International Military Testing Association 25

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International Military Testing Association2528
October 2004
Medical Indicators of Successful United States
Military-Specialty Training
L.E. Banderet, Ph.D. 1 V.J. Rice, Ph.D. 2
S.C. Allison, Ph.D. 1 J.F. Creedon, Ph.D.
1 M.A. Sharp, M.S. 1 1 U.S. Army Research
Institute of Environmental Medicine Natick,
MA USA 2 ARL-HRED AMEDD Field Office Ft. Sam
Houston, TX USA
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U.S. Army Medical Department Centerand School,
Fort Sam Houston, Texas

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Military Program Characteristics


Program Weeks Rank n
Mental Health Specialist 15 Enlisted 190
Occupational Therapy Specialist 17 Enlisted 120
Physician Assistant 52 Cadet 155
Physical Therapy Specialist 19 Enlisted 206
671
?
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Military Specialties Illustrated

PA
PT
OT
MH
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Methodology

• Mixed Model Design (between- and within-volunteer
  comparisons).
• Volunteer recruitment (first day) and three
  questionnaire administrations performed by Cadre
  from a different program.
• Questionnaires given at the beginning (first day)
  of the course, midway, and at the end 60 min
  per administration.
• Data from the Somatic Stress Scale, Profile of
  Mood States (POMS), Clyde Mood Scale, and Quality
  of Life Inventory (QOLI) reported on today.
• Appropriate safeguards ensured confidentiality of
  the volunteers data.
• These data are preliminary.

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Booklet MethodologySomatic Stress Questionnaire

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• Somatic Stress measured at midpoint and end of
  each course was greater than for the other two
  conditions studied.
• Levels at the midpoint and end were greater (on
  average) than those during the volunteers prior
  assignment.
• Levels of stress had an interaction (Somatic
  Stress increased for MH and OT before the course
  end whereas, PA and PT levels decreased).

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• Levels of Fatigue-Inertial had an interaction
  (Fatigue-Inertial trends depended upon program
  and of course completed).
• Anger-Hostility scores were greatest at end of
  course.
• Anger-Hostility scores differed in some programs
  (e.g., MH, PA).
• Relative rank ordering of the Anger-Hostility
  and Fatigue-Inertial measures observed by
  program.

Mean Construct Score
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• Friendly scores decreased during the course and
  depended upon the program.
• Students had greatest Sleepy scores at midpoint
  Sleepy scores varied with program.
• MH students were consistently Sleepy during the
  course. Even first day, MH students were very
  Sleepy.

Norm (Mean)
Norm (Mean)
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Norm (Mean)

• Sleepy scores (all students) were associated with
  Pass/Fail status at the beginning, midpoint, and
  end of course.
• Sleepy scores at the beginning were associated
  with Pass/Fail even before the course began.

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• QOLI rating from Work varied significantly with
  program.
• Ratings from Play interacted with the program and
  course completed.
• Self Esteem had an interaction PA and PT
  greatest levels MH and OT least.
• Ratings from Self Esteem were greater (2X) than
  those for Work and Play.

NOTE 25 1.76 50 2.65
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• ASVAB (GT) Scores were significant predictors of
  Pass/Fail in each program studied.
• Differences of 5-7 points appeared to
  differentiate Pass/Fail status.
• Soldiers studied ranked in the top 66-89 of the
  general population.

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Logistic Regression of ASVAB (GT) Scoreswith
Pass/Fail

• Comparison-group scores (n 81) could have
  precluded acceptance into some of these military
  programs however, many passed!
• Program was not a significant factor in LR
  analysis.
• Increased ASVAB scores provided greater odds
  ratios.

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Predictors of Course Pass/Fail

Predictor Association with Passing
Age Positive
Time on Active Duty Positive
Marital Status Positive with being married
ASVAB (GS) Score Positive
Rotters Locus Control Negative with external control (PA and PT)
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Summary

• Showed that psychological measures with norms
  can be used to document the effects of stress
  in medical academic programs.
• Demonstrated that, in these medical programs,
  psychological and demographic measures are
  associated with Pass/Fail.
• Dr. Rice is planning a study with Field Medics
  (91-W)in collaboration with us, incorporating
  some of these measures.
• Future analyses will identify the relative
  contributions of various predictor variables to
  the Pass/Fail relationship from this study.

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Conclusions

• Varied dependent measures (demographic, medical,
  psychological) predict academic outcomes such as
  Pass/Fail.
• Medical and psychological measures provide useful
  information about students adjustment (e.g.,
  Sleep, Quality of Life, Somatic Stress, Mood).