Fachbereich Psychologie
Action Control in ADHD Children:
Do Implementation Intentions Improve Self- Regulation?
Dissertationsschrift
zur Erlangung des akademischen Grades Doktor der Naturwissenschaften
Vorgelegt im Juli 2005 von Caterina Gawrilow
Erstgutachter: Prof. Peter M. Gollwitzer Zweitgutachterin: Prof. Brigitte Rockstroh
Termin der mündlichen Doktorprüfung: 29. September 2005
CONTENTS
Danksagung 1
Zusammenfassung Deutsch 2
Abstract English 5
Abbreviations 7
1. INTRODUCTION 8
1.1 PHENOMENOLOGY OF ADHD 8
1.1.1 Criteria for Diagnosing ADHD According to DSM-IV and ICD-10 8
1.1.2 Symptoms 9
1.1.3 Development of the Phenomenology 10
1.1.4 Comorbid Disorders 11
1.1.5 Epidemiology 11
1.1.6 Summary 12
1.2. CURRENT CONCEPTS ON THE ETIOLOGY OF ADHD 12
1.2.1 Genetic Factors 12
1.2.2 Environmental Risk and Protective Factors 13
1.2.3 Neurological Factors 14
1.2.4 Performance of ADHD Children in Executive Function Tasks 15 1.2.5 Summary and Introduction to Action Control Research 19 1.3 ACTION CONTROL IN CHILDREN AND ADHD CHILDREN 20 1.3.1 Definition of Action Control and Self-Regulation 20 1.3.2 Empirical Evidence Concerning Self-Regulation in Children 20 1.3.3 Empirical Evidence Concerning Self-Regulation in ADHD Children 23
1.3.4 Summary 24
1.4 ACTION CONTROL VIA IMPLEMENTATION INTENTIONS 25
1.4.1 The Model of Action Phases 25
1.4.2 Implementation Intentions as a Useful Self-regulatory Tool (Theoretical Approach)
27
1.4.3 Effects of Implementation Intentions (Empirical Evidences) 28
1.4.4 Implementation Intentions in Clinical Populations 29
1.4.5 Summary and Conclusion 30
2. STUDIES 31
2.1 STUDY 1: INHIBITION OF UNWANTED RESPONSES BY IMPLEMENTATION INTENTIONS IN CHILDREN WITH ADHD
31
2.1.1 Overview 31
2.1.2 Method 32
2.1.3 Results 37
2.1.4 Discussion 39
2.2 STUDY 2: INTERACTION OF MEDICATION WITH MPH AND IMPLEMENTATION INTENTIONS IN ADHD CHILDREN
41
2.2.1 Overview 41
2.2.2 Method 42
2.2.3 Results 44
2.1.4 Discussion 46
2.3 STUDY 3: DO IMPLEMENTATION INTENTIONS SUPPORT CHILDREN WITH AND WITHOUT ADHD IN THE DELAY OF GRATIFICATION?
47
2.3.1 Overview 47
2.3.2 Method 47
2.3.3 Results 51
2.3.4 Discussion 53
3. GENERAL DISCUSSION 55
3.1 LIMITATIONS OF PRESENT STUDIES AND GENERAL IMPLICATIONS FOR FUTURE RESEARCH
55
3.2 IMPLICATIONS FOR ADHD RESEARCH 57
3.2.1 Implications for Executive Function Research in ADHD Children 57 3.2.2 Implications for Action Control Research in ADHD Children 58
3.2.3 Summary 58
3.3. IMPLICATIONS FOR IMPLEMENTATION INTENTION RESEARCH 59 3.3.1 Theoretical Implications for the Concept of Implementation Intentions 59 3.3.2 Further Data Concerning Implementation Intention Effects in ADHD Children 60
3.3.3 Summary 62
3.4 POTENTIAL APPLICATIONS 62
3.4.1 Comparison with Self-Instruction Research 62
3.4.2 Comparison with Current Approaches in ADHD Therapy 64 3.4.3 Ideas for a Transfer of Implementation Intentions into ADHD Therapy 67
3.4.4 Summary 68
3.5 SUMMARY AND CONCLUSION 78
4. REFERENCES 70
5. APPENDIX 88
5.1 DESCRIPTION OF CPT AND SST 89
5.2 MATERIAL FOR STUDY 1(IN GERMAN) 91
5.2.1 Instructions 92
5.2.2 Questionnaires 103
5.3 MATERIAL FOR STUDY 2 (IN GERMAN) 125
5.3.1 Instructions 126
5.3.2 Questionnaires 135
5.4 MATERIAL FOR STUDY 3 (IN GERMAN) 142
5.4.1 Instructions 143
5.4.2 Questionnaires 156
Danksagung / Acknowledgement
Hiermit möchte ich mich bei allen bedanken, die zum Gelingen dieser Arbeit beigetragen haben! / I would like to thank all, who contributed to the
success of this dissertation!
Vor allem möchte ich mich bei meinem Doktorvater Prof. Peter M.
Gollwitzer für die großartige Unterstützung in den letzten zweieinhalb Jahren bedanken. Frau Prof. Brigitte Rockstroh danke ich herzlich für die Übernahme der Zweitbegutachtung dieser Arbeit.
Frau Dr. Birgit Simon sage ich „Dankeschön“ ich für die kreativen Ideen, die zur Entstehung dieser Dissertation nicht unwesentlich beigetragen haben.
Ohne Dr. Wilfried Kratzer und das Team vom SPZ in Konstanz hätte ich die Studien nicht durchführen können. Darum danke ich für das große
Vertrauen und die Unterstützung! In diesem Zusammenhang bedanke ich mich auch bei allen teilnehmenden Kindern und Eltern.
Dr. John Schureman danke ich für die Unmengen an Informationen zum Thema „ADHS und Selbstregulation“.
Ein besonderer Dank geht auch an die fleißigen Korrekturleser Aneka, Gabriela, Georg, Kyrene, Tanya und Sean und an meine „Mit-Büro-Kollegin“
Verena.
Noch ein Extra-Danke an Georg für das Programmieren der Experimente.
Den ADHS-interessierten-Diplomanden: Nadine, Wiebke, Miriam, Maria- Luisa, Peter und Diana und den an den ADHS Studien beteiligten Hiwis: Lilu, Nadine, Natalie, Sonja und Tanja danke ich für die tolle Zusammenarbeit.
Vitali danke ich für den vielseitigen Beistand in den letzten Jahren! Und
natürlich danke ich auch meinen Eltern.
Zusammenfassung
Das vorliegende Dissertationsprojekt zielte darauf ab, die folgende Frage zu beantworten: Ist eine Beeinflussung von ADHS (Aufmerksamkeitsdefizit-
/Hyperaktivitätsstörung)-typischem Verhalten durch Strategien, die die Selbstregulation verbessern, möglich? Mit anderen Worten: Sind ADHS Kinder fähig, Pläne im „wenn- dann“ Format (Vorsätze), zu fassen und wirken diese Pläne in der Art und Weise, dass die Selbstregulationsfähigkeiten von ADHS Kindern verbessert werden können?
