Adjustment disorder in ICD-11
Adjustment disorder has been identified as one of the most prevalent mental disorders worldwide.Reference Evans, Reed, Roberts, Esparza, Watts and Ritchie1,Reference Reed, Correia, Esparza, Saxena and Maj2 According to ICD-113 adjustment disorder is a maladaptive reaction to a stressful life event, ongoing psychosocial adversities or a combination of stressful life situations that usually emerges within a month of the occurrence of a stressor and tends to resolve within 6 months, unless the stressor persists for a longer duration. In ICD-11, adjustment disorder is characterised by two main symptom clusters: ‘preoccupations with the stressor’, which includes symptoms such as recurrent and distressing thoughts or rumination about the stressor or its implications, and ‘failure to adapt’, which includes difficulties concentrating, sleep disturbances and an inability to recover emotionally.Reference Maercker, Brewin, Bryant, Cloitre, Ommeren and Jones4,Reference Shevlin, Hyland, Ben-Ezra, Karatzias, Cloitre and Vallières5 For a diagnosis of adjustment disorder, the symptoms must be associated with significant impairment in functioning.
Operationalisation of adjustment disorder
The introduction of specific diagnostic criteria in ICD-11 represents a change in the conceptualisation of adjustment disorder, which previously was considered as a diagnosis if a person failed to meet criteria for another disorder.Reference Maercker, Brewin, Bryant, Cloitre, Ommeren and Jones4 In parallel to the development of the adjustment disorder symptom criteria, a scale to assess adjustment disorder has been developed for validation of the newly proposed concept. Maercker et alReference Maercker, Einsle and Köllner6 introduced and initially validated a 29-item self-report questionnaire, the Adjustment Disorder–New Module (ADNM), which was later condensed to 20 items.Reference Glaesmer, Romppel, Brähler, Hinz and Maercker7 The ADNM-20 can be used to assess the two core symptom clusters of adjustment disorder in ICD-11 (preoccupation with the stressor and failure to adapt), as well as accessory stress-related symptoms (depression, anxiety, avoidance, impulsivity). Several validation studies of both ADNM versions indicated good psychometric properties (for example convergent and discriminant validity, factor structure, internal consistency).Reference Glaesmer, Romppel, Brähler, Hinz and Maercker7,Reference Lorenz, Bachem and Maercker8 More recently and in line with the conceptualisation of adjustment disorder in the ICD-11, an eight-item brief version, consisting of only the core symptomsReference Kazlauskas, Gegieckaite, Eimontas, Zelviene and Maercker9 and an ultra-brief measure consisting of only two items of preoccupation and two items of failure to adaptReference Ben-Ezra, Mahat-Shamir, Lorenz, Lavenda and Maercker10 were produced and validated. Findings demonstrate that both the brief ADNM-8 and the ultra-brief ADNM-4 subscales are reliable and valid instruments for the assessment of adjustment disorder.Reference Kazlauskas, Gegieckaite, Eimontas, Zelviene and Maercker9,Reference Ben-Ezra, Mahat-Shamir, Lorenz, Lavenda and Maercker10
Network analytic methods
The coherence of ICD-11 adjustment disorder has been predominantly explored using factor analytic methods, as described in the above-mentioned studies. However, factor analytic models assume a pre-determined set of factors.Reference Borsboom and Cramer11 This inherent limitation of latent variable models means they are less efficient in providing the full complexity of relationships among the different symptoms of adjustment disorder.
The network approach, on the other hand, conceptualises mental disorders as systems of connected symptoms rather than reflecting an unobservable disorder. The symptoms co-occur because they reciprocally reinforce each other, not because they arise from a common underlying cause.Reference Borsboom and Cramer11,Reference Borsboom12 One of the advantages of the network approach is that the interconnections of symptoms can be mathematically analysed and visually exemplified. A network structure consists of ‘nodes’ that represent the symptoms studied and edges that represent the relationship between nodes. Edges have thicknesses (‘weights’) corresponding to the strength of the association between the nodes they connect. Graph theory has been used to represent different spatial and functional characteristics that reveal information about the type of relationship between the nodes in the network.Reference Contreras, Nieto, Valiente, Espinosa and Vazquez13 Visualising adjustment disorder in this way allows insight into the complex relations among its symptoms and allows estimating the structure of the different measures described.
