Background
Anabolic-androgenic steroids (AAS), comprising testosterone and synthetic derivatives, are typically used within the weight-lifting and bodybuilding communities to develop lean muscle mass. The global lifetime prevalence of AAS use is estimated to be 6.4% for men, and 1.6% for women, though these estimates are higher among certain populations including those with substance use disorder and athletes [
1‐
3].
AAS use has been associated with a wide range of psychiatric and somatic health consequences including cognitive deficits, aggression, cardiovascular problems, and hypogonadism [
4‐
11]. Approximately one-third of people who use AAS develop
dependence [
12,
13], which is characterized by AAS withdrawal, including hypogonadism symptoms (depression, anxiety, fatigue and sexual dysfunction), anxiety due to reduced muscle volume, and continued use despite negative impacts on physical and mental health [
14‐
16]. AAS dependence is likely driven by both psychosocial and biological factors, including perceived positive effects such as increased strength and libido, decreased executive function, and a need to continue administering exogenous testosterone as natural production is disrupted [
8,
17‐
19]. People with AAS dependence are at a greater risk for adverse health outcomes due to longer durations of use and higher doses. Thus, understanding the symptoms of and risk factors for AAS dependence is critical for providing optimal treatment to this population, and preventing severe and enduring side effects.
One of the proposed etiological factors for AAS dependence includes body image disorders, primarily
muscle dysmorphia (MD) [
16]. MD is a type of body dysmorphic disorder characterized by a persistent belief that one is too small or lacking musculature, despite having a normal or unusually muscular appearance [
20,
21]. While certain behaviors and attitudes towards diet, exercise, and supplement use are not typically considered to be indicative of any pathology, these behaviors can be taken to extremes which influence functioning and quality of life [
22]. MD is associated with appearance and performance-enhancing drug (APED) use, including AAS [
23‐
26]. Strength athletes exhibit higher levels of MD symptoms compared to the general population, with a particularly high prevalence among bodybuilders, relative to other resistance-training practitioners [
27‐
29]. Within this population, there are also significant associations between symptoms of MD and other risky health behaviors including eating disorders and compulsive exercise [
29,
30]. In addition, MD symptoms are associated with other psychiatric problems including anxiety, neuroticism, depression and perfectionism, and thus may be a marker of greater mental health problems [
27].
Previous studies indicate that MD is associated with initiating AAS use and duration of use, but the relationship to AAS dependence is less clear [
31,
32]. Some findings suggest that AAS use is a perpetuating factor in the progression of MD [
33], while others conclude that prolonged AAS use does not exacerbate symptoms of MD. However, specific symptoms, including social physique anxiety, or distress connected to the perceived evaluation of one’s body, may be related to severity of AAS dependence [
34]. Thus, the relationship between MD and AAS dependence is not well understood, and further investigation at the symptom level may provide critical insights. Pharmacological use is common among individuals with MD, and includes the use of AAS, laxatives and diuretics. Previous studies among recreational exercisers indicate that MD symptoms including exercise dependence, drive for size/symmetry, and pharmacological use are associated with intentions to use APEDs, however the relationships among these symptoms and AAS dependence symptoms has not been investigated [
35].
Understanding symptom structures of MD and AAS dependence, and the potential connections between these two groups of symptoms, may provide clinically relevant information about the development and prognosis of AAS dependence. Using network analysis, mental disorders and other complex conditions are understood as systems of interacting behaviors and experiences that dynamically influence one another, rather than manifestations of a specific latent pathology [
36‐
38]. Undirected network analysis aims to identify the structure and strength of interactions between measured symptoms, without establishing directionality or causality. In these networks, nodes represent individual symptoms, and the strength of their connections, termed edges, reflect the associations between each symptom pair (often operationalized as a correlation). Principles from graph theory can be used to describe both global and local characteristics of the network, including node centrality and various estimates of overall node clustering, i.e. the degree to which the various symptoms represent sub-clusters or modularity. Network analysis has been applied to a variety of psychiatric disorders including eating disorders, PTSD, depression and substance use disorders (SUD), with potential clinical implications. For example, nodes which are central to the network can be interpreted as primary targets for clinical intervention, as improvement on these symptoms may contribute to alleviation of other symptoms in the network [
37,
39,
40]. The persistence of the disorder or syndrome is thus determined by the extent to which the symptoms are interconnected. Nodes which connect two clusters within a network are deemed “bridge” nodes, which may indicate the pathway by which two clinical domains or disorders are connected [
41], and may provide valuable information about mechanisms of comorbidities. For example, it was demonstrated that perfectionism symptoms bridge obsessive compulsive and eating disorders, suggesting that interventions targeting perfectionism behaviors may alleviate symptoms of both obsessive compulsive and eating disorders [
42].