ADHS Kinder zeigen vielfältige Handlungskontrolldefizite. Zum Beispiel stellt es ein Problem für sie dar, bereits gelernte Stimulus-Reaktions-Assoziationen zu inhibieren, oder Belohnungsverzögerungsverhalten zu zeigen. ADHS Kinder haben weiterhin Schwierigkeiten, Ablenkungen zu widerstehen oder flexibles Verhalten zu zeigen. Vorsätze (implementation intentions oder wenn-dann Pläne) verringern solche Handlungskontrollprobleme nachweislich in Stichproben gesunder Erwachsener. Das Hauptanliegen der vorliegenden Arbeit war es die Effektivität von Vorsätzen bei ADHS Kindern zu explorieren.
Insgesamt nahmen 98 Jungen mit ADHS und 72 Jungen ohne ADHS
(Kontrollgruppe) an drei verschiedenen Studien teil. Konkret wurden die Effekte von Vorsätzen in drei verschiedenen experimentellen Paradigmen überprüft: (a) ein go/no- go Paradigma (30 ADHS Kinder im Alter von 10.9 Jahren [SA = 1.4] und 28
Kontrollkinder im Alter von 11.5 Jahren [SA = 1.1]), (b) ein ähnliches go/no-go
Paradigma mit zusätzlicher Variation der Methylphenidat-Einnahme (20 ADHS Kinder im Alter von 11.15 Jahren [SA = 1.65]) und (c) ein Belohnungsverzögerungsparadigma (47 ADHS Kinder im Alter von 10.34 Jahren [SD = 1.59] und 40 Kontrollkinder im Alter von 11.27 Jahren [SD = 1.44]).
In allen drei Studien mussten die Kinder Aufgaben am Computer bearbeiten. (a) In der ersten Studie wurde eine klassische Diskriminationsaufgabe mit einer
eingebetteten go/no-go Aufgabe kombiniert. Die Kinder mussten auf verschiedene Bildstimuli reagieren (Tiere, Transportmittel) – dies geschah per Tastendruck
(Diskriminationsaufgabe). Weiterhin hatten die Kinder die Aufgabe, diesen Tastendruck
zu inhibieren, sobald ein bestimmtes Signal am Computer erschien (go/no-go task). In
der Zielintentionsbedingung hatten die Kinder das Ziel: “Ich drücke niemals die Taste
für Bilder mit Ton“. Kinder der Vorsatzbedingung fassten sich zusätzlich folgenden
wenn-dann Plan: “Und immer wenn ein Ton kommt, dann drücke ich nicht auf die Taste“. (b) In der zweiten Studie mussten die Kinder eine ähnliche
Diskriminationsaufgabe mit eingebetteter go/no-go Aufgabe wie in Studie 1 bearbeiten.
Zusätzlich wurde die Medikation der Kinder mit einem Psychostimulanz
(Methylphenidat) variiert: die Kinder durchliefen zunächst 20 Blöcke à 30 Trials ohne Medikation, danach nahmen sie die Medikamente unter Aufsicht ihrer Eltern ein, und nach weiteren 45 Minuten wurden die 20 Blöcke à 30 Trials nun mit Medikation wiederholt. (c) In der dritten Studie wurde eine Wahlaufgabe verwendet. Die Kinder mussten sich zwischen einer sofortigen, kleinen Belohnung (rote Bilder mit wenigen Punkten assoziiert, die aber sofort verteilt werden) und einer verzögerten, großen
Belohnung (blaue Bilder mit mehr Punkten assoziiert, die erst nach 30 Sekunden verteilt werden). In der Kontrollbedingung erhielten die Kinder lediglich die Instruktionen für die Aufgabe. In der Zielintentionsbedingung hatten die Kinder das Ziel “Ich will mir so viele Punkte wie möglich holen” und in der Vorsatzbedingung fassten sich die Kinder zusätzlich den wenn-dann Plan: “Und immer wenn ein blauer Gegenstand kommt, dann klicke ich darauf“ oder “Und immer wenn ein roter Gegenstand kommt, dann warte ich auf den blauen”.
Vorsätze zeigten sich generell als ein effektiveres selbstregulatorisches
Instrument als Zielintentionen: (a) In Studie 1 konnten ADHS Kinder mit Vorsatz ihre Reaktionen signifikant besser inhibieren als ADHS Kinder, die sich nur ein Ziel gefasst hatten, t (28) = 4.05, p < .001. (b) In Studie 2 zeigte sich eine Interaktion der
Zielbedingung (Zielintention vs. Vorsatz) und der Medikation (mit Medikation vs. ohne Medikation), F (1, 19) = 5.78, p < .05. (c) In Studie 3 profitierten ADHS Kinder von Vorsätzen in der Belohnungsverzögerungsaufgabe. Wenn ADHS Kinder Vorsätze gebildet hatten, warteten sie häufiger auf die größere Belohnung im Vergleich zu bloßen Kontrollinstruktionen oder Zielintentionen, F (2, 86) = 3.72, p < .05.
Insgesamt zeigten die Ergebnisse der vorliegenden Experimente, dass Vorsätze im Vergleich zu Zielintentionen ADHS Kindern helfen können, ihr Defizit
auszugleichen, während sie Aufgaben bearbeiten, die eine effektive Handlungskontrolle
erforderlich machen. Diese Ergebnisse werden mit Hinsicht auf die Vorsatztheorie
interpretiert (Gollwitzer, 1999): Vorsätze wandeln die top-down Handlungskontrolle
(z.B. Kontrolle durch Ziele) in bottom-up Handlungskontrolle (z.B. Kontrolle durch
spezifische Stimuli). Nachfolgestudien innerhalb dieser Forschungsrichtung sollten
weitere Handlungskontrollprobleme ebenso wie die postulierten Mechanismen der
gesteigerten Handlungskontrolle durch Vorsätze untersuchen.
Abstract
The present dissertation aimed at answering an important research question with support of three experimental studies: Is it possible to reduce typical Attention-
Deficit/Hyperactivity-Disorder (ADHD) symptom behavior through strategies that improve intentional self-regulation? Thus, are ADHD children able to form if-then plans (implementation intentions) and do these plans enhance the self-regulation skills of ADHD children?
Children with ADHD usually show various action control problems. For instance, they find it very hard to inhibit a previously learned stimulus-response association, often fail to delay gratification, and have difficulties in resisting
distractions. Implementation intentions (i.e., if-then plans) alleviate such problems of action control in healthy adult samples. Therefore, the main objective in the present project was to examine the effectiveness of implementation intentions in a population of children with ADHD.
In sum 98 boys with ADHD and 72 boys without ADHD (control group) participated in three different studies addressing the above described research topics.
The effects of implementation intentions were examined in three studies using different experimental paradigms: (a) a go/no-go paradigm with a sample of 30 ADHD children (age: M = 10.9, SD = 1.4) and 28 control children (age: M = 11.5 years, SD = 1.1), (b) a similar go/no-go paradigm with an additional variation of the medication with
psychostimulants in a sample of 20 ADHD children (age: M = 11.15 years, SD = 1.65 years), and (c) a delay of gratification paradigm with 47 ADHD children (age: M = 10.34 years, SD = 1.59) and 40 control children (age: M = 11.27 years, SD = 1.44).
