Assessment of Traumatic Stress Symptoms During the Acute Posttrauma Period

Initial efforts to identify those at greatest risk for PTSD sought to use information that was based on an individual’s functioning at the time of trauma or in the immediate aftermath when acute care services were provided (7–9). Although work has supported that certain risk factors, such as previous trauma exposure (10) and preexisting psychopathology (11), are associated with an increased PTSD broadly, it is unclear how these factors affect initial symptom presentation posttrauma. An initial attempt to capture psychopathology in the acute aftermath after a PTE was the creation of the diagnosis of acute stress disorder in the DSM-IV (12). Acute stress disorder overlaps with symptoms of PTSD, including intrusion, dissociation, negative mood, avoidance, and arousal symptoms (13). A primary goal of the acute stress disorder diagnosis was to allow individuals to receive a diagnosis 2 days after their PTE and thus begin services related to treatment. It was also hypothesized that acute stress disorder could serve as a precursor to PTSD. Unfortunately, this hypothesis has not been supported, as an acute stress disorder diagnosis is not a reliable predictor of future posttrauma psychopathology (14). A systematic review examined 19 studies in which an acute stress disorder diagnosis was used as a predictor of future PTSD. In 11 of these studies, fewer than 50% met criteria for both acute stress disorder and later PTSD. These results provide compelling evidence that acute stress disorder and possibly elevated symptoms during the acute posttrauma period alone do not consistently predict a future diagnosis of PTSD. Therefore, other identification methods are needed to accurately detect who is at risk after a PTE.

Subsequent studies have developed self-report screening tools intended to have strong predictive power in determining subsequent risk for PTSD. One of the first studies evaluated a 10-item self-report measure to predict PTSD and major depressive disorder, which are commonly comorbid (8). The measure had excellent psychometric properties and showed excellent utility in identifying those at low risk of developing PTSD and major depressive disorder. It had limited utility, however, in identifying those at high risk for developing PTSD. A similar set of results were obtained for another study that evaluated a comparable measure—it had considerable utility in identifying those at low risk for PTSD but not those who would likely develop PTSD (9). Other efforts to create such instruments have shown limited utility when relying on a single measure (15). These efforts have shown that the use of self-report instruments administered shortly after the traumatic event are likely helpful for screening out those at risk but may not fulfill the need for a method to identify those who are at risk for PTSD.

Efforts to develop prediction methods that use data obtained at the time of the trauma have expanded to utilize large quantities of data and sophisticated analytic methods. PTSD is a highly heterogenous disorder, such that predicting those at greatest risk likely requires information from a range of sources (16, 17). An early investigation leveraged the considerable data available in medical records to characterize risk for subsequent PTSD (18). This approach showed promise but did not achieve the high level of predictive accuracy in its initial evaluation. A key limitation that was cited was the variability in the available data per person that could be used for such a model. That is, electronic medical records may not have complete information for an individual, which can undermine the ability of these models to make accurate predictions. More recent efforts have enhanced medical record data with self-report information obtained from the individual, characteristics about the trauma, and physiological information that is available to improve such prediction accuracy (19). The inclusion of a large number of variables, referred to as high-dimensional data, requires the use of sophisticated analytic methods such as machine learning. These strategies have been shown to be capable of accurately classifying individuals with and without chronic PTSD when examining established cases (19). When applied to predicting individuals at risk for PTSD, they show some improvements beyond the use of medical records alone or self-report inventories (17, 20). Indeed, the prediction accuracy of these models continues to be significantly better than chance but requires continued refinement before use in large-scale clinical practice.

Taken together, these studies suggest that it is challenging to predict those at risk for PTSD using data available only at the time of the traumatic event. There are several reasons for this difficulty. First, PTSD can have numerous presentations, such that two individuals with a diagnosis may present quite differently in a clinical setting. Identifying a method that can accurately predict multiple presentations that fall under a single umbrella diagnosis is a challenge. Second, the onset of PTSD may represent a developmental process in which symptoms contribute to and reinforce one another (21–23). Therefore, identifying those at risk may require understanding and evaluating this process rather than trying to predict a diagnosis at a single future time point. This approach would require an examination of symptom changes over the acute posttrauma period to provide a more comprehensive picture for who will develop PTSD.