From a clinical point of view, network analytic techniques place the focus on understanding the individual symptoms of a syndrome and can identify the symptoms that are most central within the adjustment disorder network and convey a high level of clinical information.Reference Contreras, Nieto, Valiente, Espinosa and Vazquez13 Central symptoms are those with many strong connections to other symptoms, greater numbers of connections, and those that bridge between other symptoms.Reference Borsboom14 Identifying central symptoms of a disorder is of crucial importance to clinicians in order to guide intervention efforts. It may also identify key symptoms associated with the prognosis of patients, rather than relying on global scores or a dichotomous diagnosis. Preliminary findings suggest that symptom centrality is related to the longitudinal course of a disorder.Reference van Borkulo, Boschloo, Borsboom, Penninx, Lourens and Schoevers15 In the case of adjustment disorder, very few disorder-specific interventions have been developed to dateReference Bachem and Casey16 and thus, obtaining information on symptom centrality may be particularly relevant for improving future treatment efforts.
The network analytic approach has been applied to most ICD-11 stress-related disorders, such as complicated grief,Reference Robinaugh, LeBlanc, Vuletich and McNally17 post-traumatic stress disorder and complex post-traumatic stress disorder.Reference Knefel, Tran and Lueger-Schuster18 However, to date, adjustment disorder has not been explored using this statistical framework for its newly defined core symptoms. Considering the controversies around adjustment disorder and the new structure in ICD-11, it is worthwhile to explore the networks for adjustment disorder symptoms.
The current study
We aimed to analyse the symptoms network of ICD-11 adjustment disorder using scales that estimate the core symptoms only, i.e. the brief ADNM-8 and the ultra-brief ADNM-4, in a large data-set including three samples collected in Nigeria, Kenya and Ghana. This strategy allowed us to compare the similarity of the network results in both questionnaire versions and across three different samples. We aimed to:
(a) assess conceptual validity by exploring which of the symptoms were strongly associated with one another and were geographically located adjacently. Support for ICD-11 conceptualisation would be reflected in stable connectivity of the network with high connections among preoccupation symptoms and among failure to adapt symptoms. Preoccupations should be associated to a lesser degree with failure to adapt symptoms.
(b) examine which symptoms are most central and whether they belong to the preoccupations – or the failure to adapt cluster, and
(c) to explore the stability of findings between samples and ADNM versions.
Method
Participants and procedure
The study sample included 2524 participants from Nigeria (n = 1006), Kenya (n = 1018) and Ghana (n = 500). Each sample was drawn from a panel using stratified and random probability sampling methods to ensure a close approximation of representativeness in terms of census data on age and gender in each country (for more information regarding samples seeReference Ben-Ezra, Hyland, Karatzias, Maercker, Hamama-Raz and Lavenda19). The study was approved by the institutional review board at Ariel's University (AU-MBE-2018-1029). Each participant signed an electronic informed consent prior to participation. Inclusion criteria were citizenship of one of the following countries (Nigerian. Ghana and Nigeria), age over 18 and having English proficiency.
Measurements
The Adjustment Disorder–New Module-8 (ADNM-8)Reference Kazlauskas, Gegieckaite, Eimontas, Zelviene and Maercker9 assesses preoccupation and failure to adapt similarly to the ICD-11. Participants first rate a list of stressors, indicating which stressors they experienced during the previous 2 years. Then, they rate the presence of adjustment disorder symptoms during the past 2 weeks. Four items refer to preoccupation with the stressor(s) and four items assess failure to adapt symptoms (see Table 1). Each item is scored on a four-point Likert-type scale (1, never; 2, rarely; 3, sometimes; 4, often). The total score of the ADNM-8 is the sum of responses to all items, and higher scores are indicative of greater severity of adjustment disorder. The internal reliability of the ADNM-8 was satisfactory for Ghana (0.91), Kenya (0.90) and Nigeria (0.90) for total scores as well as for the preoccupation and the failure to adapt subscales, in Ghana (0.85, 0.83), Kenya (0.85, 0.84) and Nigeria (0.86, 0.83), respectively.