All of the presented studies required to perform tasks on a computer. (a) The experimental setup of the first study used a classic discrimination task with an embedded go/no-go task. The children had to respond to different types of stimuli (animals, means of transportation) by pressing respective keys (discrimination task).
Furthermore, they had to inhibit these responses whenever the computer produced a
certain sound (go/no-go task). In the goal intention condition, the children were
assigned the goal: “I will never press a key for pictures that are accompanied by a
sound”. Children in the implementation intention condition received an additional if-
then plan: “And whenever the computer produces a sound, then I will not press any
key”. (b) In the second study, ADHD children had to accomplish a similar go/no-go task as in Study 1. Additionally, the medication of the children with psychostimulants was varied: First, the children worked on 20 blocks containing 30 trials without medication, after which they took the medication under supervision of their parents.
Second, 45 minutes after taking the medication, 20 blocks containing 30 trials were repeated. (c) The third study used a choice response task. The children had to choose between an immediate, small (red pictures associated with few but immediate points) and a delayed, big gratification (blue pictures associated with many but delayed points).
In the control condition, the children only received instructions to perform the task. In the goal condition, the children were assigned the goal “I will try to earn as many points as possible”, and in an implementation intentions condition, the children received the additional if-then plan: “And if a blue picture appears, then I will click on it” or “And if a red picture appears, then I will wait for the blue one”.
Implementation intentions generally turned out to be a more effective self- regulatory tool than mere goals: (a) In Study 1, ADHD children with an implementation intention inhibited their responses significantly better than ADHD children with mere goals, t (28) = 4.05, p < . 001. (b) In Study 2, an interaction between the type of
intention (goal vs. implementation intention) and the medication status (with vs. without MPH) indicated that the medication with MPH and a volitional strategy seem to be most effective in combination, F (1, 19) = 5.78, p < .05, and (c) In Study 3, ADHD and control children benefited from implementation intentions in delaying gratification.
When implementation intentions had been formed, they waited more often for the bigger gratification compared to control and goal participants, F (2, 86) = 3.72, p < .05.
Overall, the results of these experiments show that implementation intentions, compared to goal intentions, help ADHD children to compensate for their action control deficits when working on tasks that require effective action control. The findings are interpreted by referring to implementation intentions theory (Gollwitzer, 1999):
Implementation intentions are thought to convert the top-down control of action (i.e., control by goals) into bottom-up control of action (i.e., control by specified stimuli).
Future directions in this line of research are recommended to investigate further action
control deficits, as well as the postulated mechanism of increased action control by
implementation intentions.
Abbreviations
ADHD Attention Deficit Hyperactivity Disorder APA American Psychological Association CPT Continuous Performance Task CT Computerized Tomography CTRS Conner’s Teacher Rating Scale DAT Dopamine Transporter Gene DGT Delay of Gratification Test DRD4 Dopamine D4 Receptor Gene
DSM-IV Diagnostic and Statistical Manual of Mental Disorders, 4
thEdition DZ Dizygotic
EEG Electroencephalography ERP Event-Related Potential
ICD-10 International Classification of Diseases, 10
thEdition MEG Magnetoencephalography
MPH Methylphenidate
MRI Magnetic Resonance Imaging MZ Monozygotic
PET Positron Emission Tomography PFC Prefrontal Cortex
S Seconds
SAT Scholastic Aptitude Test SCT Sluggish Cognitive Tempo SET Six Elements Test
SST Stop Signal Task
TOH Tower of Hanoi Task
TRF Teachers Report Form
WCST Wisconsin Card Sorting Test
WM Working Memory
1. INTRODUCTION
Attention-Deficit/Hyperactivity Disorder (ADHD)
1is the most recent diagnostic label for children or adolescents showing problems with attention, impulsivity, and overactivity. It is repeatedly described as a disorder of intention (Barkley, 1997a;
Barkley, 2004). This dissertation was therefore motivated by the following main question: Is it possible to reduce ADHD symptom behavior through strategies that improve intentional strategies?
Within this introduction, the phenomenology of ADHD, current concepts concerning the etiology of ADHD with a main focus on neuropsychological studies, action control skills in children with and without ADHD, and the action control via implementation intentions are reviewed.
1.1 PHENOMENOLOGY OF ADHD
1.1.1 Criteria for Diagnosing ADHD According to DSM-IV and ICD-10
The up-to-date diagnostic criterion are defined in the Diagnostic and Statistical Manual of Mental Disorders DSM-IV (American Psychiatric Association [APA], 1994) and International Classification of Diseases ICD-10 (World Health Organization
[WHO], 1991). According to the DSM-IV, the following different types of ADHD can be diagnosed: Attention-Deficit/Hyperactivity Disorder Predominantly Inattentive Type (314.00), Attention-Deficit/Hyperactivity Disorder Combined Type (314.01), Attention- Deficit/Hyperactivity Disorder Predominantly Hyperactive-Impulsive Type (314.01), and Attention-Deficit/Hyperactivity Disorder not otherwise specified (314.9).
Following the DSM-IV, the core symptoms of ADHD are: inattention,
hyperactivity-impulsivity, and impulsivity. The symptoms have to be present for half a year, some of them have to start before the age of seven, must be present in at least two types of situations (e.g., school, home), have to be inadequate for the developmental status of the children, and have to produce significant impairments in social or academic
1 For ease of exposition in this dissertation, the term ADHD is used constantly as an abbreviation for Attention-Deficit/Hyperactivity Disorder according to the DSM-IV subtypes of ADHD (Predominantly Inattentive Type, Combined Type, Predominantly Hyperactive-Impulsive Type) and the ICD-10 category of Hyperkinetic Disorder.
functions. The validity of the DSM-IV diagnosis was supported in a recent study (Lahey et al., 2004)
2.
According to the ICD-10, the hyperkinetic disorder (F90) can be diagnosed and characterized as beginning during the first five years of the child’s development, and displaying a combination of overactive behavior with inattention and absence of persistence as a behavior that is independent of situations and stable over a period of time. The core symptoms are impaired attention and overactivity. A hyperkinetic disorder of social behavior (F90.1) can be diagnosed when both criteria for a
hyperkinetic disorder and for a disorder of social behavior are fulfilled. Furthermore, it is possible to diagnose a miscellaneous hyperkinetic disorder (F90.8) or a not specified hyperkinetic disorder (F90.9).
1.1.2 Symptoms
Inattention. Poor concentration in ADHD children is reflected in failing to pay close attention to detail or careless errors in schoolwork, work or other activities, problems in paying attention to tasks or whilst playing, not listening when being told something, experiencing trouble in organizing activities and tasks, disliking or avoiding tasks that involve sustained mental effort (e.g., homework, schoolwork), forgetting or losing materials needed for various activities (e.g., assignments, books, pencils, tools, toys), distraction by extraneous stimuli, and forgetfulness. Furthermore, DSM-IV inattention is related to sluggish cognitive tempo (SCT). Hartman, Willcutt, Rhee, and Pennington (2004) analyzed a community sample with regard to ADHD symptoms, parent and teacher ratings of ADHD, and SCT items. They reasoned that SCT seemed to be an internally consistent construct that is significantly associated with inattention, meaning that children meeting the criteria for the inattentive type exhibit more SCT symptoms compared to children meeting the criteria for the combined subtype.
