Emergence and deactivation of neurobiological reward system dysfunction – empirical data on the alternatives that substitute a risky behavior

Full text

Emergence and deactivation of neurobiological reward system dysfunction –
empirical data on the alternatives that substitute a risky behavior
Meinolf Bachmann1, Andrada Andrea Bachmann1, 2
1 Psychotherapic practice
2 Research assistant at Bielefeld University
December-2023
Summary
The construct of the interest and activity spectrum “IAS” (Bachmann, M. 2018, 2019) was verified empirically
for the first time in the following investigation (Bachmann, A. A. 2021). It includes various forms of addiction
and other psychological disorders as well in which a dysfunction of the reward system is also assumed plus
control persons. The persistent practice of an addictive or other risk behavior for emotion regulation and associ-
ated operant conditioning processes in the sense of positive (e.g., increase in well-being) and negative (e.g.,
reduction of worries) reinforcement can lead to a dominance of the risk behavior in the reward system.
It is postulated that fundamental structural changes, in the form of a neurobiological memory anchor-
ing/memory representation of risk behavior, happen in this brain area.
The result is an important narrowing of the range of interests and activities. An automation of the risk behavior
through "implicit" memory structures takes place and is triggered nearly reflexively under certain conditions.
Alternative behaviors, which also have a rewarding and emotionally balancing effect, increasingly fade into the
background and are no longer used. It is obvious to reverse this process in the same way and to restore the
functionality of the reward system by building alternative health-promoting strategies for emotional regula-
tion.
The "patient survey" should provide insights into whether the assumption of a smaller range of interests and
activities in the risk groups can be empirically proven and which alternative reinforcing interests and activ-
ities are particularly suitable for overcoming the dominance of risk behavior in the reward system. The
results of the "patient survey" support the assumption of a smaller and less differentiated range of interests and
activities for the group of addicts and provide indications that this can also be assumed for other mental disorders.
The reward effectiveness of interests and activities were assessed differently. A 10-point categorization was
carried out by means of an "expert survey" (psychologists in education to become BT psychotherapists). The ex-
perts also assessed the rewarding ability (to positively change psychological well-being) of interests and activities.
The category “showing feelings” achieved the highest mean values and the highest rated item was “laughing”
from the same category. There were meaningful parallels to the patient survey.
Including various clinical pictures, the findings serve to develop an individually adapted selection of diverse
"reward-effective" alternatives. Using self-assessment scales, resources are determined and requests for changes
regarding alternatives are recorded that replace risky behavior by improving psychological well-being and emo-
tional regulation in a sustainable manner and setting a reconstruction of the reward system in motion. If the result
is that the reward system mainly generates impulses to repeat and constantly practice these activities instead
of risky behavior, the reconstruction of functionality has been successful. It is assumed that the deactivated,
but still existing, dysfunctional memory structures represent a threat of relapse furthermore.
Keywords: theory/empirical, divers psychic disorders, neurobiological, reward system dysfunctional/reconstruc-
tion, alternatives, interests/activities
1. Theory part
1.1 Introduction
Imaging techniques provide a deeper insight into brain functions. Special attention has been
paid to the reward system (RS), which steers human well-being. Dysfunctions of this system
are found in various mental disorders. Too little care has been paid to the psychotherapeutic
conclusions to be drawn from the neurobiological findings on the dysfunctionality of the reward
system. This is the subject of this essay, a dissertation (plus additional evaluations from existing
data) and a manual based on it (Bachmann, A. A. 2021; Bachmann, M. & Bachmann, A. A.
2023).
The focus is on finding reward-effective "alternatives" to replace risky behavior that causes
dysfunctionality. These alternative activities and interests, which positively influence the

2
psychological well-being, are to be individually adapted and formed as stable habits in order to
restore the functionality of the reward system. A review of the literature reveals that research is
still in the early stages of providing a comprehensive overview of which clinical pictures are
affected by reward dysfunctionality. Thus, the term "other disorders" is more often used to
reflect this fact and a fragmentary presentation of existing empirical data and observations is
not due to a lack of "elegance" in the theory section.
The brain's reward system motivates people to provide for life necessity things such as food
and water and to enter into social relationships (Costandi 2015).
The satisfaction of important needs is experienced as pleasurable and reward generating, there-
fore the reward system activates the repetition of the actions and behaviors that led to the
positive feelings. It steers people's emotional state and serves to regulate the feel-good chem-
istry (cf. Lindenmeyer 2005). In emotional regulation the reward system (RS) initially does not
differentiate between meaningful or lastingly damaging behavior (Grüsser & Albrecht 2007;
Böning & Albrecht-Sonnenschein 2018).
If structural changes in this part of the brain activity leads to behavior that causes mental or
physical damage to health, this is referred to as a functional disorder or dysfunction of the
reward system. The neurobiological findings on a functional impairment of the reward system
have a high explanatory value in the emergence and maintenance of various addictions (alcohol-
, drug-, gambling-related disorders) and other mental disorders (e.g., forms of eating-, obses-
sive-compulsive-, affective disorders).
Overview
However, the term “risk-behavior” includes these other disorders from the start of this article.
In Sect. 1.3.1, the "other mental disorders with a dysfunctional reward system" are considered
in more detail and empirical studies are used. From the integrative cognitive-behavioral-bio-
logical explanatory approach (Bachmann, M. 2018, 2019), the gambling-related disorder es-
tablishes a connection between the substance-related addictions and the other mental dis-
orders, since here too behavior and not a (psychotropic) substance that influences the psyche
is the cause of changes in the reward system. First of all, the theoretical assumptions are mainly
explained using the addictive behavior.
The instructions for action stored in the implicit (unconscious) biographical memory to en-
gage in risky behavior (e.g., to feel bad and reach for sweets) can be influenced less directly
with progressive chronification. “Just let it be" is often ineffective advice when dealing with
this maladaptive behavior. The question arises as to why behavior, that is ultimately harmful
and undesirable, is carried out again and again and why there is a high risk of relapse. It is based
on the assumption that sustained and regular practice of addictive or other risky behavior for
emotional regulation causes fundamental structural changes in the reward system of the
brain. Operant conditioning processes based on positive (add pleasant) and negative (reduce
unpleasant) reinforcement cause neurobiological changes in the RS and trigger risky behavior
nearly reflexively like an “automatic action pattern” without the need for conscious intention
(cf. Böning & Albrecht-Sonnenschein 2018). This process grounds the assumption that risk
behavior in the chronified phase is no longer primarily maintained by the etiological con-
ditions (e.g., initial stress situation) but substantially by neurobiological structural changes in
the implicit biographical memory of reward system. The if-then causality (cause-effect re-
sponse) is influenced by an important neuro-biological component.
Such a memory representation – neuro-biological anchoring of risk behavior – which is
rather unconscious (implicit), less directly influenceable and rather resistant to deletion,

3
is also postulated for other clinical pictures with a dysfunctionality of the reward system, such
as forms of eating-, obsessive- and affective disorders. The term deactivation is introduced in
order to do justice to the continued existence of memory structures (of addictive or other risky
behavior). The problematic memory structures that cause automation of risky behavior are not
completely deleted, but are largely deactivated by building up reward effective (“reward able”
to stimulate rewarding brain circuits) alternative interests and activities.
The memory representation of risk behavior localized in deeper brain regions makes it difficult
for people to realize a more favorable behavior. The influence of reason and logic on this auto-
mated stimulus/response scheme seems to be rather small and engaging in risky behavior can
be associated with feelings of shame, guilt and secrecy.The stressful feelings make open com-
munication about the maladaptive behavior difficult. But how can this controlling brain
region be influenced? The following illustration (Fig. 1) is intended to clarify this process: The
brain region “Reason and Logic” has little direct influence (dotted arrows) on the deeper brain
regions; necessary is intensive practice of new, rewarding/relaxing behaviors (thick black
arrows). This means to activate the reward system in a different way to regulate the feelings
and thus to reduce the importance of the risk behavior again. Other behaviors that are
perceived as pleasant also stimulate the reward circuit. In order for these to become effec-
tive, an individually adapted selection of reward-effective interests and activities and their
intensive practice are necessary to displace risk behavior from its dominant position and to
build up "reflex like" new habits: e.g., not being able to wait to tell someone about experiences,
expressing stressful feelings, or putting on one's sneakers and getting excited about one's newly
won favorite sport, perhaps participating in a (moderately) exciting competition. Initially, frus-
trations and difficulties in realization must certainly be expected, so therapeutic help should not
end too soon.
Fig. 1. Deeper brain areas (reward system), reflexes/autonomic nervous system, steer risk behavior.
Overview
For both substance- and non-substance-related addictions, it is emphasized that the associated
implicit memory representations do not completely delete, so the risk of relapse remains
(Grüsser et al. 2005; Lindenmeyer 2005; Wölfling et al. 2011; Ciccarelli et al. 2016). Stimuli
associated with risk behavior are able to induce a relapse even after a long period without symp-
toms. Above all, unpleasant emotional states (fears, depression, anger, feeling offended, etc.)
contribute to this. Relapse prevention is an independent research area and there is a wide range
Building new
"reflexive"
habits
Little
direct
influence
Reason and logic
RS

4
of materials available to filter out individual vulnerabilities and counteract them (Marlatt 1985;
Bachmann, M. & El-Akhras 2014; Lindenmeyer 2018).
The therapeutic implications resulting from the addictive or risky behavior which becomes self-
perpetuating (own dynamics) have so far received too little attention. The following empirical
study forms the basis for the manual "Der Alternativen-Finder" (Bachmann, M. & Bachmann,
A. A. 2023). In this context it is intended to provide answer to the question of which “reward-
effective alternatives” are particularly suitable to
• overcome the dominance of a risk behavior in the reward system by reward effective
alternative interests and activities
• identify alternatives which have the possible greatest potential influencing psychological
state positively
• contribute to a satisfied lifestyle and a high level of well-being
• form stable new habits
• reconstruct the neurobiological reward system in this way
• largely deactivate the dysfunctional automating memory structures
• establish a persistently constructive regulation of emotions
According to Grawe (2004), the plasticity of brain structures is sufficiently documented. For
many years we have been dealing with the question of what conditions need to be created in
order not to experience abstinence of drugs or absent of other risk behavior permanently as
unpleasant or a loss but as an advantage in the long term.
The construct "interest and activity spectrum" (IAS) represents a psychological operationaliza-
tion of the reward system (RS). It is assumed that a narrowing/reduction of the spectrum, com-
pared to healthy control persons, indicates a possible dysfunction of the RS (Bachman, M. 2018,
2019).
An interest and activity pool of 176 items was created through open responses, which took
place mainly in therapy groups over several years and comparisons with mostly unsystematic
existing lists. By means of an "expert survey" (psychologists in education as behavioral psy-
chotherapists), these suggestions were first categorized according to the range of interests and
activities in order to achieve an optimal overview and manageability. An assessment of the
rewarding potential of interests and activities was also carried out by the same research
group. The results yielded a substantively and statistically meaningful category formation. With
regard to the ability to reward, different degrees of effectiveness of potential alternatives
were determined.
In a "patient survey" a comparison was made of the range of interests and activities between
addicts, the mentally ill and a control group.
The investigation validated the assumption of a smaller and less differentiated spectrum of
psychological interests and activities for the group of addicts as a whole and for various forms
of addiction (alcohol, drug addiction, gambling disorder) as well as for other disorders. They
thus supported the thesis of dysfunction (harmful) dysfunction of the neurobiological reward
system. The patient survey also gave indications that reward-generating alternatives are
differently suitable for a reconstruction of the reward system and deactivation of the persistent
memory structure.

5
The aim is to restore the health-promoting function of the reward system in the different disor-
der patterns by a common therapeutic method and to further develop the effectiveness of the
measures. This therapy-supporting approach is independent of the causes that originally set
the disease in motion. The etiological conditions require additional treatment, as is also the case
for other disorder-specific disease manifestations, so that the reconstruction of the reward sys-
tem is not a complete but only a partial aspect of the treatment program.
This investigation has meanwhile resulted in a manual (Bachmann, M. & Bachmann, A. A.
2023) that serves to make an individually adapted selection of highly "reward- generating"
alternatives and to realize them timely as possibly. Overall, the selection of alternatives is
based on addiction and health research and can be applied to various disorders.
The scientifically based classification of the pool of interests and activities resulted in ten
different manageable categories: (01 Social contacts, competence; 02 Movement, fitness; 03
Mental activity; 04 Showing feelings; 05 Recreation; 06 Experience adventure; 07 Culture en-
joyment; 08 Hobby, creative; 09 Media use; 10 Basic activities). On this basis, 10 different self-
assessment scales were developed (Bachmann, M. & Bachmann, A. A. 2023), which allow a
more systematic and empirically validated therapeutic approach and can also be used preven-
tively. Group comparisons between addicts, mentally ill and control persons were also used to
find out what the "healthy" controls might do differently, from which the patient groups can
benefit.
The reward system sends impulses to perform a behavior, even if this is no longer ex-
pressly desired or a person has even "firmly resolved", e.g., to consume less sweets/alcohol or
to reduce or completely refrain from gambling. This seems to be particularly true for behaviors
that quickly and "kick-start" a certain relief or feeling of happiness, whereupon not infre-
quently a certain remorse or even feelings of guilt soon arise when self-imposed limits are ex-
ceeded.
Dependencies, compulsions and depression then often lead to a decrease in other compensa-
tory interests and activities and undertakings that used to serve psychological and physical
well-being no longer take place sufficiently. In this way, social relationships and valuable ac-
tivities that helped to balance out stressful feelings (emotion regulation) and reduce stress are
lost.
It is obvious to reverse this process, to restore the functionality of the reward system,
across different clinical pictures, by building up alternative strategies for emotion regulation
and a diverse interest and activity spectrum, thus replacing the risky strategies. To this end,
individually adapted change requests must be identified and in particular, assistance must
be provided in actually realization and permanently anchoring them in the behavioral
repertoire. With appropriate habit formation, the reward system changes and prefers the de-
sired positive alternatives instead of risky behavior. In order to relieve itself and feel better, it
now sends out impulses and expectations, e.g., to tell other people about its own feelings, to
follow a practiced sporting activity and much more. The alternative structure serves to redis-
cover desirable experiences and to regain interest and joy in various aspects of life.
As a rule, supplementary psychotherapeutic measures are necessary to deal with environ-
mental or personal conditions that cause (etiological) disorders in order to promote and
maintain the recovery process in the long term.
1.2 The starting point is a failed crisis or stress management
A larger proportion of mental disorders appear to be due to a failure to cope with a crisis (Grawe
2004). Increased psychological tension can result in narrowed perception, "tunnel vision" and

