This longitudinal study examines the psychometric validity of the Subjective Traumatic Outlook (STO) questionnaire by evaluating its structural consistency and diagnostic performance in a conflict-affected context. The STO was used to measure trauma-related subjective distress at two time points following the terrorist attacks in Israel on 7 October 2023.

The primary aim of this study was to evaluate the STO as a concise and reliable assessment tool for populations affected by armed conflict.

A nationally representative sample of 4097 participants responded at T1, of whom 2005 completed the study at T2. Data were collected during the ongoing war in Israel. Participants completed the STO alongside validated measures of post-traumatic stress disorder (PTSD (PTSD Checklist for DSM-5) and International Trauma Questionnaire), depression, anxiety and adjustment disorder. Exploratory factor analyses were used to estimate one- to three-factor solutions using robust maximum likelihood estimation. Convergent validity was assessed through bivariate correlations with trauma- related measures. Receiver operating characteristic analyses were conducted to evaluate diagnostic utility for PTSD and complex PTSD per the ICD-11.

Exploratory factor analysis supported a stable two-factor structure across both waves. The STO demonstrated strong internal consistency and stable convergent validity over time. Receiver operating characteristic analyses indicated that the four-item version matched or slightly outperformed the five-item version, suggesting improved parsimony without loss of diagnostic accuracy.

The stable factor structure of the STO and its strong psychometric properties across both waves within a wartime context support its utility for large-scale screening and early detection of trauma-related distress.

Existing research on post-traumatic stress disorder (PTSD) development over time covers brief periods predominantly among military personnel, rather than civilians, and baseline measurements from before traumatic experiences are rarely available. This longitudinal study examined PTSD trajectories among Israeli civilians before and after the October 7, 2023, terror attack, exploring their associations with current and previous trauma.

Data included 1,231 Israeli Jewish adults from a quasi-representative sample surveyed at four time points: January 2018, April 2022, December 2023, and March 2024. Participants completed self-report measures, including the PTSD Checklist for DSM-5 (PCL-5), exposure to the October 7 attack and subsequent war, and trauma in childhood and adulthood. Latent growth mixture modeling identified PTSD trajectories.

Four trajectories were identified: resilience (70.4%), trauma recovery (9.4%), trauma vulnerability (16.8%), and chronic PTSD (3.5%). The chronic PTSD group exhibited persistently high symptoms, associated with greater childhood trauma and war-related exposure. The trauma vulnerability group showed low-medium pre-attack PTSD levels that escalated post-attack, associated with higher war-related stressors. The trauma recovery group had high pre-attack PTSD severity related to high trauma exposure, but showed significant symptom reduction post-attack.

This study, the first to examine PTSD trajectories in civilians after large-scale trauma, highlights diverse impacts. Most participants demonstrated resilience, while some exhibited chronic symptoms. Two trajectories – trauma vulnerability and trauma recovery – were event-responsive, suggesting that collective trauma can both exacerbate and paradoxically alleviate symptoms. Findings emphasize the need for targeted interventions and suggest future research using machine learning to refine PTSD trajectory prediction.

Bereavement is a globally prevalent life stressor, but in some instances, it may be followed by a persistent condition of grief and distress, codified within the 11th edition of the International Classification of Diseases (ICD-11) as prolonged grief disorder (PGD). Network analysis provides a valuable framework for understanding psychological disorders at a nuanced symptom-based level.

This study novelly explores the network structure of ICD-11 PGD symptomology in a non-Western sample and assesses the replication of this across three African country sub-samples in these data.

Network models were estimated using the “Inventory of Complicated Grief-Revised” in a sample of trauma-exposed individuals who experienced bereavement throughout life (N = 1,554) from three African countries (Ghana, n = 290; Kenya, n = 619; Nigeria, n = 645). These networks were statistically evaluated using the network comparison test.

It was found that “Feelings of Loss” and “Difficulty moving on” were the most central symptoms in the combined sample network. These findings were largely consistent for the Ghana and Nigeria sub-samples, however, network structure differences were noted in the Kenya sub-sample.

The identified PGD network highlights particular indicators and associations across three African samples. Implications for the assessment and treatment of PGD in these cultural contexts warrant consideration.

