Compared Profile of Late-Onset Versus Childhood-Onset ADHD: A Case-Control Study Among Treatment-Seeking Adult Patients

Abstract

Objective:

To compare the characteristics of childhood-onset versus late-onset Attention Deficit Hyperactivity Disorder (ADHD) in a sample of treatment-seeking patients.

Method:

Among total of 101 adult patients who were recently diagnosed for ADHD, using the Diagnostic Interview for Adult ADHD (DIVA 2.0), 56 subjects exhibited childhood-onset ADHD, versus 45 displayed late-onset ADHD. Both groups were compared according to their sociodemographic, clinical, and neuropsychological features, providing crude (OR) and adjusted odds ratios (aOR), and their 95% confidence intervals [95% CI].

Results:

Compared to late-onset ADHD, patients with childhood-onset had a lower educational score, (OR = 0.52; 95% CI [0.35, 0.76]), a greater score of impulsivity (aOR = 1.09; 95% CI [1.03, 1.16]), an increased number of hyperactive-impulsive ADHD symptoms (aOR = 1.9; 95% CI [1.46, 2.47]), and higher rates childhood trauma (aOR = 1.07; 95% CI [1.01, 1.13]), cannabis use disorder (aOR = 1.07; 95% CI [1.01, 1.13]), and working memory impairment. No difference was observed concerning age, sex, psychiatric symptoms, quality of life, and autonomy.

Conclusion:

Childhood-onset adult ADHD displayed a more severe profile, relative to late-onset ADHD.

Keywords

ADHD late-onset childhood-onset neuropsychological

Introduction

Attention Deficit with or without Hyperactivity Disorder (ADHD) has long been conceptualized as a neurodevelopmental disorder with an onset of symptoms and impairments occurring in childhood, that is, before the age of 12 years (American Psychiatric Association [APA], 2015). Prospective studies of clinic-referred children with ADHD indicated that approximately 15% would continue to meet diagnostic criteria in adulthood, and 65% will continue to have subthreshold impairing symptoms as young adults (Faraone, Biederman, & Mick, 2006) contrasting with the old “childhood-limited” theory of ADHD (Lange et al., 2010). As a result, in their fifth version, the Diagnostic and Statistical Manual of Mental Disorders criteria for ADHD elevate the age-of-onset threshold from 7 to 12 years and lower the symptom threshold from 6 to 5 at each symptom domain for individuals aged 17 years and older (APA, 2015).

More recently, the results of several lifelong cohort studies suggested that ADHD in adolescence and adulthood is not always a continuation of childhood ADHD, and that ADHD may thus arise after childhood (Agnew-Blais et al., 2016; Caye et al., 2016; Moffitt et al., 2015). Consequently, it has been suggested that ADHD could be diagnosed after the DSM age-at-onset cut-off (Asherson & Agnew-Blais, 2019). Two main theories have attempted to explain what late-onset (LO) ADHD can represent. A first hypothesis it that, in individuals with LO ADHD, symptoms in childhood have been compensated for, owing to a supportive environment and/or greater cognitive skills, while other theories suppose that LO ADHD is actually the clinical manifestation of other psychiatric disorders but not ADHD, for example, the consequences of substance use (Agnew-Blais et al., 2016; Taylor et al., 2022).

The clinical comparison of CO versus LO forms of ADHD have led to conflicting results concerning neuropsychological assessment, genetic risk, or environmental factors (Asherson & Agnew-Blais, 2019). If some studies reported no difference in the impairment of neuropsychological functions (Faraone, Biederman, Doyle, et al., 2006), others showed different profiles of cognitive performance deficit in CO versus LO ADHD (Moffitt et al., 2015) suggesting these two forms could be etiologically discrete disorders. As mentioned above, it has also been suggested that adults with LO ADHD had subthreshold symptoms in childhood, (Asherson & Agnew-Blais, 2019; Faraone & Biederman, 2016), with a higher level of cognitive functioning (Agnew-Blais et al., 2016; Moffitt et al., 2015), which decompensated later into the full criteria for ADHD, in particular when socio-professional demands are higher. The aim of our study was to compare the clinical and neuropsychological features of CO versus LO ADHD, in a French outpatient population diagnosed with ADHD.

