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Introduction Adjustment disorder (AD) is a time-delimited disorder characterized by excessive emotional distress or impaired functioning in response to an identifiable stressor. Although it is commonly diagnosed in mental health settings, its impact on occupational, social and other areas of functioning is not well understood. As a subthreshold disorder that is frequently diagnosed in conjunction with other physical and mental health disorders, the extent of its contribution to functional impairment may be obscured. During military service, research suggests AD is frequently diagnosed in early-service trainees. To help elucidate the relationship between AD and functional outcome, we explored 2 factors that may be associated with the rate of separation from service in U.S. active duty service members (SMs) with an AD diagnosis: previous mental health diagnoses and time in service when SMs receive an incident AD diagnosis (IADx). Materials and Methods Twenty-thousand SMs with an IADx were grouped by whether or not this was their first mental health diagnosis received in the military. To assess functional impairment, the 2 groups were compared on rate of separation. Those without prior diagnoses were then stratified into 5 groups based on length of time from military entrance to receipt of IADx and were further analyzed for separation rates. The Cox model was used to determine hazard ratios and create survival curves. The study was determined to be “not human subjects research.” Results Nearly half (46.4%) of SMs with an IADx previously had received a mental health diagnosis and had an increased risk of separation [hazard ratio = 1.25 (95% confidence interval: 1.207-1.286)]. Of SMs with IADx as their first diagnosis, 19.3% were diagnosed during the first 6 months of service and had the highest risk of separating [hazard ratio = 1.48 (1.381-1.589)], with a 60% probability of separating within 2 years of diagnosis. Those receiving it during the second 6 months of service (16.2%), second year (20.1%), or third year (18.2%) had approximately a 47% probability of separating within 2 years. Conclusions Previous mental health diagnoses and time in service when diagnosed appear to be important factors associated with functional impairment for SMs with AD. Nearly half of those with an IADx had previously received diagnoses for mood, anxiety, and other disorders and were at higher risk of separation following IADx. Our findings are based on diagnoses entered in electronic health records, so we cannot identify the nature of the stressor that precipitated AD. Nonetheless, early IADx predicted the fastest rate of separation, and it may be an opportune time for interventions to reduce its impact on functional outcomes.

INTRODUCTION Since the 1991 Gulf War, mental health conditions of military Service members have received increasing public attention and are a major focus for the U.S. government. A substantial proportion of military health research has been devoted to examining the pattern of change over time in mental health symptoms and diagnostic status among Service members. Unfortunately, many researchers continue to use somewhat obsolete methods to analyze trends and transitions in mental health, despite advances in statistical methodology that permit attention to the unique features inherent in longitudinal data. MATERIALS AND METHODS This article defines and describes data features and structures, and basic specifications of longitudinal data analysis to military health researchers. In particular, we highlight the respective impacts of missing data and intra-individual correlation on longitudinal data analysis. Based on the descriptions of the basic features in longitudinal data, we introduce several popular techniques to analyze a variety of longitudinal data types. RESULTS We demonstrate that traditional analytic techniques do not properly account for missing data and intra-individual correlation inherent in longitudinal data. Failure to use correct, appropriate models and methods can result in major bias in analytic results and mental health predictions. CONCLUSIONS Failure to use correct, appropriate models and methods in longitudinal data analysis can have unfortunate repercussions on a military health system that needs accurate findings to support valid policy decisions. By applying adequate models and methods, military health researchers will be able to better understand the complex interactions of biological, psychological, and social factors on mental health trends and transitions among military Service members.