute to increased reactivity, especially in conditions characterized by heightened uncertainty. This possibility is supported by research showing that threat-induced behavior is elicited more readily when someone is holding a firearm, even when no threat is present (Taylor et al., 2017). Chronic threat-related anxiety has been shown to degrade cognitive control (Grupe & Nitschke, 2013; Roxburgh et al., 2019; Xia et al., 2017) and is associated with difficulties engaging regulatory neural processes (Gorka et al., 2018). Over time, persistently exaggerated levels of threat perceptions can impair the ability to identify and recognize safety cues in conditions marked by uncertainty, resulting in increased cognitive, affective, and behavioral reactivity (Schumpe et al., 2017). Firearm owners who carry may be especially vulnerable to these effects.

A key limitation of prior research focused on associations among threat perceptions, firearm ownership, and affective arousal is overreliance on cross-sectional self-report surveys and longitudinal designs with lengthy gaps between assessments (e.g., months or years). Some studies have investigated thinking about firearms as a preferred method for attempting suicide (Rogers et al., 2022), but to our knowledge, no studies have assessed cognitive-affective states among firearm owners in real-time, however, which limits our understanding of how (or if) findings from laboratory settings generalize to firearm owners’ natural environments. Ecological momentary assessment (EMA), which allows for the assessment of psychological and behavioral phenomena close to when they actually occur, provides a method for addressing this knowledge gap.

The present study aimed to test multiple hypotheses, with an eye towards identifying similarities and differences between protective firearm owners who report carrying firearms outside their home and protective firearm owners who do not carry. First, we hypothesized that firearm carrying would be associated with significantly increased threat perceptions, assessed as a trait characteristic via self-report questionnaire. Second, we hypothesized that firearm carrying would be associated with significantly higher momentary ratings of high-arousal negative affect (e.g., anxiety, fear). Third, we hypothesized that firearm carrying would be associated with significantly increased reactivity in daily life, as indexed by reduced stability of momentary high-arousal negative affect.

Method

Participants and Procedures

Participants included 144 adults recruited from the community to participate in a study aimed at understanding risk factors for suicide among handgun owners and non-gunowners. We recruited handgun owners specifically versus firearm owners more broadly because handguns account for over 80% of firearm-related injuries and deaths in the U.S. (Planty & Truman, 2013). Potential participants first completed an online screening survey assessing demographic characteristics, firearm ownership, and medical conditions that could be exclusionary. Respondents whose responses suggested they were likely eligible were then contacted to schedule a virtual meeting with a member of the research team to complete an in-depth eligibility interview. Inclusion criteria were (1) being at least 18 years of age; (2) able to make one 2-hour visit to an on-campus laboratory for research-related activities; and (3) having regular access to either an Android or Apple smartphone to receive surveys multiple times per day via the MetricWire app. Potential participants were excluded if they had (1) serious medical conditions that could interfere with data interpretation for laboratory procedures used in the parent study (e.g., deafness, moderate or severe traumatic brain injury, or lifetime mania or psychosis); (2) psychotropic medication use within the past 4 months; (3) acute alcohol intoxication (verified via breath test); and (4) heavy recreational alcohol or cannabis use, defined as 5+ alcohol binges per month and cannabis use more than 5 times per week. Study procedures were approved by The Ohio State University’s Biomedical Institutional Review Board.

Individuals meeting eligibility completed self-report surveys and laboratory-based study procedures during an on-site lab visit. At the conclusion of the lab visit, participants downloaded the MetricWire app to their smartphone and completed a tutorial about how to complete self-report surveys within the app. Participants received 6 alerts per day for 28 consecutive days (168 total alerts) to complete brief (<5 mins) self-report surveys. Alerts were sent at a randomly selected times between 8AM-10PM. Each survey remained active for only 12 hours.

Handgun Ownership

Participants were classified as handgun owners who carry (n=35), handgun owners who do not carry (n=47), or non-owners (n=62) based on their responses to the following researcher-developed interview questions administered during an eligibility interview: (1) Do you currently own a working handgun or pistol? [yes or no]; (2) How many working handguns do you personally own? [numeric value from 0-99]; (3) Do you carry a handgun or pistol with you when you are out in your neighborhood, such as going for a walk, going to the grocery store, or somewhere else? [yes or no]; and (4) What percentage of the time would you say you carry a handgun or pistol with you when out of your home? [numeric value from 0-100].

Firearm Availability

Firearm availability was assessed separately from handgun ownership. Participants were asked the following researcher-developed questions about the availability of firearms in their homes: (1) Is a working handgun or pistol currently kept inside your home, even if you are not the owner? [yes or no]; and (2) How many handguns and pistols do you currently have in or around your home? [numeric value from 0-99]; (3) How many shotguns do you currently have in or around your home? [numeric value from 0-99]; and (4) How many rifles do you currently have in or round your home? [numeric value from 0-99].