Method

Study Population

Participants were adult patients who had consulted in the diagnosis center for adult ADHD of Lyon, and had received a confirmed diagnosis of adult ADHD, based on the Diagnostic Interview for ADHD in adults (DIVA) 2.0 (Pettersson et al., 2018). The recruitment period was Jan 2019 to Dec 2021. The DIVA 2.0 was undertaken by a trained clinician, usually with the help of the patient’s family. Mini International Neuropsychiatric Interview (MINI) 5.0.0 was used to exclude possible other axis-1 psychiatric diagnoses that could question the final diagnosis of ADHD. The study pertained only to individuals with a positive diagnosis of ADHD. Patients already receiving treatment for ADHD, that is, methylphenidate, amphetamine derivatives, atomoxetine, or bupropion, respectively, at the time of the assessment, were excluded.

Clinical and Functional Measures

The DIVA 2.0 is a validated structured interview for the assessment of adult ADHD according to DSM-IV-TR diagnostic criteria. It provides a diagnostic result for ADHD, as well as elements on the clinical subtype of ADHD, that is, inattentive, hyperactive, or mixed, respectively. Moreover, the DIVA 2.0 allows to differentiate childhood-onset ADHD (i.e., current ADHD diagnosis with reported ADHD symptoms above diagnosis cut-off before 12-year-old) versus late-onset ADHD (i.e., current ADHD diagnosis with reported ADHD symptoms below diagnosis cut-off before 12-year-old) (Ramos-Quiroga et al., 2019). We also retrieved the number of inattentive and hyperactive-impulsive symptoms during childhood to assess the severity of inattentive and/or hyperactive-impulsive symptoms.

In addition, participants underwent a series of self-questionnaires assessing their level of anxiety, using the State-Trait Anxiety Inventory (STAI-A and STAI-B) (Ercan et al., 2015), depression, using the Beck Depression Inventory (BDI-II) (Beck et al., 2011), childhood traumas, using the Childhood Trauma Questionnaire (CTQ) (Scher et al., 2001), sleep impairments, using the Pittsburgh Sleep Quality Index (PSQI) (Fabbri et al., 2021), quality of life, using the World Health Organization Quality of Life (WHOQOL-Bref) questionnaire, autonomy (World Health Organization., s. d.), using the World Health Organization Disability and Autonomy Scale (WHODAS-2) questionnaire, impulsivity, using the impulsive behavior scale (UPPS-P) (Whiteside et al., 2005), tobacco use, using the Fagerström Test for Nicotine Dependence (FTND) score (Moolchan et al., 2002), alcohol use, using the Alcohol Use Disorder Identification Test (AUDIT) score (Gache et al., 2005), and cannabis use, using the Cannabis Use Disorder Identification Test–revised (CUDIT-R) (Adamson et al., 2010).

An additional clinician-based assessment explored the use of non-prescribed psychostimulant drugs in the previous month (yes vs. no), age (in years), sex (male or female), education level, using the International Standard Classification of Education (ISCED), body mass index (BMI, in kg/m²).

Neuropsychological Assessment

Participants underwent a complete neuropsychological assessment using multiple tests: TAP (Test for Attentional Performance) for phasic alert, divided attention, sustained attention, and motor inhibition (Zimmermann & Fimm, 1992), D2 for selective attention (Brickenkamp & Zilmer, 2011), WAIS-IV Digit Span for working memory (Wechsler, 2012), Stroop test for cognitive inhibition (Stroop, 1935), TMT (Trail Making test) for cognitive flexibility (Arbuthnott & Frank, 2000), and the multiple errands test, for planning skills (Shallice & Burgess, 1991), a test designed to assess the patient’s ability to take account of several instructions simultaneously. The test consists of an instruction sheet with a shopping district map showing several stores to which the patient must go for various errands, considering multiple constraints.

To assess the impairment of each cognitive function, measures were transformed into percentile ranks, standard scores or z-scores. Here, the thresholds proposed by Ceccaldi et al. (2015) were used. In view of the lack of consensus in the literature regarding cognitive impairment in individuals with ADHD, the lower cut-off values were considered as pathological, in order to encompass cognitive weaknesses in cognitive deficits. Thus, for percentile ranks, values below 16 are considered pathological. For z-scores, values below −1 are considered failed. For standard scores, values below 7 are considered pathological. The executive functions were investigated in this study and the criteria for dysexecutive syndrome were met when participants had at least two executive impairments in the different tests (Fonctions exécutives et pathologies neurologiques et psychiatriques, 2019).

