AFRL-SA-WP-TR-2013-0003 Intelligence and Neuropsychological Aptitude Testing of U.S. Air Force MQ-1 Predator Pilot Training Candidates Wayne Chappelle, Psy.D., ABPP Neuropsychiatry Branch, USAFSAM N.V.T. Tran, MD, MPH Aerospace Medicine Education, USAFSAM William Thompson, M.A, Tanya Goodman, M.A., Kellie Hyde, Ph.D. NeuroStat Analytical Solutions San Antonio, TX November 2012 Final Report for September 2011 to September 2012 Air Force Research Laboratory 711th Human Performance Wing Distribution A: Approved for public School of Aerospace Medicine release; distribution is unlimited. Aerospace Medicine Dept Case Number: 88ABW-2013-0588, Neuropsychiatry Branch 11 Feb 2013 2510 Fifth St. Wright-Patterson AFB, OH 45433-7913 NOTICE AND SIGNATURE PAGE Using Government drawings, specifications, or other data included in this document for any purpose other than Government procurement does not in any way obligate the U.S. Government. The fact that the Government formulated or supplied the drawings, specifications, or other data does not license the holder or any other person or corporation or convey any rights or permission to manufacture, use, or sell any patented invention that may relate to them. Qualified requestors may obtain copies of this report from the Defense Technical Information Center (DTIC) (http://www.dtic.mil). AFRL-SA-WP-TR-2013-0003 HAS BEEN REVIEWED AND IS APPROVED FOR PUBLICATION IN ACCORDANCE WITH ASSIGNED DISTRIBUTION STATEMENT. //SIGNED// //SIGNED// ________________________________ ______________________________________ COL LEE BEYER, Chief FEC COL ROBERT E. CARROLL, Chair FE This report is published in the interest of scientific and technical information exchange, and its publication does not constitute the Government’s approval or disapproval of its ideas or findings. REPORT DOCUMENTATION PAGE Form Approved OMB No. 0704-0188 Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing this collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden to Department of Defense, Washington Headquarters Services, Directorate for Information Operations and Reports (0704-0188), 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. 1. REPORT DATE (DD-MM-YYYY) 2. REPORT TYPE 3. DATES COVERED (From – To) 1 Nov 2012 Final Technical Report Sep 2011 – Sep 2012 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Intelligence and Neuropsychological Aptitude Testing of U.S. Air Force MQ-1 Predator 5b. GRANT NUMBER Pilot Training Candidates 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER Wayne Chappelle, N.V.T. Tran, William Thompson, Tonya Goodman, Jennifer Heaton 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION REPORT USAF School of Aerospace Medicine NUMBER Aerospace Medicine Dept/FECN 2510 Fifth St. AFRL-SA-WP-TR-2013-0003 Wright-Patterson AFB, OH 45433-7913 9. SPONSORING / MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSORING/MONITOR’S ACRONYM(S) 11. SPONSOR/MONITOR’S REPORT NUMBER(S) 12. DISTRIBUTION / AVAILABILITY STATEMENT Distribution A: Approved for public release; distribution is unlimited. Case Number: 88ABW-2013-0588, 11 Feb 2013 13. SUPPLEMENTARY NOTES 14. ABSTRACT The increasing role of MQ-1 Predator aircraft in support of intelligence, surveillance, reconnaissance and weapons deployment operations has resulted in the need to increase the number of fully trained pilots. To date, there are no published studies assessing the cognitive functioning of MQ-1 Predator pilots despite the important role these operators have in current unmanned U.S. Air Force (USAF) aviation. To partially fill the gap in the literature, this study obtained comprehensive computer-based intelligence testing (Multidimensional Aptitude Battery-II) and neuropsychological screening (MicroCog) on USAF MQ-1 Predator nonrated pilot training candidates who passed the initial remotely piloted aircraft (RPA) flying screening course (n=108), nonrated training candidates who failed training (n=52), as well as USAF rated pilot training candidates who cross-trained to the MQ-1 Predator from manned airframes (n=157). The results of the study revealed nonrated pilot training candidates performed in the high average to superior range on a measure of intelligence. Nonrated pilot training candidates who passed training scored higher on measures of spatial analyses/reasoning, memory for novel spatial arrangements, general visual reasoning, visual construction, general executive reasoning, and general information processing accuracy when compared with nonrated pilot training candidates who failed training. Furthermore, nonrated pilot training candidates who passed training performed substantially higher on measures of spatial analyses/ reasoning, memory for novel spatial arrangements, visual reasoning, general information processing accuracy, and cognitive proficiency (a combination and accuracy of speed of information processing) in comparison to rated pilots who cross-trained from a manned airframe. The results of the study provide helpful normative data on cognitive and neuropsychological aptitudes that distinguish nonrated pilots who pass the initial RPA flying screening course. The results of the study provide insights into the aptitudes needed to adapt to the rigors of the training program, as well as the cognitive capabilities of those training candidates newly recruited for this career field. The results are considered for improving personnel selection and classification as well as aeromedical evaluation processes. 