6
failure to consider alternative coping strategies. In retrospect, people realize that there may have
been better strategies for resolving the crisis.
Persistent stressors are potential causes of a variety of somatic and mental disorders (Klauer
2012). According to Drexler (2013), stress occurs when individuals or groups experience
(resource) losses,
• conditions and foundations important for life (e.g., threatened job loss, break-up of social
relationships) are unstable or endangered,
• there is a lack of options for action to protect or expand important economic and social
conditions (e.g., rent increases reach the breaking point, a larger apartment becomes nec-
essary due to an increase in the number of children),
• the feeling is present that certain (resource) losses cannot be compensated by own efforts,
even after considerable efforts.
The resource conservation theory assumes that people have a basic motivation to acquire,
maintain and protect equipment/opportunities that are valuable to them. These can be
(Drexler 2013):
• material resources (e.g., a home, clothing, financial resources)
• psychological well-being (e.g., self-esteem, optimism)
• social conditions (e.g., relationships, social support, recognition)
• education/health (e.g., time, knowledge, physical and mental fitness)
In general, the stress level increases when the impression of not being able to sufficiently de-
termine or control one's own concerns becomes solidified.
In connection with a program for "stress management training", Kaluza (2015) emphasizes that
it is important to note that stress is not only influenced by situational demands, but also by a
subjective evaluation of the situation and the type of chosen coping strategies.
1.3 Stress vulnerability and coping in addictive and other mental disorders
Exemplary (a comprehensive account, would go beyond the scope of the investigation) empir-
ical findings on stress vulnerability and coping in addictive disorders: Severe stress and the
need to improve one's emotional state are both implicated in the development of addiction,
substance craving and relapse, so that in treatment settings testing procedures for diagnosis
and stress management procedures are used, e.g., relaxation procedures. Comparisons with the
interest and activity spectrum are therefore obvious.
It was proven that an increased stress experience temporally related to drug use enhances sen-
sitization processes in (mesolimbic) dopaminergic structures and that these processes in turn
lead to increased stress vulnerability (Böning & Albrecht-Sonnenschein 2018). Comparable
research findings on gambling disorder also demonstrate a link between the extent of gambling
behavior and stress experience (Sharpe 2002; Grüsser & Albrecht 2007; Milosevic & Ledg-
erwood 2010; Lorains et al. 2011; Müller et al. 2013; Hayer et al. 2014; Meyer 2017; Albrecht-
Sonnenschein et al. 2018; Petry, N. M. 2018; Bachmann, M. & Bachmann, A. A. 2023).
In the area of addiction disorders, the aspect of emotional regulation and the associated restruc-
turing of the neurobiological reward system is now an established subject of research. The re-
sults of the imaging procedures suggest that a whole range of other mental disorders have a
similar course in that very different risk behaviors become chronic, acquire a dynamic of their
own and have a self-damaging effect. In particular, the starting point of the disease develop-
ment, the initial improvement in emotional well-being, has not been given sufficient attention
so far, but has been pushed into the background by the ultimately damaging effect.

7
1.3.1 Other disorders with dysfunctionality of the reward system
So far, it has not been possible to clearly define which other mental disorders are influenced in
their development and maintenance by a neurobiological dysfunction of the reward system
and have their starting point in a maladaptive emotional regulation.
The respective symptom or risk behavior can be manifold. Therefore, the theoretical ac-
count on this remains fragmentary and incomplete.
The self-confrontation with one's own interest and activity spectrum, to strive for a constructive
regulation of emotions as well as a balanced way of life, however, is unlikely to have negative
effects and should possibly be integrated into everyday life as a preventive measure.
The empirical findings to date include nonsystematic observations, psychological self-assess-
ment and neurobiological imaging procedures. The neurobiological parallels of the dysfunc-
tionality of the reward system in the disease process open up the possibility to further de-
velop the therapy measures for the necessary rebuilding of reward-effective alternatives,
to overcome the dominance of risk behavior in the reward system and to make them more
efficient overall. It is not intended to classify other disorders as addictions, since there are
serious medical and socio-psychological differences apart from the undoubtedly existing
commonalities, which are by no means to be neglected. In order to take this circumstance into
account, reference should be made to the relevant literature, whereby we do not presume to
make a selection.
Overview
According to Münte (2008), the neurobiological reward system is a “department” that processes
feedback about what behavior is worthwhile in the future. In numerous neurological and psy-
chiatric disorders such as e.g., addiction, depression and obsessive-compulsive disorder, this
complex brain area is disturbed. Researching and understanding the fundamentals of the reward
system are therefore one of the major challenges of cognitive research. By using imaging tech-
niques such as functional magnetic resonance imaging (fMRI), it is possible to watch the
dopaminergic reward system "at work": Brain activity in the regions of the reward system
increases with positive feedback, such as praise or a win, but decreases with negative feedback.
When dopamine, the most important neurotransmitter in the reward system, is released, we
experience a good feeling. Once we have learned how to trigger it, we henceforth behave in
such a way that a positive change in feeling occurs again (ibid.).
In the context of dysfunction in the reward system in psychiatric disorders (alcohol depend-
ence, schizophrenia, major depressive disorder, bipolar disorder, attention deficit/hyperactivity
disorder), Hägele et al. (2015) formulate: “… that neurobiological research in psychiatric dis-
orders can be targeted at core mechanisms that are in all likelihood to be implicated in a range
of clinical entities. This approach can be promising for the understanding of psychiatric symp-
toms and for the development of new treatment strategies.”
During reward anticipation, they observed significant group differences in ventral striatal (VS)
activation: patients with schizophrenia, alcohol dependence and major depression showed sig-
nificantly less ventral striatal activation compared to healthy controls. Depressive symptoms
correlated with dysfunction in reward anticipation regardless of diagnostic entity. There was no
significant correlation between anxiety symptoms and VS functional activation.
Overview
The studies (cf. Hägele et al. 2015) in which monetary incentives are applied in group com-
parisons between mentally ill and healthy control persons, are burdened by the fact that there is
a "precarious" relationship between money and health. This is already indicated by a simple
googling of these terms or this is also expressed in group discussions. The first Google result

8
with "money and health": Studies to poverty and health: Money does not make happy...
(https://www.tagesspiegel.de/wissen/)
It is therefore hardly possible to verify the thesis of "anhedonia" (loss of the ability to feel
pleasure) in connection with a dysfunction of the reward system with this study design. Instead,
it may be suitable for assessing vulnerability to problem gambling. The optimization of the
reward system does not seem to be determined by how much money someone owns (e.g., very
wealthy people are "addicted" to fast food).
In Choi et al. (2012) obsessive-compulsive disorder (OCD) and pathological gambling (PG) are
conceptualized as behavioral addictions characterized by reward effects of repetitive gambling
behavior (distracting oneself/easing worries, for example) and compulsive behavior (also re-
lieving/calming oneself by washing hands, for example). It had been observed by means of
imaging techniques (fMRI) that the neurobiological correlates of pathological gamblers become
increasingly similar to those of OCD as PG symptoms worsen. The similarities between patients
with PG and OCD were only related to neuronal responses associated with reward expectancy,
while on the other hand functional differences had been found.
According to Fontenelle et al. (2011) obsessive-compulsive, impulse-control and substance-
related addictive disorders overlap at multiple levels, including phenomenology, comorbidity,
neurocircuitry, cognition, chemistry and family history. Figee et al. (2011) reportedly con-
ducted the first functional imaging (magnetic resonance imaging) study to explicitly examine
reward circuitry in obsessive-compulsive disorder. Their findings in obsessive-compulsive dis-
orders, which are classified as anxiety disorders, show that neurobiological features similar to
addictive behavior are present. They conclude that patients developed addiction to the com-
pulsive behaviors due to the rewarding effect (e.g., reducing anxiety about not contracting
an infection by washing their hands) of their symptom behaviors. Brain imaging studies in
obsessive-compulsive disorder would have consistently shown abnormal activation within the
ventral striatal-orbitofrontal circuitry.
The affected disorder patterns are likely to include forms of eating disorders in which the
eating behavior has been given too strong a position in emotion regulation, relief from
psychological stress or crisis.
The neurobiological correlates of a restructuring of the reward system, toward a one-sided fix-
ation of emotion regulation on maladaptive food intake, then lead to considerable resistance to
relinquishing this behavior and reorienting oneself. Thus, authors hypothesize that anorexia
nervosa patients initially attribute a positive value to their symptoms (self-starvation/keep diet).
The associated reinforcing effect leads in the course of the disease development to neuro-
biological changes in the reward system, which have a central role in the maintenance of the
disorder (Bachmann, M. & Röhr 1983a, b; Bachmann, M. 1992; Nordbø et al. 2006; Keating et
al. 2012; Steinglass et al. 2012; Monteleone et al. 2018).
In a study by Bachmann, M. (1992) using self-report measures (n = 197), items including the
following on the "instrumentality of starvation" differed significantly (0.05 level) from controls
and achieved high discriminatory power (Cronbach's alpha in parentheses): “Starving made me
feel more capable at first” (.88). “Starving made me amped up” (.88). “When I was hungry, I
felt intoxicated” (.88). “I took refuge from conflict by fasting and dieting” (.88). “By starving
myself, I wanted to escape reality” (.88).
Nordbø et al. (2006) collected qualitative information on the motivation of "starvation behav-
ior" in interviews, which they attributed be summarized in eight constructs: “Security” (feeling
of stability and security), “Avoidance” (avoiding negative emotions), “Mental strength” (inner
sense of mastery), “Self-confidence” (feeling acknowledged and worthy of compliments);
“Identity” (achieving new identity), “Care” (eliciting care from others), “Communication”
(communicating difficulties) and “Death” (wishing to starve oneself to death).

9
The "food addiction" thesis has been studied in eating disorder and obesity research for some
time. The term "food addiction" is based on the hypothesis that the excessive intake of mainly
high-calorie foods (e.g., sugar) may be based on pathophysiological mechanisms similar to
those of addiction (Starke & Müller 2021). However, it remains questionable whether the
transfer from the animal model to humans is really plausible, or whether it is really a substance-
related addiction disease (food-substance addiction) or rather a behavioral addiction (binge eat-
ing) or a combination of both. In either case, a relatively large number of people appear to
experience symptoms of "food addiction", the prevalence of which appears to be close to 8%.
According to the authors Berridge et al. (2010; cf. Schäfer et al. 2010), an increase in obesity
and eating disorders could be related to dysfunctions in complex interactive reward circuits
(hedonic circuits, opioid networks, dopamine systems, glutamate signaling). In this regard, Um-
berg et al. (2012) refer to "food-drug" dysfunction in bulimic patients. According to their find-
ings, a number of peripheral and central biological abnormalities are indicative of altered re-
ward sensitivity in these persons, particularly through effects on the dopaminergic system. Neu-
robiological findings support the assumption that there are similarities with an addictive disor-
der, which should have implications for therapy and therapeutic measures.
In depressive disorders a dysfunctionality of the reward system seems to appear, which is
characterized by a severe reduction in drive and activity and a loss of interest in reward
stimuli (anhedonia). Kuhl (2001) has stated that there is a dysfunctionality in the reward system
that can be associated with major depression and that this symptomatology is primarily charac-
terized not by the experience of negative emotions, but by a lack of positive emotions. Several
studies and a meta-analysis (fMRI-"neural responses to reward-expectations") support these
observations (Hägele et al. 2015; Wilson et al. 2018).
According to Kuhl (2001), unprocessed anxiety and external circumstances can provide the
impetus to trigger a conditional, almost autonomic response from the reward system to remain
passive in executive brain function. This can lead to an inability to move and perform the
activities needed to maintain a structured daily routine. Corresponding to Kuhl, this process is
accompanied by excessive activity in the brain regions that are responsible for cognition (think-
ing, volitional function, evaluations and decisions).
This combination leads to a paradoxical dilemma: an intense preoccupation with one's goals
and the inability to put them into action. It should be noted that in this article a terminological
distinction is made between "action activity" and "cognitive activity".
It is assumed (Bachmann, M. 2018, 2019) that the avoidance strategies of inactivity in action
and exercise, may initially produce a strong and immediate emotional relief (reward), but
this is short-lived. An example is to avoid a conflict at work by staying away, staying home,
"pulling the covers over one's head" and thus feeling relieved for the time being. This increases
the likelihood of using the "avoidance of action" strategy again. It is not unlikely that ago-
nizing thoughts will soon arise about the consequences of staying away or avoiding conflict
resolution and how to get out of the situation, so that the inactivity is accompanied by brood-
ing and stressful cognitions/thoughts. The negative social, psychological and physical health
consequences of increasingly depressive inactive behavior, which also extend to other areas of
life, worsen the stress-related initial situation. Through the frequent and conditioned use of
avoidant coping strategies and the associated decline of formerly more favorable coping strat-
egies, the risk behavior gradually dominates the reward system and its structures change. This
persistent change is stored in an unconscious (implicit) "depression memory". In the presence
of certain stimulus constellations, including stimulus generalization, the learned "relief strat-
egies", the depressive behavior pattern (behavioral inactivity), are triggered nearly auto-
matically. Previously neutral external stimuli (e.g., to "get dressed to go to the office", people
present, certain paths, buildings) or internal stimuli (such as negative cognitions or emotional

10
states) of a conflict or mobbing situation at work linked to the action-passive coping strategies
occur as triggers (stimulus generalization) of the depressive behavior. A clearly formulated de-
sire (e.g., to be passive, to stay in bed) need not be present. The result of depression memory is
that the behavioral symptoms of depression now dominate the reward system, which sup-
presses the executive brain functions of taking a desired active action, e.g., having clarifying
conversations/to relax by sporting doing.
Furthermore, reference should be made to a paper by Hennings (2021) in which a reinforcer
model is applied to borderline personality disorder in the context of non-suicidal self-injury.
This is a behavioral pattern that is clustered together with chronic suicidality in borderline per-
sonality disorder. Reinforcement mechanisms are thought to contribute meaningly to the
maintenance of the disorder pattern. Here too, positive (add pleasant) and negative reinforce-
ment (reduce unpleasant) are initially effective in order to bring about a desired affect state,
e.g., a relaxation of inner tensions. As a result, the likelihood of carrying out the risky behavior
increases.
1.4 Emergence of dysfunctionality: conditioning process and automation of risk be-
havior
An unsuccessful crisis or stress management can result from the fact that persistently stressful
feelings (such as fears, loneliness) and experiences of failure are attempted to be alleviated by
less suitable strategies in a "self-healing attempt". The use of risky behavior, such as forms of
eating behavior, increased passivity/avoidance, addictive behavior, then only has a displacing,
distracting or numbing effect, without achieving a solution in the long term (see Fig. 2). Failure
to come to terms with the reasons for the "persistent emotional stress" and the lack of alternative
coping strategies often exacerbate the initial situation in the further course, creating a vicious
circle.
Fig. 2. Circulus vitiosus (Bachmann, M. 2019)
In addition, these symptoms in turn also act as specific, learned (conditioned) stimuli in each
case, which promote renewed use of the risk behavior (Erbas & Buchner 2012). A person feels
anxious and burdened and, in this context, has repeatedly experienced that the risk behavior
initially has a positive effect on mood and therefore repeatedly resorts to this means to relieve
himself.
According to Costandi (2015) the brain reward system motivates us to seek out and repeat
pleasurable things. Involved in this process are neurotransmitters such as dopamine, adrenaline
persistent negative
emotions
attempt to cope by
engaging in potentially
addictive or risky
behavior
quick reward/strong but
relief only in the short
term

