Comparative Study of Causal Explanatory Models of Schizophrenia: Mental Health Specialists and Non-Experts in Mexico

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Comparative Study of Causal Explanatory Models of Schizophrenia: Mental Health Specialists and Non-Experts in Mexico

https://doi.org/10.21203/rs.3.rs-4824580/v1

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Introduction. Studies on intuitive theories of mental disorders, particularly causal models underlying specific disorders, have shown variations attributed to professional and cultural contexts. These intuitive theories are framed in at least three domains: medical-biological, psychosocial and sociocultural.

Objective. This study aims to identify the domains in which causal models of schizophrenia are framed in different specialists on mental health -psychologists, psychiatrists, psychoanalysts-, and non-experts.

Method. A cause-by-cause questionnaire was used to explore the attributed causes of schizophrenia and their associations. Causal network analysis identified structures and patterns among the groups.

Results. Significant variations were found in causal models among specialists and in laypersons' conceptions of schizophrenia.

Discussion. The analysis revealed consistent patterns of domain variation among mental health specialists and non-experts, aligning with previous research on causal models of mental disorders.

Schizophrenia

causal networks

mental health

intuitive theories

According to the World Health Organization, schizophrenia affects approximately 24 million people globally. The global prevalence in adults is approximately 1 in every 222 persons, with a range of 0.4–0.7% (WHO, 2022). In recent years, this disorder has been recognized as a public health issue due to the increase in diagnoses and its individual, interpersonal, community, and institutional implications. In 2021, the Secretaría de Salud in Mexico estimated that more than one million people are affected by this condition (Escamilla-Orozco et al., 2021). Stigmatization and discrimination in psychotic disorders and other mental illnesses represent a significant burden for individuals and their families (Van Dorn et al., 2006). From an anthropological perspective, stigmatization is defined as a set of discriminatory attitudes such as labeling, exclusion, and marginalization, leading to stereotypes and social status loss that hinder social recovery and integration (Garro, 2004; Van Dorn et al., 2006).

The main goal of research in mental health within cognitive anthropology is to understand how non-experts as well as experts, articulate beliefs, knowledge, attitudes, etc. for elaborate conceptions of illness, and how these conceptions are inextricably situated within social and cultural contexts. These socio-cultural conceptions influence medical decisions, perceptions of the condition, and the application of specific treatments (Garro. 2004); that is why they affect or are involved in certain cognitive processes such as prediction, counterfactual reasoning, and causal explanations. In this regard, these conceptions are based on structures known as intuitive theories (Gerstenberg and Tenenbaum, 2017). These are sets of beliefs about the causes and relationships that constitute domains such as the biological, psychological, or mental world.

Studies based on the conceptualization of intuitive theories have focused on exploring the beliefs that non-experts hold regarding the etiology, treatments, as well as the cure or chronicity of mental illnesses (Furnham, 2017; Furnham and Buck, 2003; Furnham and Carter-Leno, 2012; Furnham et al., 2011; Furnham and Winceslaus, 2011; Nunnally, 1961). According to the domain-specific hypothesis, these intuitive theories can develop from a single domain, such as the biomedical domain, psychosocial, and/or sociocultural domains, or they can integrate information from two or more knowledge areas, thus forming a cross-domain model (Lynch and Medin, 2006; Maupin, 2015). Within this framework, the biomedical model (Lynch and Medin, 2006) conceptualizes schizophrenia as a disturbance of physiological processes. Some theories associated with this model are based on domains such as genetics, dopaminergic systems, autoimmune and viral diseases, and neurological aspects (Zoch, 2002).

The psychosocial model (Lynch and Medin, 2006; Kleinman et al., 1978) argues that various social factors influence emotional, cognitive, and behavioral responses, describing the hybrid nature of disorders. The theories linked to this model include the hyperactivation theory, the theory of over-perception, the theory of the schizophrenogenic mother, the theory of developmental failure, and the psychological theory of the self (Zoch, 2002).