F statistics, means (s.d.) of the Adjustment Disorder–New Module (ADNM) items of the three samples
All P-values are <0.001, means sharing a common subscript are not significantly different at α = 0.01 according to Bonferroni significant difference procedure.
The ADNM-4Reference Ben-Ezra, Mahat-Shamir, Lorenz, Lavenda and Maercker10 is an ultra-brief version of the ADNM-8 with a clear factor structure and good convergent and discriminant validity. It assesses adjustment disorder core symptoms (preoccupations and failure to adapt) with two items each (see Table 1). Each item is scored on a four-point Likert-type scale (1, never; 2, rarely; 3, sometimes; 4, often). The score of the total ADNM-4 is the sum of responses to all items, and higher scores are indicative of greater severity of adjustment disorder. The internal reliability of the ADNM-4 preoccupation and failure to adapt scales were acceptable for the Ghana (0.82), Kenya (0.83) and Nigeria (0.80) samples.
Statistical analysis
Regularised partial correlation networks across the three samples
More information regarding network estimation and stability and accuracy of both edges and the centrality index techniques can be found in Supplementary materials available at https://doi.org/10.1192/bjp.2021.46.
Network estimation and visualisation
We estimated partial pairwise correlations parameters between all nodes, through a Gaussian graphical model (GGM). The methodology is described in details in the Supplementary materials section. We used the graphical least absolute shrinkage and selection operator (Graphical Lasso; implemented in qgraph), which visualises sparse networks using part correlations, and considered the ordinal scale of the questionnaire.
Network stability
We examined the stability of the individually estimated networks, including estimating 95% confidence intervals around the edge-weights and estimating a correlation-stability coefficient for strength centrality. More information regarding the network analysis techniques can be found in the Supplementary materials, and in a tutorial.Reference Epskamp, Borsboom and Fried20
Network comparisons
To compare differences between networks, we estimated network differences between each pair of networks using the NetworkComparisonTest (NCT) package in R.Reference Kazlauskas, Gegieckaite, Eimontas, Zelviene and Maercker9 More information regarding the network comparisons techniques can be found in the Supplementary materials.
Results
Descriptive information
Table 1 shows the mean scores on the adjustment disorder core symptoms items across the three samples. All items differed across the three samples, although the effect size (η2: small, 0.10; medium, 0.25; large, 0.50) were generally small. The Kenyan sample had higher mean scores in all individual symptoms compared with both Ghana and Nigeria. The rates of probable adjustment disorder were high in all three countries: Ghana (23.4%), Kenya (27.8%) and Nigeria (17.7%). The samples had different numbers of stressors F(2, 2521) = 34.91, P < 0.001, η2 = 0.03, which is a medium-large effect. People from Kenya and Nigeria reported higher rates of stressors compared with Ghana, in particular assault, financial problems, move to a new home, unemployment, illness of loved one and death of a loved one.
Regularised partial correlation networks across the three samples
Network estimation of the ADNM-8
Estimated networks are shown in Supplementary Fig. 1. To enhance visual comparability of edges, we estimated the average layout of the three networks and presented all networks using this layout (Fig. 1). In the ADNM-8 symptoms network, 19 of 28 possible edges (67.9%) in the Ghana network, 21 of 28 possible edges (75.0%) in the Kenya network, and 20 of 28 possible edges (71.4%) in the Nigeria network were non-zero. This designates that the symptoms had extensive connections with each other in all samples. The visual inspection of the three networks exhibited many consistent edges across the samples, such as most robust connections between the preoccupation item: ‘repeated thoughts’ (item 1) and ‘sense of burden’ (item 2). Next in the hierarchy of edges strength is the association between the impairment in functioning item (item 8) and failure to adapt items (item 6 – ‘difficulties doing work/tasks’ and item 7 – ‘sleep difficulties’).