11
and serotonin. Dopamine, called the “happiness molecule,” plays a central role in perceiving
self-harmful things as rewarding. It has an important function in determining where attention is
directed, what remains in the memory and what one moves toward.
Fig. 3 below illustrates the connections of failed crisis or stress coping with the neurobiological
reward system and the negative consequences of maladaptive (risky) strategies.
The conditioning process leads to an increase in the occurrence of the risky coping strategy
and to neurobiological changes in the brain areas (O) of the legislative, executive and especially
the reward system (see upper arrows). In the long term (see lower arrows), the stress level (S)
of the baseline situation increases (Kanfer et al. 2000).
Situation (S)
Organism (O)
Reaction (R)
Immediate posi-
tive conse-
quences (C1)
Long-term ef-
fect: increasing
negative conse-
quences (C2)
Stress situation:
persistent nega-
tive emotional
state due to in-
ter- and intra-
psychological
conflicts, e.g.:
• Lack of coping
with everyday
life.
Boredom/lack of
fulfilment.
Social, profes-
sional, family and
financial prob-
lems.
• Traumatic expe-
rience in the past.
Brain functions
involved:
(1) Legislative:
• Cognition/deci-
sion-making pro-
cesses.
(2) Executive:
• Execu-
tion/move-
ment/action/be-
havior realiza-
tion.
(3) Reward sys-
tem:
• Creation of
emotional bal-
ance.
• Impulses for
preferred reward
behavior.
Failed emotion
regulation:
(1) Legislative:
• The use of ad-
dictive/risky be-
havior relieves a
persistent emo-
tional distress
(operant condi-
tioning).
(2) Executive:
• Increasing
problem behav-
ior and inhibit-
ing alternative
strategies.
(3) The reward
system:
• Sends increased
impulses to use
the risky (mala-
daptive) coping
strategy.
Quick strong but
only short-term
effective emo-
tional relief by
the problematic
reinforcement
strategy. The like-
lihood of carrying
out the risky be-
havior increases.
*
Increasing so-
cial, psychologi-
cal and health
problems:
(1) Self-doubt,
guilt/depression
due to neglected
duties/social
problems/loss of
time. Problem be-
havior absorbs
other interests
and activities.
(2) The dysfunc-
tional strategies
jeopardize other
life interests and
strain social rela-
tionships (spouse,
children, friends).
(3) Other "con-
structive" coping
strategies de-
crease.
(K) Frequent sequence
of (R) and (C1)
restructures the
reward system (3)
The negative long-term effects C2 increase the initial stress level **
Fig. 3. Operant conditioning process of a positive and negative reinforcement (Bachmann, M. 2019)

12
In Fig. 3, the operant conditioning process is integrated into the S-O-R-K-C model “be-
havior analysis” (Kanfer & Saslow 1969; Kanfer et al. 2000), although here a distinction is
made between immediate (C1) and long-term (C2) consequences (Bachmann, M. 2018,
2019). It thus contains the following factors:
S = Situation: Person- or environment-related factors that trigger the behavior.
O = Organism: It includes the own biological history and learning repertoire.
R = Reaction to the situation after it has been processed by the organism (mental, emotional,
physiological and motor).
C = Consequence (positive or negative) determines whether the likelihood of occurrence
of a behavior increases or decreases.
K = Regularity (contingent relationship) with which C1 follows R.
• In a stress situation (S) a person tries to alleviate the initial situation "persistent emotional
stress" by an addictive/risk behavior (R).
• If the risk behavior is continued, this leads to a considerable but short-term relief (C1) from
the negative emotions.
• Both cognitive, "facilitating through the risk behavior" and physiological learning expe-
riences (release of feel-good hormones in the reward system) are stored in the organism (O).
• With increased use of the risky coping strategy (frequent sequence of R + C1 = K, large
downward arrow*),
o it takes a stronger position in the reward system and causes increasing dysfunctionality there.
o Moreover, memories of the positive effect of the risk behavior are stored in the non-conscious
(implicit) autobiographical memory.
• The first long-term negative consequences (C2) occur (e.g., social, psychological and/or
health problems). Provided that the frequency of risk behavior continues to increase, the neg-
ative initial emotional situation (S) may even worsen massively (Fig. 3: last column; lower
arrows **).
Learning theory: The influence of learning processes (classical and operant conditioning, model
learning) on changes in the reward system – including the development and maintenance of
addictions and relapse – is empirically well established (see Albrecht 2006). Sometimes learn-
ing from a model (observation), e.g., from peers, friends, or family members, can be a possibil-
ity to perceive the positive effect of risk behavior and to practice it oneself under certain con-
ditions (Bandura 1991).
This is “learning by positive consequences” or “reinforcement learning” (Elsesser & Sar-
tory 2001). This learning process is capable of restructuring the reward system in a way that
leads to massive psychological, social and somatic consequences.
The reward system steers the emotional state of a person, is therefore the seat of feelings of
pleasure or displeasure and serves to regulate the feel-good chemistry (cf. Lindenmeyer
2005). Initially, the brain does not distinguish whether the behavior is "meaningful or sustain-
ably damaging" and stores the restoration of biochemical balance by the behavior in episodic
(autobiographical) memory (Grüsser & Albrecht 2007; Böning 2009; Böning & Albrecht-Son-
nenschein 2018).
The consequence of this is that in a renewed similar situation (stimulus constellation) the re-
warding effect of the behavior is remembered and the behavior is further solidified by re-
peated practice. Under these circumstances, alternatives to generate "feel-good hormones" by
other means decrease, side effects increase and withdrawal-like phenomena occur. The negative
after-effects are faded out and in order to feel better quickly, one reacts again with the risk
behavior.

13
Evidence for an operant conditioning process (positive and negative reinforcement): In a study
incorporating a gambling motives questionnaire (GMQ) by Stewart & Zack (2008), Mackinnon
et al. (2016) find that three distinct motives predict gambling problems in young adults: in-
creasing positive emotions (enhancement), decreasing negative emotions (coping) and im-
proving social affiliation (inclusion).
If it is plausible to assume that stronger social affiliation increases positive emotions, the GMQ
results represent some empirical evidence for the operant conditioning approach. This does
not mean that operant conditioning is always an intentional process and that motives must be
conscious.
In a study by Marchica et al. (2020), the authors conclude that certain deficits in impulse control
and a lack of emotional awareness and clarity predict gambling-related disorder. Moreover,
they also validate the hypothesis that motivation to increase positive emotions and escape
negative ones is a significant cause of illness.
A conscious examination of how one's own reward system works (which strategies are used
in emotional regulation/coping with stress or increasing well-being) can be a first step in pre-
venting an undesirable development from deepening.
Obtaining health-related information and appropriate counseling can then assist in choosing
alternative behaviors. The addictive or risky behavior automates/perpetuates itself: Over
time, the person affected experiences the addictive/risky behavior as less and less pleasant, the
effect weakens, but there is still a "strong inner urge" to carry it out (see Fig. 4).
Situation (S)
Organism (O)
Reaction (R)
The initial state of psy-
chological stress is in-
creased by the negative
consequences of the
maladaptive behavior:
• Generalization of stim-
uli: Previously neutral
external and internal
stimuli trigger the addic-
tive/risky behavior, e.g.,
the emotional conse-
quences of conflicts, as-
sociated situational fea-
tures, places, "mundane"
daily routines, stressful
thoughts, feelings of hurt,
a deficit of positive expe-
riences and "feel-good"
chemistry, limited ability
to cope with everyday
life.
The maladaptive coping
strategy “risk behavior“
has taken a dominant
position in the reward
system:
• Overactive "cognitive
effort" e.g., thinking in-
tensively about problem
solving. Worrying about
standing out and brooding
about negative conse-
quences.
• Lack of control in the
"executive function":
inhibition of action,
building up alternative
reinforcers and limiting
or abandoning risk be-
havior.
• The consequence of the
restructuring of the re-
ward system is the devel-
opment of a non-con-
scious (implicit) "memory
response" to the addictive
or risky behavior, which
triggers the maladaptive
Addictive/Risky behav-
ior becomes self-perpet-
uating:
• Despite the goal of lim-
iting or stopping the risk
behavior, good intentions
and attempts often fail.
• Feelings of shame may
lead to seeking secrecy
and not admitting to the
behavior.
• The presence of
motivation for compre-
hensive treatment, insight
into the illness and the
willingness to accept
help are not always to be
presumed, but are part of
the therapeutic work.

14
behavior nearly auto-
matically/reflexively.
Fig. 4. The addictive or other risk behavior becomes self-perpetuating (Bachmann, M. 2019).
This situation is characterized by a reduction in control, withdrawal (like) symptoms, mood
swings, irritability, as well as a neglect of important areas of life and a strong absorption of
interests and activities (Bachmann, M. 2017, 2019; Böning & Albrecht-Sonnenschein 2018).
Feelings of shame and guilt often prevent affected individuals from openly sharing their prob-
lem and seeking help in a timely manner. For the most part, they do not sufficiently see through
the dynamics of the disease and both insight into the disease and motivation to seek treatment
are factors that cannot be assumed.
In order to better understand this behavior, it is useful to include neurobiological processes of
the reward system in the explanation of the development and maintenance of the disorder as
well as in therapeutic considerations. In deeper brain regions that can hardly be directly influ-
enced and without being consciously perceived, these learning processes are stored in implicit
memory.
The more frequently certain, potentially self-harming strategies are used to cope with negative
feelings or to lighten the mood and are perceived as considerably facilitating, the greater the
likelihood that one-sided neuronal wiring patterns will develop, which will cause a certain au-
tomation, nearly reflexive exercise of the addictive/risky behavior (see Fig. 5).
Fig. 5. The addictive/risky behavior as a conditioned nearly automatic response (Bachmann, M. 2019).
The reward system provides the impetus to engage in the risky behavior without the presence
of a clearly formulated intention (Hüther 2012; Böning & Albrecht-Sonnenschein 2018).
Good intentions to limit or refrain a behavior that is itself already perceived as problematic
often fail and feelings of guilt add to the burden.
Neuro-biological dysfunctions of the reward system, regardless of their original etiology, con-
tribute meaningful to the perpetuation and chronicity of various clinical pictures.
This leads to the therapeutic conclusion to consider common treatment measures for the recon-
struction of the reward system more strongly and to further develop and unify the methods. The
treatment of the causes and disease-specific factors, in accordance with the relevant specialist
literature, are to be included in the course of therapy without restriction.
Negative consequences of
addictive/risky behavior
additionally burden the initial
situation
The addictive/risky behavior is a
nearly automated
"reflexive reaction"
Persistent or even worsened
negative emotional state

15
1.5 Psychotherapeutic reconstruction of the reward system, reward-effective alterna-
tives replace risky behavior
The structural changes of the reward system with the resulting consequences of a consider-
able narrowing of the interest and activity spectrum have so far received too little entry into
the therapeutic approach.
From the neurobiological perspective of reconstructing the reward system, therapeutic efforts
aim at developing alternative interests and activities in order to have a lasting positive influence
on psychological well-being and, building on this, to establish stable habits that are as "incom-
patible" as possible with the risk behavior. The process of restoring the health-beneficial func-
tioning of the reward system for balance and well-being is successful when the reward system
predominantly provides impulses to give preference to alternative interests and activities
instead of risk behavior. Thus, in stressful situations, the strong desire to confide in others, to
share worries and needs and for example to go jogging in addition, can arise.
Fig. 6 symbolically illustrates the conditioning processes that result in situations (S) being as-
sociated with the risk behavior that provides relief, compensation or distraction (white thick
arrow).
S i t u a t i o n (S)
R e a c t i o n (R)
For example:
1. Anger
2. Conflicts
3. Unusual suc-
cess
4. Boredom
5. Stress
6. Malaise
7. Unemployment
8. Overload
Risk behavior
Development of re-
ward-effective
alternatives
For example:
● Good conversations
● Sports/exercise
● Showing emotions
● Becoming active
● Accepting help
● Supportive
relationships
● Solving conflicts
● Rewarding yourself
Fig. 6. Conditioning (white big arrow) and therapy process (gray big arrow): Alternatives replace risky
behavior (Bachmann, M. 2017).
In case of frequent repetition, a restructuring of the reward system to react nearly "reflexively"
with the risk behavior to certain situations (R) occurs.
In addition to the motivation to change behavior, to make decisions about which alternatives to
consider, the restore of the functionality of the reward system is successful when alterna-
tives take the place of the risk behavior (gray thick arrow) and become firmly anchored as

16
stable habits in the behavioral repertoire. Sufficient support in realizing therapy goals is a
crucial factor if the reward system is dysfunctional. To trust solely in insight, good intentions
and beliefs (cognitive aspects) is not very promising, as reason and logic have little direct in-
fluence in this area of the brain (Bachmann, M. & El-Akhras 2014a, b; Bachmann, M. & Bach-
mann, A. A. 2023).
The immediate question is which alternatives are particularly suitable for overcoming the
dominance of risk behavior in the reward system? In this context, methods have to be de-
veloped to record existing and missing resources and to pursue therapeutic goals systemat-
ically and individually.
The task is to record the remaining resources of reward-generating alternatives and to expand
the repertoire of positively effective interests and activities according to individual desires (tar-
get condition) in order to practice them in such a way that they develop into strong new habits
and become firmly anchored in the behavioral repertoire. Alternatives must be included that
have an effective, short-term and lasting positive effect on psychological well-being and over-
ride the dominance of problematic behavior. This means overcoming the one-sided neural cir-
cuitry and developing a diverse neural network, dealing constructively with negative feelings
and achieving the highest possible level of psychological well-being.
With appropriate training, the reward system changes by sending positive impulses and expec-
tations to behave according to established alternatives and, for example, to engage in sports,
to seek social contacts, to feel satisfaction and pleasure in interests and activities, to laugh, to
confide in other people about one's feelings and much more.
Grawe (2004) formulates on the importance of neurobiological correlates in psychotherapy in
general: "If all mental processes are based on neuronal processes, then altered mental processes
are based on altered neuronal processes. We can consider it as proven that psychic processes
can be changed effectively and permanently by psychotherapy. It follows that psychotherapy
can permanently change neuronal processes and structures. Psychotherapy works, when it
works, by changing the brain. If it does not change the brain, it is not effective."
Results of brain research on the malleability (plasticity) of brain structures supporting the
assumption that the inclusion of maintaining physiological factors (in this case structural
changes of the reward system) in the treatment process have decisive effects on the success of
therapy. Fig. 7 summarizes in key words the previous considerations concerning the course of
the disease and the therapeutical conclusions. The points 1-3 comprise the explanations of a
stressful initial situation, which is characterized by a persistent psychological strain. The cop-
ing attempt is characterized by a problematic exercise of the respective risk behavior to
experience relaxation and relief. The short-term nature of the emotional relief and the re-
peated persistent use of this strategy set an (operant) conditioning process in motion that leads
to a structural change of the reward system, results in a control reduction and nearly auton-
omy reflexive triggering of the risk behavior.
The therapy process 4-6 (arrow from right to left) takes place in the opposite direction: Sup-
porting motivation for change and insight into the disease process, building constructive
alternatives for emotion regulation, establishing a spectrum of diverse interests/activities or
with another term “reinforcement reservoir”, striving for a balanced and satisfied way of
life. By building new stable reward-effective habits, reconstruction of the reward system takes
place. This is followed by the analysis and processing of the "initial stress situation" as well as
considerations for relapse prevention.

