Occupational stress and coping mechanisms in crime scene personnel

Occupational stress and coping mechanisms in crime scene personnel Abstract Background Studies on occupational stress have shown that police officers (POs) are vulnerable to the effects of stress, demonstrated by increased risk of cardiometabolic diseases, which may be exacerbated by the use of maladaptive coping techniques. Although there is an abundance of research pertaining to stress in POs, little research has been done to assess a subset of law enforcement, crime scene personnel (CSP). Aims To assess the stress levels, anxiety levels and coping mechanisms of CSP across the state of Texas. Methods The Perceived Stress Scale (PSS), Police Stress Questionnaire (PSQ), and the Distress Thermometer were used to measure stress levels, the State-Trait Anxiety Inventory (STAI) was utilized to measure anxiety, and the Brief COPE questionnaire was used to measure coping mechanisms. Results CSP (N = 76) surveyed reported both low stress and low anxiety for all measures used, with males reporting slightly higher stress and anxiety than females. Differences in coping mechanisms used by CSP were observed between males and females, but not between sworn officers and civilian workers. Female CSP used emotional support (P < 0.01), instrumental support (P < 0.05) and positive reframing (P < 0.05) as a coping mechanism significantly more often than males. Conclusions The results suggest that adaptive coping mechanisms should be emphasized by those supervising CSP. With little research available on CSP, further evaluation of the type of stressors experienced by these members of law enforcement is warranted. Anxiety, law enforcement, work place stress Introduction Policing has been widely studied for occupational stress and post-traumatic stress disorder with the results suggesting it is a high-stress career [1,2]. The resultant stress on police officers (POs) due to the daily activities of policing is otherwise known as ‘police stress’ [3]. Career-related factors, such as work environment and bureaucratic structure, social and familial factors, including the availability of peer, familial and social support, and the types of coping mechanisms available to POs may impact on police stress [4]. The type and amount of stress and anxiety influencing police stress can affect the individual physically and mentally, the organization which they work for, their peers, family, friends and the community as a whole [3,5]. Biological changes may occur when a stressor arises or when an individual feels anxiety, including increased heart and respiration rates, changes in brain activity and alterations in hormone secretion [6–8]. When these biological changes occur over an extended period of time, individuals may experience gastrointestinal, cardiovascular and reproductive system diseases [9,10]. The impact of these stressors may also lead to burnout [11,12] resulting in distracted and unfocused officers, higher rates of work-related accidents, absenteeism and early retirement [1,13]. Previous research has demonstrated the importance of coping mechanisms in managing stressors [14,15]. Within the police community maladaptive coping and exposure to dangerous incidents are critical risk factors associated with officers’ perceived work stress [16]. Further research has shown that individuals involved in highly stressful careers have an increased risk of work stress-related health problems, especially if they rely on risky health behaviours to cope with stress [5,16]. Although there is an abundance of research about stress in POs, little research has been done to assess crime scene personnel (CSP). CSP, commonly known as crime scene investigators (CSIs), deal with the documentation, collection, preservation and analysis of evidence present at crime scenes. Due to the nature of their work, CSP encounter violent death more frequently than an average PO [17]. This may result in CSP experiencing more stress than the typical PO [16], and potentially resorting to maladaptive coping strategies to deal with stress [5,16]. The aim of this study was to assess the stress and anxiety levels and coping mechanisms of CSP employed by police departments in the state of Texas. A secondary objective was to determine the use of employee assistance programmes (EAPs) by CSP. Methods A total of 276 municipal police departments within the state of Texas were contacted for permission to recruit participants over a 3-month period from late winter until early spring. Currently, there is no state licensing in Texas required for CSP; therefore, researchers estimated one CSI per department. Municipal police departments in Texas were initially contacted by phone to acquire the contact information of the supervisors and administrators (i.e. police chief) of CSP during January and February of 2016. One hundred and thirty-two supervisors and administrators from 276 police departments were then contacted via email to inform them of the study and to ask them to distribute a self-administered online questionnaire created using Qualtrics software (2016) to their CSP. The email contained the study description and instructions for both the supervisors and administrators, and the CSP. Participation was voluntary and confidential. Participants were excluded if they did not meet at least five of the six criteria for the job description provided. The CSP job description included (i) the utilization of scene documentation methods such as photography, videography, sketching and note-taking; (ii) the collection and preservation of physical and/or biological evidence; (iii) the maintenance of chain of custody and evidence integrity; (iv) the processing of evidence; (v) report writing; and (vi) testifying at judicial proceedings. All procedures were approved by the University Institutional Review Board and participants provided informed consent during the completion of the online survey. The online questionnaire had an introductory page containing the project description and participant consent. Demographic information (age, sex, race, marital status, education level) was collected, along with job details (county employed in, years of experience, job description, position type [sworn officer (SO) or civilian worker (CW)]) and information regarding the availability of, encouragement for the use of and the actual usage of formal EAPs (which include counsellors, psychiatrists and psychologists). Finally, participants were asked to report measures of stress, anxiety and coping mechanisms. In order to measure stress levels, the Perceived Stress Scale (PSS), Police Stress Questionnaire (PSQ), and the Distress Thermometer were used. The State-Trait Anxiety Inventory (STAI) was utilized to measure anxiety levels, and the Brief COPE questionnaire was used to measure coping mechanisms amongst participants. The PSS is a 5-point Likert scale ranging from 0 (never) to 4 (very often) used to evaluate feelings and thoughts during the previous month (i.e. ‘In the last month, how often have you felt nervous or “stressed”?’) [18]. Scores can range from 0 to 40 and a higher score correlates with higher perceived stress. A score of 0–13 equates to low or average stress, a score of 14–26 equates to moderate stress and a score of 27–40 equates to high stress. The PSQ has two individual 7-point scales, each containing 20 questions, used to measure the level of stress caused by different aspects of the job over the last 6 months [19]. The PSQ is divided into the Organizational Police Stress Questionnaire (PSQ-Org) which assesses issues in dealing with supervisors and inadequate equipment, whereas the Operational Police Stress Questionnaire (PSQ-Op), evaluates factors including paperwork, fatigue and shift work. The Distress Thermometer is a visual analogue scale ranging from 0 to 10 (not distressed to extremely distressed) that measures the amount of distress in the past week [20]. The STAI contains two individual scales, each containing 20 questions, used to measure anxiety [21]. The first scale assesses how an individual feels right now (state anxiety) (i.e. ‘I feel calm.’), whereas the second scale assesses how an individual generally feels (trait anxiety) (i.e. ‘I feel pleasant.’). The level of severity ranges from mild (40–50), moderate (51–60), to severe (>60). The Brief COPE questionnaire has 28 questions that are used to assess the way an individual has been and is coping with stressors in their life (i.e. I pray or meditate) [22]; the questionnaire is measured on a 4-point scale ranging from 1 (I don’t do this at all) to 4 (I do this a lot). A high composite score for a coping strategy would imply that the strategy is used more often. The questionnaire measures 14 different coping strategies including denial, substance abuse, humour and venting. Statistical analyses were performed using the Statistical Package for the Social Sciences (SPSS, v 22). Descriptive statistics (frequencies and descriptives) were calculated for all test variables for the entire sample. The sample was then divided into subgroups to make comparisons between sex and job position to focus analysis on occupational stress rather than general stress. ANOVAs were conducted between the subgroups (e.g. male and female or sworn and civilian) on the same dependent variables. Significance of <0.05 was considered statistically significant. Correlations were calculated to analyse the relationships between perceived stress, organizational and operational stress, anxiety and distress among the entire sample and within each of the subgroups. Correlations between perceived stress (Distress Thermometer and PSS) and coping strategies were also calculated. Linear regression was used to determine the relationships between perceived stress (dependent variable) and age, sex, education and coping strategies as independent variables. Other factors, such as years of experience and marital status, were not used due to the lack of data and homogeneity of sample. Results Eighty-four individuals responded to the survey across 34 Texas counties. Eight responses were excluded; seven for lack of information and one for not meeting the job description criteria. A total of 76 participants were used in the statistical analyses. Demographics for the participants are shown in Table 1. The sample consisted largely of Caucasian (84%) males (68%), age range 35–54 (66%). The sample consisted of both SOs (67%) and CWs (33%). Of the SOs, 92% were male and 8% were female. Of the CWs, 17% were male and 83% were female. The entire population had an average of 12.75 years of experience with SOs (mean ± SD = 14.4 ± 9.5 years) having more years of experience than CWs (9.5 ± 6.6 years). Seventy-eight per cent of SOs knew of EAPs provided at their respective departments and of those, 88% were encouraged to use the services. Eighty-eight per cent of CWs knew of the services and, 86% of these were encouraged to use the services. Of the SOs and the CWs, 23% and 10%, respectively, acknowledged that they had used these services. Table 1. Participant’s information for gender, age, race, education, marital status and years of experience Demographics Entire sample (N = 76) SOs (n = 51) CWs (n = 25) Gender, n (%)  Male 51 (68) 47 (92) 4 (17)  Female 24 (32) 4 (8) 20 (83) Age, n (age range %)  25–34 