The sociocultural model (Kleinman et al., Medina-Mora et al., 2021; Jenkins and Barrett, 2006) asserts that social and cultural determinants closely relate to how symptoms are experienced, behavioral expressions, and beliefs explaining causes. It primarily draws on culturally derived language. The theories associated with this model include anomalous family roles, the theory of abnormal communication, the influence of social class, and the theory of cultural change (Zoch, 2002). Lastly, the psychoanalytic model (Fenichel, 1996) posits that individuals with schizophrenia are agents capable of meaningful acts that suggest intentions, motives, or reasons. This model aligns with the hybrid nature of disorders. The theories supporting this model currently include the theory of psychic structures and the theory of reactions to life events (Fenichel, 1996).

Intuitive theories are characterized by the knowledge domain to which they belong, as well as the type of assumptions that experts and non-experts make to explain various mental health issues. Analyzing the causal elements that compose different models is useful for uncovering the intuitions underlying diverse epistemological frameworks in expert contexts, determining the degree of influence exerted by exposure to different explanatory frameworks (Lych and Medin, 2006).

Two important antecedents in the study of causal explanatory models in the field of health, are those of Lynch and Medin (2006) and Maupin (2015). Both evaluate how biomedical training and belief systems typical of different sociocultural contexts influence explanatory frameworks of the diseases. The second emphasized that causal characteristics, albeit from different domains, are not independent of each other, and proposed that the analysis of interactions is useful for discovering the intuitions underlying the various epistemological models.

In this study, Maupin's work was used as a reference. By reconstructing the causal networks of explanatory models of schizophrenia for four groups of experts and non-experts, we described the characteristics and trends for each group. Taking into account the distinction between domain-specific and cross-domains about intuitive theories, we hypothesized that psychiatrists and psychoanalysts would have domain-specific explanatory models of schizophrenia. Specifically, explanations endorsed by both groups of experts would focus on a particular area of knowledge: psychiatrists on the biomedical model and psychoanalysts on the psychoanalytic model. The second hypothesis was that psychologists would tend to exhibit a cross-domain structure in their explanatory models, with a predominance of psychosocial and biomedical models. The third hypothesis assumed that non-experts would also have a cross-domain explanatory model, but instead of psychologist, without predominance of any single model, and rather a blend or synthesis of them all. These assumptions are based on mental health specialists' explanatory models being shaped within academic contexts that provide systematic training. The causal relationships they establish among varied factors acquire coherence and justification from explaining the mechanisms underlying cause-effect relationships. In contrast, non-experts, by appropriating elements from different causal theories, intuitively intertwine causal links without necessarily focusing on justifying the underlying causal mechanisms. This more intuitive and less systematic appropriation of causal theories about mental illness leads to the formation of more holistic explanatory models. Drawing on information from diverse non-specialized sources and/or individual experiences with diagnosed individuals, where sociocultural characteristics also play a fundamental role. To analyze all these hypotheses, a non-experimental, non-probabilistic, cross-sectional, comparative study with a mixed-methods approach was conducted.

Participants

A sample of forty volunteers was recruited through an open call on social media platforms (Instagram, Facebook, and Twitter) and recommendations from specialists. This sample was organized into four equal groups: psychiatrists, psychologists, psychoanalysts, and non-expert people. Data was collected from September to November 2021.

The inclusion criteria were as follows: 1) availability to participate in the study and sign the informed consent form; 2) for expert’s groups: being a psychiatrist or psychiatric resident, or being a psychologist with a bachelor’s degree and/or intern-interested in practicing clinical psychology; or being psychoanalyst with experience in patients with diagnosis of schizophrenia, and/or psychology or psychiatry with formal psychoanalytic training. 3) For non-experts: not having professional training in any mental health disciplines included in the project and not having relatives with a diagnosis of schizophrenia.

Instruments

A sociodemographic questionnaire was designed on the Google Forms platform, for auto-completion by each participant.

An interview consisting of two questions was conducted. In the first part, participants were asked: "Could you list the causes of schizophrenia?" In the second part, a cause-by-cause strategy was used with the question: "How does each factor you mentioned influence the origin of schizophrenia?" Each interview was conducted individually with each participant via a virtual Zoom meeting, lasting approximately 30 to 45 minutes.