Threat Perceptions

The Negative Cognitions about the World subscale of the Brief Posttraumatic Cognitions Inventory (PTCI-9) (Wells et al., 2019) was used to assess trait-like threat perceptions. Respondents used a 7-point Likert scale to answer 3 items (People can’t be trusted; I can’t rely on other people; People are not what they seem), with higher scores reflecting more extreme threat perceptions. The PTCI-9’s internal consistency and construct validity are established (Wells et al., 2019). In this sample, internal consistency was α=0.87. For the purposes of the study, we modified the scale’s original instructions by removing language that refers to recent traumatic experiences.

Mood State

The Positive and Negative Affect Scale Short Form (PANAS-SF) (Watson et al., 1988) was used to measure momentary mood state via EMA. Respondents were directed to “indicate to what extent you feel [affective state] right now” using a Likert rating scale ranging from 1 (very slightly or not at all) to 5 (extremely) for 10 positive affective (PA) states (interested, excited, strong, enthusiastic, proud, alert, inspired, determined, attentive, active) and 10 negative affective (NA) states (distressed, upset, guilty, scared, hostile, irritable, ashamed, nervous, jittery, afraid). The 10 positive items and 10 negative items are summed to obtain overall indicators of momentary positive and negative affective states (range= 10-50). The PANAS-SF’s internal consistency and construct validity are established (Crawford & Henry, 2004). In the present sample, the 2-level alpha (i.e., internal consistency) coefficients were αwithin=0.88 and αbetween=0.98 for NA and αwithin=0.77 and αbetween=0.93 for PA. Based on the circumplex model of affect (Posner et al., 2005; Russell, 1980), high-arousal NA was computed by summing the scores from the following four items: scared, nervous, jittery, afraid. The remaining six items (distressed, upset, guilty, hostile, irritable, ashamed) were summed to create a moderate-arousal NA variable.

Mood Stability

Mood stability was quantified using EMA data collected during the 4-week follow-up and based on the assumption that mood is characterized by attractive properties, a dynamical systems1 concept that means mood has a typical temporal pattern that resists change. External factors (e.g., life events) influence momentary mood state, moving it away from its typical pattern. Attraction implies a tendency to return to the typical pattern over time, overcoming these various external perturbations. From this perspective, stability is operationalized as the rate at which momentary mood returns to its mean value following perturbation. Consistent with prior research (Bryan, Butner, et al., 2020; Bryan et al., 2018; Bryan, Rozek, et al., 2019; Bryan et al., 2016), we calculated discrete change in mood state from time t to time t+1 as our indicator of stability. This change variable is entered as the criterion in a multilevel model with mood rating at t entered as the predictor and random effects on slopes and intercepts included to account for variation across participants in individual-level patterns over time. A negative coefficient for mood state at t as a predictor of change in mood state supports the hypothesis of attraction (Butner et al., 2015). Larger magnitude coefficients (i.e., further from zero) indicate mood is more resistant to change or more stable whereas smaller magnitude coefficients (i.e., closer to zero) indicate mood is easier to change or less stable.

Data Analysis

To test hypothesis 1, we used generalized linear modeling with log-transformed mean PTCI as the outcome to account for its positive skew. Comparison of Akaike’s Information Criterion and Bayesian Information Criterion values confirmed the linear regression with the log-transformed outcome provided better fit than linear regression and Poisson regression with the untransformed outcome. Firearm group (i.e., non-owners, handgun owners who carry, and handgun owners who do not carry) was entered as a categorical predictor. PTCI scores were missing completely at random from the first 6 (4.2%) enrolled participants due to a database error. To test hypothesis 2, we used mixed effects modeling with mean high-arousal NA during the 28-day EMA period as the outcome and handgun group as the predictor variable. Random effects were specified for the intercept and slope. To test the specificity of findings, we also tested three additional mixed effects models with mean moderate-arousal NA, mean PA, and mean NA during the 28-day EMA period entered as separate outcomes. Missing data at the participant level ranged from 0 to 162 out of 168 possible mood ratings (0-96.4% missing data points), with an overall mean missingness rate of 12.2% for the full sample. To test hypothesis 3, we repeated steps used for hypothesis 2, but with discrete change in high-arousal NA, moderate-arousal NA, NA, and PA, as separate outcome variables. For these models, handgun group, mood state at t, and the interaction of handgun group with mood state at time t were entered as predictor variables and random effects were specified for the intercept and slope. Analyses were conducted using SPSS 27 and SAS 9.4. Missingness was handled with maximum likelihood estimation. Owing to significant sex differences across groups, all analyses were repeated with sex entered as a covariate but results were unchanged in these follow-up analyses; we therefore report results obtained from unadjusted models.