Networks of Adjustment Disorder–New Module (ADNM)-8 Adjustment disorder symptoms in three African samples using average spring layout. (a) Kenya; (b) Ghana; (c) Nigeria.
Nodes represent ADNM-8 items, and edges regularised partial correlations with Lasso penalty. Distances among nodes and thickness of edges relate to the size of their partial correlations. Blue edges (lines) indicate positive relations and black edges indicate negative relationships. ADNM 1: repeated thoughts; ADNM 2: sense of burden; ADNM 3: difficulties concentrating; ADNM 4: constant memories; ADNM 5: thoughts revolve; ADNM 6: work/tasks difficulties; ADNM 7: sleeping problems; ADNM 8: functional Impairment. The full items can be found in Table 1.
In the Nigerian sample, there was also a substantial association between the failure to adapt item 6 (‘difficulties going to work/doing daily tasks’) and item 7 (‘sleep difficulties’), as well as a strong association between the preoccupation item 4 (‘constant memories’) and item 5 (‘thoughts often revolve’). In the Ghana sample, the preoccupation item 4 (‘constant memories’) was strongly associated with the failure to adapt item 3 (‘difficulties concentrating’).
Network stability of the ADNM-8
To confirm the visual similarity of networks, we used Spearman correlations of edge-weights for all combinations of networks, which are presented in the Supplementary materials. Analysis shows that the accuracy of the edges was satisfactory.
The results of the confidence interval showed that edge-weights were moderately large. In addition, the results showed low accuracy of the centrality strength index (see the Supplementary material text, results: Network accuracy and stability and Supplementary Figs 3–6).
Network inference of the ADNM-8
The standardised strength centrality estimates are presented in Supplementary Fig. 2. Item 2 (‘sense of burden’) was the node with the highest strength centrality in all networks. However, the nodes with the smallest centrality differ between networks, although in all of them, it was from the ‘failure to adapt’ subscale. In the Ghana network, it was the ‘difficulties going to work/doing daily tasks’, in the Kenya network, it was ‘sleep problems’, and in the Nigeria network, it was ‘constant memories’.
Network comparisons of the ADNM-8
Results from the network comparison test showed that global strength values per group were 3.56, 3.55 and 3.51 for Ghana, Kenya and Nigeria, respectively (S-statistics for each pair of samples ranged from 0.01 to 0.06 and P-values ranged from 0.32 to 0.89). The Nigeria network structure differed from Ghana (M = 0.19 (where M is an index for comparison between networks), P = 0.01). Kenya and Ghana (M = 0.14, P = 0.28) as well as Kenya and Nigeria (M = 0.09, P = 0.59) were similar concerning structure and the level that nodes were connected.
Network estimation of the ADNM-4
Estimated networks are shown in the Supplementary Fig. 7. We estimated the average layout of the three networks and presented all networks using this layout (see Fig. 2). In the symptoms network of adjustment disorder according to ADNM-4, six of six possible edges (100%) in the Ghana and Kenya networks, and five of six possible edges (83.3%) in the Nigeria network were non-zero. This designates that the symptoms had highly extensive connections with each other in all samples.
Networks of Adjustment Disorder–New Module (ADNM)-4 adjustment disorder symptoms in three African samples using average spring layout. (a) Kenya; (b) Ghana; (c) Nigeria.
Nodes represent ADNM-4 items, and edges regularised partial correlations with Lasso penalty. Distances among nodes and thickness of edges relate to the size of their partial correlations. Blue edges (lines) indicate positive relations. ADNM 1: sense of burden; ADNM 2: constant memories; ADNM 3: difficulties concentrating; ADNM 4: work/tasks difficulties. The full items can be found in Table 1.
The visual inspection of the three networks exhibited many similarities across the three samples, such as most robust connections between the two items of the preoccupation items and between the two items of the failure to adapt scale. The third item of difficulties in concentrating was associated with the two preoccupation items. The fourth item of difficulties with work/tasks was relatively weakly related to the failure to adapt items.