Hyperactivity. Overactivity is present when children are squirming in their seat or fidgeting, inappropriately leaving their seats, inappropriately running or climbing, being troubled to play quietly or engage in leisure activity, appearing to be driven or "on
2 The authors developed an interview covering the symptoms of anxiety, depression, inattention, and disruptive behavior used in the DSM-IV, ICD-10, and several implicit taxonomies and used principal factor analysis in a representative sample of 1,358 children and adolescents ranging in age from 4 to 17 years.
the go", and excessively talking. Numerous scientific studies attest that ADHD children are more active and restless than other children throughout the day and even during their sleep (Teicher, Ito, Glod, & Barber, 1996).
Impulsivity. Impulsiveness can be seen in answering questions before they have been asked in full, having trouble awaiting one’s turn, and interrupting others.. The full complexity of this symptom was demonstrated by Salbach, Huss and Lehmkuhl (2002) in a study that measured impulsivity and hyperactivity in ADHD children using several instruments. They showed a significant difference between impulsive behavior and hyperactivity. Further, they found that the correlations of numerous tools that asses impulsive behavior (e.g., Continuous Performance Test CPT, Delay of Gratification Test DGT, questionnaires for teachers: Teachers Report Form TRF, Conner’s Teacher Rating Scale CTRS) were not significant. In consequence, the authors push for further research that will be able to clearly operationalize impulsivity in ADHD.
1.1.3 Development of the Phenomenology
Although nearly all of the affected children are only diagnosed with ADHD after
starting school the ADHD symptoms can be traced back to infancy. ADHD babies show
an unbalanced temper, feeding and sleeping problems and an increased activity level
(Döpfner, Frölich, & Lehmkuhl, 2000). At kindergarten age ADHD presents itself in
short-tempered moods, decreased staying power, hyperactive behavior, worse social
competence (Barkley, 1998). Because the increased requirements in school often lead to
enormous stress for ADHD children, the situation grows even more acute after school
enrollment. The affected children show a decreased attention span and impulsive-
hyperactive behavior at school, what leads to difficulties with achievement at school
and problems with peers. During the teenage years, the hyperactivity decreases and the
ADHD problematic shifts to only attention deficit and impulsivity only, which also
causes difficulties in school and with peers. During this time-period, the likelihood that
ADHD children will develop risky behavior, such as substance abuse or dangerous
driving is extremely high (Barkley, 2004). About one-third to two-thirds of the affected
children show persistent symptoms until adulthood (Steinhausen, 2000).
1.1.4 Comorbid Disorders
Between 50% and 80% of children with ADHD also meet diagnostic criteria for other disorders (Tannock, 1998). The rates of comorbidity vary according to the sample studied and the method that is used for measurement of the symptoms. The most
frequently observed comorbidity is between ADHD and other disruptive behavior disorders. Studies suggest that 54% to 67% of ADHD children and adolescents meet full diagnostic criteria for Oppositional Defiant Disorder (Barkley, Du Paul, &
McMurray, 1990). But comorbidity between ADHD and internalizing disorders is also common: ADHD children are rated as having more symptoms of anxiety, depression, dysthymia and low self-esteem than normal children (Barkley, 1998; Baxter & Rattan, 2004). Finally, a comorbidity between ADHD and developmental learning disorders often exists. Numerous studies revealed that ADHD children show worse performance in school than children without ADHD (Biederman, Newcorn, & Sprich, 1991; Jensen, Martin, & Cantwell, 1997).
1.1.5 Epidemiology
ADHD is one of the most common psychiatric disorders in childhood and boys are affected more frequently than girls (ratios from 1:3 to 1:9 depending on the study) (Barkley, 1998). Estimations of the prevalence of ADHD in childhood and adolescence are variable, depending on, for instance, the diagnostic criterion (DSM-IV or ICD-10) and instruments used. Current estimations vary between 1% and 10% (Barkley, 1998) with a reliable center around 2% to 5% (APA, 1994; Sobanski & Alm, 2004).
Because of the predominance of American research concerning ADHD, the question of whether ADHD is an American condition arise (Faraone, Sergeant,
Gillberg, & Biederman, 2003). However, analyses of 50 studies (identified by the use of
a MEDLINE search for the years 1982 to 2001) showed that the prevalence of ADHD
children is at least as high in many non-US children as in US children, with the highest
rates being found when using DSM-IV diagnoses (Faraone et al., 2003). Therefore,
ADHD seems to be independent from cultural influences.
1.1.6 Summary
ADHD is a chronic disorder that affects 3-5% of children and adolescents, independent of culture but dependent on gender. The affected children show inattentive, hyperactive, and impulsive behavior that manifold into problems at home, at school, with parents, teachers and peers. In many cases ADHD related problems continue through adulthood with some changes in symptoms. Behavior that leads to risks in health is particularly problematic.
1.2 CURRENT CONCEPTS ON THE ETIOLOGY OF ADHD
The knowledge concerning the etiology of ADHD has been increasing rapidly due to recent studies investigating the underlying physiological and neurological mechanisms. ADHD was, for instance, examined with cerebral blood flow studies, studies of electrical brain activity, studies using neuropsychological tests sensitive to frontal lobe dysfunction, and neuroimaging studies using PET and MRI (Durston, 2003). Furthermore, genetic research concerning ADHD has contributed various studies to the etiology of ADHD over the last years (Lynn et al., 2005).
1.2.1 Genetic Factors
Family aggregation studies have shown a higher prevalence of psychopathology in parents and relatives of children with ADHD (Faraone & Doyle, 2001). Between 10- 35 % of the family members of ADHD children were found to have the disorder likewise. The risk for siblings is approximately 32% (Biederman et al., 1992). Another line of evidence of genetic involvement in ADHD has come from research into
adoption. Biederman and Faraone (2002) reported higher rates of hyperactivity in the biological parents of ADHD children than in the adoptive parents of such children.
Studies of twins provide more evidence for a genetic contribution to ADHD. Goodman and Stevenson (1989) showed a higher concordance for ADHD in monozygotic (MZ) than in dizygotic (DZ) twins. In the Minnesota Twin Family Study (Sherman, Iacono, &
McGue, 1997), teacher ratings and maternal interviews concerning the behavior of children were obtained for 194 pairs of MZ twins and 94 pairs of DZ twins. Results indicated that mother ratings showed higher heritability than teacher ratings.
Particularly, mother ratings yielded a heritability of 91% (impulsivity/hyperactivity) and
69 % (inattention), whereas teacher ratings produced a heritability of 69 % (impulsivity/hyperactivity) and 39 % (inattention).
Another approach to the etiology of ADHD is molecular genetic research (Biederman & Faraone, 2002; Faraone & Doyle, 2001). This line of research applies two main methods: The first approach is, the genome scan which examines all chromosomal locations without any prior specific hypothesis; the second is the
candidate gene approach which examines one or more genes based upon some theories and hypotheses. Results showed that there are at least 20 candidate genes (e.g., DRD4, Faraone, Doyle, Mick, & Biederman, 2001; DAT, Spencer, Biederman, & Wilens, 2000) of small effect that have been studied but none of them seem to be the major gene causing ADHD behavior. Furthermore, animal studies suggest the involvement of the brain dopamine pathway and its alteration in ADHD, however, there is no direct evidence to support this hypothesis (Shastry, 2004). Molecular genetic studies of ADHD in human beings have been ongoing for approximately 10 years and a small number of research projects include quantitative genetic analyses of large samples of families (Hebebrandt, 2004).