From the interview responses, 99 factors were identified. These factors were classified according to four theories: biomedical, psychosocial, sociocultural, and psychoanalytic. Biomedical factors were linked to biological and medical foundations, psychosocial factors to events and social situations, sociocultural factors to culturally articulated aspects of health and disease, and psychoanalytic factors to psychic and interpretative conflicts. After this initial procedure, factors connected with other nodes in the networks were selected, followed by those with the highest centrality measures. A coding table was constructed based on these characteristics and was analyzed and approved by two expert judges.

Procedure

People interested in collaborating got in touch through text messages and email. After confirming their participation and signing the informed consent, an appointment was scheduled for a virtual interview. Before starting the interview, each participant was informed that their voice would be recorded. This interview aimed to identify the direct and indirect causal factors of schizophrenia, considering the questions already mentioned in the instrument section. Recordings obtained during interviews facilitated the compilation of the mentioned factors and the classification of each factor as either direct or indirect.

Characterization of the methodology

A causal network is an applied mathematical tool known as a graph, which makes it possible to observe the association between the ideas and concepts different actors cite as the origin of a phenomenon. The configuration of the network is given by nodes and edges (Hanneman and Riddle, 2005). In this study, nodes represent the causal factors mentioned by each group of experts, and non-experts, and the edges depict the connections between each factor.

The causal chains were recorded in a structure of rows and columns called an incidence matrix according to the arrangement mentioned by every participant in each group. The factors were organized horizontally from left to right, with schizophrenia occupying the far-right position. Subsequently, other factors were placed in the opposite direction until reaching the far left. This last factor was considered by the interviewed individuals as the most indirect cause.

The centrality measures that were calculated to determine the role of each factor within the networks were:

Tie strength: it refers to the thickness of edges connecting nodes, ranging from one to eight based on intensity. Thicker edges indicate stronger relationships between factors.

Closeness: It is the shortest path between nodes. Nodes farther from the schizophrenia node (farness) require more steps, while those closer (nearness) (Aguilar-Gallegos et al., 2017) need fewer steps. In this directed network study, both nearness and farness were considered. Factors with high nearness were positioned toward the right of the causal chain, while those with high farness were located on the left or at the chain's end.

Betweenness: It is interpreted as the essential node connecting the entire network; without it, the network would split. These measures indicate connection strength, stability, and reliability between factors, helping identify shared characteristics among participant groups (Aguilar-Gallegos, 2017; Hanneman and Riddle, 2005).

Statistical Analysis

The sociodemographic questionnaire data were analyzed using the SPSS program version 25. Frequencies and percentages were obtained for qualitative variables (gender and profession) and means and standard deviations for quantitative variables (age and years of professional experience).

The causal networks were constructed with the 99 gathered factors mentioned in the instrument section. By summing the incidence matrices for each group (laypersons, psychologists, psychoanalysts, and psychiatrists), the frequency of each connection between different factors was recorded. The matrices constructed in Excel were used to feed Ucinet NetDraw 2.176 (a software package for analyzing and visualizing distinct types of networks). Four causal networks were obtained (Fig. 1–4), including factors that had significant outgoing and incoming connections.

Ethical considerations

The research followed approved protocols by the Ethical Research Committee of the Center for Transdisciplinary Research in Psychology (Project Id: CONBIOÉTICA-17-CEI-003-20190509). More details are provided on the title page.

Sociodemographic data

Thirty specialists participated, 53.3% were women, and the mean age was 34.7 years (SD = ± 10.8). Most had clinical experience and 20 (66.6%) reported having worked with patients diagnosed with schizophrenia. Non-experts comprised ten subjects, 50% women, and a mean age of 31.7 years (SD = ± 13.9) (see Table 1).

Table 1

*Sociodemographic characteristics by group of participants*
	Man	Women	Nonbinary	Age			CE	CWPS
	Fc	Fc	Fc		SD		SD	Fc
Psychologists	2	8	-	30.2	7.5	1	1.5	4
Psychiatrists	6	4	-	34.6	11.6	8.1	10.4	10
Psychoanalysts	6	4	-	39.3	11.9	3.3	2.9	6
Non-experts	4	5	1	31.7	13.9	-	-	-
Note. FC = frequency; CE = clinical experience; CWPS = Currently working with patients with schizophrenia

Summary of Results

Of the 99 causal factors mentioned, 37.4% were biomedical, 22.2% psychosocial, and 20.2% each sociocultural and psychoanalytical. Psychologists and non-experts included factors from all models, with psychologists leaning towards the biomedical model and non-experts towards the psychosocial model. Psychiatrists' networks were 60% biomedical, while psychoanalysts' networks were 61% psychoanalytic. Although expert groups are in the mental health field, they showed low concordance in their causal models.