Statistical Analyses

Descriptive statistics are presented as the mean and the standard deviation (m ± SD) for quantitative variables, and the number and percentage (n, %) for categorical variables. Bivariable comparisons between childhood-onset and late-onset ADHD were conducted using Mann-Whitney test for quantitative variables, and chi-squared test for categorical variables. Logistic regression models were built, to explore the associations between the type of ADHD (i.e., CO vs. LO), and the other parameters, which were the dependent variables. Models provided raw and adjusted odds ratios and their 95% confidence interval ([a]OR, 95% CI). Adjustment variables were age, sex, and level of education. No multivariable models were built for neuropsychological tests, as the calculation of the results already integrated the same adjustment variables.

Ethics

The study was performed in accordance with the guidelines and regulations described by the Declaration of Helsinki and Jarde law on human research ethics (Toulouse et al., 2018). This study was approved by the CNIL (French National Commission on Informatics and Liberties) (approval reference number: MR-004-2020-006).

Results

Population

During the inclusion period, 184 patients were referred by other medical centers for ADHD assessment, and, for 123 of them, the diagnosis of ADHD was confirmed, using the DIVA 2.0. Twenty-two patients were excluded because they were already medicated for ADHD. Of the 101 participants included, 56 (55.5%) met the criteria for CO ADHD, whereas 45 (45.6%) met the criteria for LO ADHD.

Demographic and Clinical Description

Descriptive results of the two groups, as well as bivariable comparisons, are presented in Table 1, while the results of multivariable comparisons are presented in Table 2. There was no difference in age between both groups. In the CO ADHD group, a significantly lower proportion of women (28.6%) were found compared to the LO group (44.4%). However, this difference did not remain significant in multivariable model analyses.

Table 1.

Socio-Demographic, Clinical and Neuropsychological Characteristics of the Study Population.

	Childhood-onset ADHD	Late-onset ADHD	p-Value	nmw
	n = 56	n = 45	p-Value	nmw
Sociodemographic parameters = n (%) or mean ± SD
Sex (n and % females)	16 (28.6%)	20 (44.4%)	<.1	0
Age (years)	31.7 ± 9.0	31.1 ± 9.0	ns	0
ISCED (1–7 level)	3.0 ± 1.1	3.9 ± 1.3	<.001	0
ADHD symptoms = n (%) or mean ± SD
DIVA 2.0-Childhood hyperactivity symptoms	5.5 ± 2.5	2.36 ± 1.8	<.001	0
DIVA 2.0-Childhood inattention symptoms	6.1 ± 1.9	2.8 ± 1.7	<.001	0
Age at symptom onset (years-old)
≤12	56 (100%)	25 (59.5%)	<.001
12–18	0	7 (16.7%)
>18	0	10 (23.8%)
Clinical parameters = n (%) or mean ± SD
BMI (kg/m²)	22.7 ± 4.0	25.1 ± 5.8	<.05	0
BDI	20.6 ± 11.3	17.8 ± 10.6	ns	4
STAI-A	51.0 ± 13.8	49.5 ± 10.4	ns	9
STAI-B	57.8 ± 11.2	58.7 ± 9.5	ns	9
UPPS	57.7 ± 6	52.6 ± 8.9	<.01	8
CTQ	60.7 ± 13.0	46.7 ± 17.9	<.01	22
PSQI	9.3 ± 3.9	9.1 ± 3.7	ns	5
FTND	2.1 ± 3.0	2.7 ± 3.23	ns	6
AUDIT	13.6 ± 10.9	9.6 ± 11.2	<.1	4
CUDIT-R	10.7 ± 10.1	4.7 ± 8.4	<.01	4
Psychostimulant use	27 (50.1%)	19 (48.7%)	ns	8
WHOQOL-phy (100-point scale)	37.0 ± 20.2	38.2 ± 15.3	ns	8
WHOQOL-psy (100-point scale)	57.7 ± 21.4	62.2 ± 12.8	ns	8
WHOQOL-soc (100-point scale)	46.5 ± 24.4	48.9 ± 21.6	ns	8
WHOQOL-env (100-point scale)	57.7 ± 21.4	62.2 ± 12.8	ns	8
WHODAS	36.3 ± 18.9	38.6 ± 18.7	ns	15
Neuropsychological parameters = n (%)
Impaired selective attention^a	28 (50.0%)	21 (46.7%)	ns	0
Impaired sustained attention^b	38 (67.9%)	26 (57.8%)	ns	0
Impaired phasic alert^b	26 (47.3%)	19 (42.2%)	ns	0
Impaired divided attention^b	29 (51.8%)	23 (51.1%)	ns	0
Impaired motor inhibition^b	21 (37.5%)	14 (31.1%)	ns	0
Impaired working memory^c	24 (42.9%)	11 (24.4%)	<0.1	0
Impaired cognitive flexibility^d	18 (32.1%)	10 (22.2%)	ns	0
Impaired cognitive inhibition^e	17 (30.4%)	15 (33.3%)	ns	0
Planning impairment^f	34 (60.7%)	27 (60.0%)	ns	0
Dysexecutive syndrome^g	24 (42.9%)	17 (37.8%)	ns	0

