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. Author manuscript; available in PMC: 2021 Dec 1.
Published in final edited form as: J Psychiatr Res. 2020 Sep 6;131:127–131. doi: 10.1016/j.jpsychires.2020.08.037

Different Trajectories of PTSD Symptoms During the Acute Post-Trauma Period

Zoe MF Brier 1,*, Julie Connor 2, Alison C Legrand 1, Matthew Price 1
PMCID: PMC7676876  NIHMSID: NIHMS1630869  PMID: 32961502

Abstract

The majority of adults in the United States will experience a potentially traumatic event during their lifetime, yet only a subset will develop posttraumatic stress disorder (PTSD). The trajectory of symptoms in the period of time immediately following the trauma (the acute post-trauma period) may be important in determining which individuals develop PTSD. The current study examined trajectories of PTSD symptom severity across the acute post-trauma period and if membership in these trajectories was predictive of PTSD symptom severity, depression symptoms, and functional impairment 1- and 3-months post-trauma. Four trajectories were identified: low and decreasing, rapid decreasing, slow decreasing, and high and consistent. Further, trajectory membership in the acute post-trauma period was found to predict differences in PTSD symptoms, depression symptoms, and functional impairment severity at both 1- and 3-months post-trauma. These findings highlight a relationship between PTSD symptoms during the acute post-trauma period and later impairment.

Keywords: Acute post-trauma period, Posttraumatic stress disorder, Latent Class Growth Analysis, Trajectories

1. Introduction

The majority of adults in the United States (89.7%) have experienced a potentially traumatic event (PTE) in their lifetime (Kilpatrick et al., 2013). Although most individuals recover, a portion (8.3%) develop Posttraumatic Stress Disorder (PTSD) (Kilpatrick et al., 2013). Specifically among survivors of traumatic injury, approximately 23% will criteria for PTSD within the first year of their traumatic event (Zatzick et al., 2007). This rate is a more than five-fold increase over the 12-month prevalence of PTSD in the general population (4.7%; Kilpatrick et al., 2013). Furthermore, PTE exposure is associated with a range of comorbid conditions, including depression (O’Donnell, Creamer, Bryant, Schnyder, & Shalev, 2003). Again, the prevalence of comorbid psychopathology is markedly higher among those who recently experienced a PTE than among the general population (Bryant et al., 2010). Despite considerable interest, it remains unclear why some who experience a PTE recover and others develop PTSD. PTSD is conceptualized as a lack of recovery after a PTE, and thus, the development of symptoms during the acute post-trauma period, defined as the 30 days post-trauma, may be important in distinguishing between these groups. Determining if different trajectories are present during this period would provide insight into which individuals are at elevated risk for PTSD and related impairments.

Initial conceptualizations of PTSD symptom development proposed a highly symptomatic trajectory and a resilient trajectory (Bryant, 2011). To capture these processes, the diagnosis of Acute Stress Disorder (ASD; American Psychiatric Association, 2013) was included in the DSM-IV (American Psychiatric Association, 1994). ASD was posited as a precursor for PTSD and represented the highly symptomatic trajectory (Bryant, 2006). Meeting criteria for ASD, however, does not adequately distinguish between those who do and do not develop PTSD. A review by Bryant (2011) examined the predictability of PTSD from an ASD diagnosis in 19 studies of adults. The majority of the studies with adult participants had low sensitivity, implying that the individuals who met criteria for PTSD at least two months post-trauma did not meet criteria for ASD. Specifically, 11 of the 19 studies of adults had less than 50% of participants who met criteria for both ASD and subsequent PTSD. This finding indicates that persistently elevated symptoms during the acute post-trauma period does not consistently predict PTSD.

