SIS Journal of Projective Psychology & Mental Health

Case 33: Projective Indicators of Substance Use Disorders on Somatic Imagery Test

Titiksha Paul & Anand P. Singh

from SIS J. Proj Psy & Mental Health (2024) 31: 1, 99-105

Substance use disorder (SUD) is characterized by long-term exposure to substances leading to mental and physical dependence, often resulting in social, academic, and occupational impairment. Understanding the projective indicators of Substance use disorders is important for targeted interventions and treatment. Thus, the aim of this study is to examine the projective indicators of substance use disorders on the SIT. The data was collected from patients with clinical diagnosis of SUDs belonging to the age group of 18-35 years old from De-Addiction Centres Delhi/NCR region. A descriptive analysis was performed, and it was found that the patients with SUDs had low human, sex, movement, most typical and typical responses as compared to normal controls. In addition, they displayed high animal, anatomical, other responses, total number of responses and rejection of cards, pathological anatomical and hostility aggression scale as compared to the normal group. The results suggested that interventions targeting emotional regulation and adjustment may be valuable in the treatment of SUDs.

Introduction:

Substance abuse is an enduring medical and societal concern (Gardner, 2011). All organisms instinctively seek positive stimuli and avoid negative ones for survival, regulated by the nervous system. Neurobiology employs evolutionary processes like homeostasis and learning to adapt to stimuli (Daniel & Pollmann, 2014). Across species, similar responses to positive and negative stimuli indicate their importance for survival, reflected in shared neurobiological mechanisms (Scaplen & Kaun, 2016). Human ingenuity has enabled the extraction and refinement of highly reinforcing stimuli that surpass naturally occurring reinforcers. Notably, humans have developed the ability to purify and deliver drugs, such as alcoholic beverages, cigarettes, drug injection equipment, and vaping devices. Advances in chemistry have also introduced potent psychoactive substances like synthetic opioids, cannabinoids, and stimulants. Access to these highly reinforcing drugs, combined with promotive environments and individual vulnerabilities, including mental illness, chronic pain, genetics, gender, and youth, contribute to drug experimentation and the risk of substance use disorders (SUD) (Volkow et al., 2019).

According to the Diagnostic and Statistical Manual of Mental Disorders 5 (DSM-5), substance use disorder (SUD) is characterized by compulsive drug seeking, impaired control of substance use, impaired social interactions, risky drug use, and pharmacological changes (American Psychiatric Association, 2013). The American Society of Addiction Medicine (2011) describes addiction as a treatable, chronic medical disease resulting from complex interactions among brain circuits, genetics, environment, and life experiences, leading to compulsive substance use or behaviour despite harmful consequences.

Globally, in 2021, approximately 270 million people (5.5% of the population aged 15-64) had used psychoactive drugs, with around 35 million affected by drug use disorders (World Health Organization, 2021). In India, alcohol, cannabis, and opiates are widely used substances, and drug misuse is prevalent in society. The most commonly used substances are alcohol, cannabis, opium, and heroin, with buprenorphine, propoxyphene, and heroin being the most commonly injected drugs. It is estimated that in India, 62.5 million people use alcohol, 8.75 million use cannabis, two million use opiates, and 0.6 million use sedatives or hypnotics (Kumar, 2004).

The research studies have provided valuable insights into the personality characteristics associated with substance use disorders (SUDs). Gonçalves et al. (2022) examined the maladaptive personality traits of individuals with Depressive Disorders (DD) and SUDs using the Personality Inventory for DSM-5 (PID-5). They found that irresponsibility, deceitfulness, and callousness were prominent traits in individuals with SUDs. Similarly, Fodstad et al. (2022) compared personality traits in a sample of Norwegian individuals with SUDs to the norm sample, revealing higher neuroticism and lower conscientiousness, agreeableness, extraversion, and openness among those with SUDs. Hashemi et al. (2019) also observed differences in personality traits between drug users and non-users, with drug users exhibiting higher novelty seeking and harm avoidance but lower reward dependence and self-directedness. Zilberman et al. (2018) explored personality profiles across various addiction types, highlighting elevated levels of impulsivity and neuroticism in addicted individuals. Finally, Habersaat et al. (2018) found sex differences in the relationship between personality disorder traits and SUDs among adolescents, with antisocial and borderline traits positively associated with SUDs.