years 13 (17) 8 (16) 5 (20)  35–44 years 26 (34) 14 (27) 12 (48)  45–54 years 24 (32) 19 (37) 5 (20)  55–64 years 12 (16) 9 (18) 3 (12)  65+ years 1 (1) 1 (2) 0 (0) Race, n (%)  White or Caucasian 64 (84) 42 (82) 22 (88)  Hispanic or Latin 5 (7) 4 (8) 1 (4)  Black or African American 4 (5) 2 (4) 2 (8)  Native American or American Indian 1 (1) 1 (2) 0 (0)  Other 2 (3) 2 (4) 0 (0) Education, n (%)  High school or equivalent 5 (7) 5 (10) 0 (0)  Some college 22 (29) 18 (35) 4 (16)  Associates/technical degree 11 (14) 5 (10) 6 (24)  Bachelor’s degree 25 (33) 16 (31) 9 (36)  Master’s degree 12 (16) 6 (12) 6 (24)  Other 1 (1) 1 (2) 0 (0) Marital status, n (%)  Single 4 (5) 2 (4) 2 (8)  Married 41 (54) 28 (55) 13 (52)  Separated 2 (3) 2 (4) 0 (0)  Divorced 7 (9) 2 (4) 5 (20)  Living with another 13 (17) 10 (20) 3 (12)  Did not answer 9 (12) 7 (14) 2 (8) Years of experience (mean ± SD) 12.8 ± 8.9 14.4 ± 9.5 9.5 ± 6.6 Demographics Entire sample (N = 76) SOs (n = 51) CWs (n = 25) Gender, n (%)  Male 51 (68) 47 (92) 4 (17)  Female 24 (32) 4 (8) 20 (83) Age, n (age range %)  25–34 years 13 (17) 8 (16) 5 (20)  35–44 years 26 (34) 14 (27) 12 (48)  45–54 years 24 (32) 19 (37) 5 (20)  55–64 years 12 (16) 9 (18) 3 (12)  65+ years 1 (1) 1 (2) 0 (0) Race, n (%)  White or Caucasian 64 (84) 42 (82) 22 (88)  Hispanic or Latin 5 (7) 4 (8) 1 (4)  Black or African American 4 (5) 2 (4) 2 (8)  Native American or American Indian 1 (1) 1 (2) 0 (0)  Other 2 (3) 2 (4) 0 (0) Education, n (%)  High school or equivalent 5 (7) 5 (10) 0 (0)  Some college 22 (29) 18 (35) 4 (16)  Associates/technical degree 11 (14) 5 (10) 6 (24)  Bachelor’s degree 25 (33) 16 (31) 9 (36)  Master’s degree 12 (16) 6 (12) 6 (24)  Other 1 (1) 1 (2) 0 (0) Marital status, n (%)  Single 4 (5) 2 (4) 2 (8)  Married 41 (54) 28 (55) 13 (52)  Separated 2 (3) 2 (4) 0 (0)  Divorced 7 (9) 2 (4) 5 (20)  Living with another 13 (17) 10 (20) 3 (12)  Did not answer 9 (12) 7 (14) 2 (8) Years of experience (mean ± SD) 12.8 ± 8.9 14.4 ± 9.5 9.5 ± 6.6 View Large Table 1. Participant’s information for gender, age, race, education, marital status and years of experience Demographics Entire sample (N = 76) SOs (n = 51) CWs (n = 25) Gender, n (%)  Male 51 (68) 47 (92) 4 (17)  Female 24 (32) 4 (8) 20 (83) Age, n (age range %)  25–34 years 13 (17) 8 (16) 5 (20)  35–44 years 26 (34) 14 (27) 12 (48)  45–54 years 24 (32) 19 (37) 5 (20)  55–64 years 12 (16) 9 (18) 3 (12)  65+ years 1 (1) 1 (2) 0 (0) Race, n (%)  White or Caucasian 64 (84) 42 (82) 22 (88)  Hispanic or Latin 5 (7) 4 (8) 1 (4)  Black or African American 4 (5) 2 (4) 2 (8)  Native American or American Indian 1 (1) 1 (2) 0 (0)  Other 2 (3) 2 (4) 0 (0) Education, n (%)  High school or equivalent 5 (7) 5 (10) 0 (0)  Some college 22 (29) 18 (35) 4 (16)  Associates/technical degree 11 (14) 5 (10) 6 (24)  Bachelor’s degree 25 (33) 16 (31) 9 (36)  Master’s degree 12 (16) 6 (12) 6 (24)  Other 1 (1) 1 (2) 0 (0) Marital status, n (%)  Single 4 (5) 2 (4) 2 (8)  Married 41 (54) 28 (55) 13 (52)  Separated 2 (3) 2 (4) 0 (0)  Divorced 7 (9) 2 (4) 5 (20)  Living with another 13 (17) 10 (20) 3 (12)  Did not answer 9 (12) 7 (14) 2 (8) Years of experience (mean ± SD) 12.8 ± 8.9 14.4 ± 9.5 9.5 ± 6.6 Demographics Entire sample (N = 76) SOs (n = 51) CWs (n = 25) Gender, n (%)  Male 51 (68) 47 (92) 4 (17)  Female 24 (32) 4 (8) 20 (83) Age, n (age range %)  25–34 years 13 (17) 8 (16) 5 (20)  35–44 years 26 (34) 14 (27) 12 (48)  45–54 years 24 (32) 19 (37) 5 (20)  55–64 years 12 (16) 9 (18) 3 (12)  65+ years 1 (1) 1 (2) 0 (0) Race, n (%)  White or Caucasian 64 (84) 42 (82) 22 (88)  Hispanic or Latin 5 (7) 4 (8) 1 (4)  Black or African American 4 (5) 2 (4) 2 (8)  Native American or American Indian 1 (1) 1 (2) 0 (0)  Other 2 (3) 2 (4) 0 (0) Education, n (%)  High school or equivalent 5 (7) 5 (10) 0 (0)  Some college 22 (29) 18 (35) 4 (16)  Associates/technical degree 11 (14) 5 (10) 6 (24)  Bachelor’s degree 25 (33) 16 (31) 9 (36)  Master’s degree 12 (16) 6 (12) 6 (24)  Other 1 (1) 1 (2) 0 (0) Marital status, n (%)  Single 4 (5) 2 (4) 2 (8)  Married 41 (54) 28 (55) 13 (52)  Separated 2 (3) 2 (4) 0 (0)  Divorced 7 (9) 2 (4) 5 (20)  Living with another 13 (17) 10 (20) 3 (12)  Did not answer 9 (12) 7 (14) 2 (8) Years of experience (mean ± SD) 12.8 ± 8.9 14.4 ± 9.5 9.5 ± 6.6 View Large The sample’s overall PSS score corresponded to low or average stress over the past month (11.0 ± 6.93). Participants’ scores ranged from 0 to 32. Both the overall PSQ-Org score (3.09 ± 1.12) and PSQ-Op score (2.98 ± 1.14) demonstrate low stress over the last 6 months. The overall scores for both the state (33.6 ± 10.5) and trait (33.2 ± 9.27) levels also demonstrated low levels of state and trait anxiety. The Distress Thermometer score for the sample also showed participants reported relatively low distress (3.54 ± 2.37). Specific differences are detailed in Table 2. Table 2. Stress and anxiety scores for all measures used for the entire sample and subgroups Entire sample Gender Position type Male (N = 76)Mean ± SD Male (n = 51) Mean ± SD Female (n = 24) Mean ± SD SOs (n = 51) Mean ± SD CWs (n = 25) Mean ± SD PSS 11.0 ± 6.93 11.3 ± 7.31 10.5 ± 6.24 11.3 ± 7.33 10.7 ± 6.18 PSQ-organizational 3.09 ± 1.12 3.18 ± 1.15 2.99 ± 1.02 3.21 ± 1.13 2.86 ± 1.08 PSQ-operational 2.98 ± 1.14 3.06 ± 1.18 2.90 ± 1.03 3.06 ± 1.13 2.81 ± 1.18 State anxiety 33.6 ± 10.5 34.4 ± 10.4 31.7 ± 10.7 34.2 ± 9.95 32.5 ± 11.6 Trait anxiety 33.2 ± 9.27 33.7 ± 9.71 32.1 ± 8.60 33.5 ± 9.63 32.6 ± 8.69 Distress Thermometer 3.54 ± 2.37 3.60 ± 2.40 3.26 ± 2.25 3.60 ± 2.32 3.42 ± 2.50 Entire sample Gender Position type Male (N = 76)Mean ± SD Male (n = 51) Mean ± SD Female (n = 24) Mean ± SD SOs (n = 51) Mean ± SD CWs (n = 25) Mean ± SD PSS 11.0 ± 6.93 11.3 ± 7.31 10.5 ± 6.24 11.3 ± 7.33 10.7 ± 6.18 PSQ-organizational 3.09 ± 1.12 3.18 ± 1.15 2.99 ± 1.02 3.21 ± 1.13 2.86 ± 1.08 PSQ-operational 2.98 ± 1.14 3.06 ± 1.18 2.90 ± 1.03 3.06 ± 1.13 2.81 ± 1.18 State anxiety 33.6 ± 10.5 34.4 ± 10.4 31.7 ± 10.7 34.2 ± 9.95 32.5 ± 11.6 Trait anxiety 33.2 ± 9.27 33.7 ± 9.71 32.1 ± 8.60 33.5 ± 9.63 32.6 ± 8.69 Distress Thermometer 3.54 ± 2.37 3.60 ± 2.40 3.26 ± 2.25 3.60 ± 2.32 3.42 ± 2.50 View Large Table 2. Stress and anxiety scores for all measures used for the entire sample and subgroups Entire sample Gender Position type Male (N = 76)Mean ± SD Male (n = 51) Mean ± SD Female (n = 24) Mean ± SD SOs (n = 51) Mean ± SD CWs (n = 25) Mean ± SD PSS 11.0 ± 6.93 11.3 ± 7.31 10.5 ± 6.24 11.3 ± 7.33 10.7 ± 6.18 PSQ-organizational 3.09 ± 1.12 3.18 ± 1.15 2.99 ± 1.02 3.21 ± 1.13 2.86 ± 1.08 PSQ-operational 2.98 ± 1.14 3.06 ± 1.18 2.90 ± 1.03 3.06 ± 1.13 2.81 ± 1.18 State anxiety 33.6 ± 10.5 34.4 ± 10.4 31.7 ± 10.7 34.2 ± 9.95 32.5 ± 11.6 Trait anxiety 33.2 ± 9.27 33.7 ± 9.71 32.1 ± 8.60 33.5 ± 9.63 32.6 ± 8.69 Distress Thermometer 3.54 ± 2.37 3.60 ± 2.40 3.26 ± 2.25 3.60 ± 2.32 3.42 ± 2.50 Entire sample Gender Position type Male (N = 76)Mean ± SD Male (n = 51) Mean ± SD Female (n = 24) Mean ± SD SOs (n = 51) Mean ± SD CWs (n = 25) Mean ± SD PSS 11.0 ± 6.93 11.3 ± 7.31 10.5 ± 6.24 11.3 ± 7.33 10.7 ± 6.18 PSQ-organizational 3.09 ± 1.12 3.18 ± 1.15 2.99 ± 1.02 3.21 ± 1.13 2.86 ± 1.08 PSQ-operational 2.98 ± 1.14 3.06 ± 1.18 2.90 ± 1.03 3.06 ± 1.13 2.81 ± 1.18 State anxiety 33.6 ± 10.5 34.4 ± 10.4 31.7 ± 10.7 34.2 ± 9.95 32.5 ± 11.6 Trait anxiety 33.2 ± 9.27 33.7 ± 9.71 32.1 ± 8.60 33.5 ± 9.63 32.6 ± 8.69 Distress Thermometer 3.54 ± 2.37 3.60 ± 2.40 3.26 ± 2.25 3.60 ± 2.32 3.42 ± 2.50 View Large Comparisons were also made between the subgroups (sex and position type) and coping strategies (Table 3). Females engaged in the use of emotional support (P < 0.01), instrumental support (P < 0.05) and positive reframing (P < 0.05) significantly more than males. When comparing position types, there were no significant differences in coping mechanisms between SOs and CWs. Because sample sizes were not large enough, further analysis between groups (e.g. male or female, SOs and male or female, CWs) was not possible. Table 3. Coping strategies adopted by subgroups Gender Position type Male (n = 51) Mean ± SD Female (n = 24) Mean ± SD SOs (n = 51) Mean ± SD CWs (n = 25) Mean ± SD Self-distraction 5.27 ± 1.44 5.13 ± 1.73 5.35 ± 1.49 5.00 ± 1.58 Active coping 6.31 ± 1.48 6.67 ± 1.27 6.33 ± 1.46 6.68 ± 1.31 Denial 2.29 ± 0.90 2.08 ± 0.28 2.29 ± 0.90 2.08 ± 0.28 Substance use 2.40 ± 0.89 2.83 ± 1.31 2.44 ± 1.01 2.72 ± 1.14 Emotional support 4.56 ± 1.29 5.50 ± 1.56** 4.73 ± 1.30 5.28 ± 1.74 Instrumental support 4.60 ± 1.33 5.38 ± 1.44* 4.79 ± 1.27 5.12 ± 1.74 Behavioral disengagement 2.46 ± 1.07 2.13 ± 0.45 2.46 ± 1.07 2.12 ± 0.44 Venting 4.08 ± 1.35 4.75 ± 1.54 4.25 ± 1.45 4.36 ± 1.44 Positive reframing 5.40 ± 1.47 6.38 ± 1.56* 5.52 ± 1.46 6.20 ± 1.71 Planning 6.33 ± 1.45 6.54 ± 1.41 6.42 ± 1.46 6.44 ± 1.42 Humour 5.48 ± 1.61 5.33 ± 1.86 5.54 ± 1.71 5.16 ± 1.62 Acceptance 6.33 ± 1.48 6.21 ± 1.56 6.29 ± 1.44 6.36 ± 1.63 Religion 5.29 ± 2.04 5.71 ± 1.85 5.50 ± 2.00 5.40 ± 2.00 Self-blame 4.08 ± 1.47 3.88 ± 1.62 4.04 ± 1.38 4.00 ± 1.76 Gender Position type Male (n = 51) Mean ± SD Female (n = 24) Mean ± SD SOs (n = 51) Mean ± SD CWs (n = 25) Mean ± SD Self-distraction 5.27 ± 1.44 5.13 ± 1.73 5.35 ± 1.49 5.00 ± 1.58 Active coping 6.31 ± 1.48 6.67 ± 1.27 6.33 ± 1.46 6.68 ± 1.31 Denial 2.29 ± 0.90 2.08 ± 0.28 2.29 ± 0.90 2.08 ± 0.28 Substance use 2.40 ± 0.89 2.83 ± 1.31 2.44 ± 1.01 2.72 ± 1.14 Emotional support 4.56 ± 1.29 5.50 ± 1.56** 4.73 ± 1.30 5.28 ± 1.74 Instrumental support 4.60 ± 1.33 5.38 ± 1.44* 4.79 ± 1.27 5.12 ± 1.74 Behavioral disengagement 2.46 ± 1.07 2.13 ± 0.45 2.46 ± 1.07 2.12 ± 0.44 Venting 4.08 ± 1.35 4.75 ± 1.54 4.25 ± 1.45 4.36 ± 1.44 Positive reframing 5.40 ± 1.47 6.38 ± 1.56* 5.52 ± 1.46 6.20 ± 1.71 Planning 6.33 ± 1.45 6.54 ± 1.41 6.42 ± 1.46 6.44 ± 1.42 Humour 5.48 ± 1.61 5.33 ± 1.86 5.54 ± 1.71 5.16 ± 1.62 Acceptance 6.33 ± 1.48 6.21 ± 1.56 6.29 ± 1.44 6.36 ± 1.63 Religion 5.29 ± 2.04 5.71 ± 1.85 5.50 ± 2.00 5.40 ± 2.00 Self-blame 4.08 ± 1.47 3.88 ± 1.62 4.04 ± 1.38 4.00 ± 1.76 *P < 0.05, **P < 0.01. View Large Table 3. Coping strategies adopted by subgroups Gender Position type Male (n = 51) Mean ± SD Female (n = 24) Mean ± SD SOs (n = 51) Mean ± SD CWs (n = 25) Mean ± SD Self-distraction 5.27 ± 1.44 5.13 ± 1.73 5.35 ± 1.49 5.00 ± 1.58 Active coping 6.31 ± 1.48 6.67 ± 1.27 6.33 ± 1.46 6.68 ± 1.31 Denial 2.29 ± 0.90 2.08 ± 0.28 2.29 ± 0.90 2.08 ± 0.28 Substance use 2.40 ± 0.89 2.83 ± 1.31 2.44 ± 1.01 2.72 ± 1.14 Emotional support 4.56 ± 1.29 5.50 ± 1.56** 4.73 ± 1.30 5.28 ± 1.74 Instrumental support 4.60 ± 1.33 5.38 ± 1.44* 4.79 ± 1.27 5.12 ± 1.74 Behavioral disengagement 2.46 ± 1.07 2.13 ± 0.45 2.46 ± 1.07 2.12 ± 0.44 Venting 4.08 ± 1.35 4.75 ± 1.54 4.25 ± 1.45 4.36 ± 1.44 Positive reframing 5.40 ± 1.47 6.38 ± 1.56* 5.52 ± 1.46 6.20 ± 1.71 Planning 6.33 ± 1.45 6.54 ± 1.41 6.42 ± 1.46 6.44 ± 1.42 Humour 5.48 ± 1.61 5.33 ± 1.86 5.54 ± 1.71 5.16 ± 1.62 Acceptance 6.33 ± 1.48 6.21 ± 1.56 6.29 ± 1.44 6.36 ± 1.63 Religion 5.29 ± 2.04 5.71 ± 1.85 5.50 ± 2.00 5.40 ± 2.00 Self-blame 4.08 ± 1.47 3.88 ± 1.62 4.04 ± 1.38 4.00 ± 1.76 Gender Position type Male (n = 51) Mean ± SD Female (n = 24) Mean ± SD SOs (n = 51) Mean ± SD CWs (n = 25) Mean ± SD Self-distraction 5.27 ± 1.44 5.13 ± 1.73 5.35 ± 1.49 5.00 ± 1.58 Active coping 6.31 ± 1.48 6.67 ± 1.27 6.33 ± 1.46 6.68 ± 1.31 Denial 2.29 ± 0.90 2.08 ± 0.28 2.29 ± 0.90 2.08 ± 0.28 Substance