1.2.2 Environmental Risk and Protective Factors
The idea that certain foods (e.g., sugar, dyestuffs) might cause ADHD received a large amount of interest in the popular press. However, systematic studies showed that a specific nutrition or diet does not diminish ADHD symptom behavior (Conners, 1984;
Conners, Goyette, & Newman, 1980; Wolraich, Wilson, & White, 1995). In contrast to
the mostly negative studies of dietary factors, some toxins have been implicated in the
etiology of ADHD. It was shown that lead contamination can cause distractibility,
hyperactivity, restlessness, and lower intellectual functioning (Needleman, 1982). But
since many children with high lead exposure do not develop ADHD and many ADHD
children do not show lead contamination, this idea also cannot satisfactorily explain all
cases of ADHD (Biederman & Faraone, 2002). Further toxins that were associated with
causing ADHD are alcohol and tobacco. Moreover, the literature concerning ADHD
and pregnancy or delivery complications suggests that both can predispose children to
ADHD (Sprich-Buckminster, Biederman, Milberger, Faraone, & Krifcher Lehman,
1993). The association of maternal smoking during pregnancy and ADHD has been
extensively studied, showing that maternal smoking can damage the brain at critical times in the developmental process and therefore cause ADHD symptoms (Biederman
& Faraone, 2002).
There are also psychosocial risk factors for ADHD within the family
environment, for instance severe marital discord, low social class, large family size, paternal criminality, maternal mental disorder, and foster placement (Rutter, Cox, Tupling, Berger, & Yule, 1975). However, psychosocial adversity is believed to be a predictor for child development in general and not specific for the development of an ADHD (Biederman & Faraone, 2002). Accordingly, it is generally accepted that ADHD behavior frequently results in interaction difficulties with the psychosocial environment but that psychosocial difficulties do not cause ADHD (Döpfner, Frölich, & Lehmkuhl, 2000).
1.2.3 Neurological Factors
ADHD is suggested to be caused by weak frontal cortical inhibitory control (Biederman & Faraone, 2004; Satterfield & Dawson, 1971). Furthermore, the similarity between ADHD symptoms and those produced by lesions to the frontal lobe more generally and the prefrontal cortex specifically, has been repeatedly noted by
investigators (Max et al., 2005). Consequently, the research that examined neurological characteristics of ADHD children has been increasing in recent years (Willis & Weiler, 2005).
The research to date has identified a number of EEG correlates of ADHD which are promising in regard to an improved understanding of the brain dysfunction
underlying the disorder. For instance, Barry, Clarke, and Johnstone (2003) suggest that in terms of resting EEG, elevated relative theta power and reduced relative alpha and beta, together with elevated theta/alpha and theta/beta ratios, are most reliably
associated with ADHD. Concerning the event-related potentials (ERP), a complex range
of deficits has been linked to the disorder. For instance, differences in the preparatory
responses and in the auditory modality were found. In an overview of 18 structural
imaging studies (either CT or MRI) Biederman and Faraone (2002) revealed evidence
of structural brain abnormalities among ADHD patients. Smaller volumes in frontal
cortex, cerebellum, and subcortical structures are the most common results. Further,
possible neurotransmitter deficiencies have been suggested, mainly resting on the responses of ADHD children to differing drugs. To date, the evidence seems to point out a selective deficit in the availability of both, dopamine and norepinephrine (Barkley, 1998; Biederman & Faraone, 2002).
1.2.4 Performance of ADHD Children in Executive Function Tasks
Over the past years, various studies of the performance of ADHD children carrying out neuropsychological tasks have been published. The main results of these studies are: (a) ADHD children show impaired performance in different cognitive tasks that are associated with executive functions, (b) when compared with children without any psychiatric disturbances, ADHD children show the weakest performance
concerning executive functions, and (c) support of the hypothesis that ADHD is related to frontal-lobe dysfunction.
At the same time numerous studies have reported poorer performance of ADHD children in various executive functioning tasks (Fisher, Barkley, Smallish, & Fletcher, 2005; Seidman et al., 2005), the debate about the interpretation of these group
differences is very intense (Miyake, Friedman, Rettinger, Shah, & Hegarty, 2001;
Zelazo, Qu, & Müller, 2005). One explanation is that ADHD children have difficulties in the inhibition of responses (Barkley, 1997), while another approach deals with working memory (WM) deficits as vital in ADHD (Pennington, Bennetto, McAleer, &
Roberts, 1996; Willcutt, Pennington, Olson, Chhabildas, & Hulslander, 2005). Sonuga- Barke (2002) formulated a theory about delay aversion in ADHD; others suggest that the general derogation in executive functions explains the ADHD deficits (Scheres et al., 2004). In summary the discussion is about whether executive functions are one unified mechanism underlying various aspects of executive control or whether executive control consists of various distinctive but interactive components. Despite the progress in cognitive neuropsychological research “the field still lacks a compelling theory of executive functions” (Miyake, Friedman, Emerson, Witzki, & Howerter, 2000; p. 50).
In general, executive functions are important for the fulfilment of various demands
because these mental control processes enable self-regulation, self-control, and goal-
directed behavior. Executive functions can be regarded as including the processes
involved in the generation of plans and the direction of responding relative to goals.
Executive functions are mediated by the frontal lobes, more precisely by the prefrontal cortex (Zhu, 2004). Even though it is difficult to find unambiguous indicators of executive function or dysfunction, the following describes different possibilities to assess aspects that seem to be related with executive functions.
Inhibition. One component of executive functions is the inhibition of an inappropriate response. This performance is usually measured with Continuous
Performance Tests (CPT, Rosvold, Mirsky, Sarason, Bransome, & Beck, 1956; Nichols
& Waschbusch, 2004) and Stop Signal Tests (SST, Logan & Cowan, 1984; Oosterlaan, Logan, & Sergeant, 1998). Because both tasks were used in this dissertation as a combined measure (see Study 1 and 2), they are described in more detail in the appendix (5.1).
CPT derived measures predict the presence of most ADHD symptoms (Epstein, Erkanli, & Conners, 2003). Children with ADHD miss more targets and show more false alarms to nontargets than children without ADHD. Today, the CPT is a widely used clinical tool that is integrated in ADHD-focused neuropsychological test batteries.
It is a neuropsychological task that has been shown to differentiate ADHD children from children without ADHD.
The SST has also been used successfully in studying childhood ADHD.
Beginning with Schachar and Logan (1990), several studies have shown that children with ADHD have slower stop signal reaction times than normal comparison children (e.g., Oosterlaan & Sergeant, 1996; Pliszka, Borcherding, Sprattey, Leon, & Irick, 1997;
Schachar, Tannock, Marriott, & Logan, 1995). These findings have supported the idea that behavioral inhibition may be a core deficit in the development of child ADHD (Barkley, 1997b; Tannock, 1998; Quay, 1997). A meta-analysis showed consistent and robust response inhibition deficits in ADHD children in a Stop-Task (Oosterlaan, Logan, & Sergeant, 1998). Furthermore, ADHD children show significantly slower reaction times in go trials.