15. SUBJECT TERMS Remotely piloted aircraft, intelligence testing, neuropsychological aptitude testing, RPA pilots, personnel selection 16. SECURITY CLASSIFICATION OF: 17. LIMITATION 18. NUMBER 19a. NAME OF RESPONSIBLE PERSON OF ABSTRACT OF PAGES Dr. Wayne Chappelle a. REPORT b. ABSTRACT c. THIS PAGE 19b. TELEPHONE NUMBER (include area U U U SAR 36 code) Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std. Z39.18 This page intentionally left blank. TABLE OF CONTENTS Section Page LIST OF FIGURES ............................................................................................................... iii LIST OF TABLES ................................................................................................................. iii ACKNOWLEDGMENTS ..................................................................................................... iv 1.0 EXECUTIVE SUMMARY ....................................................................................... 1 2.0 INTRODUCTION ..................................................................................................... 1 2.1 Aerial Combat Demands for MQ-1 Predator Operations .................................... 2 2.2 Accession Sources for MQ-1 Predator Pilot Trainees ......................................... 3 2.2.1 Operationally Experienced Cross-Trained Rated Pilots .......................... 3 2.2.2 Operationally Inexperienced Rated Pilots ............................................... 4 2.2.3 Nonpilot Commissioned Officer Nonrated Pilots .................................... 4 2.3 Training Pipeline for MQ-1 Predator Pilots......................................................... 4 2.4 Cognitive Aptitudes of USAF Pilots.................................................................... 6 2.5 Aeromedical Importance of Normative Intelligence and Neuropsychological Test Data ............................................................................. 8 2.6 Purpose of the Study ............................................................................................ 9 3.0 METHODS ................................................................................................................ 10 3.1 Subjects ................................................................................................................ 10 3.2 Measures .............................................................................................................. 10 3.2.1 Multidimensional Aptitude Battery-II (MAB-II)..................................... 10 3.2.2 MicroCog ................................................................................................. 11 3.3 Nonrated Pilot Candidate Training Outcomes: Pass vs. Fail ............................... 12 3.4 Procedure ............................................................................................................. 13 4.0 RESULTS .................................................................................................................. 13 4.1 Calculating Group Means .................................................................................... 13 4.2 Assessing Multicollinearity Across Subtests within the MAB-II and MicroCog ...................................................................................................... 13 4.3 Assessing Between Group Differences ................................................................ 14 4.4 Discriminant Analysis (DA) of Cognitive Aptitudes Contributing to Training Outcomes Among Nonrated Pilot Training Candidates ........................ 16 4.4.1 Predictive Model Development ............................................................... 16 4.4.2 Cross-Validation of Model Development ................................................ 20 i Distribution A: Approved for public release; distribution is unlimited. Case Number: 88ABW-2013-0588, 11 Feb 2013 TABLE OF CONTENTS (concluded) Section Page 5.0 DISCUSSION ............................................................................................................ 21 5.1 Nonrated Training Candidates Who Passed vs. Those Who Failed RFS Training ........................................................................................................ 21 5.2 Variables Predictive of Pass vs. Fail Performance Outcomes Among Nonrated Pilot Training Candidates ..................................................................... 22 5.3 Nonrated Pilot Training Candidates Who Passed RPA Training vs. Rated Pilot Training Candidates Who Cross-Trained ......................................... 23 5.4 Aeromedical Implications .................................................................................... 24 5.5 Limitations of the Study....................................................................................... 