Biopsychosocial theories of borderline personality disorder: a meta-synthesis and psychopathological network model from a systematic review

Carlo Lazzari1, Marco Rabottini1

1Department of Psychiatry, International Centre for Healthcare and Medical Education, London, United Kingdom.

Summary. Background. Borderline personality disorder (BPD) is a complex mental health condition with an altered image of self, impulsive acts, suicidal ideation, and self-harm requiring intensive care in outpatient and inpatient settings. The biopsychosocial (BPS) model adopted in the current study extracted the outcomes of a research about the diagnosis, causes and treatment of BPD. A network model helped link these results in a unitary model with applications in clinical practice for assessment and intervention. Methods. We conducted a literature review of current studies on the BPS causes of BPD and merged them through meta-synthesis. The results were then elaborated with a psychopathological network analysis for linking the extracted factors with higher degree of centrality in the network and merged in a final comprehensive model. Results. The theoretical modelisation suggests that BPS causes merged with the diathesis-stress model persistently activate the cortico-limbic system and prefrontal cortex, induce neuroinflammation, and stimulate suicidal and parasuicidal ideation and behaviours modulated by psychological and pharmacological treatment. Conclusions. Using a network model in psychopathology allowed the merging of data about BPD into a unitary and dynamic pattern which can be helpful to direct assessments and interventions in clinical practice.

Key words. Biopsychosocial model, borderline personality disorder, meta-synthesis, network analysis, psychopathology.

Teorie biopsicosociali del disturbo borderline di personalità: un modello di meta-sintesi e di network psicopatologico da una revisione sistematica.

Riassunto. Background. Il disturbo borderline di personalità (BPD) è una condizione di salute mentale complessa con un’immagine alterata di sé, atti impulsivi, ideazione suicidaria e autolesionismo che richiedono cure intensive in ambito ambulatoriale e ospedaliero. Il modello biopsicosociale (BPS) adottato nel presente studio ha estratto i risultati della ricerca sulla diagnosi, le cause e il trattamento del BPD. Un modello di network psicopatologico ha aiutato a collegare tali risultati in uno schema unitario con le applicazioni nella pratica clinica per la valutazione e l’intervento. Metodi. Abbiamo condotto una revisione della letteratura degli studi attuali sulle cause BPS del BPD e li abbiamo uniti attraverso la meta-sintesi. I risultati sono stati poi elaborati con analisi dei network per i link concettuali, il grado di centralità dei fattori estratti e riassunti in un modello finale comprensivo e unitario. Risultati. La modellizzazione teorica suggerisce che le cause di BPS fuse con il modello diatesi-stress attivano persistentemente il sistema cortico-limbico e la corteccia prefrontale, inducono neuro-infiammazione e stimolano ideazione e comportamenti suicidari e parasuicidari modulati dal trattamento psicologico e farmacologico. Conclusioni. L’utilizzo di un modello di rete (network) in psicopatologia ha permesso la fusione delle conoscenze di BPD in uno schema unitario e dinamico che può essere utile per indirizzare valutazioni e interventi nella pratica clinica.

Parole chiave. Analisi dei network, disturbo borderline di personalità, meta-sintesi, modello biopsicosociale, psicopatologia.

Introduction

Epidemiology

Borderline personality disorder (BPD) has a prevalence of 20% in inpatient psychiatric wards, 1.6-5.9% in the community, 10-12% in outpatient psychiatric services, and 50% among psychiatric inpatients with a diagnosis of personality disorder1-3. Patients with BPD comprise 9-33% of all suicides and more than 12% of psychiatric emergency visits during a year2. BPD is generally complex to diagnose and treat4,5. National Institute for Care and Health Excellence (NICE) advocates for multidisciplinary teams to diagnose and treat BPD6. Our research shows a prevalence of referrals of persons with BPD in general adult psychiatric wards and admission to emergency departments (ED)7. In our longitudinal study of a general adult ward in a teaching hospital in the United Kingdom, about 46% of admissions were from persons with BPD diagnoses8.

Diagnosis

The World Health Organization (WHO) Classification 1992 for BPD includes at least three of the following: i) perturbations in and ambiguity about self-image, goals and internal preferences; ii) propensity to engage in extreme and unsteady relationships, often resulting in psychological crises; iii) extreme attempts to prevent abandonment; iv) reoccurring risks or practice of self; v) persistent feelings of being empty9. In addition, features of a personality disorder must be present in the fields of: i) cognition and in the way of perceiving and interpreting things, people and events; in the way of creating attitudes and images of self and others; ii) affectivity in terms of range, intensity and appropriateness, of emotional arousal and response; iii) control over impulses and gratification of needs; iv) interpersonal behaviour and management of interpersonal circumstances9. Furthermore, the skills required by healthcare staff to prevent chronic self-harming and suicidal thoughts in this vulnerable group are complicated; these competencies must be continually updated owing to the propensity of these patients to file complaints against their healthcare providers10. Recent research from our group shows that BPD can be comorbid with factitious disorders making the differentiation between the two pathologies complex11,12.

Network models in BPD studies

Network analysis can provide a topographical and sequential structure of symptoms network by locating some as central and pivotal compared to more peripheral and ancillary symptoms13. Network analysis has shown that impulsivity and emotional dysregulations are trigger factors for BPD, antisocial, narcissistic, and histrionic personality traits13.

A network model has extracted the correlations between BPD and eating disorders14. In psychopathology networks, nodes characterise symptoms and their links (edges) represent their relationships15. Centrality indices measure several circumstances in which a trait or symptom plays an essential part in the framework provided by other symptoms15.

Network psychopathology conceptualises mental disorders as networks in which symptoms can trigger the presence of other symptoms, and this can eventually lead to a full-blown mental illness16. If this is true, symptom networks may be informative for clinical practice; symptoms that are more central in the network are thus assumed to influence many other symptoms, thus suggesting some logical argument for intervention16. The network method is predicated on the premise that symptoms are intimately connected and the relationship between them is actual, not fictitious, as a latent variable model considers it to be17.

Aim

Despite the extensive research on BPD, the authors of the current study could not find a unitary model that could merge all the findings and theories of BPD into a unique explanation. Furthermore, within the same field of exploration, such as diagnosis, causes, and treatment, there seems to be no network exploration of how multiple factors link together. The authors of the current review are unaware of research that has tried to merge into one unitary model and middle range theory, the biopsychosocial (BPS) model of BPD.