To gauge statistical power for these models, we built a series of Monte Carlo studies in Mplus following a multilevel model with 3 within-person simultaneous predictors and the inclusion of all possible random effects. These models parallel the idea of adding group membership, current negative mood, and a group*current mood interaction as predictor terms. We based our model on an intraclass correlation (ICC) of 0.5 with various predictors accounting for an additional 0.1 in the ICC for estimation of the various random effects. We also assumed a “worst-case scenario” of 50% missing data. Under these conservative conditions, power exceeded 94% to detect small effect sizes.

Results

Sample characteristics are summarized in Table 1. The sex distribution across groups significantly differed (X2(2)=7.0, p=.030): 68.6% of carry handgun owners, 55.3% of no-carry handgun owners, and 40.3% of non-owners were male. Groups did not significantly differ with respect to race, ethnicity, or age, however. The mean number of firearms kept in participants’ homes also significantly differed across groups: handguns and pistols (F(2,134)=23.3, p<.001), shotguns (F(2,134)=9.8, p<001), and rifles (F(2,134)=9.4, p<.001). Carry handgun owners reported having the most firearms at home whereas non-owners reported the fewest (see Table 1). Carry handgun owners also reported carrying a handgun or pistol when outside their homes a mean of 71.8% (SD=28.9%) of the time.

Table 1.

Sample demographics (N=144)

Not Handgun Owner (n=62) Handgun Owner
Variable Carry (n=35) No Carry (n=47) X2 F p
Biological sex, n (%) 7.4 -- .024
   Male 25 (40.3)a 24 (68.6)a 26 (55.3)
   Female 36 (59.7)a 11 (31.4)a 21 (44.7)
Race, n (%) 7.3 -- .505
   White 44 (73.3) 23 (65.7) 39 (83.0)
   Black 8 (13.3) 8 (22.9) 4 (8.5)
   Asian 5 (8.3) 2 (5.7) 2 (4.3)
   Native American 0 (0) 0 (0) 1 (2.1)
   Multiracial 3 (5.0) 2 (5.7) 1 (2.1)
Ethnicity, n (%) 1.0 -- .606
   Hispanic / Latino 6 (9.8) 3 (8.6) 7 (14.9)
Age, M (SD) 36.9 (15.0) 35.4 (9.9) 36.2 (13.1) -- 0.2 .850
No. of firearms in home, M (SD)
   Handguns and pistols 0.2 (0.7)ab 4.8 (5.0)ac 2.5 (3.3)bc -- 23.3 <.001
   Shotguns 0.2 (0.6)ab 1.3 (1.6)a 0.9 (1.5)b -- 9.8 <.001
   Rifles 0.2 (0.5)a 2.5 (4.5)ab 1.1 (1.8)b -- 9.4 <.001
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Note: Within each row, values that share a subscript letter significantly differ at p<.05.

Threat perceptions

Mean PTCI scores significantly differed across groups (Wald X2(2)=8.8, p=.012; Figure 1). Carry handgun owners had significantly higher PTCI scores than no-carry handgun owners (Mdiff=2.0, 95% CI=0.8-2.0, d=0.45, p=.001) and non-owners (Mdiff=1.8, 95% CI=0.6-2.9, d=0.42, p=.003). There was no difference between no-carry handgun owners and non-owners (Mdiff=0.2, 95% CI=−0.8-1.2, d=0.06, p=.700).

Figure 1.

Figure 1

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Mean threat perception scores with 95% confidence intervals (top) and violin plots (bottom) across groups. Threat perception was assessed using the PTCI-9 negative cognitions of the world subscale. The grey squares adjacent to the violin plots designates the group mean.

Momentary affective state

There were no significant differences across groups in mean momentary high-arousal NA (F(1,138)=0.5, p=.596), mean momentary moderate-arousal NA (F(1,138)=0.6, p=.560), mean momentary PA (F(1,138)=0.9, p=.429), or mean momentary NA (F(1,138)=0.6, p=.566). The overall mean momentary mood scores were MNA-high=7.2 (95% CI=6.9-7.5), MNA-mod=5.2 (95% CI=5.0-5.5), MPA=25.3 (95% CI=23.9-26.7), and MNA=12.4 (95% CI=11.8-12.9).

