Evaluating the Effects of Fatigue on Police Patrol Officers in Lowell, Massachusetts, Polk County, Florida, Portland, Oregon, and Arlington County, Virginia, 1997-1998 (ICPSR 2974)

Version Date: Mar 30, 2006 View help for published

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Dennis Jay Kenney, Police Executive Research Forum

https://doi.org/10.3886/ICPSR02974.v1

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This study was undertaken to assess the connections between administratively controllable sources of fatigue among police patrol officers and problems such as diminished performance, accidents, and illness. The study sought to answer: (1) What is the prevalence of officer fatigue, and what are officers' attitudes toward it? (2) What are the causes or correlates of officer fatigue? (3) How does fatigue affect officer safety, health, and job performance? and (4) Can officer fatigue be measured objectively? The final sample was comprised of all sworn, nonsupervisory police officers assigned full-time to patrol and/or community policing functions on the day that data collection began at each of four selected sites: Lowell, Massachusetts, Polk County, Florida, Portland, Oregon, and Arlington County, Virginia. Part 1, Fatigue Survey Data, includes demographic data and officers' responses from the initial self-report survey. Variables include the extent to which the respondent felt hot or cold, experienced uncomfortable breathing, bad dreams, or pain while sleeping, the time the respondent usually went to bed, number of hours slept each night, quality of sleep, whether medicine was taken as a sleep aid, estimated hours worked in a one-, two-, seven-, and thirty-day period, how overtime affected income, family relationships, and social activities, and reasons for feeling tired. Part 2, Demographic and Fatigue Survey Data, is comprised of data obtained from administrative records and demographic data forms. Several measures from the initial self-report survey are also included in Part 2. Variables focus on respondents' age, sex, race, marital status, global score on the Pittsburgh Sleep Quality Index scale, total years as a police officer assigned to any agency and current agency, and total years worked in current shift. Data for Part 3, FIT and Administrative Data, were obtained from administrative records and from the fitness-for-duty (FIT) workplace screener test. Variables include a pupilometry index score and the dates, time, and particular shift (days, evenings, or midnight) the officer started working when the pupilometry test was administered. Part 3 also includes the number of hours worked by the officer in a regular shift or in association with overtime, the number of sick leave hours taken by the officer, and whether the officer was involved in an on-duty accident, injured on duty, or commended by his/her department during a particular shift.

Kenney, Dennis Jay. Evaluating the Effects of Fatigue on Police Patrol Officers in Lowell, Massachusetts, Polk County, Florida, Portland, Oregon, and Arlington County, Virginia, 1997-1998. Inter-university Consortium for Political and Social Research [distributor], 2006-03-30. https://doi.org/10.3886/ICPSR02974.v1

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United States Department of Justice. Office of Justice Programs. National Institute of Justice (96-IJ-CX-0046)

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Inter-university Consortium for Political and Social Research
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1997 -- 1998
1997-07 -- 1998-06
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The effects of fatigue on human behavior, performance, and physiology are well understood and widely known. Excess fatigue arising from sleep loss, circadian disruption, and other factors tends to decrease alertness, impair performance, and worsen mood. As such, it is reasonable to expect that the performance, health, and safety of patrol officers, as well as police-community relations, are adversely affected by the fatigue an officer may experience. This study was undertaken to assess the connections between administratively controllable sources of fatigue among police patrol officers and problems such as diminished performance, accidents, and illness. The study sought to answer: (1) What is the prevalence of officer fatigue, and what are officers' attitudes toward it? (2) What are the causes or correlates of officer fatigue? (3) How does fatigue affect officer safety, health, and job performance? and (4) Can officer fatigue be measured objectively?