Table 2

*Closeness centrality and betweenness of factors in participants*
Factors (Nodes)	Nearness	Far-ness	Betweenness (%)
Psychologists
Changes in brain chemistry	13.4	34.2	18.2
Substance use	13.2	37.8	24.1
Dysfunctional interpersonal relationships	13.4	33.9	13.0
Sexual Abuse	-	47.5	-
Significant losses	-	32.5	-
Genetics	-	34.8	8.6
Alterations in the functioning of dopaminergic activity and other neurotransmitters	-	34.2	-
Viral diseases in the second trimester of pregnancy	-	30.7	-
Stress	-	29.7	-
Psychiatrist	-	-	-
Activation of genes susceptible to environmental phenomena	6.5	6.5	33.2
Poor nutrition during pregnancy	6.7	-	-
Genetics	-	9.5	-
Adversities of early life	6.6	-	-
Families with high expressed emotionality	6.6	-	-
Decrease of hippocampal structures	6.6	-	-
Late pregnancy	-	6.9	-
Belonging to certain religions	-	6.7	-
Environmental pollution	-	6.6	-
Neural Death	-	5.9	-
Substance use	-	-	7.2
Poor nutrition	-	-	6.5
Aggressive environment	-	-	4.5
Domestic Violence	-	-	2.4
Psychoanalysts	-	-	-
Language	8.0	8.1	10.1
Subjective personality structure	8.0	7.9	7.9
Form of relationship to experiences	8.0	8.0	8.8
Form to response to social demands	8.0	8.0	8.2
Forclusion of the father’s name	7.9	8.1	6.3
Return of libido to the self	7.9	7.9	-
Gene coding problems	-	8.6	-
Non-expert group	-	-	-
Stress	17.2	17.3	20.4
Psychological abuse	17.8	18.1	14.7
Changes in brain chemistry	17.6	17.6	6.6
Anxiety	17.2	17.5	18.1
Brain Damage	17.1	16.6	7.9
Physical violence	17.2	17.1	6.6
Depression	17.3	15.5	5.9
Feeling of constant vulnerability	16.7	17	-
Low self-confidence	18.6	-	-
Ambivalent parenting	-	19.3	-
Social and political rules	-	18.8	-
Parental overprotection	-	18.1	-
Note. Form of the relationship to experiences refers to the position taken by patients who receive a diagnosis of schizophrenia. For example, they may take a passive position or an active position.

Results of the Psychologists’ Group

Table 2 shows the results of the network analysis for the psychologists’ group. Changes in the brain chemistry factor obtained 13.4% of nearness, 34.2% of far-ness and 18.2% of betweenness. The substance use factor obtained 13.2% of nearness, 37.8% of far-ness and 24.1% of betweenness. Dysfunctional interpersonal relationships obtained 13.4% of nearness, 33.9% of far-ness, and 13.0% of betweenness. From this group's perspective, these three factors are the most influential for schizophrenia, acting as significant triggers and linking other factors. Factors with a higher indicator in a single measure were nearness, sexual abuse at 47.5%, and significant losses at 32.5%. Other factors that showed more centrality can also be seen in Table 2.

Figure 1 presents the four reconstructed networks for each group, illustrating the tie strength and factors with high centrality indicators. Figure 1-A shows the network for the psychologist group.

Results of the psychiatrists’ group

Table 2 shows the factor activation of genes susceptible to environmental phenomena with a nearness of 6.5%, far-ness of 6.5%, and betweenness of 33.2%. The factors with the greatest nearness were poor nutrition during pregnancy (6.7%), the strongest trigger (far-ness) was genetics (9.5%), and the bridging factor was the activation of genes susceptible to environmental phenomena (33.2% betweenness).

Figure 1-B shows the tie strength analysis combined with high centrality factors identified by the psychiatrists' group.