Study question

What is the theoretical model that can summarise and link the current knowledge on diagnosis, causes and treatment of BPD in one BPS paradigm?

Objectives

The primary objective was to extract current literature on the diagnosis, causes, and treatment of BPD. The secondary objective was to use Social Network Analysis (SNA) and meta-synthesis to merge the findings from the literature into a unitary model and measure the degree of prestige (DP) of psychopathological aspects in BPD. Nodes with higher DP are more central in the network as they receive or send more links to other nodes than adjected ones18.

Methods

Methodology

Qualitative Meta-synthesis (QM), based on the interpretivism approach, combines secondary data from the literature, accounts for similarities and divergencies, and deconstructs and reconstructs the data while the researcher formulates an overarching theory of interpretation19-24. The current study’s authors adopted an exploratory research approach when they tried to understand psychopathological networks in BPD, generating new ideas about the existing studies and investigating a topic with few or prior studies by using meta-synthesis and an inductive approach25. However, the numerical outcomes of SNA, the explanatory analysis, and the measurement of the degree of centralities and prestige (of nodes representing symptoms, causes and treatment) helped understand the causal relationships between the observed facts in a deductive approach25.

Literature search

Information sources and eligibility criteria

Search engines for the literature review included PubMed, EMBASE, Google Scholar, Web of Science, PsychNet, MEDLINE, grey literature, thematic books, and hand search. PRISMA flowchart summarised the steps26.

Study selection

The principal researcher (CL) reviewed the search results from the four databases in the preliminary stage of the review to find possibly relevant titles. Two reviewers (CL and MR) read the abstracts of pertinent probable studies. The same two reviewers then scrutinised the complete texts of any abstracts that seemed to satisfy the inclusion requirements, and where necessary, differences were settled through discussion with a third party. After a study was approved for review inclusion, its reference list was also looked through to find any further studies that might be pertinent. The review stage went from January 2020 to August 2022. The authors selected publications in peer-reviewed journals mostly in the last five years and with impact factors. They excluded research studies that did not fulfil robust research criteria and were opinion papers with no outcomes or blogs or studies that were not from accredited sources or authors known in the BPD field. They also used EndNote to eliminate duplicates from the retrieved literature27,28.

Eligibility criteria

SPIDER and PICOS chart guided the choice of the literature, including qualitative research and conclusions from quantitative and mixed-method studies research29. The inclusion criteria for the sample in articles were persons diagnosed with BPD in the community or psychiatric wards. The phenomenon of interest was the diagnosis, causes and treatment of BPD. The studies design for inclusion were randomised controlled trials, double-blind and placebo-controlled, systematic reviews, and qualitative, quantitative and mixed-method research. Exclusion criteria were for grey literature, publications not in English, and publications that did not complete the inclusion criteria. A second analysis with the two authors/reviewers extracted only relevant articles. A total of 5,690 articles were extracted during the first search phase, while only 80 were selected for the analysis (table 1).




Quality appraisal

The two researchers separately evaluated the quality of the studies that were part of the review using the Critical Appraisal Skills Programme (CASP) instrument for qualitative research, which was also applied to the qualitative outcomes of quantitative and mixed-method studies30. Discussions among the researchers were used to settle any disputes.

Search strategy

Primary keywords used in the Boolean search to extract relevant literature were:

• diagnosis: “Borderline-Personality-Disorder AND diagnosis AND/OR ICD-11 AND/OR DSM-5”;

causes: “Borderline Personality Disorder AND Cause* AND/OR brain AND/OR neuroinflammation AND/OR obesity AND/OR child-abuse AND/OR social-isolation AND/OR stress AND/OR gut-microbiome AND/OR prefrontal-cortex”;

therapy or psychotherapy: “borderline-personality-disorder AND psychotherapy AND/OR mindfulness AND/OR dialectic-behavioural-therapy”; “borderline-personality-disorder AND pharmacotherapy AND/OR antidepressant* AND/OR mood-stabiliser* AND/OR antipsychotic*” (figure 1; Appendix, online).




Data extraction

The panel of experts and networking a model

A panel of mental health professionals (MHPs) was set to provide the relationships between the factors emerging from the BPS model of BPD as captured by the selected articles and confirmed by their expertise in the field. All the participants were active mental health practitioners in general adult psychiatry with comprehensive knowledge of BPD. The panel included MHPs from general adult wards, psychiatric intensive care units, community psychiatric teams and liaison psychiatry from the local public hospital. The panel comprised four consultant psychiatrists, three senior ward managers, six senior mental health nurses, one clinical psychologist, one clinical pharmacist, one occupational therapist, and three former service users with a diagnosis of BPD fully recovered. During each meeting, for a length of about 30-45 minutes and a total of nine joint sessions live or via Microsoft Teams, they were meant to reach an agreement on how the causes (three sessions), symptoms (three sessions), and therapy (three sessions) were linked according to a network model. After the leading authors extracted the central concepts in the BPS model of BPD, the authors proposed targeted discussion according to two leading questions, ‘What comes first?’ or ‘What is causing what?’. The aim was to extract antecedent and consequent factors in a network chain of interrelated concepts. Therefore, they suggested which aspect was linked to which, which was the trigger, and which was the effect. For example, one consultant provided insight into the link between neuroanatomy and mood. A senior member of staff working in liaison linked the presentation to emergency departments and life events. The clinical psychologists provided the links between psychotherapy and pharmacotherapy. A moderator, selected from one of the authors, conducted the discussions and collected the agreed-upon networks from the discussions. The setting was a public mental health setting in the United Kingdom. By processes of subsequent links, networks were constructed. Other times, the findings in the research and the meta-synthesis indicated the correlation between the concepts.

Data synthesis

Meta-synthesis

Meta-synthesis is a research methodology in which the qualitative results of prior studies are classified or categorised according to particular criteria, and the findings are reinterpreted by comparison31. As applied in the current study, the authors used the qualitative or narrative results of quantitative, qualitative and mixed-method research to generate a unitary interpretation model. The qualitative synthesis, applied to systematic reviews, results from the researchers’ arrangement of segments of data merged into a new whole; therefore, meta-synthesis prepare the basis for the conversation where hypotheses and proposals are presented, generating a new model or theory about a phenomenon or more powerful explanations32,33.