17
Course of disease:
(1)
Stressful situation:
• Persistent negative emotional
state.
• Causes in personal and/or en-
vironmental factors.
(2)
Coping Attempt:
• The use of risk behavior pro-
duces considerable but short-
term relief.
• The continuing emotion regu-
lation and generation of well-
being by the risk behavior set
an operant conditioning process
in motion that leads to a struc-
tural change in the reward sys-
tem.
• Development of a noncon-
scious (implicit) persistent
"memory representation" of the
risk behavior.
• The negative psychosocial
consequences of risky behavior
can add up to the stressful ini-
tial situation (1).
(3)
Control reduction:
• A known disturbance pat-
tern develops. The risk be-
havior becomes self-perpetu-
ating, gets an "own dynamic”
(symbolized by the inclined
arrow) and is triggered in a
nearly automated/reflex man-
ner.
• In the reward system, risk be-
havior takes a dominant posi-
tion in providing emotional
balance and well-being.
• Alternative interests and ac-
tivities decrease sharply.
• Generalized stimuli (previ-
ously neutral stimuli, that were
associated with the risk behav-
ior) also trigger a risk behavior
response.
Therapeutic process: going back from the end of the course of the disease to the starting point
(6)
An
alysis and processing of the
stress-inducing initial situa-
tion (personal and/or envi-
ronmental) causes:
• Analysis of stress-inducing
conditions and existing coping
strategies/reward potentials.
• Unprocessed stresses from the
past?
• Relapse prevention  what
triggers a relapse?
(5)
Reconstruct a health reward
system: realize social
goals/establish an exercise
program and other multiple
alternatives (new and/or re-
learn):
• (a) Constructive/conducive
strategies for short-term relief
and relaxation.
• (b) Long-term effective alter-
natives to maintain and en-
hance well-being and a bal-
anced lifestyle.
• Anchoring the alternatives
(a/b) as strong habits in the be-
havioral repertoire.
• (c) The impulses of the re-
ward system prefer the newly
established alternatives.
(4)
Support of motivation and in-
sight into the disease for a
comprehensive treatment
program:
• Gain insight into the disease
process.
• Interrupting the "self-dynam-
ics of risk behavior": e.g., hav-
ing "emotionally relieving"
conversations, daily structure,
realization action/movement
goals in small steps.
• Developing constructive emo-
tion regulation.
• Buildup of a diverse alterna-
tive reinforcement reservoir of
interests and activities (IAS)
that is as “incompatible” with
risky behavior as possible.
• Disputation of maladaptive
cognitions.
Fig. 7. The relationships between disease course and treatment process (Bachmann, M. 2019).

18
This order (4-6) is plausible if the motivation for therapy and the awareness of the problem
overall are still ambivalent (Bachmann, M. 2018) and there is also a risk of relapse because
“stimulating” impulses still come from the reward system to carry out the risky behavior. This
treatment regimen serves to record the individual status of the patient and to adapt the thera-
peutic measures accordingly.
A therapy orientation focused only on the stress-triggering initial situation is unlikely to do
justice to this disease dynamic. In the further therapy process, there is a close interrelation
between the single therapy factors and the individual goals must be reviewed and deepened
repeatedly, e.g., the easing of the suffering pressure as a result of the first therapy steps can
again call into question the therapy motivation and insight into the disease and increase the
risk of relapse (ibid.).
2 The investigation of the interest and activity spectrum
2.1 Questions
The construct of the interest and activity spectrum (IAS) was created by Bachmann, M. (2018,
2019) and applied to various clinical pictures with dysfunction of the reward system. In this
investigation, a first empirical verification of this took place (Bachmann, A. A. 2021). The
following questions were examined using a questionnaire containing 176 items of the interest
and activity spectrum (IAS):
1st part of the questions (study 1)
• Are the selected interests and activities suitable as potential alternatives to addictive or
risky behavior and effective for the reconstruction of the reward system?
• Can they be classified into different categories (scales)?
• Do they differ in terms of their reward capacity/effect to "positively change the psycho-
logical state" and according to,
o whether they are suitable as a "highlight"?
2nd part of the questions (study 2)
Based on this, the aim was to demonstrate the assumed narrowing of the interest and activity
spectrum in addicts and people with other illness classifications with dysfunction of the reward
system in a group comparison to control persons.
• Furthermore, to record the extent to which there are wishes to build up the interest and
activity spectrum and how high the confidence is to realize these goals.
• To search out correlations between the range of interests and activities with other con-
structs as life satisfaction, procrastination, stress management and comorbidities.
The selection of interests and activities for the IAS questionnaire was made taking into account
results from health and addiction research, whereby particular attention was paid to the follow-
ing factors: mental and physical health, general well-being with the inclusion of social and
economic conditions, coping with everyday life, greatest possible disparity (incompatibility) to
risk behavior, potential for coping with stress, emotional regulation, feasibility.
• Hypothesis 1: The interests and activities can be assigned to predefined categories.
• Hypothesis 2: The interests and activities (as well as the higher-level categories) differ with
regard to their reward effectiveness (“reward value”) on psychological well-being and their
special suitability as "highlights".

19
• Hypothesis 3: The addicts and persons of other disease classifications with a dysfunction of
the reward system show a (a) smaller and (b) less differentiated interest and activity spec-
trum (actual state) than the control group. (c) In addition, differences are to be assumed with
regard to the “desire for change” and the “self-assessment” of the therapy “goals realiza-
tion” (buildup interests and activities).
2.2 Method
Design of investigation
This was a two-stage, cross-sectional design (single-point measurements) in which quantitative
self-report data were collected from self-selected samples. In study 1 experts (psychologists’
education to become psychotherapists VT) first assigned a catalog of interests and activities to
categories and, in a next step, assessed them according to their “rewarding ability” (effective-
ness). As part of the study 2 group comparisons were made between different forms of ad-
diction, mentally ill people and healthy controls, to what extent they pursued interests and
activities and to what extent there was a desire to increase this in the future.
Further data on the feasibility of set goals, life satisfaction, comorbidities, procrastination and
stress management were collected in order to investigate possible correlations with the interest
and activity spectrum.
2.2.1 Expert survey (Study 1)
Procedure and sample recruitment
The surveys took place from January to October 2018. First, several education institutes (be-
havioral therapy) were recruited to participate in the survey. These were informed about the
survey in advance. The participants were recruited after consultation with the heads of the re-
spective education institutes and their agreement. Participation was voluntary, anonymous and
in accordance with current data protection regulations. The participants were also informed in
advance about the purpose of the study. They were offered the opportunity to receive an e-book
version of the dissertation if they were interested. Initially, the conducting of the surveys took
place as follows: The supervisors handed out or laid out the questionnaires after informing the
participants accordingly. After the questionnaires had been returned, they were sent by post.
Due to a rather low response rate at the beginning (approx. 20 questionnaires from three insti-
tutes), the method of data collection was changed: the head of the study handed out the ques-
tionnaires herself during a seminar (after informing the participants about the study) and col-
lected them again afterwards or during the break of the event. When returning the question-
naires, the participants were given the opportunity to give short feedback and to ask questions,
if necessary. As "compensation for the effort", € 10 were enclosed in a document envelope
with the questionnaire, which had to be filled out, which obvious increased the response rate
and all but 3 questionnaires were returned with answers.
Sample
Ninety-one persons, psychological psychotherapists in education specializing in behavior ther-
apy, participated in the expert survey. The experts were composed of two groups: Group A (n
= 46) received the first half and Group B (n = 45) received the other half of the questions (88
interests and activities each). For Group A, 35 were female (76.1%) and 9 were male (19.6%);
2 individuals did not indicate gender (4.3%). Participants' ages ranged from 23 to 57 years, with
a mean of 31.71 and a median of 29.00 (SD = 7.69). There was one missing value. For group
B, 38 were female (84.4%) and 4 were male (8.9%); 3 individuals did not indicate gender
(6.7%). The age of the participants ranged from 25 to 46 years, with a mean of 30.47 and a
median of 29.00 (SD = 4.93).
In group A, 45.7% were in their 1st, 21.7% in their 2nd, 23.9% in their 3rd and 6.5% in their
4th year of education. 2.2% did not give any information. The mean value was 1.91, the median

20
was 2 and the standard deviation was 0.99. In group B, 44.4% were in the 1st year of education,
22.2% in the 2nd year and 28.9% in the 3rd year. There were two missing values (4.4%). The
mean was 1.84, the median was 2.0 and the standard deviation was 0.87. In terms of calling
practice, for Group A, the mean was 3.6 years, the median was 2.0 and the standard deviation
was 5.14. There was one missing value. For Group B, the mean was 3.81 years, the median was
2.0 and the standard deviation was 3.47.
Survey instruments – IAS questionnaire (expert version) and pretest
Initially, several pretests were conducted in which psychologists participated. The questionnaire
(paper-pencil) was tested with regard to the comprehensibility of the instructions and items,
feasibility and suitability of the content of the categories. Based on the results, the item catalog
did not have to be changed or supplemented substantial. Due to the length of the questionnaire
(a total of 176 interests and activities), the processing time proved to be too long, which is why
a division was made for the expert survey into A and B versions (split half). Both versions had
the same structure with 88 items (IAS questionnaires of both expert versions see Bachmann, A.
A. 2021) with a processing time of about 20-30 minutes.
The first task of the questionnaire consists of assigning the 176 interests and activities of the
"IAS questionnaire" according to given 13 categories and one residual category: (1) Social
contacts, (2) Fitness, physical activity, (3) Mental activity, (4) Showing feelings, (5) Recreation,
(6) Experience adventure, (7) Enjoying art, culture in an entertaining way, (8) Being culturally,
artistically active, (9) Being otherwise creative, (10) Various leisure activities, hobbies, (11)
Media consumption, (12) Treating oneself to something special, (13) Basic activities (14) Other.
By means of scaling, the reward value is then to be assessed for each item, which is opera-
tionalized as follows: "To positively change the psychological state, to what extent are the
listed interests/activities suitable for this purpose?" Each item is to be rated using a 7-point
Likert-Scale (with endpoints at 1 = not at all and 7 = to a large extent). In the last task, interests
and activities that are suitable as "highlight" are to be selected from the same item pool. Up to
24 free fields are provided for this purpose, in which the corresponding numbers are to be en-
tered.
Excerpt IAS questionnaire expert version A
Interests / Activities
In catego-
ries clas-
sify
please enter
here the
number(s)
1-14
To positively change the psychological state:
To what extent are the listed
interests/activities suitable for this purpose?
(Please mark with a cross on the number)
not at
all
to a
large
extent
1. Be on the beach
1
2
3
4
5
6
7
2. Share your experience with others
1
2
3
4
5
6
7
3. Ask others for advice on what suits
you
1
2
3
4
5
6
7
4. Help others
1
2
3
4
5
6
7
Continuing until item 176
1
2
3
4
5
6
7

21
Data Analysis
The statistical analyses were performed using the statistical program IBM SPSS 24 for Win-
dows. For the expert survey, the item assignments to the categories were first evaluated by
forming “multiple response sets” (cf. Jannsen & Laatz 2013). For this purpose, descriptive fre-
quencies had to be formed, which was also done for the reward means. The results of both
subsamples (split-half: expert group A and B) were evaluated and presented together for the
category formation, the reward mean values and the "highlights". Descriptive statistics were
also used to evaluate the highlight assessments.
2.2.2 Patient survey (Study 2)
Procedure and sample recruitment
For recruitment, the administrators of the participating facilities were first contacted in writing
and informed about the study. The surveys took place from January to October 2018, also using
a single-point measurement. In the inpatient (rehabilitants of a withdrawal treatment; n = 139)
and partly outpatient facilities (participants n = 9) as well as in the correctional facility (patho-
logical gamblers who attended a motivational group; n = 8), the surveys were conducted in the
context of a therapeutic group session. A small proportion of the surveys took place as "home-
work" (n = 5; also, outpatient). For the mentally ill (n = 20) who participated outpatient psy-
chotherapy (BT), this was done in the same way.
The survey of the control group (nursing students of a further education institute for health care
professions; n = 58) was carried out by their teachers within the framework of a teaching unit.
The participants were offered to receive a PDF copy of the dissertation if they were interested.
In order to achieve as high a response rate as possible among the control group (CG, nurses in
education), an "allowance" of € 10 was made, which was also enclosed prior to completion.
The survey was a paper-pencil survey and took between 45 and a maximum of 90 minutes to
complete. It was clarified in advance that the participants had sufficient knowledge of German
language. Participation was voluntary, anonymous and in accordance with current data protec-
tion regulations. All participants were informed in advance about the purpose of the study. It
was important to ensure that the participants were not in a critical state or intellectually over-
taxed.
Sample
248 persons participated in the patient survey. 9 questionnaires were excluded from the analysis
due to incomplete processing. Thus, 239 cases were included in the data analysis. The classifi-
cation of the addiction groups was based on the information about the addictive substances in
the sociodemographic section at the end of the questionnaire. This resulted in a total of three
groups: Alcohol addicts (n = 69; 28.9%), pathologic gamblers (n = 49; 20.5%) and drug addicts
(n = 43; 18.0%). Furthermore, a group of mental patients consisted of n = 20 (8.4 %) and the
control group (specialized nursing students) consisted of n = 58 (24.3 %) persons.
Sociodemographic data yielded the following results: Alcohol addicts had the highest age-re-
lated mean (M = 50.42) and the CG had the lowest (M = 26.45). The highest male proportion
was in the pathological Gamblers (95.9%) and the lowest in the CG (13.8%). The native lan-
guage of most of the participants in the study was German (from 75.9% in the CG to 95.2% in
the drug addicts). With regard to marital status, 60.9% of the alcohol addicts lived in a partner-
ship or marriage, 46.9% of the pathological gamblers, 48.8% of the drug addicts, 75.0% of the
mentally ill and 56.9% of the CG. A considerably smaller proportion were single parents (ad-
dicts: lowest among the athological Gamblers at 2.0%; highest among the CG at 5.2%). In terms
of living situation, the addicts were comparatively more likely to live alone (37.3% pathological
gamblers, 42.9% alcohol addicts, 45.7% drug addicts) than the CG (19.4%) and the mentally