Note. ISCED = International Standard Classification of Education; DIVA 2.0 = Diagnostic Interview for ADHD in adults; BMI = Body Mass Index; STAI; State-Trait Anxiety Inventory); A = State; B = trait; BDI = Beck Depression Inventory; CTQ; Childhood Trauma Questionnaire; PSQI = Pittsburgh Sleep Quality Index; WHOQOL= World Health Organization Quality of Life; WHODAS-2 = World Health Organization Disability and Autonomy Scale; UPPS = impulsive behavior scale; FTND = Fagerström Test for Nicotine Dependence; AUDIT = Alcohol Use Disorder Identification Test; CUDIT-R = Cannabis Use Disorder Identification Test–revised.

Using D2.

Using Test of Attentional Performance.

Using WAIS-IV Digit Span.

Using Trail Making Test.

Using Stroop test.

Using the multiple errands test.

At least two executive impairments in the different tests.

Table 2.

Bivariate and Multivariate Analysis.

	Childhood-onset vs. Late-onset ADHD		nmw
	OR [95% CI]	aOR [95% CI]^a	nmw
Sociodemographic parameters
Female sex (vs. male)	0.50 [0.22–1.14]	0.70 [0.28–1.76]	0
Age (per 1-year increase)		1.03 [0.98–1.08]	0
ISCED (per one-level increase)	0.52 [0.35–0.76]***	0.50 [0.34–0.76]***	0
Clinical parameters
DIVA 2.0-Childhood hyperactivity symptoms	1.20 [1.09–1.33]**	1.9 [1.46–2.47]***	0
DIVA 2.0-Childhood inattention symptoms	2.5 [1.08–3.61]***	2.6 [1.75–3.76]***	0
BMI (per one-point increase)	0.90 [0.83–0.99]*	0.90 [0.82–0.99]*	0
BDI (per one-point increase)	1.02 [0.99–1.06]	1.01 [0.97–1.05]	4
STAI-A (per one-point increase)	1.01 [0.98–1.04]	1.01 [0.97–1.04]	9
STAI-B (per one-point increase)	0.99 [0.95–1.03]	0.98 [0.94–1.03]	9
UPPS (per one-point increase)	1.08 [1.02–1.14]**	1.09 [1.03–1.16]**	8
CTQ (per one-point increase)	1.06 [1.02–1.12]**	1.07 [1.01–1.13]**	22
PSQI (per one-point increase)	0.98 [0.86–1.11]	0.99 [0.88–1.12]	5
FTND (per one-point increase)	1.07 [0.93–1.22]	0.99 [0.86–1.15]	6
AUDIT (per one-point increase)	1.03 [0.99–1.08]	1.02 [0.98–1.07]	4
CUDIT-R (per one-point increase)	1.07 [1.02–1.13]*	1.07 [1.01–1.13]**	4
Psychostimulant use (yes vs. no)	1.21 [0.88–1.64]	1.14 [0.83–1.57]	8
WHOQOL-phy (per one-point increase)	1.00 [0.98–1.03]	1.00 [0.98–1.03]	8
WHOQOL-psy (per one-point increase)	1.00 [0.98–1.03]	1.00 [0.98–1.03]	8
WHOQOL-soc (per one-point increase)	1.00 [0.98–1.02]	1.00 [0.98–1.02]	8
WHOQOL-env (per one-point increase)	0.99 [0.97–1.02]	0.99 [0.97–1.02]	8
WHODAS (per one-point increase)	0.99 [0.97–1.02]	0.99 [0.96–1.02]	15
Neuropsychological parameters
Impaired selective attention (yes vs. no)	1.14 [0.52–2.51]	—	0
Impaired sustained attention (yes vs. no)	1.54 [0.68–3.49]	—	0
Impaired phasic alert (yes vs. no)	1.23 [0.55–2.71]	—	0
Impaired divided attention (yes vs. no)	0.54 [0.19–1.56]	—	0
Impaired motor inhibition (yes vs. no)	1.33 [0.58–3.05]	—	0
Impaired working memory (yes vs. no)	2.32 [0.98–5.49]	—	0
Impaired mental flexibility (yes vs. no)	1.66 [0.67–4.07]	—	0
Impaired cognitive inhibition (yes vs. no)	0.87 [0.38–2.08]	—	0
Planning impairment (yes vs. no)	1.03 [0.46–2.30]	—	0
Dysexecutive syndrome (yes vs. no)	1.24 [0.55–2.75]	—	0