use 2.40 ± 0.89 2.83 ± 1.31 2.44 ± 1.01 2.72 ± 1.14 Emotional support 4.56 ± 1.29 5.50 ± 1.56** 4.73 ± 1.30 5.28 ± 1.74 Instrumental support 4.60 ± 1.33 5.38 ± 1.44* 4.79 ± 1.27 5.12 ± 1.74 Behavioral disengagement 2.46 ± 1.07 2.13 ± 0.45 2.46 ± 1.07 2.12 ± 0.44 Venting 4.08 ± 1.35 4.75 ± 1.54 4.25 ± 1.45 4.36 ± 1.44 Positive reframing 5.40 ± 1.47 6.38 ± 1.56* 5.52 ± 1.46 6.20 ± 1.71 Planning 6.33 ± 1.45 6.54 ± 1.41 6.42 ± 1.46 6.44 ± 1.42 Humour 5.48 ± 1.61 5.33 ± 1.86 5.54 ± 1.71 5.16 ± 1.62 Acceptance 6.33 ± 1.48 6.21 ± 1.56 6.29 ± 1.44 6.36 ± 1.63 Religion 5.29 ± 2.04 5.71 ± 1.85 5.50 ± 2.00 5.40 ± 2.00 Self-blame 4.08 ± 1.47 3.88 ± 1.62 4.04 ± 1.38 4.00 ± 1.76 *P < 0.05, **P < 0.01. View Large Correlations for the entire sample and each subgroup were calculated to analyse the relationship between PSS, PSQ-Org, PSQ-Op, state anxiety and trait anxiety, and the Distress Thermometer (Table 4). Significant positive correlations were observed in all cases except between the PSQ-Org and Distress Thermometer in the CW subgroup. The correlations between perceived stress and coping mechanisms were also observed. The Distress Thermometer score and the PSS score were used to determine short-term and long-term coping mechanisms. Both the sample as a whole and the male subgroup showed a correlation between the Distress Thermometer and active coping, substance use and behavioural disengagement. SOs were similar to the male subgroup in that correlations were found between the Distress Thermometer and substance use and behavioural disengagement. When comparing coping mechanisms to long-term stress, the sample as a whole displayed correlations between PSS and active coping (r = −0.409, P < 0.001), behavioural disengagement (r = 0.522, P < 0.001), positive reframing (r = −0.428, P < 0.001), planning (r = −0.298, P = 0.010), acceptance (r = −0.235, P < 0.05) and self-blame (r = 0.273, P < 0.05). Planning (female: r = −0.616, P = 0.001; civilian: r = −0.535, P < 0.01) and self-distraction (female: r = 0.458, P < 0.05; civilian: r = 0.439, P < 0.05) were coping mechanisms that were exhibited in only the female and CW subgroups and not the male and SO subgroups. However, males and SO subgroups exhibited self-blame (male: r = 0.312, P < 0.05; sworn: r = 0.311, P < 0.05). Table 4. Correlations between stress, anxiety and coping mechanism scales Measure 1 2 3 4 5 Entire sample  1. PSS (N = 76)  2. PSQ-organizational (n = 73) 0.57**  3. PSQ-operational (n = 73) 0.56** 0.76**  4. State anxiety (n = 73) 0.79** 0.61** 0.61**  5. Trait anxiety (n = 73) 0.82** 0.62** 0.56** 0.87**  6. Distress Thermometer (n = 68) 0.75** 0.62** 0.47** 0.73** 0.69** Male  1. PSS (n = 51)  2. PSQ-organizational (n = 48) 0.62**  3. PSQ-operational (n = 48) 0.54** 0.76**  4. State anxiety (n = 48) 0.78** 0.69** 0.60**  5. Trait anxiety (n = 48) 0.81** 0.69** 0.55** 0.88**  6. Distress Thermometer (n = 44) 0.77** 0.52** 0.44** 0.68** 0.70** Female  1. PSS (n = 24)  2. PSQ-organizational (n = 24) 0.54**  3. PSQ-operational (n = 24) 0.71** 0.74**  4. State anxiety (n = 24) 0.83** 0.52** 0.71**  5. Trait anxiety (n = 24) 0.87** 0.53** 0.77** 0.84**  6. Distress Thermometer (n = 23) 0.68** 0.45* 0.75** 0.82** 0.70** SOs  1. PSS (n = 51)  2. PSQ-organizational (n = 48) 0.60**  3. PSQ-operational (n = 48) 0.53** 0.75**  4. State anxiety (n = 48) 0.79** 0.70** 0.60**  5. Trait anxiety (n = 48) 0.80** 0.68** 0.54** 0.89**  6. Distress Thermometer (n = 44) 0.77** 0.53** 0.66** 0.66** 0.68** CWs  1. PSS (n = 25)  2. PSQ-organizational (n = 25) 0.52**  3. PSQ-operational (n = 25) 0.63** 0.78**  4. State anxiety (n = 25) 0.83** 0.50* 0.62**  5. Trait anxiety (n = 25) 0.88** 0.50* 0.69** 0.86**  6. Distress Thermometer (n = 25) 0.71** 0.260 0.52* 0.82** 0.72** Measure 1 2 3 4 5 Entire sample  1. PSS (N = 76)  2. PSQ-organizational (n = 73) 0.57**  3. PSQ-operational (n = 73) 0.56** 0.76**  4. State anxiety (n = 73) 0.79** 0.61** 0.61**  5. Trait anxiety (n = 73) 0.82** 0.62** 0.56** 0.87**  6. Distress Thermometer (n = 68) 0.75** 0.62** 0.47** 0.73** 0.69** Male  1. PSS (n = 51)  2. PSQ-organizational (n = 48) 0.62**  3. PSQ-operational (n = 48) 0.54** 0.76**  4. State anxiety (n = 48) 0.78** 0.69** 0.60**  5. Trait anxiety (n = 48) 0.81** 0.69** 0.55** 0.88**  6. Distress Thermometer (n = 44) 0.77** 0.52** 0.44** 0.68** 0.70** Female  1. PSS (n = 24)  2. PSQ-organizational (n = 24) 0.54**  3. PSQ-operational (n = 24) 0.71** 0.74**  4. State anxiety (n = 24) 0.83** 0.52** 0.71**  5. Trait anxiety (n = 24) 0.87** 0.53** 0.77** 0.84**  6. Distress Thermometer (n = 23) 0.68** 0.45* 0.75** 0.82** 0.70** SOs  1. PSS (n = 51)  2. PSQ-organizational (n = 48) 0.60**  3. PSQ-operational (n = 48) 0.53** 0.75**  4. State anxiety (n = 48) 0.79** 0.70** 0.60**  5. Trait anxiety (n = 48) 0.80** 0.68** 0.54** 0.89**  6. Distress Thermometer (n = 44) 0.77** 0.53** 0.66** 0.66** 0.68** CWs  1. PSS (n = 25)  2. PSQ-organizational (n = 25) 0.52**  3. PSQ-operational (n = 25) 0.63** 0.78**  4. State anxiety (n = 25) 0.83** 0.50* 0.62**  5. Trait anxiety (n = 25) 0.88** 0.50* 0.69** 0.86**  6. Distress Thermometer (n = 25) 0.71** 0.260 0.52* 0.82** 0.72** *P < 0.05, **P < 0.01. View Large Table 4. Correlations between stress, anxiety and coping mechanism scales Measure 1 2 3 4 5 Entire sample  1. PSS (N = 76)  2. PSQ-organizational (n = 73) 0.57**  3. PSQ-operational (n = 73) 0.56** 0.76**  4. State anxiety (n = 73) 0.79** 0.61** 0.61**  5. Trait anxiety (n = 73) 0.82** 0.62** 0.56** 0.87**  6. Distress Thermometer (n = 68) 0.75** 0.62** 0.47** 0.73** 0.69** Male  1. PSS (n = 51)  2. PSQ-organizational (n = 48) 0.62**  3. PSQ-operational (n = 48) 0.54** 0.76**  4. State anxiety (n = 48) 0.78** 0.69** 0.60**  5. Trait anxiety (n = 48) 0.81** 0.69** 0.55** 0.88**  6. Distress Thermometer (n = 44) 0.77** 0.52** 0.44** 0.68** 0.70** Female  1. PSS (n = 24)  2. PSQ-organizational (n = 24) 0.54**  3. PSQ-operational (n = 24) 0.71** 0.74**  4. State anxiety (n = 24) 0.83** 0.52** 0.71**  5. Trait anxiety (n = 24) 0.87** 0.53** 0.77** 0.84**  6. Distress Thermometer (n = 23) 0.68** 0.45* 0.75** 0.82** 0.70** SOs  1. PSS (n = 51)  2. PSQ-organizational (n = 48) 0.60**  3. PSQ-operational (n = 48) 0.53** 0.75**  4. State anxiety (n = 48) 0.79** 0.70** 0.60**  5. Trait anxiety (n = 48) 0.80** 0.68** 0.54** 0.89**  6. Distress Thermometer (n = 44) 0.77** 0.53** 0.66** 0.66** 0.68** CWs  1. PSS (n = 25)  2. PSQ-organizational (n = 25) 0.52**  3. PSQ-operational (n = 25) 0.63** 0.78**  4. State anxiety (n = 25) 0.83** 0.50* 0.62**  5. Trait anxiety (n = 25) 0.88** 0.50* 0.69** 0.86**  6. Distress Thermometer (n = 25) 0.71** 0.260 0.52* 0.82** 0.72** Measure 1 2 3 4 5 Entire sample  1. PSS (N = 76)  2. PSQ-organizational (n = 73) 0.57**  3. PSQ-operational (n = 73) 0.56** 0.76**  4. State anxiety (n = 73) 0.79** 0.61** 0.61**  5. Trait anxiety (n = 73) 0.82** 0.62** 0.56** 0.87**  6. Distress Thermometer (n = 68) 0.75** 0.62** 0.47** 0.73** 0.69** Male  1. PSS (n = 51)  2. PSQ-organizational (n = 48) 0.62**  3. PSQ-operational (n = 48) 0.54** 0.76**  4. State anxiety (n = 48) 0.78** 0.69** 0.60**  5. Trait anxiety (n = 48) 0.81** 0.69** 0.55** 0.88**  6. Distress Thermometer (n = 44) 0.77** 0.52** 0.44** 0.68** 0.70** Female  1. PSS (n = 24)  2. PSQ-organizational (n = 24) 0.54**  3. PSQ-operational (n = 24) 0.71** 0.74**  4. State anxiety (n = 24) 0.83** 0.52** 0.71**  5. Trait anxiety (n = 24) 0.87** 0.53** 0.77** 0.84**  6. Distress Thermometer (n = 23) 0.68** 0.45* 0.75** 0.82** 0.70** SOs  1. PSS (n = 51)  2. PSQ-organizational (n = 48) 0.60**  3. PSQ-operational (n = 48) 0.53** 0.75**  4. State anxiety (n = 48) 0.79** 0.70** 0.60**  5. Trait anxiety (n = 48) 0.80** 0.68** 0.54** 0.89**  6. Distress Thermometer (n = 44) 0.77** 0.53** 0.66** 0.66** 0.68** CWs  1. PSS (n = 25)  2. PSQ-organizational (n = 25) 0.52**  3. PSQ-operational (n = 25) 0.63** 0.78**  4. State anxiety (n = 25) 0.83** 0.50* 0.62**  5. Trait anxiety (n = 25) 0.88** 0.50* 0.69** 0.86**  6. Distress Thermometer (n = 25) 0.71** 0.260 0.52* 0.82** 0.72** *P < 0.05, **P < 0.01. View Large Linear regression statistics between perceived stress (Distress Thermometers and PSS) and age, sex, education and coping strategies were performed (Table 5). The Distress Thermometer showed a positive correlation with substance use (P < 0.05), while the PSS was positively correlated with behavioural disengagement (P < 0.05), substance use (P < 0.01), self-blame (P < 0.01) and self-distraction (P < 0.01). The PSS was also negatively correlated with positive reframing (P < 0.001), and humour (P < 0.01). Table 5. Regression analyses of the Distress Thermometer and Perceived Stress Scale as dependent variables using the entire sample Distress Thermometer Perceived Stress Scale Unstandardized coefficients B Standard coefficients Beta Unstandardized coefficients B Standardized coefficients Beta Age −0.091 −0.039 −1.624 −0.236 Gender −0.355 −0.073 −00671 −0.046 Education 0.277 0.158 0.593 0.115 Brief COPE  Self-distraction 0.148 0.097 1.236 0.273**  Active coping −0.313 −0.182 −0.673 −0.137  Denial 0.678 0.148 0.467 0.051  Substance use 0.717 0.334* 1.594 0.244**  Emotional support −0.039 −0.024 0.296 0.062  Instrumental support −0.238 −0.140 0.067 0.014  Behavioural disengagement 0.706 0.287 1.905 0.254*  Venting 0.187 0.115 0.525 0.109  Positive reframing −0.058 −0.039 −1.745 −0.393***  Planning 0.172 0.106 0.059 0.012  Humour −0.229 −0.164 −1.241 −0.302**  Acceptance −0.148 −0.092 −0.641 −0.139  Religion 0.002 0.002 0.263 0.075  Self-blame 0.250 0.166 1.254 0.275** Adjusted R2 0.214 0.567 Distress Thermometer Perceived Stress Scale Unstandardized coefficients B Standard coefficients Beta Unstandardized coefficients B Standardized coefficients Beta Age −0.091 −0.039 −1.624 −0.236 Gender −0.355 −0.073 −00671 −0.046 Education 0.277 0.158 0.593 0.115 Brief COPE  Self-distraction 0.148 0.097 1.236 0.273**  Active coping −0.313 −0.182 −0.673 −0.137  Denial 0.678 0.148 0.467 0.051  Substance use 0.717 0.334* 1.594 0.244**  Emotional support −0.039 −0.024 0.296 0.062  Instrumental support −0.238 −0.140 0.067 0.014  Behavioural disengagement 0.706 0.287 1.905 0.254*  Venting 0.187 0.115 0.525 0.109  Positive reframing −0.058 −0.039 −1.745 −0.393***  Planning 0.172 0.106 0.059 0.012  Humour −0.229 −0.164 −1.241 −0.302**  Acceptance −0.148 −0.092 −0.641 −0.139  Religion 0.002 0.002 0.263 0.075  Self-blame 0.250 0.166 1.254 0.275** Adjusted R2 0.214 0.567 *P < 0.05, **P < 0.01, ***P < 0.001. View Large Table 5. Regression analyses of the Distress Thermometer and Perceived Stress Scale as dependent variables using the entire sample Distress Thermometer Perceived Stress Scale Unstandardized coefficients B Standard coefficients Beta Unstandardized coefficients B Standardized coefficients Beta Age −0.091 −0.039 −1.624 −0.236 Gender −0.355 −0.073 −00671 −0.046 Education 0.277 0.158 0.593 0.115 Brief COPE  Self-distraction 0.148 0.097 1.236 0.273**  Active coping −0.313 −0.182 −0.673 −0.137  Denial 0.678 0.148 0.467 0.051  Substance use 0.717 0.334* 1.594 0.244**  Emotional support −0.039 −0.024 0.296 0.062  Instrumental support −0.238 −0.140 0.067 0.014  Behavioural disengagement 0.706 0.287 1.905 0.254*  Venting 0.187 0.115 0.525 0.109  Positive reframing −0.058 −0.039 −1.745 −0.393***  Planning 0.172 0.106 0.059 0.012  Humour −0.229 −0.164 −1.241 −0.302**  Acceptance −0.148 −0.092 −0.641 −0.139  Religion 0.002 0.002 0.263 0.075  Self-blame 0.250 0.166 1.254 0.275** Adjusted R2 0.214 0.567 Distress Thermometer Perceived Stress Scale Unstandardized coefficients B Standard coefficients Beta Unstandardized coefficients B Standardized coefficients Beta Age −0.091 −0.039 −1.624 −0.236 Gender −0.355 −0.073 −00671 −0.046 Education 0.277 0.158 0.593 0.115 Brief COPE  Self-distraction 0.148 0.097 1.236 0.273**  Active coping −0.313 −0.182 −0.673 −0.137  Denial 0.678 0.148 0.467 0.051  Substance use 0.717 0.334* 1.594 0.244**  Emotional support −0.039 −0.024 0.296 0.062  Instrumental support −0.238 −0.140 0.067 0.014  Behavioural disengagement 0.706 0.287 1.905 0.254*  Venting 0.187 0.115 0.525 0.109  Positive reframing −0.058 −0.039 −1.745 −0.393***  Planning 0.172 0.106 0.059 0.012  Humour −0.229 −0.164 −1.241 −0.302**  Acceptance −0.148 −0.092 −0.641 −0.139  Religion 0.002 0.002 0.263 0.075  Self-blame 0.250 0.166 1.254 0.275** Adjusted R2 0.214 0.567 *P < 0.05, **P < 0.01, ***P < 0.001. View Large Discussion Overall, this study showed that CSP within the state of Texas reported low levels of stress and anxiety. This could be due to appropriate precautions being taken (training or self-awareness) and/or the adaptive use of coping mechanisms that reduce stress levels. While EAPs were widely available, only a small percentage of the sample had used the programmes. Given the machismo present in the police force, it is surprising that SOs used the services more than CWs. Because it was not specified when these individuals used EAPs, SOs could have used them during their early years as an officer. Thus, the stressors that caused the individual to seek help may not have been related duties as a CSI, but rather a result of PO duties earlier in their career. Also, the lack of use of EAPs could be due to the law enforcement subculture or perhaps because counsellors and psychiatrists were considered to be ‘outsiders’ who lack understanding of CSP [3]. Unlike previous research which suggests that females in law enforcement have higher levels of stress [4,20], our research showed that males had slightly higher stress and anxiety levels than females in all measures used. Because sex and gender play a role in the perception of stress, males and females are believed to have not only different views of stress, but different coping mechanisms [4]. This study demonstrates that active coping, planning and acceptance were the most commonly used coping strategies by CSP providing evidence for the idea that CSP are utilizing adaptive coping strategies. This differs from past research in which CSP exhibited higher use of avoidant coping strategies (e.g. avoidance, behavioural disengagement) than positive coping strategies (e.g. emotional support, seeking assistance) [17]. Females exhibited a significantly higher use of emotional support, instrumental support and positive reframing compared to males. This is similar to previous research which suggests that females use more emotion-focused coping mechanisms than males [12]. The need for active emotional support is also related to the environment females are in. Within a male-dominated field, females typically find comfort and support in others, especially other women who understand the stressors [4]. There were no significant differences found between SOs and civilian personnel for the coping strategies utilized. Even though these subgroups may have different initial training (e.g. the majority of male SOs go through the police academy first), the CSP training programmes seem to be preparing all individuals similarly regardless of the position type. When observing correlations between perceived stress and coping mechanisms, unique correlations were found—bearing in mind that the majority of SOs were male. Both the male and SO subgroups showed a positive correlation between the PSS and self-blame. This supports previous findings that demonstrated that male officers tend to use avoidant emotional strategies, such as self-blame and negation more frequently than task-oriented strategies [4,12]. Because males seek guidance, support or counselling less than females, there is vulnerability for increased distress and burnout [4,12]. The use of avoidant emotional strategies may be related to the training received by SOs, as well as the machismo that is common within the law enforcement profession [23]. In linear regression analysis, a positive association with self-distraction, substance use and behavioural disengagement and a negative association with reframing and humour and perceived stress (PSS) support the idea that maladaptive strategies can lead to increased stress [4,12,15]. Limitations of this study included the lack of knowledge regarding target population size. According to the Bureau of Labor and Statistics, there are ~900 out of 14000 CSP employed in the state of Texas with only a small proportion of those individuals working at local level. Once state licensing and certification of CSP becomes a requirement, an accurate target population size can be obtained. Additionally, there was a dependency on the police department to provide proper contact information and on the supervisors and administrators to distribute the surveys to CSP. This study demonstrates that CSP appear to report less occupational stress compared to other POs, and that male CSP reported slightly higher levels of stress and anxiety than their female counterparts. Overall, females reported significantly greater use of emotional support, instrumental support and positive reframing compared to males; however, there were no differences in stress and coping mechanisms between SOs and civilian CSP. With little previous research on CSP, further study is needed into perceived stress, anxiety and coping mechanisms of this unique set of law enforcement personnel. Key points Crime scene personnel appeared to experience less occupational stress than police officers. Male crime scene personnel reported slightly higher levels of stress and anxiety than females, with males also reporting significantly lower use of emotional support, instrumental support and positive reframing. There were no differences in stress and coping mechanisms regarding crime scene personnel who were sworn officers and those who were civilian workers. Competing interests None declared. References 1. Collins PA , Gibbs AC . Stress in police officers: a study of the origins, prevalence and severity of stress-related symptoms within a county police force . Occup Med (Lond) 2003 ; 53 : 256 – 264 . Google Scholar CrossRef Search ADS PubMed 2. Dabney DA , Copes H , Tewksbury R , Hawk-Tourtelot SR . A qualitative assessment of stress perceptions among members of a homicide unit . Justice Q 2013 ; 30 : 811 – 836 . Google Scholar CrossRef Search ADS 3. Sewell JD . The stress of homicide investigations . Death Stud 1994 ; 18 : 565 – 582 . Google Scholar CrossRef Search ADS 4. He N , Zhao JH , Archbold CA . Gender and police stress—the convergent and divergent impact of work environment, work-family conflict, and stress coping mechanisms of female and male police officers . Policing 2002 ; 25 : 687 – 708 . Google Scholar CrossRef Search ADS 5. Maran DA , Varetto A , Zedda M , Ieraci V . Occupational stress, anxiety and coping strategies in police officers . Occup Med (Lond) 2015 ; 65 : 466 – 473 . Google Scholar CrossRef Search ADS PubMed 6. Franke WD , Ramey SL , Shelley MC , 2nd . Relationship between cardiovascular disease morbidity, risk factors, and stress in a law enforcement cohort . J Occup Environ Med 2002 ; 44 : 1182 – 1189 . Google Scholar CrossRef Search ADS PubMed 7. Webb HE , Fabianke-Kadue EC , Kraemer RR , Kamimori GH , Castracane VD , Acevedo EO . Stress reactivity to repeated low-level challenges: a pilot study . Appl Psychophysiol Biofeedback 2011 ; 36 : 243 – 250 . Google Scholar CrossRef Search ADS PubMed 8. Yoo H , Franke WD . Stress and cardiovascular disease risk in female law enforcement officers . Int Arch Occup Environ Health 2011 ; 84 : 279 – 286 . Google Scholar CrossRef Search ADS PubMed 9. Chrousos GP . Stress and disorders of the stress system . Nat Rev Endocrinol 2009 ; 5 : 374 – 381 . Google Scholar CrossRef Search ADS PubMed 10. Kyrou I , Chrousos GP , Tsigos C . Stress, visceral obesity, and metabolic complications . Ann NY Acad Sci 2006 ; 1083 : 77 – 110 . Google Scholar CrossRef Search ADS PubMed 11. Burke RJ . Stressful events, work-family conflict, coping, psychological burnout, and well-being among police officers . Psychol Rep 1994 ; 75 : 787 – 800 . Google Scholar CrossRef Search ADS PubMed 12. Chopko BA , Schwartz RC . The relation between mindfulness and posttraumatic stress symptoms among police officers . J Loss Trauma 2013 ; 18 : 1 – 9 . Google Scholar CrossRef Search ADS 13. Kelty SF , Gordon H . No burnout at this coal-face: managing occupational stress in forensic personnel and the implications for forensic and criminal justice agencies . Psychiat Psychol Law 2015 ; 22 : 273 – 290 . Google Scholar CrossRef Search ADS 14. Seeman M , Lewis S . Powerlessness, health and mortality: a longitudinal study of older men and mature women . Soc Sci Med 1995 ; 41 : 517 – 525 . Google Scholar CrossRef Search ADS PubMed 15. Creswell JD , Welch WT , Taylor SE , Sherman DK , Gruenewald TL , Mann T . Affirmation of personal values buffers neuroendocrine and psychological stress responses . Psychol Sci 2005 ; 16 : 846 – 851 . Google Scholar CrossRef Search ADS PubMed 16. Gershon RR , Lin S , Li X . Work stress in aging police officers . J Occup Environ Med 2002 ; 44 : 160 – 167 . Google Scholar CrossRef Search ADS PubMed 17. Mrevlje TP . Coping with work-related traumatic situations among crime scene technicians . Stress Health 2016 ; 32 : 374 – 382 . Google Scholar CrossRef Search ADS PubMed 18. Cohen S , Kamarck T , Mermelstein R . A global measure of perceived stress . J Health Soc Behav 1983 ; 24 : 385 – 396 . Google Scholar CrossRef Search ADS PubMed 19. McCreary DR , Thompson MM . Development of two reliable and valid measures of stressors in policing: the operational and organizational police stress questionnaires . Int J Stress Manage 2006 ; 13 : 494 . Google Scholar CrossRef Search ADS 20. Maran DA , Varetto A , Zedda M , Franscini M . Stress among Italian male and female patrol police officers: a quali-quantitative survey . Policing 2014 ; 37 : 875 – 890 . Google Scholar CrossRef Search ADS 21. Speilberger CD , Gorsuch RL , Luschene R , Vagg PR , Jacobs GA. Manual for the State-Trait Anxiety Inventory (STAI) . Palo Alto, CA : CPP , 1983 . 22. Carver CS . You want to measure coping but your protocol’s too long: consider the brief COPE . Int J Behav Med 1997 ; 4 : 92 – 100 . Google Scholar CrossRef Search ADS PubMed 23. Paoline EA . Taking stock: toward a richer understanding of police culture . J Crim Just 2003 ; 31 : 199 – 214 . Google Scholar CrossRef Search ADS © The Author(s) 2018. Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For Permissions, please email: journals.permissions@oup.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Occupational Medicine Oxford University Press

Occupational stress and coping mechanisms in crime scene personnel

Occupational Medicine , Volume Advance Article (4) – Mar 20, 2018

Loading next page...