24 6.0 CONCLUSIONS........................................................................................................ 25 7.0 REFERENCES .......................................................................................................... 26 LIST OF ABBREVIATIONS AND ACRONYMS .............................................................. 28 ii Distribution A: Approved for public release; distribution is unlimited. Case Number: 88ABW-2013-0588, 11 Feb 2013 LIST OF FIGURES Figure Page 1 General Training Pipeline Program Flow for RPA Pilot Training Candidates (July 2012) .............................................................................................. 5 LIST OF TABLES Table Page 1 Cognitive Aptitudes Considered Critical to MQ-1 Predator Pilot Performance According to Rated USAF RPA Pilot Training Instructors and Rated Pilots............ 8 2 MAB-II Factors, Subtests, and Descriptions ............................................................. 11 3 MicroCog Index Descriptions .................................................................................... 12 4 Between Group Means and Standard Deviations for Training Candidates ............... 14 5 Pearson Correlations Assessing Multicollinearity Across Subtests within the MAB-II ..................................................................................................... 15 6 Pearson Correlations Assessing Multicollinearity Across Subtests within the MicroCog .................................................................................................. 15 7 Between Group ANOVAs and Post-Hoc Dunnett Tests for the MAB-II .................. 17 8 Between Group ANOVAs and Post-Hoc Dunnett Tests for the MicroCog .............. 18 9 Linear Discriminant Function Coefficients for Variables Influencing Training Outcomes..................................................................................................... 19 10 Overall Predictive Accuracies for Initial Model Development ................................. 19 11 Overall Predictive Accuracies for Cross-Validation Model ...................................... 21 iii Distribution A: Approved for public release; distribution is unlimited. Case Number: 88ABW-2013-0588, 11 Feb 2013 ACKNOWLEDGMENTS The authors of this study would like to thank Mr. Jeff Wiseman and Mr. Robert Englehardt for their assistance. This study would not be possible without their knowledge and insights of the training pipeline, expertise in pilot training, engagement with subject matter experts, and collaboration regarding pass/fail training outcomes. The authors of this study would also like to share deep appreciation to the Wing Technology Council of the 711th Human Performance Wing for their interest and support in the direction of funds to carry out the goals and objectives of this study. iv Distribution A: Approved for public release; distribution is unlimited. Case Number: 88ABW-2013-0588, 11 Feb 2013 1.0 EXECUTIVE SUMMARY U.S. Air Force (USAF) MQ-1 Predator pilots have a critical role in intelligence, surveillance, reconnaissance basic surface attack and close air support operations. Such pilots are perceived by subject matter experts as having high levels of intelligence and visual-spatial aptitudes necessary to pass training and adapt to operational challenges. The increasing role of MQ-1 Predator aircraft in support of intelligence, surveillance, reconnaissance and weapons deployment operations has resulted in the need to increase the number of fully trained pilots. However, to date, there are no empirically published studies assessing the cognitive functioning of this high-demand and critical career field despite the important role these operations play in current USAF aviation. To partially fill the gap in the current literature, this study obtained comprehensive computer-based intelligence testing (Multidimensional Aptitude Battery-II) and neuropsychological screening (MicroCog) on USAF MQ-1 Predator nonrated pilot training candidates who passed the initial remotely piloted aircraft (RPA) flying screening course (n=108), nonrated training candidates who failed the training course (n=52), as well as rated pilot training candidates who cross-trained from manned airframes (n=157). Testing was obtained as part of the requirements for medical flight screening prior to candidates entering the pilot training pipeline. The results of the study revealed nonrated pilot training candidates performed in the high average to superior range on a comprehensive, standardized measure of intelligence. Nonrated pilot training candidates who passed training scored higher on measures assessing spatial analyses/reasoning, memory for novel spatial arrangements, general visual reasoning, visual construction, general executive reasoning, and general information processing accuracy when compared with nonrated pilot training candidates who failed training. Furthermore, nonrated pilot training candidates who passed training performed substantially higher on measures of spatial analyses/reasoning, memory for novel spatial arrangements, visual reasoning, general information processing accuracy, and cognitive proficiency (a combination and accuracy of speed of information processing) in comparison to those who cross-trained from a manned airframe. Such measures of intelligence and visual-performance based aptitudes are reasonably perceived as critical to adapting to training and operational requirements. The results suggest that cognitive aptitudes most likely predictive of performance center around visual-performance based abilities and cognitive proficiency, rather than simply high levels of general cognitive aptitude. The implications for aerospace medicine and the evaluation of USAF RPA pilot training candidates are discussed, and the results of the study are considered for improving personnel selection and classification as well as aeromedical evaluation processes for USAF RPA MQ-1 Predator pilots. 