A diagnosis of PTSD requires that symptoms persist for at least a month after the PTE, which prevents a diagnosis from being made shortly after the PTE (13). Implicit in this criterion, however, is that the symptoms are present during this period. Recent conceptualizations of PTSD have proposed that the symptoms may represent a dynamic system that develops after a traumatic event and ultimately sustains itself (22, 24). For example, an individual who experiences a PTE initially may have intrusive thoughts about the event and a strong reaction to PTE cues (cluster B PTSD symptoms). This elevated reactivity may contribute to an avoidance of situations that may contain potential PTE cues (cluster C). The feedback loop of intrusions and avoidance results in an increased sensitization toward cues of the PTE, which manifests as hyperarousal and an exaggerated startle (cluster E). This elevated and sustained stress response limits the individual’s desire to engage in enjoyable activities and interact with others, which leads to negative views of the self and strong negative affect (cluster D). This hypothetical progression points to the potential benefit of continued assessment during the acute posttrauma period, as it would provide greater insight into the individual’s recovery and potential points for intervention.

Despite the considerable variability that is observed across patients, the range of recovery and nonrecovery responses after a PTE has been shown to fall into a set of well-established trajectories. In the years after a traumatic event, individuals often will display a chronic course of symptoms, a delayed onset of symptoms, one of recovery in which symptoms are initially elevated but decline, or one of resilience in which symptoms remain low throughout (25). A large analysis that pooled results from 3,083 participants recruited from emergency departments around the world found evidence for these four trajectories in the first year after a traumatic event (26). A handful of studies that have focused exclusively on the weeks after a traumatic event have supported the presence of elevated (persistently elevated symptoms), moderate (persistently moderate symptoms), recovery (moderate symptoms that decline in the first 30 days), and resilience (persistently low symptoms) trajectories (27, 28). The consistent identification of these trajectories across a range of locations and samples potentially provides a method forward for early risk identification for PTSD. Rather than attempting to predict those who might meet criteria for a diagnosis at some point in the future, it may be more effective to predict the recovery trajectory that an individual may follow.

More recent efforts have attempted to find predictors of those who are likely to follow a trajectory in which symptoms persist. In the pooled analysis described previously, women, individuals from a marginalized racial-ethnic group, those with a history of interpersonal trauma, and individuals who experienced an assault were all associated with being a member of a more symptomatic trajectory (26). Related studies have shown that distress at the time of the trauma, diminished social support, and time in the acute care setting may also be associated with a highly symptomatic trajectory (17). Further, research has examined specific posttraumatic symptomology during the acute posttrauma period and how it may relate to symptoms that become chronic. A network analysis found intrusions and reactivity to be central symptoms during the acute posttrauma period, whereas fear-based and affect-related symptoms (e.g., emotional numbing, anger and irritability, etc.) were central in those with chronic PTSD (29). These results point to a range of potential variables that may serve as useful predictors of trajectory membership and highlight the critical need for more research in this area.

The need for our continued examination of PTSD symptom trajectories and symptom development in the immediate aftermath of a PTE has highlighted several challenges for research and clinical care teams. Chief among these challenges is the ability to obtain valid assessment data from individuals who recently experienced a PTE. The period after a PTE is filled with a range of competing concerns and demands (30) that can interfere with an individual’s ability to complete regular assessments. For example, mobility difficulties may limit an individual’s ability to attend sessions with providers for a thorough interview or gathering of biological data. Fatigue and pain may limit willingness to complete regularly administered self-report measures. This barrier to obtaining high-quality data during this period has limited the field’s understanding of how PTSD and related disorders develop shortly after a PTE.

Technological solutions provide a means to overcome many challenges in collecting data in the acute posttrauma period. In the United States in 2021, 85% of adults owned a smartphone, and 97% of adults owned a cellphone (31), making mobile technology an important means for accessing trauma-exposed individuals and assessing trajectories of symptoms. Research suggests that self-report data of traumatic stress symptoms collected from a mobile device by smartphone are comparable with such data collected with paper and pencil (32) and that these devices can be used to assess posttrauma symptomology (33). Thus, mobile devices allow for the collection of valid self-report or interview-style data. Allowing participants to complete the assessments when it is most convenient for them increases the opportunity to gather such data during the sensitive period after a PTE. Further, mobile technology use during this period will allow clinicians to assess patients’ progression of symptoms with minimal burden. That is, providers can review incoming information from participants in a manner that fits within their workflows rather than having to be “on demand” for a given patient. Thus far, research collected during the acute posttrauma period has examined the feasibility and acceptability of mobile technology using both self-report measures and, more recently, wearable, passive sensing technology (34–37). This work has consistently shown that these approaches are accepted and preferred by patients.

Mobile devices can collect a wide range of information. The manner of information has been categorized as active and passive data collection. There are strengths and limitations of each type, as outlined in the following text.