 
/lp/ou_press/occupational-stress-and-coping-mechanisms-in-crime-scene-personnel-GXhySGUVEW
Publisher
Oxford University Press
Copyright
© The Author(s) 2018. Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For Permissions, please email: journals.permissions@oup.com
ISSN
0962-7480
eISSN
1471-8405
D.O.I.
10.1093/occmed/kqy030
Publisher site
See Article on Publisher Site

Abstract

Abstract Background Studies on occupational stress have shown that police officers (POs) are vulnerable to the effects of stress, demonstrated by increased risk of cardiometabolic diseases, which may be exacerbated by the use of maladaptive coping techniques. Although there is an abundance of research pertaining to stress in POs, little research has been done to assess a subset of law enforcement, crime scene personnel (CSP). Aims To assess the stress levels, anxiety levels and coping mechanisms of CSP across the state of Texas. Methods The Perceived Stress Scale (PSS), Police Stress Questionnaire (PSQ), and the Distress Thermometer were used to measure stress levels, the State-Trait Anxiety Inventory (STAI) was utilized to measure anxiety, and the Brief COPE questionnaire was used to measure coping mechanisms. Results CSP (N = 76) surveyed reported both low stress and low anxiety for all measures used, with males reporting slightly higher stress and anxiety than females. Differences in coping mechanisms used by CSP were observed between males and females, but not between sworn officers and civilian workers. Female CSP used emotional support (P < 0.01), instrumental support (P < 0.05) and positive reframing (P < 0.05) as a coping mechanism significantly more often than males. Conclusions The results suggest that adaptive coping mechanisms should be emphasized by those supervising CSP. With little research available on CSP, further evaluation of the type of stressors experienced by these members of law enforcement is warranted. Anxiety, law enforcement, work place stress Introduction Policing has been widely studied for occupational stress and post-traumatic stress disorder with the results suggesting it is a high-stress career [1,2]. The resultant stress on police officers (POs) due to the daily activities of policing is otherwise known as ‘police stress’ [3]. Career-related factors, such as work environment and bureaucratic structure, social and familial factors, including the availability of peer, familial and social support, and the types of coping mechanisms available to POs may impact on police stress [4]. The type and amount of stress and anxiety influencing police stress can affect the individual physically and mentally, the organization which they work for, their peers, family, friends and the community as a whole [3,5]. Biological changes may occur when a stressor arises or when an individual feels anxiety, including increased heart and respiration rates, changes in brain activity and alterations in hormone secretion [6–8]. When these biological changes occur over an extended period of time, individuals may experience gastrointestinal, cardiovascular and reproductive system diseases [9,10]. The impact of these stressors may also lead to burnout [11,12] resulting in distracted and unfocused officers, higher rates of work-related accidents, absenteeism and early retirement [1,13]. Previous research has demonstrated the importance of coping mechanisms in managing stressors [14,15]. Within the police community maladaptive coping and exposure to dangerous incidents are critical risk factors associated with officers’ perceived work stress [16]. Further research has shown that individuals involved in highly stressful careers have an increased risk of work stress-related health problems, especially if they rely on risky health behaviours to cope with stress [5,16]. Although there is an abundance of research about stress in POs, little research has been done to assess crime scene personnel (CSP). CSP, commonly known as crime scene investigators (CSIs), deal with the documentation, collection, preservation and analysis of evidence present at crime scenes. Due to the nature of their work, CSP encounter violent death more frequently than an average PO [17]. This may result in CSP experiencing more stress than the typical PO [16], and potentially resorting to maladaptive coping strategies to deal with stress [5,16]. The aim of this study was to assess the stress and anxiety levels and coping mechanisms of CSP employed by police departments in the state of Texas. A secondary objective was to determine the use of employee assistance programmes (EAPs) by CSP. Methods A total of 276 municipal police departments within the state of Texas were contacted for permission to recruit participants over a 3-month period from late winter until early spring. Currently, there is no state licensing in Texas required for CSP; therefore, researchers estimated one CSI per department. Municipal police departments in Texas were initially contacted by phone to acquire the contact information of the supervisors and administrators (i.e. police chief) of CSP during January and February of 2016. One hundred and thirty-two supervisors and administrators from 276 police departments were then contacted via email to inform them of the study and to ask them to distribute a self-administered online questionnaire created using Qualtrics software (2016) to their CSP. The email contained the study description and instructions for both the supervisors and administrators, and the CSP. Participation was voluntary and confidential. Participants were excluded if they did not meet at least five of the six criteria for the job description provided. The CSP job description included (i) the utilization of scene documentation methods such as photography, videography, sketching and note-taking; (ii) the collection and preservation of physical and/or biological evidence; (iii) the maintenance of chain of custody and evidence integrity; (iv) the processing of evidence; (v) report writing; and (vi) testifying at judicial proceedings. All procedures were approved by the University Institutional Review Board and participants provided informed consent during the completion of the online survey. The online questionnaire had an introductory page containing the project description and participant consent. Demographic information (age, sex, race, marital status, education level) was collected, along with job details (county employed in, years of experience, job description, position type [sworn officer (SO) or civilian worker (CW)]) and information regarding the availability of, encouragement for the use of and the actual usage of formal EAPs (which include counsellors, psychiatrists and psychologists). Finally, participants were asked to report measures of stress, anxiety and coping mechanisms. In order to measure stress levels, the Perceived Stress Scale (PSS), Police Stress Questionnaire (PSQ), and the Distress Thermometer were used. The State-Trait Anxiety Inventory (STAI) was utilized to measure anxiety levels, and the Brief COPE questionnaire was used to measure coping mechanisms amongst participants. The PSS is a 5-point Likert scale ranging from 0 (never) to 4 (very often) used to evaluate feelings and thoughts during the previous month (i.e. ‘In the last month, how often have you felt nervous or “stressed”?’) [18]. Scores can range from 0 to 40 and a higher score correlates with higher perceived stress. A score of 0–13 equates to low or average stress, a score of 14–26 equates to moderate stress and a score of 27–40 equates to high stress. The PSQ has two individual 7-point scales, each containing 20 questions, used to measure the level of stress caused by different aspects of the job over the last 6 months [19]. The PSQ is divided into the Organizational Police Stress Questionnaire (PSQ-Org) which assesses issues in dealing with supervisors and inadequate equipment, whereas the Operational Police Stress Questionnaire (PSQ-Op), evaluates factors including paperwork, fatigue and shift work. The Distress Thermometer is a visual analogue scale ranging from 0 to 10 (not distressed to extremely distressed) that measures the amount of distress in the past week [20]. The STAI contains two individual scales, each containing 20 questions, used to measure anxiety [21]. The first scale assesses how an individual feels right now (state anxiety) (i.e. ‘I feel calm.’), whereas the second scale assesses how an individual generally feels (trait anxiety) (i.e. ‘I feel pleasant.’). The level of severity ranges from mild (40–50), moderate (51–60), to severe (>60). The Brief COPE questionnaire has 28 questions that are used to assess the way an individual has been and is coping with stressors in their life (i.e. I pray or meditate) [22]; the questionnaire is measured on a 4-point scale ranging from 1 (I don’t do this at all) to 4 (I do this a lot). A high composite score for a coping strategy would imply that the strategy is used more often. The questionnaire measures 14 different coping strategies including denial, substance abuse, humour and venting. Statistical analyses were performed using the Statistical Package for the Social Sciences (SPSS, v 22). Descriptive statistics (frequencies and descriptives) were calculated for all test variables for the entire sample. The sample was then divided into subgroups to make comparisons between sex and job position to focus analysis on occupational stress rather than general stress. ANOVAs were conducted between the subgroups (e.g. male and female or sworn and civilian) on the same dependent variables. Significance of <0.05 was considered statistically significant. Correlations were calculated to analyse the relationships between perceived stress, organizational and operational stress, anxiety and distress among the entire sample and within each of the subgroups. Correlations between perceived stress (Distress Thermometer and PSS) and coping strategies were also calculated. Linear regression was used to determine the relationships between perceived stress (dependent variable) and age, sex, education and coping strategies as independent variables. Other factors, such as years of experience and marital status, were not used due to the lack of data and homogeneity of sample. Results Eighty-four individuals responded to the survey across 34 Texas counties. Eight responses were excluded; seven for lack of information and one for not meeting the job description criteria. A total of 76 participants were used in the statistical analyses. Demographics for the participants are shown in Table 1. The sample consisted largely of Caucasian (84%) males (68%), age range 35–54 (66%). The sample consisted of both SOs (67%) and CWs (33%). Of the SOs, 92% were male and 8% were female. Of the CWs, 17% were male and 83% were female. The entire population had an average of 12.75 years of experience with SOs (mean ± SD = 14.4 ± 9.5 years) having more years of experience than CWs (9.5 ± 6.6 years). Seventy-eight per cent of SOs knew of EAPs provided at their respective departments and of those, 88% were encouraged to use the services. Eighty-eight per cent of CWs knew of the services and, 86% of these were encouraged to use the services. Of the SOs and the CWs, 23% and 10%, respectively, acknowledged that they had used these services. Table 1. Participant’s information for gender, age, race, education, marital