22
ill (11.1%). In the CG 38.8% still lived with their parents, whereas the other experimental
groups had comparatively fewer of these living arrangements (addicts: from 2.6% in the alcohol
addicts to 17.4% in the drug addicts; 7.4% in the mentally ill), which is probably due to the
lower age and educational situation of the CG.
In the area of employment, the relatively high proportion of job seekers was among the addicts,
especially among the drug addicts with 52.2% and the pathological gamblers with 33.4%. Al-
cohol addicts were slightly lower at 16.7%. With regard to the types of school attended, most
of the data for all groups were distributed among the secondary school, high school and gram-
mar school. A smaller proportion indicated "other" (from 1.4% for the alcohol addicts to 24.1%
for the CG).
The number of treatments for addicts ranged from 1.52 for pathological gamblers to 1.98 for
drug addicts. The treatment duration in weeks was M = 8.07 for alcohol addicts, M = 12.86 for
pathological gamblers and M = 11.57 for drug addicts. The high mean value for pathological
gamblers was due to a total of 5 values that ranged from 30-50 weeks of treatment duration.
Three persons of these were from a correctional facility and participated in a motivational
group. In the case of the other two persons, the reported high values could not be explained.
Survey instruments
The IAS questionnaire (patient version) begins with the following introduction: The project
is intended to provide information about the influence of the presence of certain interests and
activities on the well-being and mental health. A disease-related restriction of the "world of
experience" can thus be recorded more precisely and specifically dealt with by therapeutic
measures. The IAS questionnaire is composed as follows: From a list of a total of 176 interests
and activities, each of which is to be classified using a 5-point (endpoint-named) Likert-Scale
with the poles 1 = "not at all" to 5 = "to a large extent" according to the following two questions:
1. How often have you engaged in these interests/activities in the past year? 2. Do you have a
desire to pursue these interests/activities more frequently?
Excerpt IAS questionnaire patient version
Interests / Activities
How often have you engaged in
these interests/activities in the
past year?
(Please tick on the number)
Do you have a desire to pursue
these interests/activities
more frequently?
(Please tick on the number)
not
at all
to a
large
extent
not
at all
to a
large
extent
1. Be on the beach
1
2
3
4
5
1
2
3
4
5
2. Share your experience with others
1
2
3
4
5
1
2
3
4
5
3. Ask others for advice on what suits
you
1
2
3
4
5
1
2
3
4
5
4. Help others
1
2
3
4
5
1
2
3
4
5
Continuing until item 176
1
2
3
4
5
1
2
3
4
5
For this purpose, two columns are provided next to each item. Subsequently, there is the possi-
bility to add a maximum of five further interests and activities by means of an open answer and

23
to answer these also according to the above two questions. The next task is to indicate interests
and activities that are suitable as highlights. For this purpose, the corresponding item numbers
(maximum 24) are to be entered. Another question is how confident the person is to realize their
wishes and plans (same 5-level scale, see above). Here, the 13 category designations (from
"social contacts" to "basic activities") are to be assessed as items with additional explana-
tions/examples, as well as an overall assessment of feasibility. In addition, the strength of the
craving for alcohol, drugs and other addictive substances within the last two weeks is asked
with a five-point scale in each case (not at all to a high degree from 1-5). This is also done with
regard to the intensity of the craving for gambling. The following socio-demographic variables
are collected: Age, gender (female, male), native language (German/other), marital status, liv-
ing situation, school, type of employment, addictive substance, number of treatments and cur-
rent therapy time in weeks. There are various possible answers to tick off.
The General Procrastination Questionnaire (APROF) by Höcker et al. (2013) comprises a
total of three constructs, whereby the first sub-scale "procrastination tendency" was specifically
selected because correlations with a lack of feasibility of therapy goals are to be assumed and
both problems are possibly caused by the fact that a dominance of risk behavior in the reward
system inhibits the exercise of alternative behavior (Bachmann, M. & El-Akhras 2014a, b). It
consists of seven items with seven response options each: never, almost never, rarely, some-
times, frequently, almost always, always.
The questions on life satisfaction modules (FLZ-M; Henrich & Herschbach 1990) were cho-
sen as a measuring instrument because, in addition to psychological well-being, physical health
aspects as well as individual areas of life and general life satisfaction are included. Especially
in the case of "life satisfaction", connections to the IAS and the categorization can be assumed.
On the basis of a 5-point Likert-Scale (dissatisfied to very satisfied), the "general life satisfac-
tion" (8 items), the "global life satisfaction" and the "health" (8 items) are to be assessed. The
importance rating was omitted for ecological reasons.
The Stress and Coping Inventory (Satow 2012) measures current exposure to stress, its phys-
ical and psychological consequences (stress symptoms) and coping with stress. The scales for
coping with stress were included in this study because of their practical feasibility and their
relation to coping with addictive substances (cf. Schmidt 2013): 1. Positive Thinking, 2. Active
Stress Management, 3. Social support, 4. Support in faith, 5. Increased alcohol and cigarette
consumption, each with a four-point Likert-Scale (1 = does not apply, 2 = rather does not apply,
3 = rather applies, 4 = applies exactly).
The ICD-10 symptom rating (ISR; Tritt et al. 2006, 2008) was chosen to assess the degree of
psychological distress or indications of the presence of comorbid disorders. For this purpose, a
depression (4 items), anxiety (4 items), obsessive-compulsive (3 items), somatoform disorder
(3 items), eating disorder (3 items) scale and an additional scale for 12 further symptoms (e.g.,
concentration disorders, suicidality, sleep problems) are available. The total of 29 items are
scored as follows: 0 (= not applicable) to 4 (= extremely applicable). An overall score serves as
an indicator of subjective, symptomatic impairment (cf. Tritt et al. 2010).
The Short Questionnaire on Gambling Behavior (Petry, J. 2003) can be used to diagnose
gambling in need of counseling/treatment and also to quantify the severity (moderate/advanced
gambling addiction). It is a 20-item Likert-Scale, with item values assigned from 0 (does not
apply at all), 1 (rather does not apply), 2 (rather applies) or to 3 (is exactly correct).
The Lübeck Alcohol Dependence and Abuse Screening Test (LAST) by Rumpf, Hapke and
John (2001) is used to diagnose alcohol dependence or alcohol abuse and to detect increased
alcohol risk consumption. The LAST contains seven items to be answered with "yes or no".
The ICD-10 Checklist for Drug and Medication Dependence was used to assess drug and/or
medication dependence. The questions (criteria) of the International Classification of Mental
Disorders (ICD-10 Chapter V (F)) are to be assessed using a dichotomous assessment (yes/no)

24
with a time window of the last twelve months. According to the ICD-10, three or more criteria
must be met together to diagnose the dependence syndrome (Dilling et al. 2015).
Data analysis
The statistical analyses were also performed using the IBM SPSS 24 for Windows statistical
program. All hypothesis tests took place at a significance level of p ≤ .05. Item scale statistics
were used to form the final classification of items into categories. Cronbach's alpha served as
the reliability coefficient. The one-sample t-test was performed to test the difference between a
mean and a given (standard) value. Pearson's correlation coefficients were tested two-sided.
These exact tests can also be performed for small numbers of cases (Jannsen & Laatz 2013). In
the literature, certain conditions are stated for the application of statistical methods, which were
largely fulfilled by the data.
The testing of the differences between the groups (mean values) took place in the case of vari-
ance homogeneity with the general linear model (ANOVA, factor group) or in the case of var-
iance inequality by means of “Welch test”. To counteract alpha error accumulation (false posi-
tive results) in multiple testing, an adjustment of the significance level by means of appropriate
correction procedures would be necessary (e.g., Bonferroni or Bonferroni-Holm correction). In
particular, because of the rather small number of cases in clinical studies and in favor of a higher
statistical power, a subsequent alpha adjustment was not applied (cf. García 2004). Conse-
quently, the results obtained in this context were to be classified as less conservative (confirm-
atory) and rather on an exploratory level. Subsequent post hoc tests were either Scheffe' (vari-
ance homogeneity) or Dunnett-T3 (variance inequality). As a next step, cluster analyses took
place (aim: identification of homogeneous groups/clusters for a set of objects). For validity
testing, hypotheses about the clusters are tested in which reference is made to variables that did
not enter into the clustering (cf. Bacher 2001; Bacher, Pöge & Wenzig 2010). For this purpose,
(M)ANOVAS were calculated again. After the calculation of hierarchical cluster analyses, a
suitable cluster solution was selected using the variance criterion and content-related aspects.
Subsequently, an optimization was performed by means of a cluster center analysis according
to the K-Means method (cf. Backhaus et al. 2016). For the detailed procedure, see Bachmann,
A. A. (2021). Chi-square tests were used to examine whether the groups differ from each other
in their distribution (observed vs. expected frequency) with regard to certain variables (e.g.,
gender) (Jannsen & Laatz 2013).
2.3 Results
2.3.1 Results of expert survey (Study 1)
Categorization
When assigning the items to the 13 categories and an additional residual category "other", it
was possible for the experts to give multiple answers. Most answers amounted to 1-3 category
mentions. In 96.61% of the cases, the experts (N = 91) only mentioned three categories. Finally,
on this basis as well as from test-statistical and content-related considerations, ten categories
resulted: (1) Social contacts, competence, (2) Exercise, fitness, (3) Mental activity, (4) Showing
feelings, (5) Recreation, (6) Experience adventure, (07) Culture enjoyment, (8) Hobby, creative,
(9) Media use and (10) Basic activities. This includes the data from the patient survey, e.g.,
reliability analyses/item scale statistics): see Tab. 5.
The first hypothesis for the categorization of the interests and activities to be investigated could
be validated on the basis of the expert survey.

25
Reward values (extent to positively change the psychological state)
On the basis of the expert assessment, differences in the reward values (descriptive statistics)
could be determined at both item and category level (see the following Tab. 1). At the category
level, the respective mean scores are presented in descending order (see Tab. 2). The four cate-
gories with the highest reward mean scores were "Showing feelings”, "Recreation", "Adventure
experience" and "Exercise, fitness". "Media use" was ranked lowest. At the item level (scale:
1-7), the minimum mean score was for "Programming" (category "Media use") at 2.16 and the
maximum was for "Laughter" (category "Showing Feelings") at 6.63 for an overall mean score
of 4.57.
Table 1 IAS categories and associated reward averages
Category
Reward value - the extent to which the psychological state can be positively changed.
Mean
Minimum
(Item number)
Maximum
(Item number)
Total, all items
4.57
2.16
Programming (105)
6.63
Laughter (080)
01 Social contacts,
Competence
4.68
3.16
Being a referee, coach (116)
6.33
Being with partner (176)
02 Exercise, fitness
4.86
3.67
Competing in sports
5.76
Regular sports training (109)
03 Mental activity
3.79
2.16
Programming (105)
5.62
Making positive plans for the
future (103)
04 Showing feelings
5.38
4.57
Expressing yourself in facial
expressions and gestures (066)
6.63
Laughter (080)
05 Recreation
5.19
3.78
Living into the day (062)
6.26
Going on excursions, e.g., to
the countryside, to the sea
(007)
06 Experience adventure
5.04
4.29
Going to a sports event (169)
6.18
Travel (110)
07 Culture enjoyment
4.77
4.04
Styling one's hair, putting on
make-up, etc. (118)
5.89
Highlights, e.g., at the weekend
(058)
08 Hobby, creative
4.30
3.13
Collecting things (018)
5.09
Singing, making music (136)
09 Media use
3.46
2.70
Computer, console games (016)
4.54
DVD night (019
10 Basic activities
3.92
2.41
Financial and budget planning
(043)
5.11
Healthy eating (055)
In Tab. 2 the ten categories are ranked in descending order according to their reward averages.
The highest rewardability was given to the category "Showing feelings" (M = 5.38) and the
lowest was given to the category "Media use" (M = 3.46).
Table 2 IAS categories and reward averages rank order
Category
Reward Value (M)
04 Showing feelings
5.38
05 Recreation
5.19
06 Experience adventure
5.04
02 Exercise, fitness
4.86
07 Culture enjoyment
4.77

26
01 Social contacts, competence
4.68
08 Hobby, creative
4.30
10 Basic activities
3.92
03 Intellectual activity
3.79
09 Media use
3.46
The findings support the assumption that the selected interests and activities have different de-
grees of effectiveness in positively altering psychological well-being and are likely to contribute
in different ways to a reconstruction of the reward system.
Highlights
Tab. 3 shows the 21 "highlights" most frequently mentioned by the experts. The percentages
refer to all test participants of the respective subsample (A: with n = 46; B: n = 45). Three
persons in both expert groups did not give an assessment of the "highlights" (expert group A =
1 and B = 2). The three items most often rated as "highlights" were "Being with partner" (31
mentions or 68.9%) from the "Social contacts, competence" category, followed by "Being on
the beach" (31 mentions or 67.4%) from the "Recreation" category and "Laughter" (30 mentions
or 65.2%) from the "Showing feelings" category. The intention was to select the 20 most men-
tioned items as "Highlight". Because of two equally high ratings at rank 14 of the items "Making
positive plans for the future" and "Trekking tours (canoe, bicycle, wilderness)", a list with a
total of 21 items resulted.
Table 3 Ranking of the 21 most frequently mentioned "highlights" in study 1 "Expert survey" (A & B)
Rank
Interests and
activities
(Item number)
Category
Number
of men-
tions
%
01
Being with partner (176)
Social contacts, competence
31
68.9
02
Being on the beach (1)
Recreation
31
67.4
03
Laughter (80)
Showing feelings
30
65.2
04
Going on trips e.g.
to the countryside, to the sea (7)
Recreation
29
62.3
05
Traveling (110)
Experience adventure
26
57.8
06
Experiencing nature (94)
Recreation
25
55.6
07
Making someone happy (70)
Social contacts, competence
25
54.3
08
Sexuality, tenderness (119)
Showing feelings
23
51.1
08
Being with friends, acquaintances (175)
Social contacts, competence
23
51.1
09
Massage (85)
Recreation
22
47.8
10
Visiting a spa, sauna (30)
Recreation
20
43.5
11
Eating with friends, acquaintances (90)
Social contacts, competence
19
42.2
11
Hiking (159)
Exercise, fitness
19
42.2
11
Being with family (174)
Social contacts, competence
19
42.2
12
Spending time with animals (128)
Recreation
15
33.3
12
Sports (140)
Exercise, fitness
15
33.3
12
Being with children (173)
Social contacts, competence
15
33.3
12
Relaxing (121)
Recreation
15
33.3
13
Having an open and honest conversation (25)
Social contacts, competence
15
32.6
14
Making positive plans for the future (103)
Mental activity
14
31.1
14
Trekking (canoe, bicycle, wilderness) (152)
Experience adventure
14
31.1
2.3.2 Results of patient survey (Study 2)
Open responses
The open responses to the question about additional items or interests and activities were hardly
or not at all perceived. The few comments referred to the "expression" of certain items.