Network stability of the ADNM-4
The results of the confidence interval showed that edge-weights were moderately large. In addition, the results showed high accuracy of the centrality strength index (see Supplementary material, Results: Network accuracy and stability and Supplementary Figs 9–12 for more details).
Network inference of the ADNM-4
Analysis shows that the accuracy of the edges is satisfactory. The standardised strength centrality estimates are presented in Supplementary Fig. 8. Item 2 (‘constant memories’) was the node with the highest strength centrality in all networks. In the Kenyan network, it was equally central with item 3 (‘difficulties to concentrate’). In all three networks the least central item was ‘difficulties in work/tasks’.
Network comparison of the ADNM-4
Global strength values per group were 1.51, 1.55 and 1.48 for Ghana, Kenya and Nigeria, respectively. Ghana did not differ from Kenya (S = 0.04 P = 0.40) and Nigeria (S = 0.03 P = 0.53). The Kenyan network had a higher global strength compared with Nigeria (S = 0.6 P = 0.05). The Nigerian network structure differed from that of Ghana (mean 0.15 P = 0.05). Kenyan and Ghana (mean 0.11 P = 0.34) as well as Kenyan and Nigeria (mean 0.11 P = 0.12) networks were similar concerning structure and the level that nodes were connected.
Discussion
Main findings
The current study investigated the symptom network structure of ICD-11 adjustment disorder in three nationally representative samples from Nigeria, Kenya and Ghana. To our knowledge, this was the first investigation of ICD-11 adjustment disorder network structure. Results suggested extensive connections between items in all samples in the ADNM-8 and robust highly extensive associations in the ADNM-4 network. The network structure was relatively consistent across questionnaire versions and countries regarding the inter-associations between nodes, and results suggest that preoccupation symptoms seem to be most central to the clinical picture of adjustment disorder. This consistency of findings provides further evidence for the conceptual validity of this newly defined condition as assessed by the ADNM questionnaire. In particular, the clinical picture arising from the findings gives support to the preoccupation symptoms as more central, while failure to adapt symptoms and functioning were intertwined.
Conceptual validity
The first aim of the study was to assess conceptual validity of adjustment disorder by exploring the individual symptoms’ dynamics (i.e. evaluating which of the symptoms are strongly associated with one another). The results partially support the syndromic integrity of ICD-11 adjustment disorder as assessed by ADNM-8. Specifically, there was high connectivity between two preoccupation items – item 1 ‘repeated thoughts’ and item 2 ‘sense of burden’. Although the first symptom represents an objective observation of repeated thoughts, the second symptom represents the subjective appraisal of burden related to repeated thoughts. However, across all three networks, the remaining two preoccupation items (items 4 and 5) were not highly connected to the network based on partial correlations, which suggests that they do not add unique variance to the adjustment disorder network. Scrutinising the phrasing of the items, it is evident that item 1, item 4 and item 5 are highly similar. It is possible that these items assess the same symptom (repetitive thoughts about the stressor) rather than representing distinct symptoms of the preoccupation syndrome.
In line with this explanation, both preoccupation items of the ADNM-4 (item 2 and item 4) were highly connected and seem to represent distinct aspects of the preoccupation syndrome, that are significant above and beyond others. This finding suggests that the ADNM-4 may be sufficient to represent preoccupations as assessed by the ADNM questionnaire and implies that some items on the 8-item version may have been redundant. This is further shown by satisfactory stability of the strength centrality in the ADNM-4 network as opposed to the poor stability of the strength centrality in the ADNM-8. Nevertheless, future research should evaluate whether they adequately cover the preoccupation cluster of adjustment disorder.
Failure to adapt items did not represent a strongly interrelated network in the ADNM-8. This finding is in line with earlier observations of acceptable but relatively low internal consistencies of the subscale, ranging from Cronbach's α = 0.71 in a help-seeking sampleReference Kazlauskas, Gegieckaite, Eimontas, Zelviene and Maercker9 to α = 0.80 in a non-clinical sample exposed to burglary.Reference Lorenz, Bachem and Maercker8 The weaker associations between different failure to adapt nodes as compared with preoccupation nodes, however, has face validity, since they cover a variety of symptoms from concentration difficulties to sleep problems. Interestingly, the analysis of the network structure revealed that two failure to adapt items (item 6 ‘difficulties doing work/tasks’ and item 7 ‘sleep difficulties’) are strongly associated with functional impairment in adjustment disorder. This finding suggests that failure to adapt symptoms as assessed by the ADNM-8 are more strongly associated with functional impairment compared with preoccupation symptoms. It can also imply that failure to adapt is intertwined with functional impairment, perhaps a subjective perception of it, as opposed to more actual malfunctioning.