Investigations into the course of PTSD symptoms after a PTE suggest that there is considerable heterogeneity in how symptoms present over time. One study found that almost half (44.1%) of participants who met diagnostic criteria for PTSD 24 months post-trauma did not meet for full or subthreshold criteria three months following the trauma (Bryant et al., 2013). Further, approximately half of the individuals who met criteria for a PTSD diagnosis at assessments 3, 12, and 24 months post-trauma did not meet the symptom criteria for a diagnosis within days of the trauma (Bryant et al., 2013). These results suggest that symptoms fluctuate considerably over longer periods of time. However, these fluctuations may follow distinct patterns by which individuals can be classified. Investigations are needed to determine how to define these classes of post-trauma symptoms trajectories.

Research that has examined the progression of PTSD symptoms over longer longitudinal periods classified individuals into trajectories based on symptom severity. A study conducted by deRoon-Cassini and colleagues (2010) assessed individuals who entered the Emergency Department for a traumatic injury, and again at 1, 3, and 6 months post-trauma. Participants fell into four latent trajectory classes based on their PTSD symptom trajectories: chronic distress (high symptom severity throughout), delayed distress (initially moderate, and then high severity), recovering (initially moderate, and then decreased severity), and low distress (low severity throughout). These results demonstrated that multiple symptom severity trajectories are present post-trauma. A limitation of the described study is the spacing of assessments, which occurred months after the PTE. It is unclear if similar classes are present shortly after a PTE, however.

Only one study was identified that examined trajectories shortly after a PTE. PTSD symptoms were assessed daily in individuals exposed to rocket fire related to the Israeli-Gaza conflict from 15 to 45 days following exposure (Greene et al., 2017). Similar latent classes to those observed in studies of longer periods were present during this time. Participants had symptoms that were consistently low, decreasing, consistently moderate, or consistently high. These results provide preliminary evidence that trajectories of PTSD symptoms may be present soon after the PTE. However, this study first assessed symptoms two weeks after the trauma. Thus, it may have missed important changes that take place shortly following the PTE. Additionally, symptom progression was monitored during an ongoing conflict as opposed to an event that had ended. The ongoing conflict may have affected the presentation of certain symptoms.

Further research on the progression of PTSD symptoms after a PTE has been limited by barriers to data collection during this period. It is difficult to measure symptoms regularly after a trauma because of the numerous ongoing issues that individuals who experience trauma face in this period. In vivo and experience sampling methods such as Ecological Momentary Assessment (EMA; Shiffman et al., 2008) are a potential solution to this problem. Such methods can effectively monitor symptom progress during periods in which participants are difficult to reach. These methods also decrease the potential for retrospective bias and overgeneralization of symptomology. Additionally, daily assessments can capture important fluctuations in symptoms that may be missed by spacing assessments further apart. The use of mobile technology to collect data is less burdensome than other assessment methods commonly used in psychological research. The majority of individuals in the United States (77% of adults) own a smartphone (Pew Research Center: Internet, Science & Tech, 2018), which can be used to collect EMA data. A recent study demonstrated the feasibility of daily PTSD assessments via mobile phone during the acute post-trauma period (Price et al., 2018). Thus, mobile devices can be used to monitor symptom progression after a PTE and identify symptom trajectories.

To date, no study has examined trends of daily PTSD symptoms across the acute post-trauma period and assessed whether specific profiles are predictive of PTSD. The current study examined the latent trajectories of PTSD symptoms for 30 days following a trauma. The reviewed literature identified latent trajectories of PTSD symptom severity in the months after a traumatic experience. Similar trajectories were found across studies: persistently elevated, persistently low, increasing in severity, or decreasing in severity. However, these studies have examined PTSD trajectories over several months. The present study also examined the relationship between trajectory membership and PTSD symptom severity 1- and 3-months post-trauma. It was hypothesized that individuals would fall into four latent trajectories: consistently elevated, increasing in severity, consistently low, and decreasing in severity. Further, it was hypothesized that trajectories of individuals who experienced consistently elevated or increasingly elevated symptoms would be most predictive of PTSD symptom severity 1- and 3-months post-trauma.