Results of the group of psychoanalysts

Subjects in this group identified five key factors: language, subjective personality structure, form of relationship to experiences, and form to respond to social demand. The most direct causal factors (nearness) were language and subjective personality structure, both at 8.0. The trigger (far-ness) was gene coding problems at 8.6%, with language as the most frequent bridging factor (betweenness) at 10.1% (Table 2).

Figure 1-C shows the tie strength analysis combined with high centrality factors identified by the psychoanalysts' group.

Results of the non-experts group

Table 2 presents the layperson group's results, highlighting seven key factors for nearness, far-ness, and betweenness. Participants selected factors spanning the four theoretical models, due to their intuitive but non-specialized knowledge.

Figure 1-D shows the tie strength analysis combined with high centrality factors identified by the non-experts group.

Pairwise Pattern Comparison

Figure 2 presents four heat maps characterizing each participant group according to the four theories of schizophrenia. Each row represents one subject (numbered 1 to 10), while columns represent factors from different theories: biomedical (columns 0–3), psychoanalytic (columns 4–5), psychosocial (columns 6–10), and sociocultural (columns 11–13). The last column shows the number of times each subject attributed their causal composition to schizophrenia.

The first heat map characterizes the responses of psychologists, showing that the third and tenth subjects had similar response patterns, covering almost all columns. The first subject emphasized psychosocial and sociocultural elements (columns 11 to 13), while others favored biomedical elements (columns 0 to 3). Psychiatrists, represented in the second map, predominantly cited biomedical, psychosocial, and sociocultural factors (columns 0 to 3 and 11 to 13), with a focus on epigenetics. Psychoanalysts' responses, shown in the third map, fell within psychoanalytic elements (columns 4 and 5), with one subject resembling the psychiatrists' epigenetic approach. The final map for non-experts shows a tendency towards psychosocial and sociocultural factors (columns 6 to 13), with some choosing psychoanalytic elements, highlighting significant losses as a key factor.

DISCUSSION AND CONCLUSION

This research aimed to reconstruct and analyze causal models of schizophrenia with the collaboration of three groups of health specialists and non-experts. We hypothesized that psychiatrists and psychoanalysts would develop domain-specific causal networks based on their respective explanatory models, while psychologists would integrate psychosocial and biomedical models in cross-domain explanatory frameworks. Non-experts were expected to construct causal networks from cross-domain explanatory models without clear distinctions between specific models. The analysis of these causal models revealed consistent patterns observed in previous research, illustrating domain-specific variations among health specialists and non-experts (Lynch and Medin, 2006; Maupin, 2015).

Main findings

Our data support the domain-specific hypothesis (Lynch and Medin, 2006; Maupin, 2015) for at least two specialist groups. Psychiatrists emphasized activation of genes susceptible to environmental phenomena, poor diet during pregnancy, and genetics as key factors. Psychoanalysts identified language, subjective personality structure, form of relationship to experiences, and response to social demands as central factors.

Psychologists and non-experts align more closely with a cross-domain explanatory model. Psychologists emphasized changes in brain chemistry and substance use as direct links in the causal chain, with sexual abuse serving as an indirect bridge linked closely to dysfunctional interpersonal relationships and significant losses. Non-experts identified psychological abuse, anxiety, low self-confidence, ambivalent parenting, genetics, and stress as significant factors. These findings underscore distinct causal links and connections across the groups, despite their shared focus on mental health.

Analyzing causal networks reveals diverse perspectives among different groups, exposing epistemological, ontological, and methodological discrepancies that may be overlooked in analyses focused on a single group's causal perspectives. This approach illustrates how varying patterns of reasoning lead to the emergence of different explanatory models (Hanneman and Riddle, 2005; Lynch and Medin, 2006; Sperber, 2005).

Psychologists posit that schizophrenia can be triggered even in the absence of genetic factors, though the likelihood of chronic symptoms increases with their presence. Meanwhile, while the factors cited by psychiatrists align with biomedical theories and models by implicating physiological malfunction, they do not consider these factors to be exclusive. Despite satisfying the domain-specific hypothesis, psychiatrists do not view mental disorders as being caused by specific agents like viruses, bacteria, or physical anomalies within the body.