Mood stability

High-arousal NA stability (F(2,150)=3.7, p=.026) but not moderate-arousal NA stability (F(2,142)=1.2, p=.310) significantly differed across groups. As compared to carry handgun owners, high-arousal NA stability was significantly stronger among non-owners (B=−0.08, SE=0.04, p=.023) and no-carry handgun owners (B=−0.09, SE=0.04, p=.018; Table 2 and Figure 2). NA stability but not PA stability significantly differed across groups (PA stability: F(2,131)=2.4, p=.097; NA stability: F(2,148)=3.9, p=.025). As compared to carry handgun owners, NA stability was significantly stronger among non-owners (B=−0.10, SE=0.04, p=.008) and no-carry handgun owners (B=−0.07, SE=0.04, p=.050; Table 2).

Table 2.

Results of multilevel models predicting stability in momentary NA, high-arousal NA, and moderate-arousal NA

ΔNA
 ΔNAHigh
 ΔNAMod
Predictor B (SE) P B (SE) P B (SE) P
Intercept 7.40 (0.34) <.001 4.53 (0.20) <.001 3.50 (0.15) <.001
NA −0.61 (0.03) <.001 −0.64 (0.03) <.001 −0.69 (0.20) <.001
Handgun group
 Carry (Reference) -- -- -- -- -- --
 No Carry 0.98 (0.43) .026 0.49 (0.26) .063 0.20 (0.19) .315
 Non-Owner 1.04 (0.46) .025 0.77 (0.28) .007 0.16 (0.20) .433
Handgun owner * NA
 Carry (Reference) -- -- -- -- -- --
 No Carry −0.10 (0.04) .008 −0.08 (0.04) .023 −0.06 (0.04) .120
 Non-Owner −0.07 (0.04) .050 −0.09 (0.04) .018 −0.03 (0.04) .495
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Figure 2.

Figure 2

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Violin plots of stability parameters for high-arousal negative affect across groups. Stability is stronger (i.e., greater resistance to change) when coefficients are more negative in value. Grey squares represent group means.

Discussion

Previous research indicates firearm ownership and carrying are associated with elevated threat uncertainty and diffuse anxiety (Anestis & Bryan, 2021; Bryan, Bryan, et al., 2020; Oliphant et al., 2019; Stroebe et al., 2017), but little is known about how this cognitive-affective state manifests in firearm owners’ natural environments. As expected, carry handgun owners reported significantly higher threat perceptions than non-owners and non-carry handgun owners (hypothesis 1). This pattern supports the perspective that handgun carrying, which is often motivated by the desire to feel safe in a world perceived as dangerous, may paradoxically sustain or even exacerbate threat uncertainty by reinforcing the belief that the world is dangerous (e.g., If I carry a weapon then the world must be dangerous) (Buttrick, 2020).

Our EMA results further indicated that average mood levels did not differ across handgun owners and non-owners, thereby failing to support hypothesis 2. The stability of high-arousal NA was significantly reduced among carry handgun owners as compared to both no-carry handgun owners and non-owners, however, supporting hypothesis 3. A similar pattern was observed for overall NA although the absence of group differences for moderate-arousal NA suggests the effect for overall NA is likely specific to high-arousal NA. From a dynamical systems perspective, reduced stability in high-arousal NA implies greater vulnerability to change in response to external forces (i.e., increased reactivity) and slower return to the typical change pattern (i.e., slower recovery). Taken together, these patterns indicate that although carry handgun owners are no more anxious or fearful on average than no-carry handgun owners and non-owners, carry handgun owners are more likely to experience shifts in anxiety and fear and take longer to return to baseline. This pattern aligns with research finding enhanced reactivity among people with increased sensitivity to threat uncertainty (Grupe & Nitschke, 2013; Roxburgh et al., 2019; Xia et al., 2017), implicating a possible mechanism underlying previous findings that firearm carrying increases the likelihood of misperceiving threats in the environment (Taylor & Witt, 2014; Witt & Brockmole, 2012) and engaging in reactive behaviors like aggression and suicide (Baiden et al., 2019; Dempsey et al., 2019; Oliphant et al., 2019; Taylor et al., 2017). Although previous research and conceptual work suggests handgun carrying is an antecedent of reduced mood stability (Buttrick, 2020; Taylor et al., 2017), our study design is unable to reveal the direction of effects. It is possible, for instance, that firearm carrying reduces stability in high-arousal NA but it is also possible that reduced stability in high-arousal NA precedes the decision to begin carrying firearms. Additional research using measurement burst designs (Ram et al., 2014), wherein EMA is conducted before and after someone acquires a firearm, is warranted to further test these associations.