status and years of experience Demographics Entire sample (N = 76) SOs (n = 51) CWs (n = 25) Gender, n (%)  Male 51 (68) 47 (92) 4 (17)  Female 24 (32) 4 (8) 20 (83) Age, n (age range %)  25–34 years 13 (17) 8 (16) 5 (20)  35–44 years 26 (34) 14 (27) 12 (48)  45–54 years 24 (32) 19 (37) 5 (20)  55–64 years 12 (16) 9 (18) 3 (12)  65+ years 1 (1) 1 (2) 0 (0) Race, n (%)  White or Caucasian 64 (84) 42 (82) 22 (88)  Hispanic or Latin 5 (7) 4 (8) 1 (4)  Black or African American 4 (5) 2 (4) 2 (8)  Native American or American Indian 1 (1) 1 (2) 0 (0)  Other 2 (3) 2 (4) 0 (0) Education, n (%)  High school or equivalent 5 (7) 5 (10) 0 (0)  Some college 22 (29) 18 (35) 4 (16)  Associates/technical degree 11 (14) 5 (10) 6 (24)  Bachelor’s degree 25 (33) 16 (31) 9 (36)  Master’s degree 12 (16) 6 (12) 6 (24)  Other 1 (1) 1 (2) 0 (0) Marital status, n (%)  Single 4 (5) 2 (4) 2 (8)  Married 41 (54) 28 (55) 13 (52)  Separated 2 (3) 2 (4) 0 (0)  Divorced 7 (9) 2 (4) 5 (20)  Living with another 13 (17) 10 (20) 3 (12)  Did not answer 9 (12) 7 (14) 2 (8) Years of experience (mean ± SD) 12.8 ± 8.9 14.4 ± 9.5 9.5 ± 6.6 Demographics Entire sample (N = 76) SOs (n = 51) CWs (n = 25) Gender, n (%)  Male 51 (68) 47 (92) 4 (17)  Female 24 (32) 4 (8) 20 (83) Age, n (age range %)  25–34 years 13 (17) 8 (16) 5 (20)  35–44 years 26 (34) 14 (27) 12 (48)  45–54 years 24 (32) 19 (37) 5 (20)  55–64 years 12 (16) 9 (18) 3 (12)  65+ years 1 (1) 1 (2) 0 (0) Race, n (%)  White or Caucasian 64 (84) 42 (82) 22 (88)  Hispanic or Latin 5 (7) 4 (8) 1 (4)  Black or African American 4 (5) 2 (4) 2 (8)  Native American or American Indian 1 (1) 1 (2) 0 (0)  Other 2 (3) 2 (4) 0 (0) Education, n (%)  High school or equivalent 5 (7) 5 (10) 0 (0)  Some college 22 (29) 18 (35) 4 (16)  Associates/technical degree 11 (14) 5 (10) 6 (24)  Bachelor’s degree 25 (33) 16 (31) 9 (36)  Master’s degree 12 (16) 6 (12) 6 (24)  Other 1 (1) 1 (2) 0 (0) Marital status, n (%)  Single 4 (5) 2 (4) 2 (8)  Married 41 (54) 28 (55) 13 (52)  Separated 2 (3) 2 (4) 0 (0)  Divorced 7 (9) 2 (4) 5 (20)  Living with another 13 (17) 10 (20) 3 (12)  Did not answer 9 (12) 7 (14) 2 (8) Years of experience (mean ± SD) 12.8 ± 8.9 14.4 ± 9.5 9.5 ± 6.6 View Large Table 1. Participant’s information for gender, age, race, education, marital status and years of experience Demographics Entire sample (N = 76) SOs (n = 51) CWs (n = 25) Gender, n (%)  Male 51 (68) 47 (92) 4 (17)  Female 24 (32) 4 (8) 20 (83) Age, n (age range %)  25–34 years 13 (17) 8 (16) 5 (20)  35–44 years 26 (34) 14 (27) 12 (48)  45–54 years 24 (32) 19 (37) 5 (20)  55–64 years 12 (16) 9 (18) 3 (12)  65+ years 1 (1) 1 (2) 0 (0) Race, n (%)  White or Caucasian 64 (84) 42 (82) 22 (88)  Hispanic or Latin 5 (7) 4 (8) 1 (4)  Black or African American 4 (5) 2 (4) 2 (8)  Native American or American Indian 1 (1) 1 (2) 0 (0)  Other 2 (3) 2 (4) 0 (0) Education, n (%)  High school or equivalent 5 (7) 5 (10) 0 (0)  Some college 22 (29) 18 (35) 4 (16)  Associates/technical degree 11 (14) 5 (10) 6 (24)  Bachelor’s degree 25 (33) 16 (31) 9 (36)  Master’s degree 12 (16) 6 (12) 6 (24)  Other 1 (1) 1 (2) 0 (0) Marital status, n (%)  Single 4 (5) 2 (4) 2 (8)  Married 41 (54) 28 (55) 13 (52)  Separated 2 (3) 2 (4) 0 (0)  Divorced 7 (9) 2 (4) 5 (20)  Living with another 13 (17) 10 (20) 3 (12)  Did not answer 9 (12) 7 (14) 2 (8) Years of experience (mean ± SD) 12.8 ± 8.9 14.4 ± 9.5 9.5 ± 6.6 Demographics Entire sample (N = 76) SOs (n = 51) CWs (n = 25) Gender, n (%)  Male 51 (68) 47 (92) 4 (17)  Female 24 (32) 4 (8) 20 (83) Age, n (age range %)  25–34 years 13 (17) 8 (16) 5 (20)  35–44 years 26 (34) 14 (27) 12 (48)  45–54 years 24 (32) 19 (37) 5 (20)  55–64 years 12 (16) 9 (18) 3 (12)  65+ years 1 (1) 1 (2) 0 (0) Race, n (%)  White or Caucasian 64 (84) 42 (82) 22 (88)  Hispanic or Latin 5 (7) 4 (8) 1 (4)  Black or African American 4 (5) 2 (4) 2 (8)  Native American or American Indian 1 (1) 1 (2) 0 (0)  Other 2 (3) 2 (4) 0 (0) Education, n (%)  High school or equivalent 5 (7) 5 (10) 0 (0)  Some college 22 (29) 18 (35) 4 (16)  Associates/technical degree 11 (14) 5 (10) 6 (24)  Bachelor’s degree 25 (33) 16 (31) 9 (36)  Master’s degree 12 (16) 6 (12) 6 (24)  Other 1 (1) 1 (2) 0 (0) Marital status, n (%)  Single 4 (5) 2 (4) 2 (8)  Married 41 (54) 28 (55) 13 (52)  Separated 2 (3) 2 (4) 0 (0)  Divorced 7 (9) 2 (4) 5 (20)  Living with another 13 (17) 10 (20) 3 (12)  Did not answer 9 (12) 7 (14) 2 (8) Years of experience (mean ± SD) 12.8 ± 8.9 14.4 ± 9.5 9.5 ± 6.6 View Large The sample’s overall PSS score corresponded to low or average stress over the past month (11.0 ± 6.93). Participants’ scores ranged from 0 to 32. Both the overall PSQ-Org score (3.09 ± 1.12) and PSQ-Op score (2.98 ± 1.14) demonstrate low stress over the last 6 months. The overall scores for both the state (33.6 ± 10.5) and trait (33.2 ± 9.27) levels also demonstrated low levels of state and trait anxiety. The Distress Thermometer score for the sample also showed participants reported relatively low distress (3.54 ± 2.37). Specific differences are detailed in Table 2. Table 2. Stress and anxiety scores for all measures used for the entire sample and subgroups Entire sample Gender Position type Male (N = 76)Mean ± SD Male (n = 51) Mean ± SD Female (n = 24) Mean ± SD SOs (n = 51) Mean ± SD CWs (n = 25) Mean ± SD PSS 11.0 ± 6.93 11.3 ± 7.31 10.5 ± 6.24 11.3 ± 7.33 10.7 ± 6.18 PSQ-organizational 3.09 ± 1.12 3.18 ± 1.15 2.99 ± 1.02 3.21 ± 1.13 2.86 ± 1.08 PSQ-operational 2.98 ± 1.14 3.06 ± 1.18 2.90 ± 1.03 3.06 ± 1.13 2.81 ± 1.18 State anxiety 33.6 ± 10.5 34.4 ± 10.4 31.7 ± 10.7 34.2 ± 9.95 32.5 ± 11.6 Trait anxiety 33.2 ± 9.27 33.7 ± 9.71 32.1 ± 8.60 33.5 ± 9.63 32.6 ± 8.69 Distress Thermometer 3.54 ± 2.37 3.60 ± 2.40 3.26 ± 2.25 3.60 ± 2.32 3.42 ± 2.50 Entire sample Gender Position type Male (N = 76)Mean ± SD Male (n = 51) Mean ± SD Female (n = 24) Mean ± SD SOs (n = 51) Mean ± SD CWs (n = 25) Mean ± SD PSS 11.0 ± 6.93 11.3 ± 7.31 10.5 ± 6.24 11.3 ± 7.33 10.7 ± 6.18 PSQ-organizational 3.09 ± 1.12 3.18 ± 1.15 2.99 ± 1.02 3.21 ± 1.13 2.86 ± 1.08 PSQ-operational 2.98 ± 1.14 3.06 ± 1.18 2.90 ± 1.03 3.06 ± 1.13 2.81 ± 1.18 State anxiety 33.6 ± 10.5 34.4 ± 10.4 31.7 ± 10.7 34.2 ± 9.95 32.5 ± 11.6 Trait anxiety 33.2 ± 9.27 33.7 ± 9.71 32.1 ± 8.60 33.5 ± 9.63 32.6 ± 8.69 Distress Thermometer 3.54 ± 2.37 3.60 ± 2.40 3.26 ± 2.25 3.60 ± 2.32 3.42 ± 2.50 View Large Table 2. Stress and anxiety scores for all measures used for the entire sample and subgroups Entire sample Gender Position type Male (N = 76)Mean ± SD Male (n = 51) Mean ± SD Female (n = 24) Mean ± SD SOs (n = 51) Mean ± SD CWs (n = 25) Mean ± SD PSS 11.0 ± 6.93 11.3 ± 7.31 10.5 ± 6.24 11.3 ± 7.33 10.7 ± 6.18 PSQ-organizational 3.09 ± 1.12 3.18 ± 1.15 2.99 ± 1.02 3.21 ± 1.13 2.86 ± 1.08 PSQ-operational 2.98 ± 1.14 3.06 ± 1.18 2.90 ± 1.03 3.06 ± 1.13 2.81 ± 1.18 State anxiety 33.6 ± 10.5 34.4 ± 10.4 31.7 ± 10.7 34.2 ± 9.95 32.5 ± 11.6 Trait anxiety 33.2 ± 9.27 33.7 ± 9.71 32.1 ± 8.60 33.5 ± 9.63 32.6 ± 8.69 Distress Thermometer 3.54 ± 2.37 3.60 ± 2.40 3.26 ± 2.25 3.60 ± 2.32 3.42 ± 2.50 Entire sample Gender Position type Male (N = 76)Mean ± SD Male (n = 51) Mean ± SD Female (n = 24) Mean ± SD SOs (n = 51) Mean ± SD CWs (n = 25) Mean ± SD PSS 11.0 ± 6.93 11.3 ± 7.31 10.5 ± 6.24 11.3 ± 7.33 10.7 ± 6.18 PSQ-organizational 3.09 ± 1.12 3.18 ± 1.15 2.99 ± 1.02 3.21 ± 1.13 2.86 ± 1.08 PSQ-operational 2.98 ± 1.14 3.06 ± 1.18 2.90 ± 1.03 3.06 ± 1.13 2.81 ± 1.18 State anxiety 33.6 ± 10.5 34.4 ± 10.4 31.7 ± 10.7 34.2 ± 9.95 32.5 ± 11.6 Trait anxiety 33.2 ± 9.27 33.7 ± 9.71 32.1 ± 8.60 33.5 ± 9.63 32.6 ± 8.69 Distress Thermometer 3.54 ± 2.37 3.60 ± 2.40 3.26 ± 2.25 3.60 ± 2.32 3.42 ± 2.50 View Large Comparisons were also made between the subgroups (sex and position type) and coping strategies (Table 3). Females engaged in the use of emotional support (P < 0.01), instrumental support (P < 0.05) and positive reframing (P < 0.05) significantly more than males. When comparing position types, there were no significant differences in coping mechanisms between SOs and CWs. Because sample sizes were not large enough, further analysis between groups (e.g. male or female, SOs and male or female, CWs) was not possible. Table 3. Coping strategies adopted by subgroups Gender Position type Male (n = 51) Mean ± SD Female (n = 24) Mean ± SD SOs (n = 51) Mean ± SD CWs (n = 25) Mean ± SD Self-distraction 5.27 ± 1.44 5.13 ± 1.73 5.35 ± 1.49 5.00 ± 1.58 Active coping 6.31 ± 1.48 6.67 ± 1.27 6.33 ± 1.46 6.68 ± 1.31 Denial 2.29 ± 0.90 2.08 ± 0.28 2.29 ± 0.90 2.08 ± 0.28 Substance use 2.40 ± 0.89 2.83 ± 1.31 2.44 ± 1.01 2.72 ± 1.14 Emotional support 4.56 ± 1.29 5.50 ± 1.56** 4.73 ± 1.30 5.28 ± 1.74 Instrumental support 4.60 ± 1.33 5.38 ± 1.44* 4.79 ± 1.27 5.12 ± 1.74 Behavioral disengagement 2.46 ± 1.07 2.13 ± 0.45 2.46 ± 1.07 2.12 ± 0.44 Venting 4.08 ± 1.35 4.75 ± 1.54 4.25 ± 1.45 4.36 ± 1.44 Positive reframing 5.40 ± 1.47 6.38 ± 1.56* 5.52 ± 1.46 6.20 ± 1.71 Planning 6.33 ± 1.45 6.54 ± 1.41 6.42 ± 1.46 6.44 ± 1.42 Humour 5.48 ± 1.61 5.33 ± 1.86 5.54 ± 1.71 5.16 ± 1.62 Acceptance 6.33 ± 1.48 6.21 ± 1.56 6.29 ± 1.44 6.36 ± 1.63 Religion 5.29 ± 2.04 5.71 ± 1.85 5.50 ± 2.00 5.40 ± 2.00 Self-blame 4.08 ± 1.47 3.88 ± 1.62 4.04 ± 1.38 4.00 ± 1.76 Gender Position type Male (n = 51) Mean ± SD Female (n = 24) Mean ± SD SOs (n = 51) Mean ± SD CWs (n = 25) Mean ± SD Self-distraction 5.27 ± 1.44 5.13 ± 1.73 5.35 ± 1.49 5.00 ± 1.58 Active coping 6.31 ± 1.48 6.67 ± 1.27 6.33 ± 1.46 6.68 ± 1.31 Denial 2.29 ± 0.90 2.08 ± 0.28 2.29 ± 0.90 2.08 ± 0.28 Substance use 2.40 ± 0.89 2.83 ± 1.31 2.44 ± 1.01 2.72 ± 1.14 Emotional support 4.56 ± 1.29 5.50 ± 1.56** 4.73 ± 1.30 5.28 ± 1.74 Instrumental support 4.60 ± 1.33 5.38 ± 1.44* 4.79 ± 1.27 5.12 ± 1.74 Behavioral disengagement 2.46 ± 1.07 2.13 ± 0.45 2.46 ± 1.07 2.12 ± 0.44 Venting 4.08 ± 1.35 4.75 ± 1.54 4.25 ± 1.45 4.36 ± 1.44 Positive reframing 5.40 ± 1.47 6.38 ± 1.56* 5.52 ± 1.46 6.20 ± 1.71 Planning 6.33 ± 1.45 6.54 ± 1.41 6.42 ± 1.46 6.44 ± 1.42 Humour 5.48 ± 1.61 5.33 ± 1.86 5.54 ± 1.71 5.16 ± 1.62 Acceptance 6.33 ± 1.48 6.21 ± 1.56 6.29 ± 1.44 6.36 ± 1.63 Religion 5.29 ± 2.04 5.71 ± 1.85 5.50 ± 2.00 5.40 ± 2.00 Self-blame 4.08 ± 1.47 3.88 ± 1.62 4.04 ± 1.38 4.00 ± 1.76 *P < 0.05, **P < 0.01. View Large Table 3. Coping strategies adopted by subgroups Gender Position type Male (n = 51) Mean ± SD Female (n = 24) Mean ± SD SOs (n = 51) Mean ± SD CWs (n = 25) Mean ± SD Self-distraction 5.27 ± 1.44 5.13 ± 1.73 5.35 ± 1.49 5.00 ± 1.58 Active coping 6.31 ± 1.48 6.67 ± 1.27 6.33 ± 1.46 6.68 ± 1.31 Denial 2.29 ± 0.90 2.08 ± 0.28 2.29 ± 0.90 2.08 ± 0.28 Substance use 2.40 ± 0.89 2.83 ± 1.31 2.44 ± 1.01 2.72 ± 1.14 Emotional support 4.56 ± 1.29 5.50 ± 1.56** 4.73 ± 1.30 5.28 ± 1.74 Instrumental support 4.60 ± 1.33 5.38 ± 1.44* 4.79 ± 1.27 5.12 ± 1.74 Behavioral disengagement 2.46 ± 1.07 2.13 ± 0.45 2.46 ± 1.07 2.12 ± 0.44 Venting 4.08 ± 1.35 4.75 ± 1.54 4.25 ± 1.45 4.36 ± 1.44 Positive reframing 5.40 ± 1.47 6.38 ± 1.56* 5.52 ± 1.46 6.20 ± 1.71 Planning 6.33 ± 1.45 6.54 ± 1.41 6.42 ± 1.46 6.44 ± 1.42 Humour 5.48 ± 1.61 5.33 ± 1.86 5.54 ± 1.71 5.16 ± 1.62 Acceptance 6.33 ± 1.48 6.21 ± 1.56 6.29 ± 1.44 6.36 ± 1.63 Religion 5.29 ± 2.04 5.71 ± 1.85 5.50 ± 2.00 5.40 ± 2.00 Self-blame 4.08 ± 1.47 3.88 ± 1.62 4.04 ± 1.38 4.00 ± 1.76 Gender Position type Male (n = 51) Mean ± SD Female (n = 24) Mean ± SD SOs (n = 51) Mean ± SD CWs (n = 25) Mean ± SD Self-distraction 5.27 ± 1.44 5.13 ± 1.73 5.35 ± 1.49 