2. Method

2.1. Participants

Participants were 90 individuals who experienced a criterion A traumatic event and were admitted to the Acute and Critical Care service at a large northeastern university medical center. A criterion A event was defined as “exposure to actual or threatened death, serious injury, or sexual violence” (American Psychiatric Association, 2013). Informed consent was obtained for all participants. Table 1 presents the types of trauma experienced. Participants were eligible for the study if they owned a smartphone that ran the iOS or Android operating systems and experienced a criterion A traumatic event. Exclusion criteria included current suicidal ideation, current or recent history of psychosis, being in police custody, non-English speaking, or being in an altered state of mind which prevented giving informed consent. Ages for participants ranged from 19–63 years (M = 35.00, SD = 10.41) and 36.7% of the sample identified as female. The majority of the sample identified as White (88.9%), 4.4% as African American, 1.1% as Asian American, 1.1% as Pacific Islander, 2.2% as American Indian, and 2.2% as Bi-racial. The majority of participants completed high school (95.4%) and 39.9% completed college, and 32.2% reported an annual income of $30,000 or less. Injury Severity Scores (ISS) for the sample ranged from 1–43 (M = 14.31, SD = 11).

Table 1.

Type of trauma in the sample (N = 90)

Type of Trauma Percentage of Sample
Motor vehicle crash or motorcycle crash 50.0%
Assault 1.1%
Recreational accident 12.2%
Work Accident 7.8%
Fall 14.4%
Crush Injury 2.2%
Burn 7.8%
Other 4.4%
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2.2. Measures

Standardized Trauma Interview

(STI; Foa & Rothbaum, 2001). The STI is a 41-item interview administered by trained research assistants, which assesses details of a participant’s traumatic experience. The STI was used in the present study to assess if participants’ traumatic experience met criterion A.

PTSD Checklist for DSM-5

(PCL-5; Weathers et al., 2013). The original PCL-5 is a 20-item self-report measure which assesses severity of PTSD symptoms in which participants are asked to rate how much they were bothered by their symptoms on a Likert scale (0 = not at all, 4 = extremely). Scores on the PCL-5 range from 0–80, and a score of greater than 30 has been recommended as a cutoff for a probable diagnosis of PTSD in traumatic injury survivors (Geier, Hunt, Nelson, Brasel, & deRoon-Cassini, 2019). An 8-item adapted version of the PCL-5 (Price et al., 2016) was used in the present study to assess daily PTSD symptom severity to reduce participant burden of the daily mobile assessments. The abbreviated version assesses each of the four PTSD symptom clusters, as well as generates a total severity score. Higher scores indicate greater severity of PTSD symptoms and scores on the abbreviated measure range from 0–32. PTSD symptoms were also assessed 1- and 3-months after the initial trauma using the full PCL-5. PCL-5 scores assessed at 1-month had an internal consistency of 0.94 and PCL-5 scores at 3-months had internal consistency of 0.95.

Patient Health Questionnaire-8

(PHQ-8; Kroenke & Spitzer, 2002). The PHQ-8 is an 8-item self-report measure which measures the frequency of depression symptoms over the past two weeks on a Likert Scale (0 = Not at all, 3 = Nearly every day). Higher scores indicate increased severity of depression symptoms. The PHQ-8 is identical to the original PHQ-9, but does not include item-9, which assesses suicidal ideation. The PHQ-8 scores had an internal consistency of 0.88 at the 1-month follow-up and 0.91 at the 3-month follow-up.

Sheehan Disability Scale

(SDS; Sheehan et al., 1996). The SDS is a 3-item self-report measure which assesses impact of mental illness on functional impairment. The SDS is assessed 10-point Likert scale assessing impairment (0 = not at all, 10 = extremely) in categories of work/school activities, family relationships, and social functioning. Higher scores indicate greater functional impairment associated with mental health symptoms. SDS scores assessed at 1-month had an internal consistency of 0.86 and an internal consistency of 0.86 at 3-months.