Overall, our results suggest firearm owners who carry handguns report exaggerated threat perceptions and display reduced stability in high-arousal NA, two components of anticipatory anxiety (Grupe & Nitschke, 2013). From this lens, firearm carrying may function as a safety behavior enacted to prevent feared outcomes that are unlikely to happen (e.g., physical assault) that instead paradoxically maintains or even exacerbates anxious responding (Helbig-Lang & Petermann, 2010). Firearm carrying may therefore contribute to chronic anxiety, which has been shown to increase suicide risk (Bryan, Bryan, et al., 2020; Petrey et al., 2019), possibly by degrading cognitive control and the ability to activate regulatory neural processes (Gorka et al., 2018). Scalable strategies that reduce sensitivity to stressful situations and/or increase tolerance of uncertainty could mitigate these vulnerabilities. Low-intensity (<1 hour) psychoeducation programs focused on teaching coping strategies for improving tolerance of uncertainty, for example, have been shown to significantly reduce anxiety (Shapiro et al., 2023). Disseminating these programs within the firearm community could potentially reduce threat perceptions and reactivity in this population.

Clinically, our results implicate the potential value of integrating these strategies into evidence-based treatments with firearm owners diagnosed with anxiety-related disorders. Several core components of these interventions include cognitive reappraisal skills training to identify and modify uncertainty-related beliefs that sustain anxiety and education about how certain behaviors engaged in to gain a sense of certainty (e.g., carrying firearms) may paradoxically serve to increase or sustain anxiety. Building tolerance for uncertainty may also be useful when working with firearm-owning patients with elevated suicide risk. A recommended strategy for working with suicidal patients is lethal means counseling, a clinical intervention designed to encourage patients to reduce or limit their access to potentially lethal suicide attempt methods like firearms (Anestis et al., 2021; Britton et al., 2016; Bryan et al., 2011). Interventions that reduce patient anxiety and fear of uncertainty may increase their willingness to enact these measures (e.g., storing firearms unloaded and locked up), which could reduce their risk for suicide (Shenassa et al., 2004).

Conclusions based on this study should be made cautiously, however, considering several limitations. First, this study included a relatively small sample of participants who predominantly lived in urban or suburban areas. Because patterns of firearm ownership correlate with level of urbanicity (Bryan et al., 2022), the present results may not extend to firearm owners in rural areas. Regional and state differences in firearm attitudes and laws may further limit generalizability of our findings. Second, our carry handgun group had a larger percentage of male participants than our other groups, especially the non-owner group. Although this sex imbalance matches national trends in firearm ownership (Parker et al., 2020), it may nonetheless have influenced outcomes. Third, we did not assess whether firearm carrying occurred within the context of occupational duties (e.g., law enforcement, military). Threat perceptions and corresponding affective states may vary as a function of firearm training, threat vigilance training, and firearm exposure level.

Despite these limitations, the present study provides novel information about psychological processes among handgun owners as they occur in daily life. Our results suggest adults who carry handguns report elevated threat perceptions, demonstrate greater reactivity in high-arousal NA like anxiety and fear, and take longer to recover after experiencing momentary increases in these mood states.

Highlights.

  • Little is known about firearm owners’ affective states in natural environments

  • Ecological momentary assessment was used to repeatedly assess affective state

  • Firearm owners who carry handguns reported elevated threat perceptions

  • Stability in anxiety and fear was reduced among firearm owners who carry handguns

Funding/Support

Research reported in this publication was supported in part by the National Institute of Mental Health of the National Institutes of Health under Award Number R61MH125759. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The study sponsor had no role in the design or conduct of the study; the collection, management, analysis, and interpretation of the data; the preparation, review, or approval of the manuscript; or the decision to submit the manuscript for publication.

Declaration of Competing Interest

Dr. C.J. Bryan reported grants from the Department of Defense, the National Institute of Mental Health, the New Jersey Gun Violence Research Center, the Bob Woodruff Foundation, the USAA Foundation, the Boeing Company, and the American Foundation for Suicide Prevention during the conduct of the study; personal fees from Oui Therapeutics outside the submitted work; and ownership of Anduril, LLC, outside the submitted work. Dr. S.M. Gorka reported grants from the National Institute of Mental Health and the National Institute on Alcohol Abuse and Alcoholism during the conduct of this study. Dr. Tabares reported grants from the New Jersey Gun Violence Research Center and the National Institute of Mental Health during the conduct of the study. Dr. Butner reported grant funding from the National Institute of Mental Health during the conduct of the study. Dr. Coccaro reported grant funding from the National Institute of Mental Health during the conduct of the study.

Footnotes

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1

Dynamical systems theory is a branch of mathematics used to describe the behavior of phenomena that change (Butner et al., 2015).

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