Meta-synthesis capitalises on various contexts, techniques, and theoretical orientations to provide a richer, more complex, and more multidimensional approach to a phenomenon34. As we account for more layers of the subject matter we are studying, we evaluate it from a greater variety of perspectives34. As we question it with more and more theoretical interpretations, we increase the likelihood of grasping its fundamental character or inherent truth34.

Social Network Analysis

Social Network Analysis (SNA), using the Open Source Social Network Visualizer SocNetv V2.5 (https://socnetv.org) software, combined the themes emerging from meta-synthesis. SNA figuratively captures the relation between concepts and information represented by network nodes; then, it extracts the degree of prestige (DP) where the value of 100% represents more central positions in the network of acquired nodes/concepts35,36.

In the Network Model of psychopathology, social, biological, and genetic causes are mutually linked and interacting37-39. As explored in the current study, SNA has been used to connect related concepts into a network model, providing a pictorial configuration of ideas linked together, while the distance between concepts measured; notions that had more links with others had a higher degree of centrality and prestige compared to more separated themes. SNA is a method where the connections between the individual nodes or edges of the network (people, concepts, organisations, facts, information, and others) are qualitatively and quantitatively described by using pictorial representations of them (qualitative analysis) or by capturing and measuring the intensity of the interunit bonds between them, or by extracting their number or the strength of their links (quantitative analysis)40. The individual nodes or edges are linked according to the underlying theoretical modelisation – in this study, their conceptual relatedness – while the central positions in the graphs are occupied by those concepts that are ‘central’ and play a pivotal role in being more linked to any other concepts or ideas. The lines in a graph can have a ‘direction’ to denote the flow of influence in a social network, and they can be assigned a ‘value’ to signify the strength of the relation18. Edge weight and differences in the degree of prestige from SNA were assessed for statistical differences with Chi-square statistics. We used a closing hierarchical clustering of the equivalence matrix showing the co-correlation of the nodes with high centrality from all models.

The authors, supported by the panel of expert meetings, assigned their weights independently to the individual themes in the current study. The final averaged weight positioned the pieces into the network as more central or peripheral. Each network was generated by answering the question, ‘What comes first?’. For instance, does suicidal ideation come before or after a crisis? If, for example, a problem was regarded as a trigger, then the arrow of network influence went from ‘life crisis’ to ‘suicidal ideation’.

Similarly, for example, if ‘relationship splitting’ comes before ‘life crisis,’ then the influence arrow goes from ‘splitting’ to ‘crisis.’ By progressive accretion of reciprocal influences, we constructed our SNA networks. More central concepts had multiple causes; for instance, ‘suicidal ideation’ could be triggered by a ‘life crisis,’ ‘change of medication,’ or ‘chronic feeling of emptiness.’ The Chi-square goodness of fit test for the significance of the aggregated theoretical model elaborated the final numerical results. The authors, specialists in the topic treated, helped locate the themes and edges by linking them sequentially with single-headed arrows for unilateral influence and double-headed arrows for reciprocal influence. The expert panel was also guided by the current theories about the weighed concepts (figure 2).




Results

Diagnosis

Mental disorders are mental health states that affect feelings, behaviours and thoughts41. According to The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5)1 and The International Classification of Diseases 11th Revision (ICD-11)9, persons with BPD present symptoms in five or more of the following area: i) hectic efforts to escape actual or imaginary rejection; ii) turbulent and intense social interactions, characterised by contrasting values, from idealisation to degradation; iii) continuous drastic and unpredictable self-esteem or consciousness of oneself; iv) unpredictability in at least two intrinsically self-damaging aspects, (e.g., money, sexuality, drugs, driving, binge eating); v) chronic suicide conduct, speech and/or threats, or deliberate self-harm (DSH); vi) short-lived psychological unrest due to extreme unplanned mood; vii) durable perceptions of emptiness; viii) severe and irrational anger that may be hard to control; and ix) fleeting paranoid ideas under stress, psychotic symptoms, or extreme dissociative symptoms.

A categorical model is often complemented by a dimensional version of classifying BPD based on the seriousness and frequency of symptoms1,9,42-44. The diagnosis of BPD is not always straightforward as it can be comorbid with the factitious disorder11,12. The leading author (CL) hypothesises the existence of a syndrome characterised by comorbidity between BPD, depression and factitious disorder as follows: i) fictitious behaviours: asserting more severe physical and mental health issues that do not receive diagnostic and instrumental confirmation; ii) self-inflicted wounds and diseases, in addition to intentional self-harm; iii) seeking invasive diagnostic and treatment procedures; iv) medication craving for major pain killers or sedative medication (e.g., pregabalin, paracetamol); v) construction or intensification of physical symptoms resulting in emergency hospitalisation and admission to medical or surgical wards; vi) claiming various allergies to medications to guide physician’s choices of treatment albeit with consequent polypharmacy; vii) clinical presentation mimicking physical conditions; viii) unconsciously seeking invasive therapy or examinations by exaggerating physical and psychological complaints that do not find objective clinical and surgical confirmation; ix) various and migrating forms of pain leading to accretion of painkillers and sedative medication; x) neuropathic pains that are problematic to confirm via standard diagnostic and clinical procedures inclusive of diffuse abdominal pains, musculoskeletal pains, headaches11,45.

The Antecedents, Behaviour, Consequences (ABC) model of Cognitive Behavioural Therapy (CBT) complemented by naturalistic observations helps diagnose symptoms as ‘Antecedents’ or triggers in the environment, impacting the ‘Belief’ system and interpretation, hence ‘Causing’ feelings, behaviours, and physical reactions46,47. Naturalistic observations of BPD in psychiatric wards and communities suggest that: i) ‘A’ or triggers of clinical relapses are real or imaginary rejection, loss of face-to-face interaction with carers, social isolation, and turbulent social interactions; ii) they lead to ‘B’, such as feelings of emptiness, anger towards self and others, paranoia and short psychotic episodes; and iii) these last cause ‘C’, such as unpredictability, impulsivity, suicidal and parasuicidal acts48-53.