2.3. Procedure

Recruitment:

Participants were recruited from the Acute and Critical Care Service at a large northeast hospital. Trained research assistants approached participants at bedside M = 4.88 days (SD = 5.22 days) post-trauma. Of the prospective participants for the study, 46 declined participation, 72 could not be approached due to ongoing medical care, and 22 were approached but did not have own a smartphone. Total data collection took approximately 23 months. Participants were instructed to download the mobile application Metricwire (Waterloo, Ontario) for EMA data collection to their smartphone, which was available for free download from the app stores.

Mobile Assessments:

Mobile assessments began within 1 week following the trauma and were examined for 34 days post-trauma in the current study. Participants received one mobile assessment per day in the evening between 7:00 PM and 8:00 PM, which included the 8-item PCL-5 to assess PTSD symptomology for that day. Participants were able to complete the assessment for 10 hours following the initial assessment prompt.

Follow-up Assessments:

Participants were contacted via phone by trained research assistants 1 and 3 months following the trauma to complete the full PCL-5, the PHQ-8, and the SDS.

2.4. Data Analytic Plan

Data preparation was conducted in R version 4.0.0 (2020). Thirty days of PCL-8 daily total scores were used in these analyses (days 5–34 post-trauma), resulting in 30 days of assessment data to calculate the class trajectories. Latent Class Growth Analysis (LCGA) was used to create trajectories and conducted using the LCMM package (version 1.91, Proust-Lima, Phillipps, Liquet, 2017). LCGA is an analytic technique that identifies latent trajectories and the probability that individual participants belong to a given trajectory. First, a traditional Latent Class Growth Model (LCGM) was estimated to examine the assumption of homogeneity in the sample. Then, models containing 2–5 classes were estimated with linear models (time scaled as 0, 1, 2, … , 29). The optimal model was assessed using the Information Criteria (IC) statistics [i.e., Bayesian information criterion indices (BIC), sample-size adjusted Bayesian information criterion indices (SSABIC), Aikake information criterion indices (AIC)], entropy values, and the Lo-Mendell-Rubin likelihood ratio test (LMR-LRT). Best fit was determined by lower IC statistics, entropy values above .80, and significant (p < .05) LMR-LRT. Three participants were not included in these analyses as they did not provide any mobile data. Thus, 87 participants were included in these analyses.

To determine if class membership was associated with PTSD, depression, and functional impairment, an series of ANCOVAs were conducted. Class membership was treated as the predictor variable, baseline scores were treated as a covariate, and scores at 1-month and 3-month were the outcome. To correct for multiple comparisons, a p-value correction was applied such a that a p-value of .017 was required for significance.

3. Results

3.1. Latent Class Growth Models

A simple LCGM was estimated for the data in order to examine heterogeneity between distinct classes. Mplus version 7.4 (Muthén & Muthén, 1998–2012) was used to run the LCGM This model did not provide a good fit for the data (χ2(df) = 1857.08(460) p < .001; RMSEA (90%) = .187 (.178, .196); CFI/TLI = .580, .603; SRMR = .089). Variances for intercept (32.96, p < .001) and slope (.021, p < .001) were also significant, implying that there was significant variability between individual participants in change over time.

3.2. Latent Class Growth Analysis Models

Linear models of two, three, four, and five classes were estimated. A four-class model demonstrated the optimal fit for the data (Table 2). It had the lowest BIC, SSABIC, and AIC, high entropy (.95), and the lowest LMR-LRT. The four-class model estimated a “low and decreasing” class (n = 40; 46.0%), a “rapid decreasing” class (n = 22; 25.3%), a “slow decreasing” class (n = 21; 24.1%), and a “consistently high” class (n = 4; 4.6%) (Table 3, Figure 1).

Table 2.

Fit Indices for Models with Two to Five Classes

Fit Index 2 Classes 3 Classes 4 Classes 5 Classes
AIC 8426.01 7983.44 7699.32 7635.50
BIC 8440.80 8005.63 7728.91 7672.49
SSABIC 8421.87 7977.23 7691.05 7625.16
Entropy 0.94 0.97 0.95 0.92
LMR-LRT 844.26 417.41 269.97 64.97
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Note: LMR-LRT: Lo-Mendell-Rubin Likelihood Ratio Test.