The failure to adapt item 3 (‘concentration difficulties) was associated to an equal extent with preoccupation symptoms as with other failure to adapt symptoms. Consequently, concentration difficulties may act as a bridge symptom between the two core symptom clusters, potentially increasing the likelihood of experiencing one syndrome when experiencing the other.Reference Cramer, Waldorp, Van Der Maas and Borsboom21 Concentration problems may be a result of both preoccupation and failure to adapt symptoms. For example, it is possible that preoccupations, such as constant, uncontrollable memories (for example item 4), are a cause of concentration difficulties among patients with adjustment disorder. At the same time, concentration difficulties may result from sleep problems (item 7), which belongs to the failure to adapt cluster. As the network approach does not assume that the indicators of a disorder are independent, it can visualise such potentially causal relationships.Reference Borsboom12 Future research is needed in order to clarify the temporal order and interdependence of adjustment disorder symptoms.
Overall, the two adjustment disorder core symptom clusters of preoccupations and failure to adapt were clearly interrelated. This finding aligns with previous factor analytical studies that lent support to a unidimensional conception of adjustment disorder as assessed by the ADNM. They showed high correlations of between 0.75 to 0.96 between subfactors of adjustment disorder.Reference Glaesmer, Romppel, Brähler, Hinz and Maercker7,Reference Zelviene, Kazlauskas, Eimontas and Maercker22 The current study contributes to this evidence by using a methodology that did not assume latent factor but rather visualises the complex relationships between symptoms.
Central symptoms
The second aim of the study was to examine which symptoms are most central to the adjustment disorder network and whether they belong to the preoccupations or the failure to adapt core symptom clusters. In the ADNM-8 and ANDM-4, the node with the highest strength centrality belonged to the preoccupation scale. More specifically, in ADNM-8 the preoccupation item 2 (‘sense of burden’) had the highest strength centrality in all three networks. This finding, however, was limited by the fact that the stability of the index was insufficient, creating some ambiguity about the centrality of this preoccupation symptom. Thus, the ADNM-4 network was explored and yet again a preoccupation item (item 2 ‘constant memories’) showed the most strength centrality, with high and satisfying stability. Highly central symptoms have the potential to maintain a disorder.Reference Hallquist, Wright and Molenaar23 The results thus highlight the relatively greater importance of preoccupation symptoms as compared with failure to adapt symptoms. This finding aligns with results from a longitudinal study over a 1-year period that showed that intrusive memories was the symptom that was most likely to be associated with a diagnosis of adjustment disorder.Reference O'Donnell, Alkemade, Creamer, McFarlane, Silove and Bryant24
Stability
Finally, the study aimed to explore the stability of findings between samples and measures. The overall connectivity was similar across countries. However, as could be expected, there were several differences between the networks of different countries. Whereas Nigeria and Kenya, as well as Ghana and Kenya did not differ in terms of network structure invariance, Nigeria and Ghana differed significantly in both ADNM-8 and ADNM-4. Importantly, the global score of the ADNM-8 was similar in all networks. This implies that the associations have the same magnitude of overall connectivity in all networks as well as the same structure, but the edges structure is significantly different between the Nigeria and Ghana networks.