The availability of new tools to monitor recovery after a PTE, identify individuals at risk, and intervene when it is appropriate has resulted in the development of acute posttrauma mental health programs (48–51). One such initiative is the Trauma Resilience and Recovery Program (TRRP), a technology-enhanced, stepped-care program designed to address the mental health needs of survivors of traumatic injury using four steps: in-hospital education, screening, and brief intervention; tracking patients’ emotional recovery by means of an automated text-messaging system; a 30-day screen using a chatbot to identify patients who are good candidates for psychological treatment; and provision of referral to best-practice treatment. This model of care has been found to be feasible and acceptable among both adult and pediatric patients (5, 52). TRRP is able to effectively identify at bedside those who are at a higher risk for elevated posttrauma symptoms 30 days after the injury (53) and has since been implemented in 10 additional Level I and Level II trauma centers in the southeastern United States.

Patients are eligible for the program if they are admitted to the hospital for at least 24 hours for their injury. The program follows a stepped-care model in which adult patients are screened at bedside using the Injured Trauma Survivor Screen (ITSS) (54) to assess for symptoms of traumatic stress and depression, and all patients are provided brief psychoeducation of the program. The ITSS is a nine-item measure; all of the items have “yes” or “no” responses. Each item assesses risk for PTSD, depression, or both PTSD and depression by asking about past history and current symptomology since the accident. Patients with significant scores on the ITSS are then provided a brief bedside intervention, which involves a flexible combination of evidence-based psychoeducation and skills focused on early recovery from trauma. At this time, patients are given the option to enroll in both daily text messaging over the acute posttrauma period and the 30-day screen.

During this acute posttrauma text assessment period, patients answer questions regarding their daily psychological distress. These questions include six questions from the Kessler–6 (55, 56) and four questions that assess trauma-related specific symptoms (53). Patients receive one question by text per day, and questions rotate over a 10-day block. Patients are contacted by a chatbot for a 30-day screen, in which they complete the Patient Health Questionnaire–9 (PHQ-9) (57) to assess depression symptoms over the previous 2 weeks and the PTSD Checklist for DSM-5 (PCL-5) (58) to assess PTSD symptoms over the past month. Clinically significant symptoms on the PCL-5 are indicated by a total score ≥33 (59), and a score ≥10 on the PHQ-9 (60). Those who are clinically significant on these measures are then provided referrals to appropriate mental health services. Among these are telehealth services provided by TRRP; see Ruggiero et al. (5) for a full description of this stepped-care model.

TRRP goes beyond “screen-and-treat” methodologies described previously (e.g., a one-time symptom screen immediately posttrauma), through continuous monitoring over the acute posttrauma period. Patients who choose to enroll in the program are given the option to opt in to daily text messaging and the 30-day follow-up, regardless of the presence of significant symptoms captured through baseline measures. This is important, as the initial presence of traumatic symptoms (or lack of symptoms) does not necessarily indicate recovery versus resilience trajectories over the acute posttrauma period. Daily text messaging collects self-report data over the acute posttrauma period. Average ratings of distress over aggregated 10-day blocks from the texting data have been shown to be predictive of clinically elevated scores on the 30-day follow-up (53). This indicates that, despite the presence of missing data collected through active data collection, mobile technology still provides a useful screening tool during this time. A recent study examined differences in engagement and retention rates between Black and White patients enrolled in TRRP (61). There were no significant differences in use of the text-message system found between Black and White patients enrolled in TRRP, in which 35.7% of enrolled Black patients and 39.5% of enrolled White patients used the system. Additionally, there were no differences in completion between Black (39.6%) and White (40.1%) patients at the 30-day follow-up. This study also examined differences in engagement by type of injury. Those who were hospitalized for a violent injury (e.g., gunshot wound) had a higher risk to loss of follow-up at the 30-day follow-up. Considerations for engaging survivors of violent injury may include partnerships with violence intervention programs in both the hospital and the community (61). These considerations will be particularly important for not only continuing to engage patients in screening immediately after the acute posttrauma period, but also engaging patients in treatment in the future.

TRRP is also highly automated, thus reducing burden to providers through the use of technology. An extensive amount of information can be collected during the active collection of information over the acute posttrauma period without the need of additional personnel. The success of this program highlights the importance of technology as an assessment tool to aid in the detection of symptoms during the acute posttrauma period. An additional important consideration is the need for personnel and resources to implement a program such as TRRP. Many hospital systems and acute care facilities may not have the necessary resources to follow up with patients after the acute posttrauma period. Recent best practice guidelines from the American College of Surgeons (62) state that additional mental health assessments can be administered to patients who screen positive on acute posttrauma measures, which may provide a more comprehensive understanding for appropriate individualized patient referrals.