Network model of symptoms

In the SNA, suicidal ideation holds the highest DP at 21.50%, triggered mainly by feelings of anger toward self and others (DP=17%), turbulent social interactions (DP=13%), escaping rejection (DP=8.6%), and chronic feelings of emptiness (DP=12%). All these factors are conducive to unpredictability and impulsivity (DP=4.5%), paranoia, and short psychotic episodes (DP=9%) (figure 3).




Causes

A necessary cause of a mental illness is a required attribute that generates a disorder (e.g., gene Huntingtin in Huntington’s disease), a sufficient cause ensures its presence, and a contributory cause increases its likelihood of developing51. The BPS model of causes of BPD emphasises the diathesis-stress paradigm produced by multiplicative effects of individual vulnerability and stressful life events, inclusive of: i) adverse childhood, including abuses, neglect, father-daughter incest, trauma; ii) deprived social conditions; iii) genetic predisposition; iv) problematic parental bonding with lack of affection and autonomy, physical and emotional abuse; and v) family breakdown51,54-57.

Brain magnetic resonance imaging (MRI) in BPD shows stress-induced hyperactivity of the Hypothalamic-Pituitary-Adrenal (HPA) axis, emotional over-reactivity linked to hyperstimulation of the amygdala, impulsivity liked to a smaller hippocampus, low prefrontal-to-amygdala coupling, and reduced grey matter and white matter diffusion in frontal, parietal and temporal lobes leading to the low inhibiting activity of the prefrontal cortex (figure 4)51,58-63.




Social isolation enhances stress-related hyperactivity of the HPA axis and anxiety disorders in BPD64-67. Chronic psychosocial stresses and abuses during childhood and adolescence increase the inflammatory markers (C-Reactive Protein) in adults and neuroinflammation of the hippocampus and microglia with an augmented incidence of mental illnesses68-70. An altered gut-brain-microbiome system also causes neuroinflammation; for instance, altered gastrointestinal metabolism and absorption, inflammatory bowel syndrome, irritable bowel syndrome, chronic diarrhoea or constipation, infections of the intestine, gastrointestinal operations or eating disorders, pathological body mass index (BMI); they can cause physiological stress impacting the HPA axis and brain neurotransmitters with a pathological BMI also being reported for an influence to cognitive function mediated by the hippocampus, amygdala, and reward-processing centres; re-establishing a regular metabolism and adding omega-3-fatty-acids can normalise the gut microbiome and reduce impulsivity71-76. SNA of functional MRI studies captures the more stimulated and activated brain in BPD36. In a longitudinal study of 10 years in the author’s ward for measuring weight gain in psychiatric inpatients, female patients were prevalent with the diagnosis of BPD and a mean pathological BMI of 31.2177. In 26.9% of the obese population, a USA report found a prevalence of BPD that ties personality disorder to compulsive eating78. Research shows that childhood abuse in women is linked to obesity later in life79. A researcher suggested that high pathological BMI might be related to axonal/myelin irregularities in the white matter, with a decrease in the grey matter and consequent damage to neurons80.

Network model of causes

The SNA disclosed a higher DP for BPS and diathesis-stress model (DP=12%) together with pathological BMI (DP=9%), leading to neuroinflammation (DP=9%), altered frontal, parietal and temporal lobes functions (DP=6%), followed by increased inflammatory markers (DP=6%) and reduced volume of the hippocampus (DP=6%) (figure 5).




Treatment

Psychotherapy is when therapists and clients set a time to discuss the client’s current and past life events, feelings, thoughts, and behaviours causing the client’s concerns81. A therapeutic outcome in psychiatry is what happens to a patient’s mental health due to an action by healthcare professionals or services82.

Psychoanalytic psychotherapy helps elaborate and change the interaction between the patient and the therapist83. Dialectic Behavioural Therapy (DBT) helps patients’ treatment and prevention while assisting them in accepting themselves, acknowledging their conflicts, and finding a dialectic answer to reconcile and synthesise opposite polarities such as insecurity, social invalidation, defeatism, and evident abilities84.

Mindfulness-based therapy entails mindfulness and knowledge of everyday experience to favour a fast change in attention from complete engagement in the emotion or behaviour to self-observation and self-reflection; this loop of self-reflection about an experience allows patients to control the impact of a situation50.

Mindfulness increases the brain grey matter in the right orbitofrontal area and the lower brain stem while reducing the hyperactivation of the prefrontal cortex (PFC) and frontal-limbic system involved in emotion regulation and modulates the midline prefrontal and posterior cingulate cortex by increasing self-awareness85-90. DBT modulates the brain’s cortico-limbic and PFC and reduces amygdala hyperactivity91. Overall, patients with BPD have an overactive and smaller amygdala (emotional propeller) and underactive prefrontal and cortico-limbic system (emotional brake)92,93.

Pharmacotherapy suggests that selective serotonin reuptake inhibitors (SSRIs), such as sertraline, fluoxetine, and fluvoxamine, positively affect the PFC and reduce depression and lability of mood, impulsivity, anxiety and aggression94-96. Mood stabilisers (e.g., lithium and carbamazepine) decrease emotional instability and behavioural dysregulation by activating Beta-1-adrenergic and Dopamine-D2 receptors in the PFC; atypical antipsychotics (e.g., olanzapine, risperidone, aripiprazole, clozapine) control psychotic symptoms and anger94,97-99. However, there are debates about the possible effect of antidepressants on impulsivity. At the same time, our research group has found positive results with antipsychotic depot injections (e.g., Zuclopenthixol) while avoiding, when possible, prescribing SSRI antidepressants alone, which are often accompanied, in our studies, by increased suicidal and parasuicidal behaviours12.

Network model of treatment

In the SNA, psycho-pharmacotherapy in BPD targets PFC (DP=57%), frontal-limbic network (DP=29%), and HPA axis (DP=21%) by modulating their activities (figure 6).




Meta-aggregation of results

The theoretical modelisation of BPD suggests that BPS causes merged with the diathesis-stress model persistently activate the cortico-limbic system and prefrontal cortex, induce neuroinflammation, and stimulate suicidal and parasuicidal ideation and behaviours modulated by psychological and pharmacological treatment. The aggregated model confirmed a different DP for all edges except for the causes of BPD that aggregate equally. The effect sizes were large for symptoms, diagnosis and treatment. Suicidal ideation and psychological-psychopharmacological treatment targeting the prefrontal cortex are two aspects that attract more meaning, research, and weight in the integrated BPS model (tables 3 and 4; figures 7 and 8).