Table 3.

Growth Estimates for Trajectory Classes

Class Intercept (se) Slope (se)
Low/decreasing 2.60** (0.29) −0.07** (0.02)
Rapid Decreasing 8.29** (0.40) −0.12** (0.02)
Slow Decreasing 12.55** (0.36) −0.06* (0.02)
High/Consistent 24.29** (0.96) −0.01 (0.06)
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Note:

*

= p < .05.

**

= p < .001.

Figure 1.

Figure 1

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LCGA Trajectories Across Acute Post-Trauma Period

Note: Low: Low and decreasing; Rapid dec: Rapid Decreasing; Slow dec: Slow and decreasing; High: Consistently high

3.3. Distal Outcomes

A series of an ANCOVA’s suggested that class membership was significantly associated with PTSD and depression at 1 month and 3 month post trauma (p’s < .001). For PTSD symptoms at 1 month, the Low and Decreasing class (M = 6.08) had significantly lower symptoms at 1 month than all other groups. The Rapid Decreasing (M = 20.16) was significantly lower than the Slow Decreasing (M = 32.00) and High (M = 54.00) classes. The Slow Decreasing and High classes did not differ. For PTSD symptoms at 3 month, the Low and Decreasing (M = 5.25) and Rapid Decreasing (M = 12.89) classes did not differ from each other but did differ from the Slow Decreasing (M = 32.86) and High (M = 48.00).

For depression symptoms, the same patterns of differences were found for 1 month and 3 month post trauma. The Low and Decreasing (1-Month: M = 3.46; 3-Month: M = 3.19) and Rapid Decreasing (1-Month: M = 9.37; 3-Month: M = 4.86) classes did not differ from another. However, these classes did differ from the Slow Decreasing (1-Month: M = 12.25; 3-Month: M = 12.43) and the High (1-Month: M = 19.67; 3-Month: M = 16.00) classes. These two higher severity classes did not differ from one another.

The omnibus test for differences in functional impairment at 1 month was not statistically significant at the threshold set for the current analysis, F (3, 68) =2.76, p = .049. There was a difference amongst the classes at 3 month, however, F (3, 62) = 5.85, p = .001. Similar to the prior 3 month findings, those in the Low and Decreasing (M = 7.76) and Rapid Decreasing (M = 7.22) classes did not differ from another. These classes did differ from both the Slow Decreasing (M = 16.71) and the High (M = 21.50) classes. As with the other variables, these two higher severity classes did not differ from each other.

4. Discussion

The present study identified four distinct trajectories of PTSD symptom severity were identified: 1) low and decreasing, 2) rapidly decreasing, 3) slow decreasing, and 4) consistently high. Further, these trajectories were associated with different levels of PTSD and depression symptoms at 1-month in a dose-response manner such that increasing trajectory severity was associated with more severe symptoms. At 3-months post-trauma, there was a clear separation among the classes such that initial low and rapidly decreasing classes had lower PTSD, depression, and functional impairment than those in the slow decreasing and consistently high group. Interestingly, the mean level of these higher classes was above the proposed clinical cutoff for PTSD, suggesting that those who belonged to trajectories likely had PTSD. Taken together, these findings suggest that there are distinct trajectories of PTSD symptom progression in the month after a trauma and that trajectory membership is associated with distal outcomes. It is also of note that the high and consistent and slow decreasing groups were likely above the clinical cutoff of 30 for PTSD during the month post-trauma, using a proportional score (x 2.5) to convert their PCL-8 item scores to that of a total score. Thus, determining which trajectory an individual belongs to is important in determining their overall recovery.