There is cumulative evidence of the importance of exploring the change of dynamics between symptoms over time as reflective of consolidation of psychopathology.

To explore the interactions between symptoms of ICD-11 adjustment disorder before and after the second lockdown of the COVID-19 pandemic in Israel and identify the most central symptoms and their concurrent and prospective associations with probable adjustment disorder.

This is a population-based study drawn from a probability-based internet panel. A representative sample of the adult Israeli population was assessed at two time points (T1, pre-second lockdown, n = 1029, response rate 76.17%; T2, post-second lockdown, n = 764, response rate 74.24%). Symptoms of adjustment disorder were assessed by the International Adjustment Disorder Questionnaire (IADQ).

Although the overall strength of associations at the two measurement points was similar and two same communities were found, there was a significant change in their structure, with a more consolidated network at T2. The most central item was ‘difficult to relax’ in both networks. Cross-sectionally, all symptoms of failure to adapt significantly predicted adjustment disorder. ‘Worry a lot more’ (preoccupation) and ‘difficult to adapt to life’ (failure to adapt) at T1 significantly predicted this diagnosis at T2.

Adjustment disorder symptoms consolidated during the second lockdown of the pandemic. In line with the ICD-11 conceptualisation of adjustment disorder, both preoccupation and failure-to-adapt symptoms have prognostic validity. This highlights the importance of identifying and targeting adjustment disorder symptoms during a period of stress such as the COVID-19 pandemic.

International Classification of Diseases, 11th revision (ICD-11) adjustment disorder (AjD) is characterized by two main symptom clusters: preoccupation with the stressor and failure to adapt to the stressor. The network analytic approach provides important information on the structural validity of a disorder and reveals which symptoms are most prominent. To date, no study compared the network structure of AjD symptoms in clinical and nonclinical samples, which could potentially inform our understanding of psychopathological mechanisms that underlie AjD and identify core targets for therapy.

A network analysis was conducted on AjD symptoms as assessed by the Adjustment Disorder—New Module (ADNM-8) using data from 330 clinical participants from the UK and a nonclinical sample of 699 participants from Switzerland.

Comparisons of network structure invariance revealed differences between the network structure of the clinical and the nonclinical samples. Results highlight that in terms of both edges strength and centrality, failure to adapt symptoms was more prominent in the clinical sample, while the preoccupation symptoms were more prominent in the nonclinical sample. Importantly, global strength was similar across networks.

Results provide evidence of the coherence of AjD in the ICD-11 as assessed by the ADNM questionnaire. They tentatively suggest that subclinical AjD may be characterized by emerging preoccupation symptoms that may result in failure to adapt and functional impairment in clinical manifestation of AjD. However, there is a need for replication and longitudinal research to further validate this hypothesis.

Adjustment disorder is one of the most widespread mental disorders worldwide. In ICD-11, adjustment disorder is characterised by two main symptom clusters: preoccupation with the stressor and failure to adapt. A network analytic approach has been applied to most ICD-11 stress-related disorders. However, no study to date has explored the relationship between symptoms of adjustment disorder using network analysis.

We aimed to explore the network structure of adjustment disorder symptoms and whether its structure replicates across questionnaire versions and samples.

A network analysis was conducted on adjustment disorder symptoms as assessed by the Adjustment Disorder–New Module (ADNM-8) and an ultra-brief version (ADNM-4) using data from 2524 participants in Nigeria (n = 1006), Kenya (n = 1018) and Ghana (n = 500).

There were extensive connections between items across all samples in both ADNM versions. Results highlight that preoccupation symptoms seem to be more prominent in terms of edges strengths (i.e. connections) and had the highest centrality in all networks across samples and ADNM versions. Comparisons of network structure invariance revealed one difference between Nigeria and Ghana in both ADNM versions. Importantly, the ADNM-8 global strength was similar in all networks whereas in the ADNM-4 Kenya had a higher global strength score compared with Nigeria

Results provide evidence of the coherence of adjustment disorder in ICD-11 as assessed by the ADNM questionnaire. The prominence of preoccupation symptoms in adjustment disorder highlights a possible therapeutic target to alleviate distress. There is a need to further replicate the network structure of adjustment disorder in non-African samples.