Note. ISCED = International Standard Classification of Education; BMI = Body Mass Index; STAI = State-Trait Anxiety Inventory; A =State; B = trait; BDI = Beck Depression Inventory; CTQ = Childhood Trauma Questionnaire; PSQI = Pittsburgh Sleep Quality Index; WHOQOL = World Health Organization Quality of Life; WHODAS-2 = World Health Organization Disability and Autonomy Scale; UPPS = impulsive behavior scale; FTND = Fagerström Test for Nicotine Dependence; AUDIT = Alcohol Use Disorder Identification Test; CUDIT-R = Cannabis Use Disorder Identification Test -revised.

Adjusted on sex, age, and ISCED level.

p < .5. **p < .1. ***p < .01.

Participants in the CO group had a significantly lower educational level, relative to the LO group, that is, a lower ISCED score (OR = 0.52; 95% CI [0.35, 0.76]). They also displayed a lower rate of childhood trauma (aOR = 1.07; [1.01, 1.13]). Concerning the clinical features, a lower BMI was found in the CO group (aOR = 0.90; [0.82, 0.99]), as well as a higher level of impulsivity (aOR = 1.09; [1.03, 1.16]), a higher number of hyperactive-impulsive childhood ADHD symptoms (aOR = 1.9; [1.46, 2.47]) and inattentive childhood ADHD symptoms (aOR = 2.6; [1.75, 3.76]) at the DIVA.

Age at onset of first ADHD symptoms were below 12 for the CO ADHD group. For the LO group, 59.5% were 12 years-old or younger at onset, while 16.7% were adolescents, i.e., aged between 12 and 18 years, and 23.8% were adults, that is, aged 18 years or more when first symptoms occurred.

CO subjects had higher rates of cannabis and alcohol use disorders. The difference remained significant for cannabis use only in the adjusted regression model (aOR = 1.07 95% CI [1.01, 1.13]). There was no significant difference between groups concerning the level of anxiety, depression, sleep impairment, tobacco use, quality of life, or autonomy. Mean levels of anxiety (state and trait) were elevated in both groups, as well as the level of sleep disorder risks. Mean depression scores were moderated in both groups.

Concerning quality of life, scores in the four domains (physical, psychological, social, and environmental) were lower than the normative population in previous studies (Murphy & Murphy, 2006), meaning that CO and LO have a poorer quality of life in these different domains. Poor level of functioning/autonomy was also retrieved in both groups according to the WHODAS scale.

Neuropsychological Data

As presented in Tables 1 and 2. There was no difference concerning neuropsychological testing between CO and LO ADHD, except for working memory, which tends to be more impaired in CO group (42.9% had an impairment in working memory) compared to LO group (24.4%) (OR = 2.32; 95% CI [0.98, 5.49]). Among the different cognitive functions assessed, sustained and divided attention, and planification were the most impacted in both groups (more than 50% of participants in each group).

Discussion

Our study aimed to compare the clinical and neuropsychological characteristics of participants with either CO or LO ADHD in a clinical population with a current diagnosis of ADHD. Our results emphasize that CO ADHD that persisted during adulthood had more severe functional impairments, relative to subjects with LO ADHD, with a lower educational level, higher level of impulsivity, more hyperactive-impulsive symptoms, increased risk of childhood trauma, cannabis used disorder, and increased impairment in working memory.