27
Group comparisons: interest and activity spectrum (IAS) – MANOVA and ANOVAS Addicts
(total), mentally ill and Control Group
A multivariate analysis of variance (MANOVA) revealed significant group differences includ-
ing the IAS actual state total and the 10 categories on the IAS actual state with Wilk's λ = .564,
F(22, 452) = 6.819, p ≤ 0.001. Analysis of variance (or Welch test for variance heterogeneity)
revealed significant differences between groups for the actual state total and all 10 categories
of the IAS actual state (DVs) (see Tab. 4). The factor group (addicts total, mental ill patients
and control group) served as the independent variable. Analyses were two-tailed at the signifi-
cance level of p ≤ .05. Tab. 4 includes the group-specific means, associated 95% confidence
intervals and standard deviations. All mean scores of the addicts (n = 161) were significantly
lower than those of the control group in the post hoc tests.
Hypothesis 3(a) could be validated for the IAS actual state total as well as for all ten categories:
The addicts (total) had a significantly lower range of interests and activities than the control
group.
The addicts scored significantly lower mean scores on the basic activities compared to the men-
tally ill. The mean values of the mentally ill were significantly lower than those of the control
group with regard to the actual state overall and in six categories ("Social contacts, compe-
tence", "Exercise, fitness", "Showing feelings", "Adventure experience", "Culture enjoyment",
"Media use").
Furthermore, the addicts (overall) had selected the scaled response option "not exercised at all"
(based on the past 12 months and all 176 items) more frequently compared to the control group,
with a ratio of 60 to 40 (or 1.5 times). This served as evidence that the addicts had a less differ-
entiated interest and activity spectrum than the control group (validation of hypothesis 3b).
Table 4 Comparisons between addicts (total), mentally ill and control group on the IAS actual state total and categories: Means,
standard deviations, confidence intervals, ANOVAS/Welch tests and post hoc tests.
IAS actual
state
Addicts
(total)
n = 161
M (SD)
[95% KI]
Mentally
ill
n = 20
M (SD)
[95% KI]
Control-
Group
n = 58
M (SD)
[95% KI]
F
df
p
Post hoc test
Significant
group compar-
ison
Actual state-
total
2.16 (0.44)
[2.10; 2.22]
2.28 (0.29)
[2.14; 2.42]
2.60 (0.31)
[2.52; 2.70]
35.2301
2, 55.9121
≤ .0011
1,3***
2,3***
Categories
01 Social
contacts,
competence
2.31 (0.51)
[2.23; 2.39]
2.46 (0.46)
[2.25; 2.68]
2.84 (0.37)
[2.74; 2.94]
34.5001
2, 51.0011
≤ .0011
1,3***
2,3**
02 Exercise,
fitness
1.76 (0.57)
[1.67; 1.85]
1.71 (0.33)
[1.55; 1.86)
2.02 (0.54)
[1.87; 2.16]
5.8201
2, 59.7181
≤ .011
1,3**
2,3*
03 Intellec-
tual activity
1.94 (0.49)
[1.86; 2.01]
2.13 (0.37)
[1.95; 2.30]
2.38 (0.41)
[2.27; 2.49]
19.621
2, 236
≤ .001
1,3***
04 Showing
feelings
2.57 (0.74)
[2.46; 2.69]
2.86 (0.60)
[2.58; 3.14]
3.45 (0.58)
[3.29; 3.60]
33.788
2, 236
≤ .001
1,3***
2,3**
05 Recreation
2.42 (0.52)
[2.34; 2.50]
2.45 (0.39)
[2.27; 2.63]
2.67 (0.44)
[2.56; 2.79]
5.750
2, 236
≤ .01
1,3**
06 Experi-
ence adven-
ture
1.86 (0.55)
[1.78; 1.95]
1.76 (0.30)
[1.62;1.89]
2.28 (0.55)
[2.13; 2.42]
15.7841
2, 62.4121
≤ .0011
1,3***
2,3***
07 Culture
enjoyment
2.24 (0.59)
[2.15; 2.33]
2.31 (0.62)
[2.01; 2.60]
2.93 (0.45)
[2.81; 3.05]
33.063
2, 236
≤ .001
1,3***
2,3***
08 Hobby,
creative
1.65 (0.44)
[1.58; 1.72]
1.63 (0.30)
[1.49; 1.77]
1.84 (0.41)
[1.73; 1.95]
4.569
2, 236
≤ .05
1,3*
09 Media use
2.63 (0.76)
[2.52; 2.75]
2.76 (0.82)
[2.37; 3.14]
3.37 (0.67)
[3.19; 3.55]
20.910
2, 236
≤ .001
1,3***
2,3**
10 Basic ac-
tivities
2.59 (0.69)
[2.49; 2.70]
3.21 (0.51)
[2.97; 3.46]
3.23 (0.52)
[3.09; 3.36]
31.1391
2, 53.5981
≤ .0011
1,2***
1,3***
Notes. 1Welch test (variance inequality). *p ≤ 0.05; **p ≤ 0.01; ***p ≤ 0.001.

28
Item assignment to the categories (reliability statistics)
Test statistical validation for the use of the 10 categories (scales; see tab. 5): The reliability
analyses on the basis of the patient survey on the IAS actual state of the 176 items validated the
reduction of the number of categories (scales) to 10, since the values of the internal consistency
(Cronbach's alpha) could be improved in this way. The reliability statistics of the categories (1-
10) of the IAS actual state and desire for change related to all study groups are shown in Tab.
5. Summarizing the response of the items to the IAS actual state, the reliability coefficients
ranged from Cronbach's alpha = .921 with an excellent ("Mental activity"), at Cronbach's alpha
= .820 with a good ("Showing feelings"), to the lowest but acceptable internal consistency of
Cronbach's alpha = .725 ("Media use"). For the change requests, the overall reliability coeffi-
cients were somewhat lower: Four scales were classified as "good" (> .8), four as "acceptable"
(˃ .7) and two as "question-worthy-approximately acceptable" (˃ .6) ("Experience adventure"
and “Culture enjoyment"). The categories could thus be used for further analyses (including the
group comparisons). The consistently significant positive medium to high ("Media use" some-
what lower) inter-scale correlations (see Bachmann, A. A. 2021) to the IAS categories under-
lined that the interests and activities as well as the categories were related variables (in accord-
ance with the hypothesis).
Table 5 Reliability statistics: IAS-scales
Category (scale)
Item count
Cronbach’s Alpha
IAS-Actual state
IAS-Change request
01 Social contacts, competence
39
.910
.879
02 Exercise, fitness
21
.873
.801
03 Mental activity
22
.921
.777
04 Showing feelings
8
.820
.778
05 Recreation
22
.776
.781
06 Experience adventure
11
.747
.676
07 Culture enjoyment
10
.767
.676
08 Hobby, creative
20
.783
.806
09 Media use
7
.725
.727
10 Basic activities
16
.871
.835
Alcohol addicts, pathological gamblers and drug addicts in comparison with the mentally ill
and the control group
In a further statistical analysis, it was to be examined whether the three addiction-related groups
also showed a lower interest and activity spectrum compared to the control group.
A multivariate analysis of variance (MANOVA) revealed significant group differences includ-
ing the 10 categories on the IAS actual state, the IAS change requests as well as the feasibility
assessment with Wilks λ = .321, F(84, 843,779) = 3.352, p ≤ 0.001. Subsequently, single facto-
rial analyses of variance (ANOVAs) and post hoc tests were calculated for each category ac-
cordingly. The factor group (alcoholics, pathological gamblers, drug addicts, mentally ill and
control group) was included as an independent variable. The analyses were two-tailed at the
significance level of p ≤ .05.
In terms of the individual addiction groups, alcohol addicts, pathological gamblers and drug
addicts, the mean values on the IAS actual state (total) were again significantly lower than the
control group. This was also true for seven of ten categories: "Social contacts, competence",

29
"Mental activity", "Showing feelings", "Experience adventure", "Culture enjoyment", "Media
use" and "Basic activities". In the three remaining categories, individual addiction-related
groups differed significantly from the control group (CG), e.g., the pathological gamblers and
the alcohol addicts were significantly below the CG in "Recreation". The mentally ill group
tended to show similar results. Because of the large heterogeneity and small size of this sample,
further research on this is needed (Bachmann, A. A. 2021). In the evaluation of IAS change
desires ("Do you have the desire to pursue these interests/activities more frequently?"), the ad-
dicts were significantly higher than the CG with regard to the "difference value" (ACTUAL
minus DESIRED). With regard to the subjective assessment of feasibility, the addicts were sim-
ilarly optimistic as the control group.
Hypothesis 3(c): In summary, it can be stated that overall, there were less significant differences
with regard to change desires between the three addiction-related groups and the CG. However,
information on individual addiction-related groups could be determined, which provided indi-
cations for a differentiated therapeutic approach.
In addition, deviations were found in the following psychological parameters: The addiction-
related groups had a significantly higher tendency to cope with stress with alcohol and cigarettes
than the control group and the mentally ill and also showed significantly lower life satisfaction
(overall and life domains) than the control group (for test statistics, see Bachmann, A. A. 2021).
In addition, the addiction-related groups tended to have higher psychological distress (similar
to that of the mentally ill). In terms of substance or gambling craving, the addicts tended to have
higher levels of craving, although overall craving was rather low. They also showed increased
procrastination compared to the norm: Two-tailed T-tests: the mean of the addiction-related
groups (alcohol, gambling and drugs: n = 160 and M = 4.18) was significantly higher than that
of the norm sample (M = 3.84): t(159) = 3.081, p = .002. The 95% confidence interval of the
difference was (95%-CI[0.12; 0.55]). The mean of the control group (n = 57; M = 4.41) was
also significantly higher than that of the norm sample t(56) = 3.623, p = .001. The 95% confi-
dence interval of the difference was (95%-CI[0.25; 0.88]).
Highlights
Just like the experts, the patients and control persons (from the 176-item pool) rated interests
and activities as "highlights". Tab. 6 shows the 22 (because of three equally high ratings, there
were 22 instead of 20 as originally intended) most frequently mentioned "highlights" in relation
to all study groups of the "patient survey" at item and category level. The item "Being together
with partner" (category "Social contacts, competence") was rated most frequently as a "high-
light" with 61 mentions at 33.9% and "Laughter" second most frequently with 60 mentions at
33.3% (category "Showing feelings"). In third place came the item "Travel" (category "Experi-
ence adventure") with 56 ratings at 31.1%.
Table 6 Ranking of the 22 most frequently mentioned "highlights" in study 2 "patient survey" (all study groups; N = 180).
Rank
Interests and activities
(Item number)
Category
Quantity
%
01
Being with partner (176)
Social contacts, competence
61
33.9
02
Laughter (80)
Showing feelings
60
33.3
03
Travel (110)
Experience adventure
56
31.1
04
Sexuality, tenderness (119)
Show feelings
54
30.0
05
Being on the beach (1)
Recreation
51
28.3
06
Being with family (174)
Social contacts, competence
50
27.8
07
Going on trips, e.g., to the countryside, to
the sea (7)
Recreation
44
24.4
08
Doing something for your health (36)
Exercise, fitness
41
22.8
09
Going out to eat (35)
Culture enjoyment
37
20.6
10
Spending time outdoors (e.g., park, pic-
nic) (60)
Recreation
36
20.0

30
Rank
Interests and activities
(Item number)
Category
Quantity
%
11
Make someone happy (70)
Showing feelings
35
19.4
11
Spending time with animals (128)
Recreation
35
19.4
11
Being with friends, acquaintances (175)
Social contacts, competence
35
19.4
12
Walking the dog (88)
Recreation
33
18.3
13
Having an open and honest conversation
(25)
Social contacts, competence
30
16.7
13
Listening to the radio, music (108)
Recreation
30
16.7
14
Being together in a cozy atmosphere (52)
Social contacts, competence
29
16.1
15
Regular sports training (109)
Exercise, fitness
27
15.0
15
Doing sports (140)
Exercise, fitness
27
15.0
16
Visiting a spa, sauna (30)
Recreation
26
14.4
16
Making positive plans for the future (103)
Mental activity
26
14.4
16
Problem solving (104)
Mental activity
26
14.4
Correlations
To validate the IAS scales, correlative calculations (Pearson correlation coefficient, 2-sided
tests)/inter-scale correlations to the IAS actual state were performed (see Tab. 7). Almost all
categories (exception: "Media use") correlated highly significantly with each other in medium
to (very) high strength. The highest correlation was shown for "Social contacts, competence"
and "Showing feelings" r(237) = .808, p ≤ .001. The second highest correlation was for "Social
contacts, competence" and "Culture enjoyment" with r(237) = .780, p ≤ .001 and the lowest
correlation was r(237)= .441, p ≤ .001 between "Exercise, fitness" and "Showing feelings".
"Media use" had overall lower correlations with the other categories of the IAS actual state than
the other scales had with each other. A highly significant strong negative correlation with age
r(232) = -.530, p ≤ .001 was conspicuous for "Media use", which did not turn out at this level
for any other category (for assessments of correlation levels, see Cohen 1988).
Table 7 IAS inter-scale correlations: Current status categories 1-10, Current status total according to Pearson, 2-tailed tests; N = 238-
239.
Notes. Correlations ≥ .30 are highlighted in bold. * p ≤ .05, ** p ≤ .01, *** p ≤ .001.
For further validation, correlations of the IAS actual state (total and categories) with the other
variables (procrastination, stress management, substance/gambling craving and life satisfac-
tion) were determined. In the area of life satisfaction (FLZ-M), the correlations between the 10
categories on IAS actual state and actual state-total with life satisfaction (1. overall, 2. life do-
mains and 3. health) proved to be almost all significantly positive. Of the thirty significant
02
03
04
05
06
07
08
09
10
11
01 Social con-
tacts, comp.
.559***
.669***
.808***
.657**
.742***
.780***
.549***
.479***
.664***
.914***
02 Exercise, fit-
ness
.556***
.441***
.570***
.638***
.525***
.511***
.161*
.482***
.724***
03 Mental activ-
ity
.618***
.658***
.578***
.599***
.608***
.251**
.684***
.822***
04 Showing feel-
ings
.616***
.626***
.698***
.454***
.466***
.631***
.816***
05 Recreation
.621***
.620***
.613***
.334***
.478***
.804***
06 Experience
adventure
.709***
.582***
.355***
.500***
.810***
07 Culture en-
joyment
.556***
.430***
.601***
.830***
08 Hobby, crea-
tive
.227**
.502***
.721***
09 Media use
.181**
.458***
10 Basic activi-
ties
.764***
11 Actual State
Total

31
correlations, twelve were (r > .30) and three were (r > .40) of moderate strength. With regard
to the other variables, there were also several significant results, which are reported in more
detail in Bachmann, A. A. (2021).
Cluster analysis
Furthermore, cluster analyses were calculated in order to identify and analyze different sub-
groups (types) with regard to the interest and activity spectrum (type-forming categories IAS
actual state and desire for change; for the procedure see Bacher et al. 2010; Bachmann, A. A.
2021): In summary, the 4-cluster solution generated by the K-Means procedure (optimized by
cluster centers based on the Ward procedure) can be interpreted in terms of content as well as
classified as sufficiently valid with regard to the quality criteria (internally homogeneous as
well as externally heterogeneous clusters). The corresponding results of the test-statistics can
be found in Bachmann, A. A. (2021).
The findings make clear that addicts who were in the "mixed" cluster 1 (relatively high propor-
tion with 50.1%) and had a higher IAS actual state also achieved better values in the other
psychological parameters, e.g., a higher life satisfaction. In addition, two clusters predomi-
nantly consisting of addicts (cluster 2: 89%; cluster 3: 69.2%) with lower IAS scores were found
to be affected by more unemployment (Chi2 (18) = 34.426, p = .006), lived alone more often
(Chi2 (12) = 35.348, p < .001), had higher psychological distress, tended to consume more al-
cohol and cigarettes under stress, had less social support and procrastinated more. In cluster (3),
low desire for change and low confidence in realization the own goals were also unfavorable
constellations. In addition, there were significant age differences (Welch test: F(3, 121,561) =
26.377, p ≤ .001). Significant post hoc tests (Dunnett-T3): Clusters (1) and (3) at p = .010 and
(4) with all other three clusters each at p = ≤ .001. This was due to the high percentage from the
control group (nurses in education who were younger compared to the experimental groups) in
cluster 4. There were no significant group differences between the clusters for marital status
and gender.
Additional results
With regard to the severity of various psychological stresses, the following results were deter-
mined: all experimental groups and the control group showed low mean scores in depression,
anxiety, obsessive-compulsive and eating disorders (cut-off score ≥ 1.0 < 2.0).
In the case of somatoform disorders, the pathological gamblers showed a low symptom load
(from 0.75), in all other groups there was a suspicion (cut-off value from 0.33).
The additional scale: It contained 12 further symptoms, which provide indications for the pres-
ence of different syndromes. The mean scores of the drug addicts and the mentally ill were
elevated.
Overall burden: The experimental groups had a medium overall burden (cut-off value from 0.9)
and the CG a low one (cut-off value from 0.6).
Despite the rather low syndrome expressions in the test procedure (ISR) in the addiction groups
and the mentally ill, there were significant negative correlations with the interest and activity
spectrum (according to Pearson, 2-sided tests; N=238-239). This means that the IAS values
decrease, i.e., a narrowing of the interest and activity spectrum is to be expected, if a mental
disorder (e.g., depression) tends to increase. However, in the case of correlations, causal rela-
tionships cannot be inferred, which are reserved for experimental study conditions.
The "total IAS score" correlated significantly negatively with the "depression scale" at r(236)
= -.253, p ≤ .001, with an approximately medium effect. This result provides evidence that
depressiveness is associated with a narrowing of the interest and activity spectrum. In addition,
significant negative correlations ("weak effect") were shown with the "additional scale" at
r(237) = -.143, p ≤ .05 and the "total stress" at r(237) = -.141, p ≤ .05.