Error monitoring. Error recognition refers to the online detection of errors and
subsequent adjustment of performance. Error monitoring is evident in slowing of
responses following errors of speeded reaction time tasks, reasoning tasks, verbal
analogies, and memory search tasks (Rabbitt, 1966a, 1966b, 1968). It is more often
investigated and documented in adults than in children. Only a few studies deal with error monitoring in children.
It is well known that children with ADHD make more errors in executive functioning tasks than children without ADHD (e.g., in a time-reproduction task Bauermeister, Barkley, & Martínez, 2005). Sergeant and van der Meere (1988) determined that children without ADHD under high cognitive load following an error take their time to ensure that a correct response is given in the subsequent trial. This is not the case in trials with low cognitive load. Children with ADHD, show, irrespective of cognitive load, no response adjustment, a constant rate of processing and no slowing of reaction after an error occurred. Schachar et al. (2004) investigated error monitoring in ADHD children compared to normally developed peers in a stop task (Logan et al., 1997) and demonstrated that ADHD children slow down less than control children following nonstopped (error) responses. Furthermore, slowing after inhibition errors (error monitoring) was not correlated to response inhibition (latency of the stopping process).
Working memory. WM deficits are also well documented in ADHD children (Klingberg, Fernell, & Olesen, 2005). Current findings within a framework of
Baddeley`s model of WM (Baddeley, 1996) suggest that children with ADHD do not have generalized impairments in WM. ADHD children are able to rehearse verbal and spatial information in the same manner as healthy children but may have deficits in the central executive component of WM (Karatekin, 2004). To speak in Baddeley’s terms:
WM impairments of ADHD children are due to a dysfunction in the central executive component rather than in the verbal or spatial buffers or rehearsal processes. Thus, within the WM concept the module that is responsible for the coordination of multiple concurrent cognitive processes and for the strategic intentional and attentional control over goal-directed actions is disturbed in ADHD children. Further, the impairment of the central executive refers to frontal lobe deficits (Max et al., 2005).
Sense of time. Time perception deficits are found among ADHD children even when matching for working memory (Smith, Taylor, Rogers, Newman, & Rubia, 2002).
In a recent study, Bauermeister et al. (2005) found that ADHD children show larger
errors compared to control children in a time reproduction than in a time estimation
task. However, another research group demonstrated that children with ADHD were
more likely to overestimate the time taken for a test than children without ADHD but with a reading disorder. There were no group differences when the children were to judge when 30 seconds had elapsed, therefore, the group differences concerning time perception tasks are not consistent (McGee, Brodeur, Symons, Andrade, & Fahie, 2004).
Fluency. A further cognitive function highly correlated with executive functioning and attention capacity is the fluency of speech. This function is usually defined as the number of words produced within a restricted category and over a limited period of time (mostly 60 seconds). Two major categories of verbal fluency tasks can be distinguished: (a) semantic category fluency (SCF) which requires the recitation of examples of a given category and (b) initial letter fluency (ILF) which requires the generation of words beginning with a given initial letter.
Earlier research concerning the performance of ADHD children in fluency tasks was inconclusive (Hurks et al., 2004). Current research revealed no differences between ADHD and healthy children when the fluency tasks were analyzed with the normal, classical procedure. In contrast, it was shown that ADHD children performed less well than controls within the first 15 seconds of a complex ILF task (Hurks et al., 2004).
These results are suggested to indicate that ADHD children show a delay in the development of automated skills for processing abstract verbal information.
Set-shifting. The Stroop Interference Test (Stroop, 1935) is most often described as measuring the individuals ability to shift a cognitive set. Numerous versions of the Stroop task exist. In a meta-analysis Homack and Riccio (2004) showed that ADHD children exhibit consistently poorer performances when compared to children without ADHD and without any psychiatric diagnose on Stroop Tasks (Stroop, 1935). But the Stroop Task was not able to differentiate between ADHD children and children with other psychiatric disorders. That means poor performance in a Stroop task is not sufficient for an ADHD diagnosis.
Flexibility and perseveration. The Wisconsin Card Sorting Test (WCST) was
originally introduced as a test of problem-solving and decision-making (Berg & Grant,
1947; Grant & Berg, 1948). Nowadays, the WCST is also used to measure executive
functions like the tendency to perseverate. In a recent meta-analytic study Romine, Lee,
Wolfe, Homack, George, and Riccio (2004) found that ADHD children consistently
exhibit poorer performances in various dependent variables measured with the WCST.
Recent work by Schneikert (in preparation) also replicated that ADHD children have difficulties in performing the WCST.
Planning and multitasking. Shallice and Burgess (1991) emphasize that most neuropsychological tests are far away from and much different than the requirements of every day situations. Tests like the WCST have mostly only one task to solve, clear instructions, and a defined processing time. One test to measure complex planning behavior in the sense of multitasking situations is the Six Elements Test SET (Burgess, 2000). Clark, Prior, and Kinsella (2000) demonstrated that ADHD teenagers show significantly worse results in a SET than controls. ADHD children had difficulties developing strategies, and observing their own behavior. However, Stumpf (2004) could not replicate this difference between ADHD and control children in a German
ambulatory sample.
1.2.5 Summary and Introduction to Action Control Research
Different approaches explore the etiology of ADHD. Mostly, biologically and physiologically oriented models (e.g., genetic models) are the ones being investigated.
However, one promising approach is the neuropsychological approach, which describes ADHD as a disorder in executive functioning. The results concerning the measurement of executive functions in ADHD children are very heterogeneous. This might be due to the heterogeneity of the ADHD group and the variety of constructed tasks measuring executive functions. Thus, it seems more promising to look at the performance of ADHD children in specific tasks that assess various executive functions instead of concentrating on only one main explanatory deficit. That is also important because (a) the findings concerning different executive tasks are not consistent, and (b) some executive functions were shown to be separable.
What do executive functions and action control have in common? “Executive
functions are composed of the major classes of behavior toward oneself used in self-
regulation” (Barkley, 2001, p. 5). In other words: executive functions are self-directed
actions normally used in self-regulation. Therefore, the inhibition of a response is
necessary to show self-regulated behavior.
1.3 ACTION CONTROL IN CHILDREN AND ADHD CHILDREN
1.3.1 Definition of Action Control and Self-Regulation
Motivation in humans not only includes basic human needs but also action control. Present theories on action control illustrate the different requirements needed when a wish is to be transformed into an action (Gollwitzer, 1990; 1993). Consequently, action control or self-control is defined as self-regulation of goal pursuit. Thus, self- regulated, goal-directed behavior can be identified as behavior that is characterized with a high level of action control. Action control can be further understood as the conscious causal agency of people: people consider and reflect their actions in advance and therefore (have the feeling to) control their own actions. Intentions, beliefs, desires, and plans play a decisive role in this conscious causal agency (Wegner, 2002).
The understanding of self-regulation in goal pursuit in children has proven to be important for the development of children because the acquisition of self-control is a critical aspect in the socialization of children (Finkenauer, Engels, & Baumeister, 2005).