Conclusions

Our study is a novel approach to condensing and linking theories and findings in BPD research. Using a network model allowed us to capitalise on the relevant information and merge it in a unitary model of explanation, albeit not the only one possible. Using meta-theories impacts clinical settings where mental health practitioners look for cause and effect or psychopathological causality to plan their actions, remedies, therapies and clinical interventions. Therefore, the model helps understand priorities of action, for example, correcting pathological BMI and metabolic imbalance and consensually reducing social isolation and initiating psychotherapy to reduce impulsivity. Or pharmacological intervention combined with psychotherapy will impact the corticolimbic system and help mitigate impulsive acts, anger outbursts and suicidal ideation (figure 9).

The network model of the psychopathology of BPD helps link symptoms, causes, and treatments to find central factors in the network, such as suicidal and parasuicidal behaviour and address them in care plans. However, as all elements are correlated, no etiological cause should be considered necessary or sufficient. For instance, childhood sexual abuse is a contributory cause, while family instability is a mediator100. Furthermore, all psychotherapies have positive outcomes, mostly on DSH and suicidal ideation, as long as they are provided by judicious therapists forming a robust therapeutic alliance realistically, using outcome measures to target symptoms101. In addition, medication should be used with caution as it has been suggested that there might be increased impulsivity, suicidal ideation and aggression risk from treatment with SSRI antidepressants and adverse side effects with polypharmacology102,103.

Therefore, multidisciplinary teams should be mindful in confirming presentation symptoms, causes and treatments as these are all dynamically networked.

Limitations

The current study has several limitations. The first is linked to meta-analysis as it is a qualitative approach to theorisation; it retains the subjective choices of participants, authors and panel members in indicating the links between concepts. Other researchers and panels could have expressed different or diverging opinions. Another limitation of our transtheoretical model is that it did not receive experimental confirmation. Efforts were made to collate the findings into a unitary and quantitative model. Therefore, it could be argued that the current study has limited external validity, although it can still hold clinical validity.

Suggestions for future research

Since the current psychopathology model of summing up symptoms has information gaps, the authors suggest that future research should use a small-world social network theory of psychopathology where diagnosis, causes, and treatment are dynamically interdependent, showing networks structured between regular to random configurations38,104,105. SNA will identify those central nodes of the network that are important in creating and maintaining clusters of symptoms; this would determine the focus of therapy since it reveals the casual interaction between nodes/symptoms38,39,104,106,107.

Telemedicine and teleconsultation108 are promising areas for future research. Whatever the therapeutic intervention proposed, there should be relevant outcome studies regarding the quality of life and pertinent signs for patients, families, and care providers6. A longitudinal study found similar effects in anxiety outcomes between online and face-to-face counselling109. A hybrid technology merging online with face-to-face psychotherapy, based on smartphone technology, will allow service users to access the required resources despite geographical barriers and limited resources while implementing continuity of care and reducing barriers to consultation, especially during Covid-19 restrictions110-112.
















Take home messages.

Using a network model allows one to capitalise on a psychopathology’s relevant information and merge it into a unitary model of explanation.

A network theory of psychopathology allows us to link diagnosis, causes, and treatment of psychiatric pathologies into dynamic systems of reciprocal influences. 

Network analysis may reveal a topographical and sequential structure of symptoms by identifying specific signs as core and essential compared to other peripheral and auxiliary symptoms.

Psychopathology networks may be helpful in clinical treatment because concepts more central in the network are presumed to impact many other symptoms; therefore, there may be some justification for intervention if those symptoms are more prevalent.

Competing interests: no competing interests were disclosed.

Acknowledgements: the authors are grateful to all participating panel members for the discussions that allowed the conceptualisation for the creation of the reported networks. Participation was voluntary.




























References

1. APA - American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders: DSM-5. 5th edn. Washington: American Psychiatric Association, 2013.

2. Ellison WD, Rosenstein LK, Morgan TA, Zimmerman M. Community and clinical epidemiology of borderline personality disorder. Psychiatr Clin North Am 2018; 41: 561-73.

3. Widiger TA, Weissman MM. Epidemiology of borderline personality disorder. Hosp Community Psychiatry 1991; 42: 1015-21.

4. Comtois KA, Russo J, Snowden M, Srebnik D, Ries R, Roy-Byrne P. Factors associated with high use of public mental health services by persons with borderline personality disorder. Psychiatr Serv 2003; 54: 1149-54.

5. Gunderson JG, Herpertz SC, Skodol AE, Torgersen S, Zanarini MC. Borderline personality disorder. Nat Rev Dis Primers 2018; 4: 18029.

6. NICE. Borderline personality disorder: recognition and management. Research recommendations. Available from: https://lc.cx/NDxfPi [last accessed September 2023].

7. Lazzari C, Shoka, A, Papanna B, Kulkarni K. Current healthcare challenges in treating the borderline personality disorder “epidemic.” British Journal of Medical Practitioners 2018; 11: 2-4.

8. Lazzari C, Shoka A, Papanna B, Kulkarni K. Predominant diagnoses, gender, and admission duration in an adult psychiatric inpatient hospital in United Kingdom. Open Journal of Psychiatry & Allied Sciences 2018; 9: 37-40.

9. WHO - World Health Organization. The ICD-10 classification of mental and behavioural disorders. Geneva: World Health Organization, 1992.

10. De Zutter AWEA, Horselenberg R, van Koppen PJ. Motives for filing a false allegation of rape. Arch Sex Behav 2018; 47: 457-64.

11. Lazzari C, Nusair A. Comorbidity between factitious disorder and borderline personality disorder: assessment in medical and psychiatric care. International Journal of Psychiatry Research 2020; 2: 7-11.

12. Mousailidis G, Lazzari C, Bhan-Kotwal S, Papanna B, Shoka A. Factitious disorder: a case report and literature review of treatment. Progress in Neurology and Psychiatry 2019; 23: 14-8.