32
The narrowing of the interest and activity spectrum could be further specified on the basis of
the study, that is, which of the identified 10 categories were particularly affected.
Accordingly, at the category level, the following significant correlations (*p ≤ .05; **p ≤ .01;
***p ≤ .001) with ISR were found:
• Depression: 01 Social contacts, competence -.245***, 02 Physical exercise -.216***, 03 Men-
tal activity -.171**, 04 Showing feelings -.249***, 05 Recreation -.177**, 06 Experience ad-
venture -.276***, 07 Culture enjoyment -.313***.
• Anxiety disorder: 02 Physical exercise -.153*, 06 Experience adventure -.173**, 07 Culture
enjoyment -.194**.
• Obsessive-compulsive disorder: 04 Showing feelings -1.63*, 06 Experience adventure .148*,
07 Culture enjoyment -.175**.
• Additional scale: 01 Social contacts, competence -.200**, 04 Showing feelings -.211***, 06
Experience adventure -.182**, 07 Culture enjoyment -.234***.
• Total load: 01 Social contacts, competence -.158*, 04 Showing feelings -.198**, 06 Experi-
ence adventure -.199**, 07 Culture enjoyment -.233***.
Most significant negative correlations to IAS categories were present for depression. Only so-
matization had a positive correlation with 08 Hobby, Creative at .128*. The categories 06 Ex-
perience Adventure and 07 Culture enjoyment seemed to tend to be the most frequently im-
paired for the other symptom classes.
The significant correlations between the categories on the IAS actual state with each other (in-
ter-scale correlations) and with the questionnaires used for life satisfaction, procrastination and
stress management indicate sufficient internal and external validity of the scales on the interest
and activity spectrum.
The interest and activity spectrum (IAS) in connection with life satisfaction, stress management,
psychological strain and procrastination
The addiction-related groups showed significantly lower life satisfaction (overall and different
life domains) than the control group. The alcohol dependents were also more dissatisfied with
their health than the control group. These findings are in line with the results of a study by Koch
et al. (2016), according to which the narrowing of the experienced behavioral spectrum and
action radius is associated with a lower quality of life. In the area of procrastination, there were
no significant group differences between the CG and the addicts. On the other hand, the com-
parisons with the norm sample are conspicuous, according to which all addiction-related groups
and the CG were significantly above the norm value. Since the CG consisted of nurses in edu-
cation, the question arises as to whether this sample had a tendency to procrastination similar
to that of students (cf. Höcker et al. 2013). Thus, as expected, it could be demonstrated that the
addicts procrastinated more. Since increased procrastination can make the feasibility of goals
more difficult, it is a factor to be taken into account and possibly validates the assumption that
previous results on the assessment of feasibility are too optimistic. Not realization or postponing
important tasks or goals is often a consequence or component of mental illnesses and addictions
(Höcker et al. 2013; cf. Bachmann & El-Akhras 2014a, b).
With regard to overall psychological distress, elevated values of medium degree were found for
all three addiction-related groups. In the area of individual syndromes (depressive, anxiety,
compulsive, somatization, eating disorder), predominantly low (or suspected) distress was ob-
tained. Since the participants in the addiction groups were already in therapy at the time of the
survey and the test only records "the last 2 weeks" as a time window (with the exception of one
item), this may also indicate that (initial) psychological relief had already set in during treat-
ment.

33
2.4 Discussion
Findings of the interest and activity spectrum (IAS)
It should be emphasized that the "cross-sectional study design" available here does not al-
low for any causal conclusions. For further background in this regard, please refer to the
publication of the dissertation (Bachmann, A. A. 2021).
Both the empirical investigation and the diagnostic criteria, as well as unsystematic observa-
tions, support the assumption of a narrowing of the interest and activity spectrum as a result of
addictive and other risk behaviors with a dysfunction of the reward system. However, this does
not exclude the possibility that low IAS scores may also be a cause of the disorder. The group
of mentally ill patients show similar results. Technical problems during the time of investigation
(e.g., a lack of funding and a deficit of institutional equipment) led to insufficient data collection
from the mentally ill persons. Because of the great heterogeneity and small size of this sample,
further research on this is needed (Bachmann, A. A. 2021).
The results for the difference value of the IAS actual state and desire for change make clear
that all addiction groups would like to expand their range of interests and activities and are
likely to be motivated to participate in appropriate therapeutic measures. This was also
shown in (non-systematic) feedback from the patients after the test conducting and in selective
debriefings in the group setting. In the sense of a desired restructuring of the reward system
these results are to be classified as promising. Losses of quality of life experienced in many
ways may especially lead to the desire to develop neglected interests and activities again and to
discover new ones. Since the addicts were already in therapy at the time of the survey (and a
small proportion in a motivational group), it can also be assumed that they had very high posi-
tive expectations of achieving their own aims. The high level of confidence is probably overly
optimistic in some cases and should not lead to neglecting the aspect of feasibility under eve-
ryday conditions in the further course of therapy. In order to prevent disappointment, care must
be taken to ensure a realistic approach and sufficient support for the permanent establish-
ment and anchoring of new behavior. Particular attention must be paid to the high expecta-
tions of drug addicts (greatest discrepancy between ACTUAL and TARGET), so that the initial
euphoria is not followed by rapid frustration, which leads to renewed addictive behavior.
The results of the cluster analysis indicate that a group of addicts with fewer resources requires
more social-psychological attention. This goes hand in hand with data from the German Addic-
tion Aid Statistics from 2009, according to which the proportion of unemployed clients was
higher than for employed clients for the following variables: living alone, precarious housing
situation (without a home, emergency shelters), without completed vocational or higher educa-
tion, problematic debts and multiple treatments (Kipke et al. 2015). The proportion of regular
terminations was 13.3 percentage points lower for unemployed outpatient clients and 10.9 per-
centage points lower for inpatient clients than for employed clients, so a higher risk of recidi-
vism can be assumed. Therefore, not only measures for (re)integration into the labor market
should be taken, but also additional addiction-preventive steps (e.g., adaptation treatment) if no
job prospects are foreseeable. In this context, more intensive cooperation between addiction
support facilities, self-help groups, employment agencies, vocational training centers, job cen-
ters, debt counselors and youth and social welfare offices could prove valuable.
In the investigation conducted here, no differentiation was made between short-term and long-
term effective alternatives (to change the psychological state positively). For example, projects
such as "addressing conflicts", "financial and budget planning", which achieve quite low values,
are possibly initially rather stressful but considerably relieving when viewed in the longer
term. The long-term effects of interests and activities do not seem to have been sufficiently
taken into account in the recording of reward values. Is it perhaps part of the human character-
istic to rather aim at a quick, short-term positive psychological relief? Further investigations
should include these aspects.

34
The assumption of a certain sequence ("from bottom to top" pyramid) of alternative reconstruc-
tion, taking into account the gradual differences in reward ability, remains to be discussed on
the basis of the present results. There are indications that "basic activities" (everyday life skills,
not letting oppressive worries arise) are an important prerequisite for the pursuit of other inter-
ests and activities and based on this, the categories "Showing feelings", "Social contacts,
competence" and a good level of "Exercise, fitness" should form a further basis of the alterna-
tive reconstruction. This is then followed by the other categories as well as the realization of
individual "highlights", which implies a certain emphasis in order to establish an essential con-
dition for a balanced lifestyle (cf. Marlatt 1985).
The overall objective is to regain interest and pleasure in many other aspects of life, to form
stable new habits and thus to activate the reward system in a way other than through addictive
or risky behavior. This approach forms the basis for changing the neurobiological processes
in the brain in the long term and for experiencing the abandonment of risk behavior not as a
renunciation, but even as an advantage and for maintaining the alternative behavioral orienta-
tions in the long term (cf. Bachmann, M. 2018, 2019).
Classification of the findings in other theoretical approaches
As various empirical findings suggest (Fenzel 2005; Vaughan et al. 2009; Meshesha et al. 2015;
Daughters et al. 2018; Martínez-Vispo et al. 2018; cf. Acuff et al. 2019), there are alternative,
non-substance reinforcers that protect against substance use and contribute to life improvement.
In addition, it is emerging that certain categories of non-substance alternatives, such as exercise
and social activities, are likely to have a stronger impact on reducing substance use than others.
However, because indices, "total scores”, or global averages of activities in terms of exercise
and their strength to experience pleasure have been predominantly available to date, no catego-
rizations have been made and substance-related items have been included in some cases, the
results can only be marginally compared with those of this investigation. The categories deter-
mined and the associated reward values from the "expert view" thus represent a specification
and differentiation of addiction-incompatible alternatives.
Further projects are:
• A larger randomized sample of people with reward system dysfunction from various
psychological disorders.
• Men are in the minority in both the control group and the expert sample and there is also an
age bias: a representative sample is therefore necessary.
• From the existing data, further insights may be possible: e.g., do narrowing of interests/ac-
tivities and change requests vary (at item and category level) across different clinical
pictures.
• Can the item pool be meaningful divided into interests and activities and does this change
the results in the case of "narrowing down" or "requests for change" in the various groups?
For example, do depressives avoid activities such as exercise more than other study groups?
Correspondence address:
Meinolf Bachmann (PhD)
meinolf.bachmann@web.de

35
Reference
Acuff, S. F., Dennhardt, A. A., Correia, C. J., & Murphy, J. G. (2019). Measurement of sub-
stance-free reinforcement in addiction: A systematic review. Clinical Psychology Re-
view, 70, 79 –90.
Albrecht, U. (2006). Reizreaktionen und Verlangen bei pathologischen Glücksspielern: Psy-
chologische und physiologische Parameter. Berlin: Logos Verlag.
Albrecht-Sonnenschein, U., Wölfling, K., & Grüsser-Sinopoli, S. M. (2018). Glücksspielsucht.
Diagnostische und klinische Aspekte. In I. Gebhardt & S. Korte (Hrsg.), Glücksspiel.
Ökonomie, Recht, Sucht (2. vollst. überarb. Aufl., S. 837–865). Berlin: De Gruyter.
Bacher, J. (2001). Teststatistiken zur Bestimmung der Clusterzahl für Quick Cluster. ZAInfor-
mation / Zentralarchiv für Empirische Sozialforschung, 48, 71–97.
Bacher, J., Pöge, A., & Wenzig, K. (2010). Clusteranalyse: Anwendungsorientierte Einführung
in Klassifikationsverfahren (3.vollst. überarb. Aufl.). München: Oldenbourg.
Bachmann, A. A. (2021). Alternative belohnungsfähige Interessen und Aktivitäten – therapeu-
tische Implikationen zur Annahme eines „Suchtgedächtnisses“. (Dissertation). Univer-
sität Bremen. Verfügbar unter https://doi.org/10.26092/elib/797
Bachmann, M. (1992). Alkoholismus, Magersucht und Bulimia nervosa – Parallelen bei der
Krankheitsgenese und dem therapeutischen Vorgehen. Dissertation, 1990, erschienen im
Universitätsverlag, Bochum: Dr. N. Brockmeyer.
Bachmann, M. (2017). Grundsätzliches zur Spielsuchttherapie. In G. Meyer & M. Bachmann,
Spielsucht. Ursachen, Therapie und Prävention von Glücksspielbezogenem Suchtver-
halten (4. vollst. überarb. Aufl., S. 223–296). Heidelberg: Springer.
Bachmann, M. (2018). Psychotherapie der Depression unter Annahme eines Depressionsge-
dächtnisses. https://nbn-resolving.org/urn:nbn:de:0168-ssoar-57756-1
Bachmann, M. (2019). Psychotherapy for depression under the (speculative) assume of a "de-
pression memory" due to a structural change in the neurobiological reward system.
https://nbn-resolving.org/urn:nbn:de:0168-ssoar-63043-4
Bachmann, M. & Röhr, H.-P. (1983a). Alkoholismus – Eßsucht – Magersucht. Ein Vergleich.
Psychother. med. Psychol., 33, 111-116.
Bachmann, M. & Röhr. H.-P. (1983b). A speculative illness model of overeating and anorexia
nervosa. Psychological Reports, 53, 831-838.
Bachmann, M., & El-Akhras, A. (2014a). Glücksspielfrei. Ein Therapiemanual bei Spielsucht
(2. überarb. Aufl.). Heidelberg: Springer.
Bachmann, M., & El-Akhras, A. (2014b). Lust auf Abstinenz. Ein Therapiemanual bei Alkohol,
Medikamenten- und Drogensucht (2. überarb. Aufl.). Heidelberg: Springer.
Bachmann, M., & Bachmann, A. A. (2023). Der Alternativen-Finder: Manual zur Therapie-
Unterstützung bei Suchterkrankungen, affektiven, Ess-, Zwangsstörungen und anderem
Risikoverhalten mit Fehlfunktion des Belohnungssystems. Berlin, Heidelberg: Springer.
Backhaus, K., Erichson, B., Plinke, W., & Weiber, R. (2016). Multivariate Analysemethoden.
Eine anwendungsorientierte Einführung (14. überarb. Aufl.). Heidelberg: Springer Gab-
ler.
Bandura, A. (1991). Sozial-kognitive Lerntheorie. Stuttgart: Klett-Cotta Verlag.
Berridge, K. C., Ho, C. Y., Richard, J. M. & DiFeliceantonio, A. G. (2010). The tempted brain
eats: pleasure and desire circuits in obesity and eating disorders. Brain Res., 1350, 43-
64.
Böning, J. (2009). Addiction memory as a specific, individually learned memory imprint. Phar-
macopsychiatry, 42(S 01), 66- 68.
Böning, J., & Albrecht-Sonnenschein, U. (2018). Wie kann glücksspielsüchtiges Verhalten ent-
stehen? In I. Gebhardt & S. Korte (Hrsg.), Glücksspiel. Ökonomie, Recht, Sucht (2. über-
arb. Aufl., S. 867-883). Berlin: DeGruyter.