Thus, the aim of the study was to explore the Projective Indicators of Substance Use Disorders on Somatic Inkblot Test.

Method:

Sample:

The data was collected from patients with clinical diagnosis of substance use disorder. Thus, a total of 30 (15 patients with substance use disorder and 15 normal controls) participants falling between the age group of 18-35 years old from De-addiction Centres, Delhi/NCR region. Further, patients with family history of psychiatric illness, families involving step parents/adopted parents and patients with neurodegenerative/ neurodevelopmental disorders were excluded from the study. Purposive sampling was used in this study.

Procedure:

The consent was taken from the participants and a data sheet containing Information about sociodemographic data was collected. Alcohol, Smoking and Substance involvement Screening test (ASSIST) was used to determine the severity of the substance used among patients with substance use disorder followed by the administration of Somatic Inkblot Test to assess the personality of the participants.

Measures:

The tools used in the research study are –

Alcohol, Smoking and Substance Involvement Screening test (ASSIST)

The Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST) was created by a global team of addiction researchers and clinicians affiliated with the World Health Organization (WHO) in response to the significant global public health challenges associated with psychoactive substance use. The ASSIST (version 3.1) is an 8-item questionnaire designed to be administered by a healthcare professional with an aim to screen for the use of different substances such as tobacco, alcohol, cannabis, cocaine, amphetamine-type stimulants (ATS), sedatives and sleeping pills (benzodiazepines), hallucinogens, inhalants, opioids, and other drugs. (World Health Organization, 2010). The test demonstrates good to excellent test-retest reliability, with reliability coefficients (kappas) ranging from 0.90 for consistency of reporting substance use to 0.58 for regretted actions under the influence. Reliability coefficients for different substance classes range from 0.61 for sedatives to 0.78 for opioids (WHO ASSIST Working Group, 2002). It also exhibits strong concurrent, construct, and discriminative validity (Humeniuk et al., 2008).

Somatic Inkblot Test

The Somatic Inkblot Test (SIT) is a semi-structured, projective, diagnostic test and an adjunct to psychotherapy. The SIT is available at www.dubayhealingcenter.com, with 30 images was released for quick assessment, after 30 years of intense data collection on clinical, organizational, and normal groups. Researchers have reported high reliability and validity and papers published in the international journal, “SIS Journal of Projective Psychology and Mental Health''(www.somaticinkblots.com) clearly show the advantages of the SIT both in the “individual” as well as “group administration” settings. The test provides insights into the patient's imaginative capacity, functioning intelligence, self-projection, interpersonal relationships, and psychological well-being. The SIT is backed by three theories known as Somatic Imagery Theory, Theory of Body Symbolism and Theory of Inner Cry. These have fulfilled the theoretical gap of the Rorschach test (Cassell & Dubey, 2003; Dubey et al., 2019).

Data Analysis

Inkblot protocols were analysed using the standard procedure (Dubey et al,2019) The data was further analysed using IBM SPSS for Mac, Version 20.0.

Results:

Preliminary Analysis

Preliminary analysis of the data was conducted, which includes descriptive statistics. The key variables used are various parameters on Somatic Inkblot Test (SIT) such as Human, Animal, Anatomical, Sex, Other responses, Most Typical Responses, Typical Responses, Movement, Pathological scales and Total number of responses.

The data indicates that the 40% of the subjects lies in the age range of 31-35 years and 27% lies in the age range of 8-24 years among patients with substance use disorders, whereas 47% of the subjects lies in the age range of 25-30 and 20% lies in the age range of 31-35 among normal controls. Thus, it suggests that the mean age of patients with substance use disorder and normal controls was 27.93% and 26.47% respectively, which is crucial age to contribute to the economic development of the society. 60% of the subjects were unemployed and 40% were employed among patients with substance use disorders, whereas all in normal group were employed. 33% of the subjects had only single parents among patients with substance use disorder, whereas 60% of the subjects had nuclear family structure among normal controls. 54% of the subjects had a diagnosis of polysubstance which indicates that they consumed more than one drug such as alcohol, tobacco, cannabis, and opioids, 20% were alcohol dependent and 13% were cannabis and opioids dependent each.