These findings, when considered in the context of prior work, provide strong evidence for consistently low and consistently elevated classes. A study by deRoon-Cassini and colleagues (2010) found four similar, but not identical, trajectories. When assessed at baseline, 1-, 3-, and 6-months post-trauma, a chronic elevated, delayed, recovering, and consistently low class were found. A study that examined trajectories two weeks after the traumatic experience (Greene et al., 2017) found similar trajectory classes (e.g., low, reducing, moderate, high). Taken together, those with very low symptoms shortly after a trauma are likely to remain low throughout the acute post trauma period and are at low risk for subsequent mental health difficulties. Similarly, those with persistently elevated symptoms after a trauma are at increased risk for more severe mental health outcomes and are unlikely to have their symptoms resolve independently. Those in this group are likely strong candidates for early intervention.

The present study identified two moderate groups that presented with similar symptoms initially but followed divergent trajectories. Furthermore, these groups consistently differed in their PTSD, depression, and functional impairment months after the event. Those in the class with a steeper slope had less severe outcomes and did not significantly differ from those in the low class. Alternatively, those with the shallower slope had more severe outcomes and did not differ from those in the high class. These two trajectories highlight the difficulty in relying on a single measurement of post-trauma distress to predict distal outcomes. Continuous early assessment may make it possible to distinguish these groups over time. However, additional work is needed to confirm the presence of these two groups and how best to determine to which group a given individual belongs.

This study had several limitations of note. The sample was recruited from an Acute Care setting. Thus, all participants had an index event that was a traumatic injury, and the majority experienced a motor vehicle crash. Many types of traumatic experiences were not represented in the sample, such as interpersonal types of trauma (e.g., sexual assault). It is unclear if these results would generalize to other trauma types. Indeed, much of this literature has focused on victims of injury and this narrow focus may bias the field’s understanding of symptom development. Additionally, the PCL-8 was used for daily assessments rather than the full PCL-5 to reduce burden for participants. However, this reduces the amount of information collected for daily assessments, in that all 20 symptoms of PTSD were not assessed. Another limitation was the small sample size of the current study. Though the LCGA trajectories provide important information, LCGA assumes homogeneity within classes (Wickrama et al., 2016), implying that all members of a class have the same intercept and slope. Though analyses such as Growth Mixture Modeling (GMM) do not make these assumptions, they require larger sample sizes (Wang & Bodner, 2007). Therefore, further study is necessary to confirm the trajectories found in the present study.

The current study provided important information regarding individual development of PTSD symptoms during the acute post-trauma period, and aids in understanding how PTSD symptoms develop after a traumatic experience. These findings have the potential to aid in the development of a targeted early intervention for PTSD, specifically in the individuals who have elevated and constant symptoms in the first month post-trauma. Future research is important to explore these trajectories further and examine early intervention techniques.

Table 4.

Mean Distal Outcome Scores at 1- and 3-Month Follow-ups

PTSD Depression Functional Impairment
M SD M SD M SD
1-Month
Low/decreasing 6.08a 5.55 3.46a 3.45 12.62a 9.38
Rapid Decreasing 20.16b 12.04 9.37a 4.73 16.26a 9.80
Slow Decreasing 32.00c 14.90 12.25b 5.74 21.00a 6.72
High/consistent 54.00c 12.49 19.67b 5.13 23.50a 2.12
3-Month
Low/decreasing 5.25a 5.60 3.19a 3.88 7.76a 8.31
Rapid Decreasing 12.89a 10.49 4.89a 3.49 7.22a 7.29
Slow Decreasing 32.86b 16.45 12.43b 7.52 16.71b 9.66
High/consistent 48.00b 17.15 16.00b 7.55 21.50b 5.45
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Note: Superscripts denote significant differences among the classes within a time point and measure. Values with the same superscript are not significantly different at p < .05.

Highlights.

  • Four trajectories of PTSD symptom severity were found during the acute post-trauma period

  • Trajectories were low and decreasing, rapid decreasing, slow decreasing, and high and consistent

  • PTSD trajectory membership predicted PTSD symptom severity at 1- and 3- months post-trauma

  • PTSD trajectory membership predicts depression and disability at 1- and 3- months post-trauma

Footnotes

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The authors have no conflicts of interests to declare.

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