The Lackland Behavioral Questionnaire: The use of biographical data and statistical prediction rules for public safety screening.

Abstract

Screening for public safety positions (e.g., police officers, fire fighters, military service members) is a difficult and challenging task. Notably, the military has been widely criticized because of the general lack of an empirically based system or program for mental health screening. The purpose of the present study is to describe the use of statistical prediction rules for this task. Prediction rules were derived and validated using U.S. Air Force (USAF) recruits in basic military training (N = 50,322). Items from the Lackland Behavioral Questionnaire were used as predictors. General attrition (discharge for any reason before completing term of service) and disciplinary offenses (including criminal charges) were used as outcomes. For trainees in the top 2% or 1% of the general attrition prediction rule, 63% and 68% were discharged before they completed their first 4 years. The base rate was 25%. Similarly, for trainees in the top 2% or 1% of the disciplinary offenses prediction rule, 35% and 39% had a significant disciplinary offense over the following 4 years. The base rate was 15.5%. The results suggest that we may be able to use biographical data inventories and statistical prediction rules to identify a small percentage of trainees in public safety fields with significant mental health or behavioral histories who are at elevated risk for general attrition and disciplinary offenses. (PsycINFO Database Record

Psychological interventions for posttraumatic stress injuries among public safety personnel: a systematic review and meta-analysis

“…For example, among military personnel and veterans exposed to combat-related violence, the lifetime prevalence of PTSD is as high as 31% [18][19][20][21][22][23]. Public safety personnel (PSP) are also exposed to PPTE more frequently than the general population [24][25][26][27][28][29][30]. The term PSP refers to several related occupations with professionals dedicated to maintaining public safety and wellbeing, such as border services o cers, correctional workers, re ghters, paramedics, police, and public safety communicators (e.g., call centre operators, 911 operators).…”

Methodological advances in statistical prediction.

“…In mental health settings, in addition to predicting violence, they have been useful or at least showed promise for predicting (a) onset of psychosis (Cannon et al, 2008), (b) course of mental disorders (Kessler et al, 2016), (c) psychotherapy failure (Boswell, Kraus, Miller, & Lambert, 2015), and (d) suicide attempts and suicides (Kessler et al, 2015; Walsh, Ribeiro, & Franklin, 2017). In military settings, statistical prediction has been used to identify trainees who are likely to have poor mental health or behavioral outcomes, so that these trainees can be interviewed and recommendations and referrals can be made (Garb, Wood, & Baker, 2018). For all of these tasks, one can expect statistical prediction to be more successful than clinical judgment.…”

“…Failure to complete term of service is an important issue for the United States Air Force because so many active duty enlisted personnel are discharged before they complete their first four years. In a sample of 89,032 active duty personnel, the relation between excessive drinking and discharge rate was not monotonic (Garb, 2013). The highest discharge rates were obtained for personnel who drank excessively more than once a week (five or more drinks in a sitting).…”