Previous studies have constructed dependence symptom networks for psychoactive substances, though this method has not been applied to APEDs. Network modeling supported the intuitive notion that using a drug more than planned, and spending a significant amount of time obtaining, using, or recovering from substance use were the most central symptoms of SUD [
43,
44]. Furthermore, a network analysis of body dysmorphic disorder in a clinical sample found that interference in functioning because of appearance-related compulsions was the most central symptom [
45]. These studies provide evidence that network analyses contribute to clinically relevant findings, and applying these methods to AAS dependence will similarly elucidate the most critical symptoms. Network analysis can identify differences in symptom structures between groups, including variations in MD symptom centrality between those who use AAS and those who do not, which may provide clinically relevant information about specific symptoms connections within those that use AAS. In addition, these methods can further understanding of the relationships among symptoms of AAS dependence and MD, potentially identifying key symptoms or clusters that drive these frequently co-occurring disorders. While there is a need for research in clinical MD samples, the present study examines behaviors and attitudes as symptoms rather than diagnoses to provide insight into the structure of these symptoms among males who regularly weight train, and those that use AAS [
46].
With the goal of illuminating clinical targets for those seeking to cease AAS use, the current study aimed to identify the most central symptoms of AAS dependence and their connections to symptoms of MD using network analyses. Based on previous findings and current models of comorbidity we pursued the following hypotheses: (1) In a network of AAS dependence symptoms, using more or longer than planned will be most central. (2) In a comparison of MD symptom networks in AAS consumers and weight-lifting controls, supplement and pharmacological use will be more central to the AAS consumers’ network.
3) In a network of AAS dependence and MD symptoms among AAS consumers, we expect that the symptom “using more or for longer than planned” will be a bridge with MD symptoms.
Discussion
In this network analysis of dependence symptoms in AAS consumers, continuing use despite physical/mental problems was the most central symptom, and thus a relevant clinical target. However, life interference, tolerance, and using longer than planned were also highly influential, indicating the connections and importance of both physical and mental symptoms. Our findings also demonstrated higher severity of symptoms of MD in AAS consumers compared to WLC. Additionally, the structures of these symptoms appear to vary between the two groups, suggesting that experiences of MD symptoms differ between those who use AAS and those who do not.
The dependence network identified in this study differs from previous networks based on SUD patients using psychoactive substances [
43,
44]. For example, in the present study,
time spent had the least influence on a network of AAS dependence symptoms. Conversely, in previous studies this symptom was the most central in a network of dependence and harmful substance use symptoms among SUD patients [
44]. In the same study,
continuing use despite physical/mental problems, had high strength in the networks of several substances (alcohol, cocaine, opioids, and stimulants), but had relatively low strength in the cannabis network, suggesting that the symptom structure of AAS dependence may be more similar to stimulants or opioids than cannabis [
44]. It is possible that time spent on substance use is less influential in the AAS network due to the difference in lifestyle and motivation for use of AAS compared to certain psychoactive substances. People who use AAS and other APEDs often report strict diet and exercise routines, requiring significant amounts of time, in addition to forming friendships around these objectives, which may normalize these regiments [
59,
60]. Furthermore, people who use AAS often report spending a considerable amount of time researching these compounds before commencing use [
61], and likely spend considerable amounts of time on other aspects of bodybuilding or fitness including training, diet and supplement use, indicating that further analyses are needed to evaluate the validity of this symptom in AAS dependence specifically.