Mischel, Ayduk, & Mendoza-Denton (2003) reported that the self-control skill to delay gratifications in preschool age is correlated to various variables during adolescence. For instance, the time children can wait in experimental situations correlates to higher SAT scores and better (inter-)personal competencies (e.g., Shoda, Mischel, & Peake, 1990), whereby these positive outcomes persist until adulthood (Ayduk et al., 2000). However, only a few earlier studies report on the phenomenon of action control in children, whereas the majority of recent studies uses resistance to distraction (or temptation) and delay of gratification paradigms. The most important studies are described in more detail below.
1.3.2 Empirical Evidence Concerning Self-Regulation in Children
Resistance to distraction. Hartig and Kanfer (1973) investigated the effects of overt self-instructions with different contents in a resistance to temptation situation.
Children (kindergarten and first grade) were confronted with the following paradigm:
the experimenter introduced herself as a representative from a toy store and asked the
children to rate new toys in a surprise game. The child had to sit in a separate room with
the new toys behind his back. Afterwards, the experimenter pretended that she had
forgotten her paper and pencil. Consequently, she had to leave the room again, and instructed the child not to turn around and look at the toys until she returned, because that would spoil the surprise. Children that verbalized positive consequences for non- transgression (“I must not turn around and look at the toy. If I don’t look at the toy, I will be a good boy/girl”), negative consequences for transgression (“I must not turn around and look at the toy. If I don’t look at the toy, I will be a bad boy/girl”) or the instruction not to transgress (“I must not turn around and look at the toy”) showed significantly longer tolerance of resistance than children that formed a task-irrelevant verbalization (”Hickory dickory dock, the mouse went up the clock”) or no
verbalization at all. Hartig and Kanfer interpreted these findings in terms of self-control:
self-instructions can prolong the resistance to temptation in children.
Patterson and Mischel (1975, 1976), as well as Mischel and Patterson (1976) investigated how plans help to resist distractions in preschool children. They developed the following paradigm: The children had to complete a repetitive task (e.g., copying task, pegboard task) while “Mr. Clown Box”, a large wooden box that was painted to resemble a clown with a tape recorder and speakers inside, distracted the children. They found that children worked longer on the task when they were instructed with three plans (e.g., “No, I can’t, I’m working”, “I’m going to keep working so I can play with the fun toys and Mr. Clown Box later”, “ When you really want to look, tell yourself that there’s a brick wall there“) compared to no plan. Moreover, children who were given one plan worked as much as children with three plans and more than children with no plan (Patterson & Mischel, 1975). Further, they demonstrated that resistance to distraction was facilitated in a temptation-inhibiting and reward-orienting condition, and only when the respective plans were presented in an elaborated form. In the elaborated condition the plan was specified (e.g., “And you say: No, I’m not going to look at Mr.
Clown Box”), whereas in the unelaborated condition the children were only generally told to plan (e.g., “And you say something to keep yourself from looking at Mr. Clown Box”) (Mischel & Patterson, 1976). In addition, they replicated the finding that
temptation-inhibiting plans (“I’m not going to look at Mr. Clown Box”) are superior to
task-facilitating plans (“I’m going to look at my work”) and to the combination of both
plans (“I’m not going to look at Mr. Clown Box; I’m going to look at my work”)
(Patterson & Mischel, 1976). In contrast to the Hartig and Kanfer Study (1973) and for
the first time, the effectiveness of plans in regard to the performance in a respective task was shown to depend on relatively subtle differences in the formulation of these plans.
These findings can be interpreted as the efficacy of self-instructional plans being dependent on the relationship between characteristics of the particular plan, and characteristics of the particular situation in which the plan must be implemented.
Delay of gratification. Another approach to the self-control of children is the research line concerning delay of gratification (Mischel, 1974). Mischel defines will power as “the ability to postpone immediate gratification for the sake of future
consequences, to impose delays of reward on oneself, and to tolerate such self-initiated frustration” (Mischel, 1974, p. 249). Therefore, the following experimental paradigm was established and examined with preschool children in an abundance of studies:
children were asked to learn a game in which they had to decide between a small but immediate and a big but delayed reward. For instance, they could get one cookie immediately, but two cookies if they waited for the experimenter returns to the room after an undetermined time. Mischel and colleagues (for an overview see Mischel, 1996) have extensively explored this paradigm. They showed that preschool children waited the longest time when both rewards (delayed and immediate) were obscured from view and interpreted this finding in a self-distraction sense: The children can convert the frustrating waiting situation in a more tolerable non-waiting situation by means of distraction. Further, Mischel and Baker (1975) examined the effects of a cognitive focus and revealed that a more abstract “cool” focus (marshmallows are clouds) made delay easier for children than an arousing “hot” focus (marshmallows taste sweet and chewy).
With reference to this dynamic of self-regulation Metcalfe and Mischel (1999)
suggested a “Hot-Cool Model” including two interacting systems – a cognitive “cool”
system and an emotional “hot” system. The cool system is responsible for planful, strategic, and reflective behavior, and which increases with age and attenuates under stress. Also, the cool system seems to be connected with hippocampal and frontal lobe regions in the brain. The hot system is associated with impulsive and reflexive behavior, is most dominant in young children and might be connected to the amygdala.
The effects of verbalization on delay of gratification skills were tested in experiments by Toner and his colleagues (Toner & Smith, 1977; Toner, Lewis, &
Gribble, 1979; Toner, 1981). At first, they found that the content of overt self-
verbalizations expressed by a child during a delay of gratification period greatly influenced his/her duration of delay. Furthermore, they showed that children who verbalized with a focus on rewards, either positively or negatively (“I like the tokens”;
“I don’t like the tokens”) waited less time than children without any verbalization.
Additionally, there was no difference between the conditions in which the children had to negatively verbalize delay behavior (“I don’t like to wait”) and the control condition (without verbalization). Only children who positively verbalized delay behavior (“I like to wait”) waited longer than children in the control condition (without verbalization). In support of this, Toner (1981) demonstrated that children wait longer when they receive a task-centred statement instead of a reward-centred statement beforehand.
1.3.3 Empirical Evidence Concerning Self-Regulation in ADHD Children
Most of the research concerning action control in ADHD children has observed the performance of ADHD children only in classic self-control tasks, such as delay of gratification tasks without the explicit application of plans. Some of the most important research approaches and results concerning the action control of ADHD children are reported in the following section.
Meichenbaum and Goodman (1971) were the first to investigate self-instructions in children with behavioral problems causing impulsivity. They proposed that impulsive children can be trained to talk to themselves. Specifically, two experiments were
conducted in which children were taught to use their private speech (e.g., “Good, I’m doing fine so far. Remember go slow.”) in a so called cognitive self-instructional training group. Results indicated further that children showed fewer errors only when they ran through a cognitive modeling plus self-instructional training. Cognitive modeling alone was not sufficient to improve the performance of impulsive children.
Almost 20 years later, Rodriguez, Mischel, and Shoda (1989) investigated self- regulation in a delay of gratification paradigm with children from a summer residential program (Wediko Children’s Services, New Hampshire) that showed social adjustment and impulsivity-related problems. They demonstrated that the most important correlate of delay time was attention deployment, for example interpreted in the place “where the children focused their attention during the delay period” (Mischel, 1996, p. 214).