2. 0 INTRODUCTION Over the past decade, U.S. Air Force (USAF) remotely piloted aircraft (RPA) have emerged as critical assets to intelligence, surveillance, reconnaissance (ISR) and close air support (CAS) operations. Among the variety of USAF RPAs, the MQ-1 Predator and MQ-9 Reaper airframes have emerged as the most dominant weapons-bearing ISR platforms in support of theater operations. As a result, Predator/Reaper pilots have become critical assets to a uniquely challenging, high-demand, high-precision profession (1). The high demand for these missions and the unique aspects of RPA platforms that make them distinct from conventional manned 1 Distribution A: Approved for public release; distribution is unlimited. Case Number: 88ABW-2013-0588, 11 Feb 2013 airframes have led the USAF to seek training candidates from outside the traditional pool of pilots who are trained and rated to fly manned aircraft. RPA platforms are different from manned airframes, and little is known about the skills and abilities that are necessary to pilot these missions successfully. The effective selection of Predator/Reaper pilot training candidates for such aircraft is essential to successful training and operational performance. Although RPA operations are largely centered on advanced satellite and computer-based technology, subject matter experts (SMEs) perceive cognitive aptitudes have a key role in successful performance and adaptation to the demands of Predator/Reaper operations (1). 2.1 Aerial Combat Demands for MQ-1 Predator Operations Over the past decade, the MQ-1 Predator has served a variety of roles in providing real- time information to commanders for identifying fixed and moving targets, tracking enemy movements and assets, tracking and/or eliminating enemy combatants, catching insurgents planting roadside bombs, locating and destroying weapons caches, directing and protecting ground forces, safeguarding convoys, augmenting manned-strike missions, and surveying post- strike battle damage. Such aircraft provide a wide range of ISR and CAS capabilities in support of battlefield operations around the globe. USAF leadership lauds the role of the MQ-1 Predator as a complex force multiplier with dynamic air combat capabilities with the advantage of shielding crew members from the traditional aviation-related threats to personal safety (2). Within the last 5 years, the number of MQ-1 Predator missions and combat air patrols sustained 24 hours a day has increased significantly. For example, the number of weapons strikes conducted by MQ-1 Predator/MQ-9 Reaper aircraft in Afghanistan has progressively increased every year for the past few years, while the number of strikes provided by manned airframes has progressively declined. Since 2009, there have been approximately 1160 weapons strikes performed by RPA aircraft in Afghanistan. The shift in weapons strikes is reflective of USAF aviation operations becoming more reliant upon the decisive advantages of RPA capabilities. The success of the MQ-1 Predator as well as other RPA airframes (e.g., MQ-9 Reaper and RQ-4 Global Hawk) has influenced budget allocations for such aircraft beyond amounts requested by USAF leadership (3). The acquisitions budget is a demonstration of devotion to the vision of USAF leader that RPA operations will increasingly take over missions traditionally accomplished by manned airframes during this next century (2,4). Despite advancements in computer-based technology and the automated nature of certain aspects of RPA operations, USAF Predator pilots are central to effective surveillance, targeting, weapons deployment, and battle damage assessment of enemy combatants and assets. Such pilots perform a wide range of manual and computer-based tasks to actively and/or passively control, maneuver, and fly the aircraft during planned, unplanned, and in-flight emergencies. The following are examples of MQ-1 Predator pilot duties reported in qualitative studies based upon input from USAF training cadre and rated MQ-1 Predator operators (Nagy JE, Kalita SW, Eaton G, U.S. Air Force Unmanned Aircraft Systems Performance Analyses, Predator Pilot Front End Analysis (FEA) Report, SURVIAC-TR-06-203, Feb 2006; available through the Defense Technical Information Center to U.S. Government agencies and their contractors only) (1). 2 Distribution A: Approved for public release; distribution is unlimited. Case Number: 88ABW-2013-0588, 11 Feb 2013