Our results are in line with other studies, demonstrating that CO ADHD is a more severe ADHD (Agnew-Blais et al., 2016; Lopez et al., 2017), with a higher level of hyperactive-impulsive symptoms (Solanto, 2019), and functional difficulties, such as a lower education attainment (Agnew-Blais et al., 2018). In contrast with some previous studies, we did not find that LO ADHD was more associated with substance use disorder risk and therefore the hypothesis that LO ADHD could be a consequence of substance consumption (Agnew-Blais et al., 2018; Moffitt et al., 2015; Sibley et al., 2018) is not corroborated by our results. For both CO and LO ADHD, we found high level of anxiety and depressive symptoms, low quality of life and autonomy, as well as high level of neuropsychological impairment accordingly to previous study (Agnew-Blais et al., 2016; Cooper et al., 2018; Faraone, Biederman, Doyle, et al., 2006). Both CO and LO ADHD are associated with a considerable personal burden.

As previously suggested in the scientific literature, it is plausible, in view of our findings, that individuals LO ADHD were not diagnosed earlier because of a sub-clinical symptomatology. In our population, more than half of the LO ADHD group reported some inattention and/or hyperactive-impulsive symptoms before 12 years of age, even if the number of symptoms was below the diagnosis cut-off.

Also, we found a lower rate of childhood trauma in the LO ADHD group. Childhood trauma could be a reason for early specialized consultation, leading to an earlier assessment of children with trauma-related suffering and an earlier ADHD diagnosis (Chronis-Tuscano, 2022).

Our study had several limitations. Because of its retrospective design, we could not distinguish whether CO ADHD was more severe because the duration of the disorder was longer, or, on the contrary, if CO ADHD occurred sooner in life because the form of the disorder was intrinsically more severe in these individuals. The impact of lifelong medications, including previous ADHD treatments, was not investigated. Moreover, we did not compare the IQ between groups, which would have provided useful pieces of information. In particular, we could not explore the hypothesis that better intellectual performances explain the differential profile of LO versus CO ADHD. Last, although the DIVA scale allows for a retrospective ADHD diagnosis, several studies have identified some potential recall and classification bias for retrospective ADHD diagnosis (Breda et al., 2020; Mannuzza et al., 2002). Our results should thus be interpreted regarding this potential misclassification. It is possible that recall of childhood symptoms was facilitated by a more severe or noticeable symptomatology.

Conclusion and Perspective

Individuals with CO ADHD appeared to have more severe functional features, relative to LO ADHD. Overall, our results are more in line with the hypotheses which suggest that LO ADHD could be a “compensated” form of ADHD, with symptoms that are both less severe and occur later in life. Of course, our findings are retrospective and are based on a single-center study and should be replicated in additional samples and prospective data.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Lucie Jurek

Author Biographies

Lucie Jurek is a child and adolescent psychiatrist working in the field of learning disorders and ADHD. She is a Ph.D. candidate in public health at the University of Lyon.

Solène Montègue is a neuropsychologist currently working in Addictology at Vinatier Hospital Lyon (SUAL—Service Universitaire d’Addictologie de Lyon).

Agathe Larrieu is a clinical research associate currently working in Addictology at Vinatier Hospital Lyon (SUAL—Service Universitaire d’Addictologie de Lyon).

Christophe Icard is a general practitioner and addictologist working in Addictology at Vinatier Hospital Lyon (SUAL—Service Universitaire d’Addictologie de Lyon).

Benjamin Rolland is a professor of psychiatry and addictology. He is at the head of the SUAL—Service Universitaire d’Addictologie de Lyon

References

Adamson

S. J.

Kay-Lambkin

F. J.

Baker

A. L.

Lewin

T. J.

Thornton

Kelly

B. J.

Sellman

J. D.

(2010). An improved brief measure of cannabis misuse: The Cannabis Use Disorders Identification Test-Revised (CUDIT-R)☆. Drug and Alcohol Dependence, 110(1–2), 137–143. https://doi.org/10.1016/j.drugalcdep.2010.02.017