13. Nelson RK, Lass AN, Fanning JR, McCloskey MS, Winer ES, Berman ME. A network model of borderline personality traits, aggression, and self-harm. Journal of Affective Disorders Reports 2022; 8: 100330.

14. De Paoli T, Fuller-Tyszkiewicz M, Huang C, Krug I. A network analysis of borderline personality disorder symptoms and disordered eating. J Clin Psychol 2020; 76: 787-800.

15. Richetin J, Preti E, Costantini G, De Panfilis C. The centrality of affective instability and identity in borderline personality disorder: evidence from network analysis. PLoS One 2017; 12: e0186695.

16. Bos FM, Snippe E, de Vos S, et al. Can we jump from cross-sectional to dynamic interpretations of networks? Implications for the Network Perspective in Psychiatry. Psychother Psychosom 2017; 86: 175-77.

17. Cramer AO, Waldorp LJ, van der Maas HL, Borsboom D. Comorbidity: a network perspective. Behav Brain Sci 2010; 33: 137-50; 150-93.

18. Scott J. Social network analysis: developments, advances, and prospects. Social Network Analysis and Mining 2011; 1: 21-6.

19. Barker J. Evidence-based practice for nurses. London: Sage, 2013.

20. Cresswell JW, Cresswell JD. Research Design. 5th edn. London: Sage, 2018.

21. Erwin E, Brotherson M, Summers J. Understanding qualitative metasynthesis. Journal of Early Intervention, 2011; 33: 186-200.

22. Sandelowski M, Docherty S, Emden C. Focus on qualitative methods. Qualitative metasynthesis: issues and techniques. Res Nurs Health 1997; 20: 365-71.

23. Thorne S, Jensen L, Kearney MH, Noblit G, Sandelowski M. Qualitative metasynthesis: reflections on methodological orientation and ideological agenda. Qual Health Res 2004; 14: 1342-65.

24. Stapleton A, Wright N. The experiences of people with borderline personality disorder admitted to acute psychiatric inpatient wards: a meta-synthesis. J Ment Health 2019; 28: 443-57.

25. Collis J, Hussey R. Business Research. 4th Ed. London: Pelgrave-McMillan, 2014.

26. Moher D, Liberati A, Tetzlaff J, Altman DG; PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med 2009; 6: e1000097.

27. Bramer WM, Giustini D, de Jonge GB, Holland L, Bekhuis T. De-duplication of database search results for systematic reviews in EndNote. J Med Libr Assoc 2016; 104: 240-3.

28. Kwon Y, Lemieux M, McTavish J, Wathen N. Identifying and removing duplicate records from systematic review searches. J Med Libr Assoc 2015; 103: 184-8.

29. Cooke A, Smith D, Booth A. Beyond PICO: the SPIDER tool for qualitative evidence synthesis. Qual Health Res 2012; 22: 1435-43.

30. CASP - Critical Appraisal Skills Programme. CASP Qualitative Research Checklist. 2017. Available from: https://lc.cx/5qaDzZ [last accessed September 2023].

31. Dinçer S. E˘gitim bilimleri aras¸tırmalarında içerik analizi: meta-analiz, meta-sentez, betimsel içerik analizi. Bartın Üniversitesi E˘gitim Fakültesi Dergisi 2018; 7: 176-90.

32. Lachal J, Revah-Levy A, Orri M, Moro MR. Metasynthesis: an original method to synthesize qualitative literature in psychiatry. Front Psychiatry 2017; 8: 269.

33. Siddaway AP, Wood AM, Hedges LV. How to do a systematic review: a best practice guide for conducting and reporting narrative reviews, meta-analyses, and meta-syntheses. Annu Rev Psychol 2019; 70: 747-70.

34. Paterson BL, Thorne SE, Canam C, Jillings C. Meta-study of qualitative health research: a practical guide to meta-analysis and meta-synthesis. London: Sage, 2001.

35. Wu Y, Duan Z. Social network analysis of international scientific collaboration on psychiatry research. Int J Ment Health Syst 2015; 9: 2.

36. Xu T, Cullen KR, Mueller B, et al. Network analysis of functional brain connectivity in borderline personality disorder using resting-state fMRI. Neuroimage Clin 2016; 11: 302-15.

37. Borsboom D. A network theory of mental disorders. World Psychiatry 2017; 16: 5-13.

38. Boschloo L, van Borkulo CD, Rhemtulla M, Keyes KM, Borsboom D, Schoevers RA. The Network Structure of symptoms of the Diagnostic and Statistical Manual of Mental Disorders. PLoS One 2015; 10: e0137621.

39. Fried EI, van Borkulo CD, Cramer AO, Boschloo L, Schoevers RA, Borsboom D. Mental disorders as networks of problems: a review of recent insights. Soc Psychiatry Psychiatr Epidemiol 2017; 52: 1-10.

40. Scott J. Social Network Analysis. 4th ed. London: Sage, 2017.

41. Mayo Clinic. Mental illness. 2020. Available from: https://lc.cx/gywxj1 [last accessed September 2023].

42. Kaunomäki J, Jokela M, Kontio R, Laiho T, Sailas E, Lindberg N. Interventions following a high violence risk assessment score: a naturalistic study on a Finnish psychiatric admission ward. BMC Health Serv Res 2017; 17: 26.

43. Kraemer HC, Noda A, O’Hara R. Categorical versus dimensional approaches to diagnosis: methodological challenges. J Psychiatr Res 2004; 38: 17-25.

44. Bach B, First MB. Application of the ICD-11 classification of personality disorders. BMC Psychiatry 2018; 18: 351.

45. Lazzari C, Shoka A, Papanna B, Rabottini M. The hypothesis of a tripolar syndrome in liaison psychiatry and medicine: depression comorbid with factitious disorders and borderline personality disorder. Indian Journal of Medical Research and Pharmaceutical Sciences 2018; 5: 61-8.

46. Lam D, Gale J. Cognitive behaviour therapy: teaching a client the ABC model: the first step towards the process of change. J Adv Nurs 2000; 31: 444-51.

47. Kinsella P, Garland A. Cognitive Behavioural Therapy for mental health workers: a Beginner’s Guide. London: Routledge, 2008.

48. Angrosino MV. Naturalistic observation. London: Routledge, 2016.

49. Ross CA, Ferrell L, Schroeder E. Co-occurrence of dissociative identity disorder and borderline personality disorder. J Trauma Dissociation 2014;15: 79-90.