Table 1. Mean and S.D. of Adjustment, Emotional Regulation, and Indices on Somatic Inkblot Test

	Substance Use Disorder		Normal Controls
	Mean	S.D.	Mean	S.D.
Human	3.27	0.88	11.6	1.40
Animal	8.47	2.41	3.47	1.13
Anatomical	6.8	1.52	4.93	1.83
Sex	0.40	0.63	1.93	1.03
Other Response	11.13	2.07	2.07	0.80
Most Typical	7.93	0.80	9.73	0.46
Typical	5.53	0.91	7.07	0.96
Movement	3.8	1.15	7.8	0.94
Total Responses	49.49	2.77	48.93	3.41

Table 2. Comparison of two groups on Somatic Inkblot Test – Content Category

	Substance Use Disorders		Normal Controls
	Frequency	Percentage (%)	Frequency	Percentage (%)
Human	49	6.60	174	23.71
Animal	127	17.12	52	7.08
Anatomical	102	13.75	74	10.08
Sex	6	0.80	29	3.95
Other response	167	22.51	31	4.22
Movement	57	7.68	117	15.94
Most Typical Response	119	16.04	146	19.89
Typical	83	11.19	106	14.44
Pathological Anatomy Scale (PAS)	10	1.35	0	0
Depression Scale (D)	3	0.40	3	0.41
Hostility Aggression Scale (HAS)	18	2.43	2	0.27
Paranoia Scale (P)	1	0.13	0	0
Total Number	742		734
Rejection of responses	9		2

A descriptive analysis was carried out, tabulated, and depicted in Table 2 for Content category. It demonstrated that patients with substance use disorder had low human (7.04%), sex (0.80%) and movement (7.685) among patients with substance use disorders as compared to normal controls. In addition, they displayed high animal (17.12%), anatomical (13.75%) and other (22.51%) responses as compared to the normal group. Further, patients with substance use disorder displayed low most typical (16.04%) and typical (11.19%) responses as compared to the normal group. In addition, patients with substance use disorders scored high on Pathological Anatomical Scale (1.35%) and Hostility Aggression scale (2.43%) as compared to the normal controls. Lastly, there were high number of total responses and rejection of card among patients with substance use disorder as compared to the normal controls.

Table 3. Comparing the Somatic Inkblot Indices among two groups on Mann-Whitney U test

Variables	Groups	N	Mean Rank	U	Z	P
Human	SUD	15	8	225	4.711	.000*
	Normal	15	23
Animal	SUD	15	22.40	9.000	- 4.339	.000*
	Normal	15	8.60
Anatomical	SUD	15	21.93	16	- 4.081	.000*
	Normal	15	9.07
Sex	SUD	15	9.93	196	3.627	.000*
	Normal	15	21.07
Other Response	SUD	15	23	.000	- 4.717	.000*
	Normal	15	8
Most Typical	SUD	15	8	225	4.833	.000*
	Normal	15	23
Typical	SUD	15	8	225	4.757	.000*
	Normal	15	23
Movement	SUD	15	8.03	224.50	4.691	.000*
	Normal	15	22.97
Pathological Anatomy Scale (PAS)	SUD	15	15.50	112.50	.000	1.000
	Normal	15	15.50
Depression Scale	SUD	15	15.10	118.50	.384	.806
	Normal	15	15.90
Hostility Aggression Scale (HAS)	SUD	15	22.80	3.000	- 4.848	.000*
	Normal	15	8.20
Paranoia Scale (P)	SUD	15	16	105	-1.000	.775
	Normal	15	15

(p<.50*)

Discussion:

The study explored the underlying mechanism of the various parameters of Somatic Inkblot Test. A descriptive analysis was carried out, tabulated and depicted in Table 2 for Content category. It demonstrated that patients with substance use disorder had low human responses (7.04%) which was indicative of lack of interest in other and poor interpersonal skills. There were low sex responses (0.80%) on images with imbedded sexual structure among patients with substance use disorder which may indicate deep rooted sexual conflict and a strong indicator of impotency (Dubey & Dubey, 2021). In a meta-analysis which included five case–control studies with a total of 3,395 men demonstrated a higher prevalence of erectile dysfunction in cannabis users (more than two-thirds) and leading to four times increased odds ratio of erectile dysfunction in cannabis users compared to controls (Pizzol et al., 2019). In another study, it was found that illicit drug male abusers were prone to have ED, decreased sexual desire, and increased ejaculation latency. Erectile dysfunction and decreased sexual desire were most commonly seen in heroin, followed by amphetamine and MDMA mono-users, while increased ejaculation latency occurred commonly in all of the abusers (Bang-Ping, 2009). Vallejo‐Medina & Sierra (2013)reported that the erection scale scores obtained by people with a history of substance abuse were lower than those of non-users. Therefore, the results obtained are consistent with the studies on the role of impotence among drug users.