An earlier investigation of dependence symptoms across all psychoactive substance classes identified
using more/for longer than planned as the most central symptom [
43]. Interestingly, in a subsequent network analysis of only those who used opioids, both
interference with work/life and
using more/longer than planned were identified as highly central symptoms, which demonstrates some similarity with the network identified in this study [
43]. Although speculative, this similarity may be partially explained by shared reward mechanisms for opioid and AAS dependence involving opioid receptors in the dopamine system of the ventral tegmental area, which is often implicated in substance use and addiction [
62‐
64]. In addition, common personality traits and cognitive dysfunctions have been identified in both AAS and opioid consumers [
8,
65,
66]. Furthermore, some of the strong edges in the AAS dependence network may be explained by similarly worded or clearly related items. For example, spending significant amounts of time acquiring and using AAS may take away from time spent on work and personal life, and increasing doses may be representative of a tolerance to AAS. It is therefore logical that
time spent is correlated with
work/life interference, and
using more/longer than planned is correlated with
tolerance in the network.
The differences in MD symptoms between males who used AAS and WLC in the current study align with previous findings, which have identified elevated pathology among those using AAS and other APEDs [
26,
67‐
69]. Furthermore, increased body image disturbance has previously been associated with increased risk of APED use and more time spent exercising weekly [
70]. More broadly, body image concerns likely drive a range of practices, including eating disorders and exercise addiction that put individuals’ health at risk in pursuit of performance or aesthetic goals [
26,
71,
72]. Many practices related to body dissatisfaction may co-occur, as previous research has identified associations between AAS use and eating disorder psychopathology [
72]. In the present study, the structure of MD symptoms varied between AAS consumers and WLC, indicating that
exercise dependence was the most central symptom for AAS consumers, whereas
size/symmetry was most central in the WLC network, suggesting potential differences in body image concerns manifesting as stronger connections among behaviors rather than attitudes. Furthermore, people who use AAS regularly report rewarding effects, including enhanced mood and increased self-esteem while using AAS, which may decrease negative feelings regarding musculature or physique concealment while on-cycle [
73]. While those who used AAS still reported higher levels of physique concealment, the positive effects while on-cycle may partially explain the differences in MD symptom structure. The group differences of
pharmacological use suggest that in addition to abstaining from AAS, those in the WLC group use few or no laxatives or diuretics, whereas a significant portion of the AAS group also use laxatives and/or diuretics in addition to AAS, which is in line with earlier studies indicating that APED polypharmacy is common among AAS consumers [
74]. In addition, the low inter-individual variation in pharmacological use among WLC may explain the low centrality of this symptom.
Furthermore, certain edges differed between the networks in the two groups, particularly those related to diet. Within the AAS group, diet appeared strongly related to both supplement use and exercise dependence, whereas in WLC diet was most strongly associated with size/symmetry concerns. This suggests that MD for AAS consumers consists of particularly strong connections among symptoms that involve taking action to change ones appearance (diets, supplements, training), whereas the WLC network demonstrates greater influence of nodes representative of internalized thoughts and feelings such as wanting to conceal their physiques. AAS consumers have previously demonstrated elevated levels of impulsivity and neuroticism, which may contribute to using more extreme practices and willingness to accept increased risk to achieve their desired results compared to those who do not use AAS [
65,
75].
Motivation for AAS use may partially explain variation in MD symptoms among those who use AAS, as individuals reporting appearance concerns as their main motivation for use are more likely to demonstrate body image psychopathology than those driven by performance enhancement [
76]. However, MD and body image concerns have been reported as both a cause for, and a result of, AAS use [
73]. Thus, motivation for initiation of and continued AAS use should be taken into consideration in clinical settings when evaluating body image concerns. Moreover, in our sample, a greater proportion of AAS consumers participate in bodybuilding, which places a high value on appearance. A previous network analysis of body dysmorphic disorder patients identified interference in functioning due to appearance related compulsions as the most central symptom [
45], which is more similar to the WLC network in the current study. However, it is important to note this study used a different tool to evaluate dysmorphia symptoms in a non-clinical sample, and that the WLC group in this study demonstrated fewer symptoms of dysmorphia on all scales compared to AAS consumers.