5.00 ± 1.58 Active coping 6.31 ± 1.48 6.67 ± 1.27 6.33 ± 1.46 6.68 ± 1.31 Denial 2.29 ± 0.90 2.08 ± 0.28 2.29 ± 0.90 2.08 ± 0.28 Substance use 2.40 ± 0.89 2.83 ± 1.31 2.44 ± 1.01 2.72 ± 1.14 Emotional support 4.56 ± 1.29 5.50 ± 1.56** 4.73 ± 1.30 5.28 ± 1.74 Instrumental support 4.60 ± 1.33 5.38 ± 1.44* 4.79 ± 1.27 5.12 ± 1.74 Behavioral disengagement 2.46 ± 1.07 2.13 ± 0.45 2.46 ± 1.07 2.12 ± 0.44 Venting 4.08 ± 1.35 4.75 ± 1.54 4.25 ± 1.45 4.36 ± 1.44 Positive reframing 5.40 ± 1.47 6.38 ± 1.56* 5.52 ± 1.46 6.20 ± 1.71 Planning 6.33 ± 1.45 6.54 ± 1.41 6.42 ± 1.46 6.44 ± 1.42 Humour 5.48 ± 1.61 5.33 ± 1.86 5.54 ± 1.71 5.16 ± 1.62 Acceptance 6.33 ± 1.48 6.21 ± 1.56 6.29 ± 1.44 6.36 ± 1.63 Religion 5.29 ± 2.04 5.71 ± 1.85 5.50 ± 2.00 5.40 ± 2.00 Self-blame 4.08 ± 1.47 3.88 ± 1.62 4.04 ± 1.38 4.00 ± 1.76 *P < 0.05, **P < 0.01. View Large Correlations for the entire sample and each subgroup were calculated to analyse the relationship between PSS, PSQ-Org, PSQ-Op, state anxiety and trait anxiety, and the Distress Thermometer (Table 4). Significant positive correlations were observed in all cases except between the PSQ-Org and Distress Thermometer in the CW subgroup. The correlations between perceived stress and coping mechanisms were also observed. The Distress Thermometer score and the PSS score were used to determine short-term and long-term coping mechanisms. Both the sample as a whole and the male subgroup showed a correlation between the Distress Thermometer and active coping, substance use and behavioural disengagement. SOs were similar to the male subgroup in that correlations were found between the Distress Thermometer and substance use and behavioural disengagement. When comparing coping mechanisms to long-term stress, the sample as a whole displayed correlations between PSS and active coping (r = −0.409, P < 0.001), behavioural disengagement (r = 0.522, P < 0.001), positive reframing (r = −0.428, P < 0.001), planning (r = −0.298, P = 0.010), acceptance (r = −0.235, P < 0.05) and self-blame (r = 0.273, P < 0.05). Planning (female: r = −0.616, P = 0.001; civilian: r = −0.535, P < 0.01) and self-distraction (female: r = 0.458, P < 0.05; civilian: r = 0.439, P < 0.05) were coping mechanisms that were exhibited in only the female and CW subgroups and not the male and SO subgroups. However, males and SO subgroups exhibited self-blame (male: r = 0.312, P < 0.05; sworn: r = 0.311, P < 0.05). Table 4. Correlations between stress, anxiety and coping mechanism scales Measure 1 2 3 4 5 Entire sample  1. PSS (N = 76)  2. PSQ-organizational (n = 73) 0.57**  3. PSQ-operational (n = 73) 0.56** 0.76**  4. State anxiety (n = 73) 0.79** 0.61** 0.61**  5. Trait anxiety (n = 73) 0.82** 0.62** 0.56** 0.87**  6. Distress Thermometer (n = 68) 0.75** 0.62** 0.47** 0.73** 0.69** Male  1. PSS (n = 51)  2. PSQ-organizational (n = 48) 0.62**  3. PSQ-operational (n = 48) 0.54** 0.76**  4. State anxiety (n = 48) 0.78** 0.69** 0.60**  5. Trait anxiety (n = 48) 0.81** 0.69** 0.55** 0.88**  6. Distress Thermometer (n = 44) 0.77** 0.52** 0.44** 0.68** 0.70** Female  1. PSS (n = 24)  2. PSQ-organizational (n = 24) 0.54**  3. PSQ-operational (n = 24) 0.71** 0.74**  4. State anxiety (n = 24) 0.83** 0.52** 0.71**  5. Trait anxiety (n = 24) 0.87** 0.53** 0.77** 0.84**  6. Distress Thermometer (n = 23) 0.68** 0.45* 0.75** 0.82** 0.70** SOs  1. PSS (n = 51)  2. PSQ-organizational (n = 48) 0.60**  3. PSQ-operational (n = 48) 0.53** 0.75**  4. State anxiety (n = 48) 0.79** 0.70** 0.60**  5. Trait anxiety (n = 48) 0.80** 0.68** 0.54** 0.89**  6. Distress Thermometer (n = 44) 0.77** 0.53** 0.66** 0.66** 0.68** CWs  1. PSS (n = 25)  2. PSQ-organizational (n = 25) 0.52**  3. PSQ-operational (n = 25) 0.63** 0.78**  4. State anxiety (n = 25) 0.83** 0.50* 0.62**  5. Trait anxiety (n = 25) 0.88** 0.50* 0.69** 0.86**  6. Distress Thermometer (n = 25) 0.71** 0.260 0.52* 0.82** 0.72** Measure 1 2 3 4 5 Entire sample  1. PSS (N = 76)  2. PSQ-organizational (n = 73) 0.57**  3. PSQ-operational (n = 73) 0.56** 0.76**  4. State anxiety (n = 73) 0.79** 0.61** 0.61**  5. Trait anxiety (n = 73) 0.82** 0.62** 0.56** 0.87**  6. Distress Thermometer (n = 68) 0.75** 0.62** 0.47** 0.73** 0.69** Male  1. PSS (n = 51)  2. PSQ-organizational (n = 48) 0.62**  3. PSQ-operational (n = 48) 0.54** 0.76**  4. State anxiety (n = 48) 0.78** 0.69** 0.60**  5. Trait anxiety (n = 48) 0.81** 0.69** 0.55** 0.88**  6. Distress Thermometer (n = 44) 0.77** 0.52** 0.44** 0.68** 0.70** Female  1. PSS (n = 24)  2. PSQ-organizational (n = 24) 0.54**  3. PSQ-operational (n = 24) 0.71** 0.74**  4. State anxiety (n = 24) 0.83** 0.52** 0.71**  5. Trait anxiety (n = 24) 0.87** 0.53** 0.77** 0.84**  6. Distress Thermometer (n = 23) 0.68** 0.45* 0.75** 0.82** 0.70** SOs  1. PSS (n = 51)  2. PSQ-organizational (n = 48) 0.60**  3. PSQ-operational (n = 48) 0.53** 0.75**  4. State anxiety (n = 48) 0.79** 0.70** 0.60**  5. Trait anxiety (n = 48) 0.80** 0.68** 0.54** 0.89**  6. Distress Thermometer (n = 44) 0.77** 0.53** 0.66** 0.66** 0.68** CWs  1. PSS (n = 25)  2. PSQ-organizational (n = 25) 0.52**  3. PSQ-operational (n = 25) 0.63** 0.78**  4. State anxiety (n = 25) 0.83** 0.50* 0.62**  5. Trait anxiety (n = 25) 0.88** 0.50* 0.69** 0.86**  6. Distress Thermometer (n = 25) 0.71** 0.260 0.52* 0.82** 0.72** *P < 0.05, **P < 0.01. View Large Table 4. Correlations between stress, anxiety and coping mechanism scales Measure 1 2 3 4 5 Entire sample  1. PSS (N = 76)  2. PSQ-organizational (n = 73) 0.57**  3. PSQ-operational (n = 73) 0.56** 0.76**  4. State anxiety (n = 73) 0.79** 0.61** 0.61**  5. Trait anxiety (n = 73) 0.82** 0.62** 0.56** 0.87**  6. Distress Thermometer (n = 68) 0.75** 0.62** 0.47** 0.73** 0.69** Male  1. PSS (n = 51)  2. PSQ-organizational (n = 48) 0.62**  3. PSQ-operational (n = 48) 0.54** 0.76**  4. State anxiety (n = 48) 0.78** 0.69** 0.60**  5. Trait anxiety (n = 48) 0.81** 0.69** 0.55** 0.88**  6. Distress Thermometer (n = 44) 0.77** 0.52** 0.44** 0.68** 0.70** Female  1. PSS (n = 24)  2. PSQ-organizational (n = 24) 0.54**  3. PSQ-operational (n = 24) 0.71** 0.74**  4. State anxiety (n = 24) 0.83** 0.52** 0.71**  5. Trait anxiety (n = 24) 0.87** 0.53** 0.77** 0.84**  6. Distress Thermometer (n = 23) 0.68** 0.45* 0.75** 0.82** 0.70** SOs  1. PSS (n = 51)  2. PSQ-organizational (n = 48) 0.60**  3. PSQ-operational (n = 48) 0.53** 0.75**  4. State anxiety (n = 48) 0.79** 0.70** 0.60**  5. Trait anxiety (n = 48) 0.80** 0.68** 0.54** 0.89**  6. Distress Thermometer (n = 44) 0.77** 0.53** 0.66** 0.66** 0.68** CWs  1. PSS (n = 25)  2. PSQ-organizational (n = 25) 0.52**  3. PSQ-operational (n = 25) 0.63** 0.78**  4. State anxiety (n = 25) 0.83** 0.50* 0.62**  5. Trait anxiety (n = 25) 0.88** 0.50* 0.69** 0.86**  6. Distress Thermometer (n = 25) 0.71** 0.260 0.52* 0.82** 0.72** Measure 1 2 3 4 5 Entire sample  1. PSS (N = 76)  2. PSQ-organizational (n = 73) 0.57**  3. PSQ-operational (n = 73) 0.56** 0.76**  4. State anxiety (n = 73) 0.79** 0.61** 0.61**  5. Trait anxiety (n = 73) 0.82** 0.62** 0.56** 0.87**  6. Distress Thermometer (n = 68) 0.75** 0.62** 0.47** 0.73** 0.69** Male  1. PSS (n = 51)  2. PSQ-organizational (n = 48) 0.62**  3. PSQ-operational (n = 48) 0.54** 0.76**  4. State anxiety (n = 48) 0.78** 0.69** 0.60**  5. Trait anxiety (n = 48) 0.81** 0.69** 0.55** 0.88**  6. Distress Thermometer (n = 44) 0.77** 0.52** 0.44** 0.68** 0.70** Female  1. PSS (n = 24)  2. PSQ-organizational (n = 24) 0.54**  3. PSQ-operational (n = 24) 0.71** 0.74**  4. State anxiety (n = 24) 0.83** 0.52** 0.71**  5. Trait anxiety (n = 24) 0.87** 0.53** 0.77** 0.84**  6. Distress Thermometer (n = 23) 0.68** 0.45* 0.75** 0.82** 0.70** SOs  1. PSS (n = 51)  2. PSQ-organizational (n = 48) 0.60**  3. PSQ-operational (n = 48) 0.53** 0.75**  4. State anxiety (n = 48) 0.79** 0.70** 0.60**  5. Trait anxiety (n = 48) 0.80** 0.68** 0.54** 0.89**  6. Distress Thermometer (n = 44) 0.77** 0.53** 0.66** 0.66** 0.68** CWs  1. PSS (n = 25)  2. PSQ-organizational (n = 25) 0.52**  3. PSQ-operational (n = 25) 0.63** 0.78**  4. State anxiety (n = 25) 0.83** 0.50* 0.62**  5. Trait anxiety (n = 25) 0.88** 0.50* 0.69** 0.86**  6. Distress Thermometer (n = 25) 0.71** 0.260 0.52* 0.82** 0.72** *P < 0.05, **P < 0.01. View Large Linear regression statistics between perceived stress (Distress Thermometers and PSS) and age, sex, education and coping strategies were performed (Table 5). The Distress Thermometer showed a positive correlation with substance use (P < 0.05), while the PSS was positively correlated with behavioural disengagement (P < 0.05), substance use (P < 0.01), self-blame (P < 0.01) and self-distraction (P < 0.01). The PSS was also negatively correlated with positive reframing (P < 0.001), and humour (P < 0.01). Table 5. Regression analyses of the Distress Thermometer and Perceived Stress Scale as dependent variables using the entire sample Distress Thermometer Perceived Stress Scale Unstandardized coefficients B Standard coefficients Beta Unstandardized coefficients B Standardized coefficients Beta Age −0.091 −0.039 −1.624 −0.236 Gender −0.355 −0.073 −00671 −0.046 Education 0.277 0.158 0.593 0.115 Brief COPE  Self-distraction 0.148 0.097 1.236 0.273**  Active coping −0.313 −0.182 −0.673 −0.137  Denial 0.678 0.148 0.467 0.051  Substance use 0.717 0.334* 1.594 0.244**  Emotional support −0.039 −0.024 0.296 0.062  Instrumental support −0.238 −0.140 0.067 0.014  Behavioural disengagement 0.706 0.287 1.905 0.254*  Venting 0.187 0.115 0.525 0.109  Positive reframing −0.058 −0.039 −1.745 −0.393***  Planning 0.172 0.106 0.059 0.012  Humour −0.229 −0.164 −1.241 −0.302**  Acceptance −0.148 −0.092 −0.641 −0.139  Religion 0.002 0.002 0.263 0.075  Self-blame 0.250 0.166 1.254 0.275** Adjusted R2 0.214 0.567 Distress Thermometer Perceived Stress Scale Unstandardized coefficients B Standard coefficients Beta Unstandardized coefficients B Standardized coefficients Beta Age −0.091 −0.039 −1.624 −0.236 Gender −0.355 −0.073 −00671 −0.046 Education 0.277 0.158 0.593 0.115 Brief COPE  Self-distraction 0.148 0.097 1.236 0.273**  Active coping −0.313 −0.182 −0.673 −0.137  Denial 0.678 0.148 0.467 0.051  Substance use 0.717 0.334* 1.594 0.244**  Emotional support −0.039 −0.024 0.296 0.062  Instrumental support −0.238 −0.140 0.067 0.014  Behavioural disengagement 0.706 0.287 1.905 0.254*  Venting 0.187 0.115 0.525 0.109  Positive reframing −0.058 −0.039 −1.745 −0.393***  Planning 0.172 0.106 0.059 0.012  Humour −0.229 −0.164 −1.241 −0.302**  Acceptance −0.148 −0.092 −0.641 −0.139  Religion 0.002 0.002 0.263 0.075  Self-blame 0.250 0.166 1.254 0.275** Adjusted R2 0.214 0.567 *P < 0.05, **P < 0.01, ***P < 0.001. View Large Table 5. Regression analyses of the Distress Thermometer and Perceived Stress Scale as dependent variables using the entire sample Distress Thermometer Perceived Stress Scale Unstandardized coefficients B Standard coefficients Beta Unstandardized coefficients B Standardized coefficients Beta Age −0.091 −0.039 −1.624 −0.236 Gender −0.355 −0.073 −00671 −0.046 Education 0.277 0.158 0.593 0.115 Brief COPE  Self-distraction 0.148 0.097 1.236 0.273**  Active coping −0.313 −0.182 −0.673 −0.137  Denial 0.678 0.148 0.467 0.051  Substance use 0.717 0.334* 1.594 0.244**  Emotional support −0.039 −0.024 0.296 0.062  Instrumental support −0.238 −0.140 0.067 0.014  Behavioural disengagement 0.706 0.287 1.905 0.254*  Venting 0.187 0.115 0.525 0.109  Positive reframing −0.058 −0.039 −1.745 −0.393***  Planning 0.172 0.106 0.059 0.012  Humour −0.229 −0.164 −1.241 −0.302**  Acceptance −0.148 −0.092 −0.641 −0.139  Religion 0.002 0.002 0.263 0.075  Self-blame 0.250 0.166 1.254 0.275** Adjusted R2 0.214 0.567 Distress Thermometer Perceived Stress Scale Unstandardized coefficients B Standard coefficients Beta Unstandardized coefficients B Standardized coefficients Beta Age −0.091 −0.039 −1.624 −0.236 Gender −0.355 −0.073 −00671 −0.046 Education 0.277 0.158 0.593 0.115 Brief COPE  Self-distraction 0.148 0.097 1.236 0.273**  Active coping −0.313 −0.182 −0.673 −0.137  Denial 0.678 0.148 0.467 0.051  Substance use 0.717 0.334* 1.594 0.244**  Emotional support −0.039 −0.024 0.296 0.062  Instrumental support −0.238 −0.140 0.067 0.014  Behavioural disengagement 0.706 0.287 1.905 0.254*  Venting 0.187 0.115 0.525 0.109  Positive reframing −0.058 −0.039 −1.745 −0.393***  Planning 0.172 0.106 0.059 0.012  Humour −0.229 −0.164 −1.241 −0.302**  Acceptance −0.148 −0.092 −0.641 −0.139  Religion 0.002 0.002 0.263 0.075  Self-blame 0.250 0.166 1.254 0.275** Adjusted R2 0.214 0.567 *P < 0.05, **P < 0.01, ***P < 0.001. View Large Discussion Overall, this study showed that CSP within the state of Texas reported low levels of stress and anxiety. This could be due to appropriate precautions being taken (training or self-awareness) and/or the adaptive use of coping mechanisms that reduce stress levels. While EAPs were widely available, only a small percentage of the sample had used the programmes. Given the machismo present in the police force, it is surprising that SOs used the services more than CWs. Because it was not specified when these individuals used EAPs, SOs could have used them during their early years as an officer. Thus, the stressors that caused the individual to seek help may not have been related duties as a CSI, but rather a result of PO duties earlier in their career. Also, the lack of use of EAPs could be due to the law enforcement subculture or perhaps because counsellors and psychiatrists were considered to be ‘outsiders’ who lack understanding of CSP [3]. Unlike previous research which suggests that females in law enforcement have higher levels of stress [4,20], our research showed that males had slightly higher stress and anxiety levels than females in all measures used. Because sex and gender play a role in the perception of stress, males and females are believed to have not only different views of stress, but different coping mechanisms [4]. This study demonstrates that active coping, planning and acceptance were the most commonly used coping strategies by CSP providing evidence for the idea that CSP are utilizing adaptive coping strategies. This differs from past research in which CSP exhibited higher use of avoidant coping strategies (e.g. avoidance, behavioural disengagement) than positive coping strategies (e.g. emotional support, seeking assistance) [17]. Females exhibited a significantly higher use of emotional support, instrumental support and positive reframing compared to males. This is similar to previous research which suggests that females use more emotion-focused coping mechanisms than males [12]. The need for active emotional support is also related to the environment females are in. Within a male-dominated field, females typically find comfort and support in others, especially other women who understand the stressors [4]. There were no significant differences found between SOs and civilian personnel for the coping strategies utilized. Even though these subgroups may have different initial training (e.g. the majority of male SOs go through the police academy first), the CSP training programmes seem to be preparing all individuals similarly regardless of the position type. When observing correlations between perceived stress and coping mechanisms, unique correlations were found—bearing in mind that the majority of SOs were male. Both the male and SO subgroups showed a positive correlation between the PSS and self-blame. This supports previous findings that demonstrated that male officers tend to use avoidant emotional strategies, such as self-blame and negation more frequently than task-oriented strategies [4,12]. Because males seek guidance, support or counselling less than females, there is vulnerability for increased distress and burnout [4,12]. The use of avoidant emotional strategies may be related to the training received by SOs, as well as the machismo that is common within the law enforcement profession [23]. In linear regression analysis, a positive association with self-distraction, substance use and behavioural disengagement and a negative association with reframing and humour and perceived stress (PSS) support the idea that maladaptive strategies can lead to increased stress [4,12,15]. Limitations of this study included the lack of knowledge regarding target population size. According to the Bureau of Labor and Statistics, there are ~900 out of 14000 CSP employed in the state of Texas with only a small proportion of those individuals working at local level. Once state licensing and certification of CSP becomes a requirement, an accurate target population size can be obtained. Additionally, there was a dependency on the police department to provide proper contact information and on the supervisors and administrators to distribute the surveys to CSP. This study demonstrates that CSP appear to report less occupational stress compared to other POs, and that male CSP reported slightly higher levels of stress and anxiety than their female counterparts. Overall, females reported significantly greater use of emotional support, instrumental support and positive reframing compared to males; however, there were no differences in stress and coping mechanisms between SOs and civilian CSP. With little previous research on CSP, further study is needed into perceived stress, anxiety and coping mechanisms of this unique set of law enforcement personnel. Key points Crime scene personnel appeared to experience less occupational stress than police officers. Male crime scene personnel reported slightly higher levels of stress and anxiety than females, with males also reporting significantly lower use of emotional support, instrumental support and positive reframing. There were no differences in stress and coping mechanisms regarding crime scene personnel who were sworn officers and those who were civilian workers. Competing interests None declared. References 1. Collins PA , Gibbs AC . Stress in police officers: a study of the origins, prevalence and severity of stress-related symptoms within a county police force . Occup Med (Lond) 2003 ; 53 : 256 – 264 . Google Scholar CrossRef Search ADS PubMed 2. Dabney DA , Copes H , Tewksbury R , Hawk-Tourtelot SR . A qualitative assessment of stress perceptions among members of a homicide unit . Justice Q 2013 ; 30 : 811 – 836 . Google Scholar CrossRef Search ADS 3. Sewell JD . The stress of homicide investigations . Death Stud 1994 ; 18 : 565 – 582 . Google Scholar CrossRef Search ADS 4. He N , Zhao JH , Archbold CA . Gender and police stress—the convergent and divergent impact of work environment, work-family conflict, and stress coping mechanisms of female and male police officers . Policing 2002 ; 25 : 687 – 708 . Google Scholar CrossRef Search ADS 5. Maran DA , Varetto A , Zedda M , Ieraci V . Occupational stress, anxiety and coping strategies in police officers . Occup Med (Lond) 2015 ; 65 : 466 – 473 . Google Scholar CrossRef Search ADS PubMed 6. Franke WD , Ramey SL , Shelley MC , 2nd . Relationship between cardiovascular disease morbidity, risk factors, and stress in a law enforcement cohort . J Occup Environ Med 2002 ; 44 : 1182 – 1189 . Google Scholar CrossRef Search ADS PubMed 7. Webb HE , Fabianke-Kadue EC , Kraemer RR , Kamimori GH , Castracane VD , Acevedo EO . Stress reactivity to repeated low-level challenges: a pilot study . Appl Psychophysiol Biofeedback 2011 ; 36 : 243 – 250 . Google Scholar CrossRef Search ADS PubMed 8. Yoo H , Franke WD . Stress and cardiovascular disease risk in female law enforcement officers . Int Arch Occup Environ Health 2011 ; 84 : 279 – 286 . Google Scholar CrossRef Search ADS PubMed 9. Chrousos GP . Stress and disorders of the stress system . Nat Rev Endocrinol 2009 ; 5 : 374 – 381 . Google Scholar CrossRef Search ADS PubMed 10. Kyrou I , Chrousos GP , Tsigos C . Stress, visceral obesity, and metabolic complications . Ann NY Acad Sci 2006 ; 1083 : 77 – 110 . Google Scholar CrossRef Search ADS PubMed 11. Burke RJ . Stressful events, work-family conflict, coping, psychological burnout, and well-being among police officers . Psychol Rep 1994 ; 75 : 787 – 800 . Google Scholar CrossRef Search ADS PubMed 12. Chopko BA , Schwartz RC . The relation between mindfulness and posttraumatic stress symptoms among police officers . J Loss Trauma 2013 ; 18 : 1 – 9 . Google Scholar CrossRef Search ADS 13. Kelty SF , Gordon H . No burnout at this coal-face: managing occupational stress in forensic personnel and the implications for forensic and criminal justice agencies . Psychiat Psychol Law 2015 ; 22 : 273 – 290 . Google Scholar CrossRef Search ADS 14. Seeman M , Lewis S . Powerlessness, health and mortality: a longitudinal study of older men and mature women . Soc Sci Med 1995 ; 41 : 517 – 525 . Google Scholar CrossRef Search ADS PubMed 15. Creswell JD , Welch WT , Taylor SE , Sherman DK , Gruenewald TL , Mann T . Affirmation of personal values buffers neuroendocrine and psychological stress responses . Psychol Sci 2005 ; 16 : 846 – 851 . Google Scholar CrossRef Search ADS PubMed 16. Gershon RR , Lin S , Li X . Work stress in aging police officers . J Occup Environ Med 2002 ; 44 : 160 – 167 . Google Scholar CrossRef Search ADS PubMed 17. Mrevlje TP . Coping with work-related traumatic situations among crime scene technicians . Stress Health 2016 ; 32 : 374 – 382 . Google Scholar CrossRef Search ADS PubMed 18. Cohen S , Kamarck T , Mermelstein R . A global measure of perceived stress . J Health Soc Behav 1983 ; 24 : 385 – 396 . Google Scholar CrossRef Search ADS PubMed 19. McCreary DR , Thompson MM . Development of two reliable and valid measures of stressors in policing: the operational and organizational police stress questionnaires . Int J Stress Manage 2006 ; 13 : 494 . Google Scholar CrossRef Search ADS 20. Maran DA , Varetto A , Zedda M , Franscini M . Stress among Italian male and female patrol police officers: a quali-quantitative survey . Policing 2014 ; 37 : 875 – 890 . Google Scholar CrossRef Search ADS 21. Speilberger CD , Gorsuch RL , Luschene R , Vagg PR , Jacobs GA. Manual for the State-Trait Anxiety Inventory (STAI) . Palo Alto, CA : CPP , 1983 . 22. Carver CS . You want to measure coping but your protocol’s too long: consider the brief COPE . Int J Behav Med 1997 ; 4 : 92 – 100 . Google Scholar CrossRef Search ADS PubMed 23. Paoline EA . Taking stock: toward a richer understanding of police culture . J Crim Just 2003 ; 31 : 199 – 214 . Google Scholar CrossRef Search ADS © The Author(s) 2018. Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For Permissions, please email: journals.permissions@oup.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)

Journal

Occupational MedicineOxford University Press

Published: Mar 20, 2018

There are no references for this article.

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off