50. Bateman AW, Krawitz R. Borderline Personality Disorder: an evidence-based guide for generalist mental health professionals (Illustrated ed.). Oxford, UK: Oxford University Press, 2013.

51. Hooley JM, Butcher JN, Nock MK, Mineka S. Abnormal Psychopathology. 7th edition. London and others: Pearson, 2017.

52. Lazarus SA, Beeney JE, Howard KP, Strunk DR, Pilkonis PA, Cheavens JS. Characterization of relationship instability in women with borderline personality disorder: a social network analysis. Personal Disord 2020; 11: 312-20.

53. Lazzari C, Shoka A. Chapter 2. Corporate Management of patients with borderline personality disorder through integrated care. In: Anderson R. Borderline Personality Disorder (BPD): prevalence, management options and challenges. New York: Nova, 2016.

54. Paris J. Social factors in the personality disorders. Cambridge: Cambridge University Press, 1996.

55. Nelson CA, Scott RD, Bhutta ZA, Harris NB, Danese A, Samara M. Adversity in childhood is linked to mental and physical health throughout life. BMJ 2020; 371: m3048.

56. Arnau-Soler A, Adams MJ, Clarke TK, MacIntyre DJ, Milburn K, Navrady L; Generation Scotland; Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Hayward C, McIntosh A, Thomson PA. A validation of the diathesis-stress model for depression in Generation Scotland. Transl Psychiatry 2019; 9: 25.

57. Andrews G, Tennant C. Life event stress and psychiatric illness. Psychol Med 1978; 8: 545-9.

58. Brambilla P, Soloff PH, Sala M, Nicoletti MA, Keshavan MS, Soares JC. Anatomical MRI study of borderline personality disorder patients. Psychiatry Res 2004; 131: 125-33.

59. Herpertz SC, Jeung H, Mancke F, Bertsch K. Social dysfunctioning and brain in borderline personality disorder. Psychopathology 2014; 47: 417-24.

60. Jovev M, Garner B, Phillips L, et al. An MRI study of pituitary volume and parasuicidal behavior in teenagers with first-presentation borderline personality disorder. Psychiatry Res 2008; 162: 273-7.

61. Lyoo IK, Han MH, Cho DY. A brain MRI study in subjects with borderline personality disorder. J Affect Disord 1998; 50: 235-43.

62. Sagarwala R, Nasrallah HA. White matter pathology is shared across multiple psychiatric brain disorders: Is abnormal diffusivity a transdiagnostic biomarker for psychopathology? Biomarkers in Neuropsychiatry 2020; 2: 100010.

63. Völlm BA, Zhao L, Richardson P, et al. A voxel-based morphometric MRI study in men with borderline personality disorder: preliminary findings. Crim Behav Ment Health 2009; 19: 64-72.

64. Baek SB. Psychopathology of social isolation. J Exerc Rehabil 2014; 10: 143-7.

65. Butler TR, Ariwodola OJ, Weiner JL. The impact of social isolation on HPA axis function, anxiety-like behaviors, and ethanol drinking. Front Integr Neurosci 2014; 7: 102.

66. Cacioppo JT, Hawkley LC, Norman GJ, Berntson GG. Social isolation. Ann N Y Acad Sci 2011; 1231: 17-22.

67. Cacioppo JT, Cacioppo S, Boomsma DI. Evolutionary mechanisms for loneliness. Cogn Emot 2014; 28: 3-21.

68. Calcia MA, Bonsall DR, Bloomfield PS, Selvaraj S, Barichello T, Howes OD. Stress and neuroinflammation: a systematic review of the effects of stress on microglia and the implications for mental illness. Psychopharmacology (Berl) 2016; 233: 1637-50.

69. Danese A, Moffitt TE, Pariante CM, Ambler A, Poulton R, Caspi A. Elevated inflammation levels in depressed adults with a history of childhood maltreatment. Arch Gen Psychiatry 2008; 65: 409-15.

70. Eidson LN, deSousa Rodrigues ME, et al. Chronic psychological stress during adolescence induces sex-dependent adulthood inflammation, increased adiposity, and abnormal behaviors that are ameliorated by selective inhibition of soluble tumor necrosis factor with XPro1595. Brain Behav Immun 2019; 81: 305-16.

71. Miller AA, Spencer SJ. Obesity and neuroinflammation: a pathway to cognitive impairment. Brain Behav Immun 2014; 42: 10-21.

72. Dragano NR, Haddad-Tovolli R, Velloso LA. Leptin, neuroinflammation and obesity. Front Horm Res 2017; 48: 84-96.

73. Bozzatello P, Rocca P, Bellino S. Combination of Omega-3 fatty acids and valproic acid in treatment of borderline personality disorder: a follow-up study. Clin Drug Investig 2018; 38: 367-72.

74. Bozzatello P, Rocca P, Mantelli E, Bellino S. Polyunsaturated fatty acids: what is their role in treatment of psychiatric disorders? Int J Mol Sci 2019; 20: 5257.

75. Bullmore E. The inflamed mind: a radical new approach to depression (Reprint ed.). London: Picador, 2019.

76. Rea K, Dinan TG, Cryan JF. The microbiome: a key regulator of stress and neuroinflammation. Neurobiol Stress 2016; 4: 23-33.

77. Lazzari C, Shoka A, Nusair A, Rabottini M. Weight gain and obesity in general adult psychiatric inpatients: a longitudinal and cross-sectional study. Riv Psichiatr 2021; 56: 211-6.

78. Sansone RA, Sansone LA. Childhood trauma, borderline personality, and eating disorders: a developmental cascade. Eat Disord 2007; 15: 333-46.

79. Danese A, Tan M. Childhood maltreatment and obesity: systematic review and meta-analysis. Mol Psychiatry 2014; 19: 544-54.

80. Marques C, Meireles M, Faria A, Calhau C. High-fat diet-induced dysbiosis as a cause of neuroinflammation. Biol Psychiatry 2016; 80: e3-4.

81. O’Driscoll. What is counselling and psychotherapy? British Association for Counselling and Psychotherapy 2017. Available from: https://lc.cx/9Ef4Fj [last accessed September 2023].