36
Choi, J. S., Shin, Y. C., Jung, W. H. et al. (2012). Altered brain activity during reward anticipa-
tion in pathological gambling and obsessive‐compulsive disorder. PLoS O-NE 2012; 7:
e45938.
Ciccarelli M, Nigro G, Griffiths MD, Cosenza M, D’Olimpio F (2016). Attentional bias in non-
problem gamblers, problem gamblers, and abstinent pathological gamblers: an experi-
mental study. Journal of Affective Disorders 206: 9–16.
Costandi, M. (2015). 50 Schlüsselideen - Hirnforschung. Berlin, Heidelberg: Springer.
Daughters, S. B., Magidson, J. F., Anand, D., Seitz-Brown, C. J., Chen, Y., & Baker, S. (2018).
The effect of a behavioral activation treatment for substance use on post-treatment ab-
stinence: a randomized controlled trial. Addiction, 113(3), 535–544.
https://doi.org/10.1111/add.14049
Dilling, H., Mombour, W., & Schmidt, M. H. (Hrsg.). (2015). Internationale Klassifikation psy-
chischer Störungen ICD-10 Kapitel V (F) Klinisch-diagnostische Leitlinien (10. über-
arb. Aufl.). Göttingen: Hogrefe.
Drexler, D. (2013). Mit beiden Augen sehen – Ressourcenorientierung in Gesundheitsförderung
und Stressmanagement. In A. Lampe, P. Abilgaard & K. Ottomeyer (Hrsg.), Mit beiden
Augen sehen: Leid und Ressourcen in der Psychotherapie (S. 190–215). Stuttgart: Klett-
Cotta.
Elsesser, K., & Sartory, G. (2001). Medikamentenabhängigkeit. Göttingen: Hogrefe.
Erbas, B., & Buchner, U. G. (2012). Review Article: Pathological Gambling Prevalence, Diag-
nosis. Comorbidity and Intervention in Germany, 109, 173–179.
Fenzel, L. M. (2005). Multivariate analyses of predictors of heavy episodic drinking and drink-
ing-related problems among college students. Journal of College Student Development,
46(2), 126–140. https://doi.org/10.1353/csd.2005.0013
Figee, M., Vink, M., de Geus, F., Vulink, N., Veltman, D. J., Westenberg, H., et al. (2011).
Dysfunctional reward circuitry in obsessive–compulsive disorder. Biological Psychia-
try, 69, 867–874.
Fontenelle, L. F., Oostermeijer, S., Harrison, B. J., Pantelis, C., Yücel, M. (2011). Obsessive-
compulsive disorder, impulse control disorders and drug addiction: common features
and potential treatments. Drugs, 71, 827–840.
García, L. V. (2004). Escaping the Bonferroni iron claw in ecological studies. Oikos, 105, 657-
663. DOI: 10.1111/j.0030-1299.2004.13046.x
Grawe, K. (2004). Neuropsychotherapie. Göttingen: Hogrefe.
Grüsser, S. M., & Albrecht, U. (2007). Rien ne va plus – Wenn Glücksspiele Leiden schaffen.
Bern: Huber.
Grüsser, S. M, Plöntzke, B., & Albrecht, U. (2005). Pathologisches Glücksspiel – Eine empiri-
sche Untersuchung des Verlangens nach einem stoffungebundenen Suchtmittel. Ner-
venarzt, 76, 592–597.
Hägele, C., Schlagenhauf, F., Rapp, M., Sterzer, P., Beck, A., Bermpohl, F., … Heinz, A.
(2015). Dimensional psychiatry: reward dysfunction and depressive mood across psy-
chiatric disorders. Psychopharmacology, 232(2), 331-341.
Hayer, T., Meyer, G., & Brosowski, T. (2014). Stressverarbeitungsstrategien bei pathologi-
schen Glücksspielern: Auffälligkeiten und Implikationen für die klinische Praxis. Sucht-
therapie, 15, 137–144.
Hennings, J. M. (2021). Das Verstärkermodell der Suizidalität: Chronische Suizidalität bei der
Borderline-Persönlichkeitsstörung verstehen und behandeln. Verhaltenstherapie, 31(4),
285-296.
Henrich, G., & Herschbach, P. (1990). Fragen zur Lebenszufriedenheit-Module (FLZ-M). Mün-
chen: HeHe.
Höcker, A., Engberding, M., & Rist, F. (2013). Prokrastination. Ein Manual zur Behandlung
des pathologischen Aufschiebens. Göttingen: Hogrefe.

37
Hüther, G. (2012). Was wir sind und was wir sein könnten. Ein neurobiologischer Mutmacher.
Frankfurt a. M.: Fischer.
Jannsen, J., & Laatz, W. (2013). Statistische Datenanalyse mit SPSS. Eine anwendungsorien-
tierte Einführung in das Basissystem und das Modul exakte Tests (8. überarb. Aufl.).
Berlin: Springer Gabler.
Kaluza, G. (2015). Stressbewältigungstraining. In M. Linden & M. Hautzinger (Hrsg.), Verhal-
tenstherapiemanual. Psychotherapie: Praxis (8. Aufl., S. 417-422). Berlin: Springer.
Kanfer, F. H., & Saslow, G. (1969). Behavioral diagnosis. In C. M. Franks (Ed.), Behavior
therapy: Appraisal and status. New York: McGraw-Hill.
Kanfer, F. H., Reinecker H. & Schmelzer, D. (2000). Selbstmanagement-Therapie. (3. Aufl.).
Heidelberg: Springer.
Keating, C., Tilbrook, A. J., Rossell, S. L, Enticott, P. G., & Fitzgerald, P. B. (2012). Reward-
processing in anorexia nervosa. Neuropsychologia, 50, 567-575.
Kipke, I., Brand, H., Geiger, B., Pfeiffer-Gerschel, T., & Braun, B. (2015). Arbeitslosigkeit und
Sucht – Epidemiologische und soziodemographische Daten aus der Deutschen Sucht-
hilfestatistik 2007 – 2011, Sucht, 61(2), 81-94.
Klauer, T. (2012). Stressbewältigung. Grundlagen und Intervention. Psychotherapeut, 57, 263–
278.
Koch, A., Müller K., Naab, L., Dreier, M., & Boddin, M. (2016). Katamnese-Erhebung zur
stationären Rehabilitation bei Pathologischem Glücksspiel. Eine qualitative Addon-
Analyse. ZMVI1-2515DSM236. Bundesverband für stationäre Suchtkrankenhilfe e. V.
(buss). Abgerufen von https://www.suchthilfe.de/informationen/projektbericht-
gluecksspielkatamnese-addon-160530.pdf
Kuhl, J. (2001). Motivation und Persönlichkeit. Interaktionen psychischer Systeme. Göttingen:
Hogrefe.
Lindenmeyer, J. (2005). Alkoholabhängigkeit (2. Aufl.). Reihe: Fortschritte der Psychotherapie,
Bd. 6. Göttingen: Hogrefe.
Lindenmeyer, J. (2018). Rückfallprävention. Lehrbuch der Verhaltenstherapie, Band 1: Grund-
lagen, Diagnostik, Verfahren und Rahmenbedingungen psychologischer Therapie, 617-
640.
Lorains, F. K., Cowlishaw, S., & Thomas, S. A. (2011). Prevalence of comorbid disorders in
problem and pathological gambling: Systematic review and meta-analysis of population
surveys. Addiction, 106, 490–498.
Mackinnon, S. P., Lambe, L., & Stewart, S. H. (2016). Relations of five-factor personality do-
mains to gambling motives in emerging adult gamblers: A longitudinal study. Journal
of Gambling Issues, 34, 179–200.
Marchica, L. A., Keough, M. T., Montreuil, T. C., & Derevensky, J. L. (2020). Emotion Regu-
lation Interacts with Gambling Motives to Predict Problem Gambling Among Emerging
Adults. https://doi.org/10.1016/j.addbeh.2020.106378
Marlatt, G. A. (1985). Relapse prevention: theoretical rational and overview of the model. In
G. A. Marlatt & J. R. Gordon (Eds.), Relapse prevention: Maintance strategies in the
treatment of addictive behaviours (pp. 3–70). New York: Guilford Publications.
Martínez-Vispo, C., Martínez, Ú., López-Durán, A., Fernández del Río, E., & Becoña, E.
(2018). Effects of on substance use and depression: a systematic review. Substance
Abuse Treatment, Prevention, and Policy, 13, 36. https://doi.org/10.1186/s13011-018-
0173-2
Meshesha, L. Z., Dennhardt, A. A., & Murphy, J. G. (2015). Polysubstance use is associated
with deficits in substance-free reinforcement in college students. Journal of Studies on
Alcohol and Drugs, 76(1), 106–16. https://www.ncbi.nlm.nih.gov/pubmed/25486399
Meyer, G. (2017). Theoretische Erklärungsansätze zur Entstehung und Aufrechterhaltung des
glücksspielbezogenen Suchtverhaltens. In G. Meyer & M. Bachmann, Spielsucht.

38
Ursachen, Therapie und Prävention von Glücksspielbezogenem Suchtverhalten (4.
vollst. überarb. Aufl., S. 131–168). Heidelberg: Springer.
Milosevic, A., & Ledgerwood, D. M. (2010). The subtyping of pathological gambling: A com-
prehensive review. Clinical Psychology Review, 30, 988–998.
Monteleone, A. M., Castellini, G., Volpe, U., Ricca, V., Lelli, L., Monteleone, P., et al., (2018).
Neuroendocrinology and brain imaging of reward in eating disorders: a possible key to
the treatment of anorexia nervosa and bulimia nervosa. Prog. Neuropsychopharmacol.
Biol. Psychiatry ,80, 132–142.
Müller, K. W., Wölfling, K., & Giralt, S. (2013). Update Glücksspielsucht Pathologisches
Glücksspiel. Eine aktuelle Übersicht zu Verbreitung, Merkmalen und therapeutischer
Handhabung. Konturen, 6, 8–13.
Münte, T. (2008). Forscher machen das Belohnungssystem und seine Bedeutung bei Krankhei-
ten sichtbar. Ärzte Zeitung. Springer Medizin. https://www.aerztezeitung.de/Medi-
zin/Forscher-machen-das-Belohnungssystem-und-seine-Bedeutung-bei-Krankheiten-
sichtbar-358215.html
Nordbø, R. H. S., Espeset, E. M. S., Gulliksen, K. S., Skårderud, F., & Holte, A. (2006).
Themeaning of self‐starvation: Qualitative study of patients’ perception of anorexia ner-
vosa. International Journal of Eating Disorders, 39, 556– 564.
Petry, J. (2003). Glücksspielsucht. Entstehung, Diagnostik und Behandlung. Göttingen: Ho-
grefe.
Petry, N. M. (2018). Gambling and substance abuse. In I. Gebhardt & S. Korte (Hrsg.), Glücks-
spiel. Ökonomie, Recht, Sucht (2. vollst. überarb. Aufl., S. 881-896). Berlin: De Gruyter.
Rumpf, H.-J., Hapke, U., & John, U. (2001). LAST. Lübecker Alkoholabhängigkeits- und -miss-
brauchs-Screening-Test. Göttingen: Hogrefe.
Satow, L. (2012). Stress- und Coping-Inventar (SCI). Testmanual und Normen. Abgerufen von
http://www.drsatow.de/tests/stress-und-coping-inventar.html
Schäfer, A., Vaitl, D., & Schienle, A. (2010). Regional grey matter volume abnormalities in
bulimia nervosa and binge‐eating disorder. Neuroimage, 50, 639– 643.
Sharpe, L. (2002). A reformulated cognitive-behavioral model of problem gambling: A biopsy-
chosocial perspective. Clinical Psychology Review, 22, 1–25.
Starke, R., & Müller, A. (2021). Verhaltenssüchte. Psychotherapeut, 66(2), 91-96.
Steinglass, J. E., Figner, B., Berkowitz, S., Simpson, H. B., Weber, E. U., & Walsh, B. T.
(2012). Increased capacity to delay reward in anorexia nervosa. Journal of the Interna-
tional Neuropsychological Society, 18, 773– 780.
Stewart, S. H. & Zack, M. (2008). Development and psychometric evaluation of a three-dimen-
sional Gambling Motives Questionnaire. Addiction, 103(7), 1110-1117.
Tritt, K., von Heymann, F., Zaudig, M., Probst, T., Loew, T., Klapp, B., … Bühner, M. (2006).
ICD-10-Symptom-Rating (ISR) Fragebogen. Abgerufen von http://www.iqp-on-
line.de/index.php?page=downloads/ISR_Standard_2- 0_2009%20(1).pdf
Tritt, K., von Heymann, F., Zaudig, M., Zacharias, I., Söllner, W., & Loew, T. (2008). Entwick-
lung des Fragebogens »ICD-10-Symptom-Rating« (ISR). Zeitschrift für Psychosomati-
sche Medizin und Psychotherapie, 54(4), 409–418.
Tritt, K., von Heymann, F., Zaudig, M., Söllner, W., Klapp, B., Loew, T., & Bühner, M. (2010).
Der Fragebogen ICD-10-Symptom-Rating (ISR) Kurzdarstellung der Normierung. Ab-
gerufen von http://www.iqp-online.de/index.php?page=download
Umberg, E. N., Shader, R. I., Hsu, L. K., & Greenblatt, D. J. (2012). From disordered eating to
addiction: the ‘food drug’ in bulimia nervosa. J Clin Psychopharmacol, 32, 376– 389.
Vaughan, E. L., Corbin, W. R., & Fromme, K. (2009). Academic and social motives and drink-
ing behavior. Psychology of addictive behaviors, 23(4), 564–576.
https://doi.org/10.1037/a0017331

39
Wilson, R. P., Colizzi, M., Bossong, M. G., Allen, P., Kempton, M., & Bhattacharyya, S. (2018).
The neural substrate of reward anticipation in health: a meta-analysis of fMRI findings
in the monetary incentive delay task. Neuropsychology review, 28, 496-506.
Wölfling, K., Müller, K. W., Giralt, S., & Beutel, M. E. (2011). Emotionale Befindlichkeit und
dysfunktionale Stressverarbeitung bei Personen mit Internetsucht. Sucht, 57(1), 27-37.