Although initiatives such as TRRP successfully reach and assess individuals who have experienced a traumatic injury or those who have sought medical care after a PTE, there is a need for similar strategies to address other types of PTE—especially those in which an individual may not seek medical attention shortly after the PTE. These include survivors of sexual assault or intimate partner violence, or those with experiences of childhood maltreatment, among others. Relatedly, the modern hospital-based system does not have sufficient resources to implement such a service in every type of care unit (63–65). Thus, methods to access these individuals and engage them in initiatives to assess acute posttrauma reactions are imperative for examining previous findings in these populations.

Although significant progress in expanding the understanding of symptom development and progression during the acute posttrauma period has been made since the introduction of the acute stress disorder diagnosis into the DSM-IV, gaps in the research remain that limit the practical applicability of these findings. It remains unclear as to what key variables are predictive of future chronic courses of PTSD. It is unlikely that there is a single variable that will have a highly accurate predictor, and algorithmic solutions show the most promise for risk prediction. Several considerations for future work can help improve our ability to identify those at risk.

Implementation of changes to the assessment method approach are necessary to continue collecting temporal symptom changes that may occur over the acute posttrauma period. Previous research has aimed to assess these changes using repeated-measures assessment, such as active data collection. However, progress in this area has been limited by high variability in participant compliance in assessment, and data aggregation is often needed in analyses (40), thereby eliminating nuanced changes in self-reported symptoms. Passive data collection of participant biomarkers by means of wearable technology may provide this nuance but has, thus far, been limited in research with trauma-exposed populations, and even more so during the acute posttrauma period. Future work should focus on identifying the biomarkers that are most relevant to PTSD recovery that can be obtained using passive data. Once such markers are identified, the full potential of passive sensing as a means to monitor the acute posttrauma period can be fully realized. Currently, as seen in initiatives such as TRRP, providers in health care settings can utilize these technologies as an important resource in obtaining highly relevant clinical information across the acute posttrauma period, which can aid in early identification of symptoms and allow providers to make referrals to appropriate services.

It is important to consider how these approaches may be incorporated into screening tools that are currently in place for early identification, such as the Screening, Brief Intervention, and Referral to Treatment, a tool used to screen and identify those at risk for substance use disorders (66). Evidence-based treatment protocols, such as Concurrent Treatment of PTSD and Substance Use Disorders Using Prolonged Exposure (67) are available that aim to treat co-occurring substance use and PTSD. Future work should be conducted to assess early intervention approaches to known evidence-based treatment to simultaneously screen and assess risk for comorbid conditions posttrauma.

A concern consistently highlighted by this literature is the overrepresentation of studies that examine the acute posttrauma period in participants who are survivors of traumatic injury and the lack of such research in other trauma-exposed populations. This is partly due to the nature of recruitment during the acute posttrauma period. Those who have experienced a traumatic injury are likely to present at an emergency department or acute care setting. In contrast, other trauma-exposed individuals, particularly those who have experienced interpersonal trauma, may not seek immediate care. Further, those with interpersonal trauma may be less likely to seek treatment because of stigma or fear around the disclosure of the traumatic experience itself, making these individuals “hard-to-reach” populations in research recruitment (68, 69). Although challenges with recruiting for research studies present with these populations in traumatic stress research broadly, it is especially difficult during the acute posttrauma period due to time sensitivity in data collection. As with all community-based research, building rapport with community organizations that work with trauma-exposed populations is crucial (68), and additional work is necessary to build these relationships to reach these populations during the acute posttrauma period.

It is also necessary to consider this work in the context of minoritized groups in the United States. Broadly, there are wide disparities that are based on race-ethnicity regarding access to and engagement in mental health treatment (70). These disparities are the result of provider bias toward racial and ethnic minorities and associated mistrust of the medical system (71). Specifically in treatment for PTSD, multiple studies have found that those from minoritized racial or ethnic backgrounds have lower initial initiation in treatment as well as reduced retention than White Americans (72). Further, research has found the usability of technology-based mental health resources to be decreased in minoritized populations (73), implying lack of community stakeholder involvement in the initial creation of these technologies (74). Taken together, cultural adaptations of posttrauma digital mental health with involvement from the community will be important for engaging minoritized populations in this work.

There is a limited time frame after a PTE to identify individuals who may be most at risk for later development of posttrauma psychopathology. Considerable attention should be given to readily accessible prevention-based tools to identify those at a greater risk for developing PTSD. Because of the innovation of limited large-scale programs and technology-based assessments to monitor individuals after traumatic experiences, early signs of posttrauma symptoms can be captured at the onset. Still, much of the established work and identification methodology is conducted with traumatic injury populations over limited periods. Future studies should examine other trauma-exposed populations to assess for acute trauma reactions and validate previous study findings on future symptomology. The acute posttrauma period is a highly dynamic period of time, and the use of resources such as mobile technology will allow clinicians and providers to identify those who may be most at risk and obtain important information to direct patients to the necessary next steps in their recovery.