This difference may be rooted in the Nigerian sample, which had stronger associations of two failure to adapt items (items 6 and 7) than was the case in the samples from Ghana and Kenya. Moreover, among the preoccupation symptoms the Nigerian network also included stronger connections (items 4 and 5) compared with the other samples, which indicates that both core symptom clusters were more distinctly represented in the Nigerian sample. Interestingly, studies show that Nigeria may be a particularly disadvantaged country with regard to mental health access and support.Reference Odeyemi and Nixon25 There was a higher level of exposure to life events in Nigeria compared with Ghana and equal exposure to life events compared with Kenya.Reference Ben-Ezra, Hyland, Karatzias, Maercker, Hamama-Raz and Lavenda19 It may be speculated that the higher prevalence of exposure may result in higher support of the adjustment disorder structure in the Nigerian network compared with Ghana.
Limitations
The study has several limitations. First, it relied on self-report data rather than clinician-administered interviews, which may have biased the reports. Second, findings in community samples may not generalise to treatment-seeking or clinical samples. Third, the stability of the centrality index in the ADNM-8 networks did not reach the acceptable cutoff for the stability index (see Supplementary materials).. However, the high stability in the ADNM-4 networks confirmed the centrality of preoccupations and made our conclusions more solid. Fourth, the cross-sectional nature of the data does not allow for any inferences on causality. Fifth, the samples that were examined represented non-western cultures and it remains to be explored in replication studies whether the results generalise to Western societies. However, given the rarity of studies focused on adjustment disorder in a non-Western context, the findings also represent an important step in validating the ICD-11 adjustment disorder concept more widely.
Implications
Despite the study's limitations, the current findings provide an important first impression of the network structure of adjustment disorder and revealed patterns of association that can guide future research and practice. Despite cultural variations in samples, the structure of the network remained relatively consistent across all three countries. First and foremost, results provide further evidence for the validity of this newly defined condition, particularly with regard to the preoccupation syndrome. As the ICD-11 and the DSM-5 conceptualisations of adjustment disorder differ, most significantly with regard to the focus on preoccupation with the stressor in ICD-11, investigations regarding the nature of the preoccupation syndrome are crucial. The current study sheds light on the two adjustment disorder core symptom criteria of the ICD-11 and shows the complexity in the relationship between them.
One of the major benefits of defining specific symptom criteria for ICD-11 adjustment disorder is that it facilitates the development of disorder-specific interventions.Reference Glaesmer, Romppel, Brähler, Hinz and Maercker7 The current study further contributes to guide future intervention development by emphasising the central role of preoccupation with the stressor and highlighting this as a particularly promising target for intervention. In cognitive– behavioural therapy, for example, an important treatment component is psychoeducation regarding functional thoughts and problems-solving, on the one hand, and dysfunctional rumination, on the other hand. Furthermore, imaginal exposure-based techniques may be adequate interventions if patients with adjustment disorder are oscillating between preoccupations with the stressors and attempts to avoid remembering the stressor.Reference Bachem and Casey16 Given its central role in adjustment disorder networks across different questionnaire versions and countries, future research should aim to better understand the clinical importance of the preoccupation cluster.
Supplementary material
To view supplementary material for this article, please visit https://doi.org/10.1192/bjp.2021.46.
Data availability
The data that support the findings of this study are available from the corresponding author, Y.L., upon reasonable request.
Author contributions
Y.A.: substantial contributions to the conception and design of the work, analysis, interpretation of the work, drafting and revising the work in all stages, final approval of the version to be published, and agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. R.B.: substantial contributions to the conception of the work, interpretation of the work, drafting and revising the work in all stages, final approval of the version to be published, and agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. T.K.: substantial contributions to the design of the work, interpretation of the work, revising the work in all stages, final approval of the version to be published, and agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. M.S.: substantial contributions to the design of the work, revising the work in all stages, final approval of the version to be published, and agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. A.M.: substantial contributions to the conception of the work, revising the work in all stages, final approval of the version to be published, and agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. M.B.-E.: substantial contributions to the conception and design of the work, revising the work in all stages, final approval of the version to be published, and agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
Funding
An internal research grant was awarded to M.B.-E. from Ariel University (grant no. RA1700000037). The sponsor had no involvement in study design, data collection, analysis, interpretation of the results, writing of the report or the decision to submit the article for publication.
Declaration of interest
None.
eLetters
No eLetters have been published for this article.