Agnew-Blais

J. C.

Polanczyk

G. V.

Danese

Wertz

Moffitt

T. E.

Arseneault

(2016). Evaluation of the persistence, remission, and emergence of attention-deficit/hyperactivity disorder in young adulthood. JAMA Psychiatry, 73(7), 713. https://doi.org/10.1001/jamapsychiatry.2016.0465

Agnew-Blais

J. C.

Polanczyk

G. V.

Danese

Wertz

Moffitt

T. E.

Arseneault

(2018). Young adult mental health and functional outcomes among individuals with remitted, persistent and late-onset ADHD. The British Journal of Psychiatry, 213(3), 526–534. https://doi.org/10.1192/bjp.2018.97

American Psychiatric Association (Éd.). (2015). Diagnostic and statistical manual of mental disorders: DSM-5 (5th ed). American Psychiatric Association.

Arbuthnott

Frank

(2000). Trail making test, part B as a measure of executive control : Validation using a set-switching paradigm. Journal of Clinical and Experimental Neuropsychology, 22(4), 518–528. https://doi.org/10.1076/1380-3395(200008)22:4;1-0;FT518

Asherson

Agnew-Blais

(2019). Annual research review : Does late-onset attention-deficit/hyperactivity disorder exist? Journal of Child Psychology and Psychiatry, 60(4), 333–352. https://doi.org/10.1111/jcpp.13020

Beck

A. T.

Steer

R. A.

Brown

(2011). Beck Depression Inventory–II [Data set]. American Psychological Association. https://doi.org/10.1037/t00742-000

Breda

Rohde

L. A.

Menezes

A. M. B.

Anselmi

Caye

Rovaris

D. L.

Vitola

E. S.

Bau

C. H. D.

Grevet

E. H.

(2020). Revisiting ADHD age-of-onset in adults : To what extent should we rely on the recall of childhood symptoms? Psychological Medicine, 50(5), 857–866. https://doi.org/10.1017/S003329171900076X

Brickenkamp

Zilmer

(2011). D2 Test of Attention [Data set]. American Psychological Association. https://doi.org/10.1037/t03299-000

10.

Caye

Rocha

T. B.-M.

Anselmi

Murray

Menezes

A. M. B.

Barros

F. C.

Gonçalves

Wehrmeister

Jensen

C. M.

Steinhausen

H.-C.

Swanson

J. M.

Kieling

Rohde

L. A.

(2016). Attention-deficit/hyperactivity disorder trajectories from childhood to young adulthood : Evidence from a birth cohort supporting a late-onset syndrome. JAMA Psychiatry, 73(7), 705–712. https://doi.org/10.1001/jamapsychiatry.2016.0383

11.

Ceccaldi

Chaudat

R.M.

Thomas-Antérion

Tramoni

È.

Truche

(2015). Le bilan neuropsychologique. Neurologies, 18, 315–326.

12.

Chronis-Tuscano

(2022). ADHD in girls and women : A call to action – reflections on Hinshaw et al. (2021). Journal of Child Psychology and Psychiatry, 63(4), 497–499. https://doi.org/10.1111/jcpp.13574

13.

Cooper

Hammerton

Collishaw

Langley

Thapar

Dalsgaard

Stergiakouli

Tilling

Davey Smith

Maughan

O’Donovan

Thapar

Riglin

(2018). Investigating late-onset ADHD : A population cohort investigation. Journal of Child Psychology and Psychiatry, 59(10), 1105–1113. https://doi.org/10.1111/jcpp.12911

14.

Ercan

Hafizoglu

Ozkaya

Kirli

Yalcintas

Akaya

(2015). Examining cut-off values for the state-trait anxiety inventory. Revista Argentina de Clinica Psicologica, 24, 143–148.

15.

Fabbri

Beracci

Martoni

Meneo

Tonetti

Natale

(2021). Measuring subjective sleep quality : A review. International Journal of Environmental Research and Public Health, 18(3), 1082. https://doi.org/10.3390/ijerph18031082

16.

Faraone

S. V.

Biederman

(2016). Can attention-deficit/hyperactivity disorder onset occur in adulthood? JAMA Psychiatry, 73(7), 655. https://doi.org/10.1001/jamapsychiatry.2016.0400

17.

Faraone

S. V.

Biederman

Doyle

Murray

Petty

Adamson

J. J.

Seidman

(2006). Neuropsychological studies of late onset and subthreshold diagnoses of adult attention-deficit/hyperactivity disorder. Biological Psychiatry, 60(10), 1081–1087. https://doi.org/10.1016/j.biopsych.2006.03.060

18.