Patients with substance use disorders also displayed low movement responses (7.68%) as compared to normal control, indicating a tendency towards withdrawal and aloofness, as well as poor adjustment and interpersonal relationships. Loneliness was found to be stronger in drug abusers, potentially leading to a sense of being different from the community and an increased likelihood of engaging in risky behaviours (Dubey & Dubey, 2021). In a study conducted by Hosseinbor et al. (2014) it was revealed that there were statistically significant difference between the scores of all four emotional, social, familial, and romantic dimensions of loneliness in substance dependent individuals. Thus, it could be inferred that the feeling of loneliness is stronger in drug abusers rather than non-drug abusers that could develop the sense of being different from community and increase the probability of taking high risk behaviours and abusing drugs. Longitudinal analyses indicated that high levels of drug use early in the year were related to subsequent increases in behavioural and emotional maladjustment (Luthar & Cushing, 1997).

Moreover, patients with substance use disorders exhibited high animal responses (17.12%) as compared to normal group, suggesting a stereotypical approach to the world, immature thinking, and an aggressive attitude. Substance abuse can lead to an increase in domestic violence, sexual assault, suicide attempts, and other aggressive behaviours (Martens & Generes, 2022). The results have been consistent with various studies which indicates that aggression and delinquency were positively correlated with each other whereas delinquency was positively correlated with drug use. Aggression also had a positive relation with drug use. The results further explained that drug use act as a moderator among aggression and delinquency for male adults (Shabbir, Javaid, et al., 2020). Another form of aggression known as cyber aggression appears in many ways to be an insidious extension of traditional human aggressive behaviour intended to cause and may result in harm to the target, who is often a known peer or relationship partner. Research has suggested that substance use, specifically alcohol use, is associated with an increased risk of perpetrating cyber aggression and it is more likely to occur among older than younger participants and within the context of an intimate partnership rather than a peer relationship. Aside from alcohol, cyber aggression shared a small-to-negligible correlation with other substances, all evidencing a comparable magnitude (Crane et al., 2021).

Furthermore, patients with substance use disorders showed high anatomical and other responses (13.75%) as compared to normal controls, indicating somatic preoccupation, bodily symptoms, tension, anxiety, and psychological disturbances. In contrast, the normal control group displayed high human responses, indicating smooth interpersonal relationships, high self-esteem, and good interpersonal skills, as well as high movement responses associated with fantasy, creativity, intelligence, and active involvement (Dubey & Dubey, 2021).

The findings from table 2 also suggested that patients with substance use disorders had fewer typical and most typical responses compared to the normal controls, indicating difficulties in adjustment and interpersonal relations. These individuals are often misunderstood and struggle to fit into teams, showing a withdrawn attitude and ignorance of societal demands. Patients with substance use disorder also exhibited minor abnormalities in the Pathological Anatomical Scale and Hostility Aggression scale, but did not meet the criteria for hypochondria or excessive concern about physical health. Their responses displayed minor aggression, making it challenging to control their aggressive behavior, particularly in emotionally provoking situations. Furthermore, in the Pathological scales category, both patients with substance use disorders and normal controls had low scores on the Paranoia and Depression scales (Dubey & Dubey, 2021).

Conclusion:

The findings of this study contribute to our understanding of the projective indicators of adjustment and emotional regulation among patients with SUDs. The results suggest that interventions targeting emotional regulation and adjustment may be valuable in the treatment of SUDs. Future research should further explore these projective indicators and their implications for intervention and treatment strategies. By addressing these psychological factors, clinicians and researchers can enhance the effectiveness of interventions and improve outcomes for individuals with SUDs.

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