Particularly, as the length of the delay and the frustration of the situation increased,
children who spent a higher amount of effort to distract themselves from the tempting elements of the delay situation were able to delay longer. However, the children examined in this experiment were not children diagnosed with ADHD and therefore supposedly constituted a heterogeneous group. Furthermore, no intentional strategies such as plans were implemented.
In a recent work by Salbach, Huss, and Lehmkuhl (2002) the delay of
gratification paradigm (Mischel, 1958; Sonuga-Barke, Taylor, Sembi, & Smith, 1992;
Schweitzer & Sulzer-Azaroff, 1995) was realized in a computer task. Within this task, children earned more points when, (a) they suppressed clicking on a figure on the screen while this figure was on the first determined, “sensible” area of the screen, and, (b) they waited until the figure was in the second “sensible” area. Results showed that ADHD children reacted significantly more impulsively in this task (i.e., clicked more often in the first “sensible” area and earned less points) compared to control children without ADHD.
Gerjets et al. (2002) investigated ADHD-specific intentions and impairments of action control experimentally. ADHD and control children first had to work on a CPT and subsequently worked on a secondary task (naming of animals). To vary the degree of stimulation during the CPT, rock music was presented within certain time periods. To vary the degree of necessary action control during the CPT, slides with animals (related to the secondary task) were presented within certain time periods. CPT performance of ADHD children (but not of control children) improved under acoustic stimulation. The authors interpreted this result as support for the external stimulation hypothesis (Imhof, 2004). Under conditions of high necessary action control, the performance of control children (but not of ADHD-children) improved. This result is interpreted as indicating ADHD-specific impairment of action control. Still, this study doesn’t provide any information on planning behavior of ADHD children in action control demanding tasks.
1.3.4 Summary
The terms self-control, action control, and self-regulation all refer to self-guided
goal-directed behavior required in resistance to distraction or delay of gratification
situations. It has been shown that plans support children resisting distractions and
delaying gratifications. It could also be demonstrated that ADHD children have
problems in resisting temptations or distractions and in delaying gratifications or rewards. To the best of our knowledge, no experimental study has investigated the effects of implementation intentions as a type of a plan and the interaction of implementation intentions and MPH in ADHD children to date. Therefore, the theoretical and empirical backgrounds concerning implementation intentions are presented subsequently.
1.4 ACTION CONTROL VIA IMPLEMENTATION INTENTIONS
According to Barkley (1997a) “ADHD impairs the human will and one’s volition” (Barkley, 1997a; p. 315). Besides behavior therapy and psychostimulant medication, another opportunity to facilitate goal-directed intentional behavior of ADHD children might be the utilization of volitional planning strategies.
Implementation intentions are an efficient instrument for the development of goal- directed, controlled behavior using one single mental act (Gollwitzer, 1999). Numerous studies confirmed that implementation intentions promote goal achievement in different areas (Gollwitzer & Sheeran, in press). Implementation intentions enhance not only the performance in different laboratory tasks (Gollwitzer & Brandtstätter, 1997), but they are also useful in applied settings (Sheeran & Orbell, 1999). Because implementation intentions promote goal-directed behavior in populations that demonstrate severe action control problems, as schizophrenic patients, opiate addicts, and patients with frontal brain lesions (Brandstätter, Lengfelder, & Gollwitzer, 2001; Lengfelder & Gollwitzer, 2001), children suffering from ADHD should also profit from implementation
intentions. According to Gollwitzer (1996) implementation intentions are formed within the second, pre-actional phase in the model of action phases. Therefore, this model is explained in detail before implementation intentions are characterized as a self- regulatory tool, theoretically and empirically.
1.4.1 The Model of Action Phases
The model of action phases differentiates between goal setting and goal striving.
Goal setting and goal striving are integrated in this model that assumes a chronological
development from the first appearance of a wish to the evaluation process after goal attainment. Therefore, the model postulates four discrete phases (see Figure 1):
1. Predecisional phase,
2. Postdecisional but preactional phase, 3. Action phase, and
4. Postactional phase.
Figure 1. The model of action phases (adapted from Gollwitzer, 1996)
The four different phases and their characteristics are described in detail below:
Predecisional phase. Characteristic of this phase are wishes and the deliberation of these wishes. Because it is not possible to transform all wishes into actions at the same time, wishes are tested in regard to their desirability and feasibility. The
desirability of a wish is determined by the expected value of wish fulfillment (e.g., the likelihood of positive or negative outcomes of having achieved the desired wish). The feasibility is related to a reflection of the chances that the wish can be realized (e.g., possession of relevant skills, time, etc. for realization).
Preactional phase. Within this phase the favored wishes need to be transformed into intentions. Thus, in a transition from wishes and desires to binding goals, goal intentions will be formed. Consequently, humans feel the obligation to fulfill the
implied wish and develop a commitment to the goal. Heckhausen and Gollwitzer (1987)
Preferences are set between wishes by deliberating the desirability and feasibility
The “when”,
“where” and
“how” of getting started is
Determined and persistent pursuit of
Evaluation of whether further goal pursuit is necessary and worthwhile Predecisional
phase (motivational)
Actional (volitional) Preactional
phase (volitional)
Postactional phase (motivational) Decision
(goal intention) Action initiation Action
wishes,
desires wishes,
desires
described this formation with the metaphor “to cross the rubicon” to make clear that this act is irrevocable
3. This phase is further characterized with planning; meaning that on the way from wishes to action, individuals have to reflect and decide on when, where, and how to act. Individuals therefore create plans for their actions.
Actional phase. The actional phase starts with the initiation of goal-directed behavior. If a goal intention leads to action initiation depends on (a) the strength of volition (compared to the strength of volition of concurrent goal intentions) and (b) the convenience of the situation (compared to other concurrent goal intentions and
compared to relevant future opportunities).
Postactional phase. Within this phase, individuals need to evaluate their goal achievement. There are two different criteria for evaluation of the action. Firstly, the question as to whether the goal was attained or not has to be answered. Next is the question whether the actual value of the attained goal corresponds to the expected value.
Summary. Primarily, the model identifies typical problems humans run into when attempting the translation of their wishes and desires into reality. But the model has also stimulated two theoretical concepts that explain people’s functioning at various stages of wish fulfillment. These are the concepts of mind-set and implementation intention. Both are useful for understanding the positive effects of planning on the realization of goals. Implementation intentions are particularly important for the studies conducted within this dissertation. Therefore, only implementation intention research (theoretic and empiric aspects) will be explained in detail.
1.4.2 Implementation Intentions as a Useful Self-Regulatory Tool (Theoretical Approach)
Implementation intentions are if-then plans that specify when, where, and how a goal has to be transferred into action. Implementation intentions take the format of “If situation X is encountered, then I will perform behavior Y” and thus link the critical situation (if-part) with a goal-directed behavior (then-part). It is important to distinguish implementation intentions from goal intentions. Goal intentions merely specify a desired outcome and have the format of “I intend to reach Z”. Whereas goal intentions assign preferred end-states, that the individual feels committed to attain, implementation
3 Therefore, this model is also referred to as the “rubicon model of action phases”.