Four police agencies were recruited to participate in the study. Once the officers meeting the selection criteria were identified and the purpose of the study was explained during the officers' roll call sessions, officers were asked to volunteer to participate in the study. All participating officers were assigned identification numbers and given initial self-report surveys to complete during a roll call briefing. The survey instrument included all 19 items from the Pittsburgh Sleep Quality Index (PSQI), combined with additional questions designed to capture information on officer demographics, experience, attitudes regarding fatigue held by respondents themselves and their peers, and perceptions regarding the causes and effects of fatigue, particularly on professional performance and physical and emotional well-being. The PSQI was scored as a global index as well as on seven sub-scales. These included sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction. Demographic information was also collected later from either demographic data forms placed in officers' mailboxes (with instructions to complete and return to the on-site study coordinator) in Polk and Arlington counties, or from administrative records for officers in Portland and Lowell. In addition to the subjective measures of fatigue, all officers were asked to take a non-invasive eye-reduction test throughout the study period at the beginning of each on-duty shift. This objective test, referred to as the fitness-for-duty (FIT) workplace screener test, produces a pupilometry reading that indicates changes in the central nervous system that result from the influence of fatigue. The tester itself was a self-contained, tabletop unit that required the test subject to look into a view port and visually follow a lighted target for approximately 30 seconds. The test was completely safe and caused no discomfort to the participant. Each time an officer's pupilometry reading fell in the top 10 percent of measures (the most tired), he or she was asked to complete a brief questionnaire designed to gather additional information to help explain his or her current fatigue level. Administrative data were also collected from each participating agency through a review of administrative files, including personnel files and payroll records. Among the data gathered were the number of work and leave hours taken by each participating officer during the study period, the shifts each officer worked, and the number and type of accidents, complaints, and commendations each officer incurred during the study period.

Convenience sampling.

All sworn, nonsupervisory police officers assigned full-time to patrol and/or community policing functions at each of four sites: Lowell, Massachusetts, Polk County, Florida, Portland, Oregon, and Arlington County, Virginia.

Parts 1-3: Individuals

self-enumerated questionnaires, Fitness-For-Duty (FIT) Workplace Safety Screener Test, and official records

Part 1, Fatigue Survey Data, includes demographic data and officers' responses from the initial self-report survey. Variables include the extent to which the respondent felt hot or cold, experienced uncomfortable breathing, bad dreams, or pain while sleeping, the time the respondent usually went to bed, number of hours slept each night, quality of sleep, whether medicine was taken as a sleep aid, estimated hours worked in a one-, two-, seven-, and thirty-day period, how overtime affected income, family relationships, and social activities, and reasons for feeling tired. Part 2, Demographic and Fatigue Survey Data, is comprised of data obtained from administrative records and demographic data forms. Several measures from the initial self-report survey are also included in Part 2. Variables focus on respondents' age, sex, race, marital status, global score on the Pittsburgh Sleep Quality Index scale, total years as a police officer assigned to any agency and current agency, and total years worked in current shift. Data for Part 3, FIT and Administrative Data, were obtained from administrative records and from the fitness-for-duty (FIT) workplace screener test workplace screener test. Variables include a pupilometry index score and the dates, time, and particular shift (days, evenings, or midnight) the officer started working when the pupilometry test was administered. Part 3 also includes the number of hours worked by the officer in a regular shift or in association with overtime, the number of sick leave hours taken by the officer, and whether the officer was involved in an on-duty accident, injured on duty, or commended by his/her department during a particular shift.

Unknown.

Several Likert-type scales were used.

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2001-12-14

2018-02-15 The citation of this study may have changed due to the new version control system that has been implemented. The previous citation was:
  • Kenney, Dennis Jay. Evaluating the Effects of Fatigue on Police Patrol Officers in Lowell, Massachusetts, Polk County, Florida, Portland, Oregon, and Arlington County, Virginia, 1997-1998. ICPSR02974-v1. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2001. http://doi.org/10.3886/ICPSR02974.v1

2006-03-30 File UG2974.ALL.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads.

2006-03-30 File CB2974.ALL.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads.

2001-12-14 ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection:

  • Standardized missing values.
  • Checked for undocumented or out-of-range codes.
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Notes

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