82. Slade M. What outcomes to measure in routine mental health services, and how to assess them: a systematic review. Aust N Z J Psychiatry 2002; 36: 743-53.

83. Piper W, Joyce AS. Psychosocial treatment outcome’. In: Livesley WJ (ed). Handbook of personality disorders. London: The Guilford Press, 2001.

84. Cottraux J, Blackburn I-M. Cognitive therapy. In: Livesley WJ (ed). Handbook of personality disorders, London: The Guilford Press, 2001.

85. Barsaglini A, Sartori G, Benetti S, Pettersson-Yeo W, Mechelli A. The effects of psychotherapy on brain function: a systematic and critical review. Prog Neurobiol 2014; 114: 1-14.

86. Chafos VH, Economou P. Beyond borderline personality disorder: the mindful brain. Soc Work 2014; 59: 297-302.

87. Collerton D. Psychotherapy and brain plasticity. Front Psychol 2013; 4: 548.

88. Luders E, Kurth F. The neuroanatomy of long-term meditators. Curr Opin Psychol 2019; 28: 172-78.

89. Marceau EM, Meuldijk D, Townsend ML, Solowij N, Grenyer BFS. Biomarker correlates of psychotherapy outcomes in borderline personality disorder: a systematic review. Neurosci Biobehav Rev 2018; 94: 166-78.

90. Tang YY, Hölzel BK, Posner MI. The neuroscience of mindfulness meditation. Nat Rev Neurosci 2015; 16: 213-25.

91. Schmahl C, Niedtfeld I, Herpertz SC. Borderline-Persönlichkeitsstörung: Veränderung der Hirnstruktur und -funktion durch Psychotherapie. Nervenarzt 2018; 89: 1232-36.

92. Porr V. Overcoming borderline personality disorder: a family guide for healing and change. Oxford: Oxford University Press, 2010.

93. Ruocco AC, Amirthavasagam S, Zakzanis KK. Amygdala and hippocampal volume reductions as candidate endophenotypes for borderline personality disorder: a meta-analysis of magnetic resonance imaging studies. Psychiatry Res 2012; 201: 245-52.

94. Markowitz P. Pharmacotherapy. In: Livesley WJ (ed). Handbook of personality disorders. London: The Guilford Press, 2001.

95. Rinne T, van den Brink W, Wouters L, van Dyck R. SSRI treatment of borderline personality disorder: a randomized, placebo-controlled clinical trial for female patients with borderline personality disorder. Am J Psychiatry 2002; 159: 2048-54.

96. Zhang Y, Han Y, Wang Y, et al. A MRS study of metabolic alterations in the frontal white matter of major depressive disorder patients with the treatment of SSRIs. BMC Psychiatry 2015; 15: 99.

97. Limandri BJ. Psychopharmacology for borderline personality disorder. J Psychosoc Nurs Ment Health Serv 2018; 56: 8-11.

98. Mercer D, Douglass AB, Links PS. Meta-analyses of mood stabilizers, antidepressants and antipsychotics in the treatment of borderline personality disorder: effectiveness for depression and anger symptoms. J Pers Disord 2009; 23: 156-74.

99. Montezinho LP, Castro MM, Duarte CB, Penschuck S, Geraldes CF, Mørk A. The interaction between dopamine D2-like and beta-adrenergic receptors in the prefrontal cortex is altered by mood-stabilizing agents. J Neurochem 2006; 96: 1336-48.

100. Bradley R, Jenei J, Westen D. Etiology of borderline personality disorder: disentangling the contributions of intercorrelated antecedents. J Nerv Ment Dis 2005; 193: 24-31.

101. Zanarini MC. Psychotherapy of borderline personality disorder. Acta Psychiatr Scand 2009; 120: 373-7.

102. Hengartner MP, Amendola S, Kaminski JA, Kindler S, Bschor T, Plöderl M. Suicide risk with selective serotonin reuptake inhibitors and other new-generation antidepressants in adults: a systematic review and meta-analysis of observational studies. J Epidemiol Community Health 2021: jech-2020-214611.

103. Sharma T, Guski LS, Freund N, Gøtzsche PC. Suicidality and aggression during antidepressant treatment: systematic review and meta-analyses based on clinical study reports. BMJ 2016; 352: i65.

104. Solmi M, Collantoni E, Meneguzzo P, Tenconi E, Favaro A. Network analysis of specific psychopathology and psychiatric symptoms in patients with anorexia nervosa. Eur Eat Disord Rev 2019; 27: 24-33.

105. Watts DJ, Strogatz SH. Collective dynamics of ‘small-world’ networks. Nature 1998; 393: 440-2.

106. Constantine LS. Understanding the linkages in organisational and human relations: a review of social network analysis. The Qualitative Report 2014; 19: 1-22.

107. Goekoop R, Goekoop JG. A network view on psychiatric disorders: network clusters of symptoms as elementary syndromes of psychopathology. PLoS One 2014; 9: e112734.

108. Ateriya N, Saraf A, Meshram VP, Setia P. Telemedicine and virtual consultation: the Indian perspective. Natl Med J India 2018; 31: 215-18.

109. Spence SH, Donovan CL, March S, et al. A randomized controlled trial of online versus clinic-based CBT for adolescent anxiety. J Consult Clin Psychol 2011; 79: 629-42.

110. Iyengar K, Upadhyaya GK, Vaishya R, Jain V. COVID-19 and applications of smartphone technology in the current pandemic. Diabetes Metab Syndr 2020; 14: 733-7.

111. Krysta K, Krzystanek M, Cubała WJ, et al. Telepsychiatry and virtual reality and the teatment of patients with intellectual and developmental disabilities. Psychiatr Danub 2017; 29: 656-9.

112. Smith K, Ostinelli E, Macdonald O, Cipriani A. COVID-19 and telepsychiatry: development of evidence-based guidance for clinicians. JMIR Ment Health 2020; 7: e21108.

113. Meares R, Stevenson J, Gordon E. A Jacksonian and biopsychosocial hypothesis concerning borderline and related phenomena. Aust N Z J Psychiatry 1999; 33: 831-40.

114. Crowell SE, Beauchaine TP, Linehan MM. A biosocial developmental model of borderline personality: elaborating and extending Linehan’s theory. Psychol Bull 2009; 135: 495-510.