This epistemic conflict underscores the profession's stance that there is no singular biological mechanism responsible for the psychological and cognitive dysfunctions characteristic of schizophrenia. This perspective is supported by the multitude of factors cited as causing the disorder, which psychiatrists believe form distinct causal patterns impacting each patient individually rather than universally (Boorse, 1975; Borsboom et al., 2016; González, 2007; Sanchez de las Matas, 2011).

Psychoanalysts do not view schizophrenia as either a disease or a psychiatric category. Instead, they see it as a psychic structure that develops through interpersonal exchanges, enabling individuals to assert themselves in society through language. They emphasize coping mechanisms for incidents or circumstances that can disrupt identity. According to psychoanalysts, these acts, when interpreted retrospectively, reveal an individual's unique ways of suffering, desiring, loving, and living (Allouch, 2022).

Non-experts' understandings are based on lifetime observations and informal explanations from relatives and friends, as none of them had relatives with the condition (per the inclusion criteria), consistent with Furnham and Rees (1988). However, genetics was also deemed significant in this group, similar to the psychiatrists' group. Unlike psychiatrists, non-experts believe genetics plays a crucial role, considering schizophrenia more likely if there is a genetic component.

Contrary to Furnham and Rees (1988), recent research emphasizes the genetic and neurobiological origins of schizophrenia, and this information has permeated society (Abel and Nickl-Jockschat, 2016; Charney et al., 2017; Ross and Margolis, 2006) Additionally, it is now more common for the study and treatment of schizophrenia to occur within an institutional-medical framework. However, given its multifactorial origin and the social, cultural, and historical differences in its manifestation, it is essential to reevaluate this position. Broadening perspectives to include other disciplinary frameworks and incorporating views from outside academic and hospital institutions is necessary (Sacristán, 2020; Sperber, 2005).

Final considerations and limitations of the study

The methodology and results of this study could significantly benefit future research on schizophrenia and other mental disorders. This study offers initial evidence of causal explanation networks in Mexico, comparing diverse groups of specialists. However, replicating these findings in a larger sample is needed to validate observed differences in factors.

These results explore the different patterns of causal attribution between mental health specialists and non-experts. Future analyses should consider the diverse contexts in which these groups operate and how these contexts influence the construction of causal networks and support for various explanatory models.

This study aims to foster interdisciplinary dialogue and engage individuals outside traditional mental health disciplines. Collaborations between fields like cognitive medical anthropology, psychology, and sociology suggest incorporating perspectives from patients, family members, and cultural contexts where the illness manifests. This approach deepens our understanding of how societies conceptualize and experience these conditions, and we hope this research advances interdisciplinary discussions and insights into mental health phenomena.

Conflict of interest

The authors declare that they have no conflict of interest.

Funding

None

Author Contribution

Cecilia Ávalos-Tinoco: made substantial contributions to the conception or design of the work; the acquisition, analysis, and interpretation of data; and, drafted the workDiana Platas-Neri: made substantial contributions to the conception or design of the work; the interpretation of data; and drafted the work.Silvia Piña-Romero: made substantial contributions to the conception or design of the work; the analysis, and interpretation of data;Bernarda Téllez-Alanís: revised it critically for important intellectual content, and approved the version to be published.Marta Caballero: revised the manuscript critically for important intellectual content, and,approved the version to be published.Mariana Salcedo-Gómez: made substantial contributions to the conception or design of the work; the interpretation of data; and drafted the work.

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No competing interests reported.

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Comparative Study of Causal Explanatory Models of Schizophrenia: Mental Health Specialists and Non-Experts in Mexico

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Abstract

Figures

INTRODUCTION

METHOD

Participants

Instruments

Procedure

Characterization of the methodology

Statistical Analysis

Ethical considerations

RESULTS

Sociodemographic data

Summary of Results

Results of the Psychologists’ Group

Results of the psychiatrists’ group

Results of the group of psychoanalysts

Results of the non-experts group

Pairwise Pattern Comparison

DISCUSSION AND CONCLUSION

Main findings

Final considerations and limitations of the study

Declarations

Conflict of interest

Funding

Author Contribution

References

Additional Declarations

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