Contrary to our expectation, few connections were identified between MD and dependence symptoms. Small connections may exist between being
unable to stop using AAS and
size/symmetry concerns, however the results did not identify any statistically significant differences in bridge EI, though this study may lack power to detect bridges between these symptom groups. The findings indicate clear differences in MD symptoms between WLC and AAS consumers, but no clear connections between MD symptoms and AAS dependence symptoms. It is possible that these associations cannot be detected on the symptom level, but that group differences between people who use AAS with and without dependence may differ on a combined measure of MD. It may also be the case that MD is related to AAS use, but not dependence, in line with previous findings [
31]. However, greater physique anxiety has been associated with more severe dependence, indicating some heterogeneity within the few studies on this relationship [
34]. This may also reflect the heterogeneous nature of people with AAS dependence and MD symptoms, where intra-individual networks could reveal connections between the symptom groups within a single person.
Limitations
The current study has some limitations. The sample size is relatively small for a network analysis, particularly for the MGM analysis. However, this is a hard-to-reach population and the current sample is derived from the largest study to date investigating the effects of AAS on brain health. These results should thus be interpreted with caution, and bootstrapped results and CS coefficients were computed to provide a view of how stable and reliable the results are. In addition, not all participants completed all questionnaires, which may bias results, particularly when comparing the results of the individual networks (of SCID and MDI networks) with the MGM network, as the samples are not identical. This study also relies on self-report measures, which may introduce bias, although the instruments used have been to found to have good validity. The AAS group comprised both past and previous use, which may influence the reporting of dependence symptoms in particular. The cross-sectional nature of this study does not allow for establishing the direction of the relationships among dependence and MD symptoms. Additionally, the MDI scale “pharmacological use” inquired about laxative, diuretic, and anabolic steroid use, the last of which will be homogenous within each of the groups, which may influence the outcome of these networks. Finally, the study sample does not represent a population meeting the clinical criteria for MD. However, the current study aimed to identify relationships among symptoms of AAS dependence and MD in a relevant demographic group, in order to provide an insight into the relationships among these symptoms for men engaged in heavy resistance training, though the results may not be generalizable outside of the Norwegian context.
Conclusion
The current findings from a symptom network analysis support that
continuing use despite negative side effects is a key symptom of AAS dependence.
Life interference,
tolerance, and
using longer than planned had similar degrees of influence on the symptom network, suggesting that alleviating both psychiatric and physical symptoms will be imperative for those with dependence symptoms who want to cease AAS use. Thus, future studies should explore the heterogeneity of these effects, as people who use AAS may be more likely to seek treatment as a result of mental, rather than somatic, health concerns [
77]. The problems related to ongoing AAS use include both physical and mental health issues such as gynecomastia, cardiovascular and liver pathology, mood swings, irritability, and aggressiveness [
78,
79]. Withdrawal symptoms related to hypogonadism are commonly experienced for months during off periods [
80], contributing to continued AAS use to relieve these symptoms. The most central symptoms to the network indicate that this cycle of experiencing side effects and potentially continuing AAS use to alleviate these side effects typifies AAS dependence. Hence, clinicians should aim to identify this experience, and be aware that reducing the discomfort experienced by those who want to quit AAS use is critical.
Additionally, the experience of MD symptomology may differ between those that use AAS and those that do not, in both severity and structure of symptoms. MD symptoms indicative of taking action (diet, exercise, and supplement use) appear to cluster together more for those who use AAS than those who do not, which may be a marker of use for clinicians. In clinical settings, motivation to initiate or continue AAS use should be addressed in order to provide personalized care. Considering that body dissatisfaction is associated with poorer mental health, and greater psychopathology [
81,
82], clinicians, particularly mental health care providers, should take the use or planned use of AAS, and potentially other APEDs, into account when working with men experiencing MD symptoms or body dysmorphic disorders. Additionally, MD symptoms and body image should be evaluated when working with men who use AAS, and their psychological response to changes in muscle volume following a cycle or when attempting to cease use should be explored.
Further studies and larger sample sizes are required to verify the symptom structures identified in the current study, particularly the network including both AAS dependence and MD symptoms. Additionally, network analysis provides a clinically relevant approach to psychiatric disorders, which allows for embracing the complexity of these disorders, and should be applied to AAS dependence and muscle and body dysmorphic disorder more broadly in future research [
83,
84].
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