Faraone

S. V.

Biederman

Mick

(2006). The age-dependent decline of attention deficit hyperactivity disorder : A meta-analysis of follow-up studies. Psychological Medicine, 36(2), 159–165. https://doi.org/10.1017/S003329170500471X

19.

Fonctions exécutives et pathologies neurologiques et psychiatriques : Évaluation en pratique clinique . (2019). De Boeck.

20.

Gache

Michaud

Landry

Accietto

Arfaoui

Wenger

Daeppen

J.-B.

(2005). The alcohol use disorders identification test (AUDIT) as a screening tool for excessive drinking in primary care : Reliability and validity of a French version. Alcoholism: Clinical & Experimental Research, 29(11), 2001–2007. https://doi.org/10.1097/01.alc.0000187034.58955.64

21.

Lange

K. W.

Reichl

Lange

K. M.

Tucha

(2010). The history of attention deficit hyperactivity disorder. ADHD Attention Deficit and Hyperactivity Disorders, 2(4), 241–255. https://doi.org/10.1007/s12402-010-0045-8

22.

Lopez

Micoulaud-Franchi

J.-A.

Galera

Dauvilliers

(2017). Is adult-onset attention deficit/hyperactivity disorder frequent in clinical practice? Psychiatry Research, 257, 238–241. https://doi.org/10.1016/j.psychres.2017.07.080

23.

Mannuzza

Klein

R. G.

Klein

D. F.

Bessler

Shrout

(2002). Accuracy of adult recall of childhood attention deficit hyperactivity disorder. American Journal of Psychiatry, 159(11), 1882–1888. https://doi.org/10.1176/appi.ajp.159.11.1882

24.

Moffitt

T. E.

Houts

Asherson

Belsky

D. W.

Corcoran

D. L.

Hammerle

Harrington

Hogan

Meier

M. H.

Polanczyk

G. V.

Poulton

Ramrakha

Sugden

Williams

Rohde

L. A.

Caspi

(2015). Is adult ADHD a childhood-onset neurodevelopmental disorder? Evidence from a four-decade longitudinal cohort study. American Journal of Psychiatry, 172(10), 967–977. https://doi.org/10.1176/appi.ajp.2015.14101266

25.

Moolchan

E. T.

Radzius

Epstein

D. H.

Uhl

Gorelick

D. A.

Cadet

J. L.

Henningfield

J. E.

(2002). The fagerstrom test for nicotine dependence and the diagnostic interview schedule do they diagnose the same smokers? Addictive Behaviors, 27(1), 101–113.

26.

Murphy

E. K.

(2006). Comparing quality of life using the World Health Organization Quality of Life measure (WHOQOL-100) in a clinical and non-clinical sample : Exploring the role of self-esteem, self-efficacy and social functioning. Journal of Mental Health, 15(3), 289–300. https://doi.org/10.1080/09638230600700771

27.

Pettersson

Söderström

Nilsson

K. W.

(2018). Diagnosing ADHD in adults : An Examination of the discriminative validity of neuropsychological tests and diagnostic assessment instruments. Journal of Attention Disorders, 22(11), 1019–1031. https://doi.org/10.1177/1087054715618788

28.

Ramos-Quiroga

J. A.

Nasillo

Richarte

Corrales

Palma

Ibáñez

Michelsen

Van de Glind

Casas

Kooij

J. J. S.

(2019). Criteria and concurrent validity of DIVA 2.0 : A semi-structured diagnostic interview for adult ADHD. Journal of Attention Disorders, 23(10), 1126–1135. https://doi.org/10.1177/1087054716646451

29.

Scher

C. D.

Stein

M. B.

Asmundson

G. J. G.

McCreary

D. R.

Forde

D. R.

(2001). The childhood trauma questionnaire in a community sample : Psychometric properties and normative data. Journal of Traumatic Stress, 14(4), 843–857. https://doi.org/10.1023/A:1013058625719

30.

Shallice

Burgess

P. W.

(1991). Deficits In Strategy Application Following Frontal Lobe Damage In Man. Brain, 114(2), 727–741. https://doi.org/10.1093/brain/114.2.727

31.

Sibley

M. H.

Rohde

L. A.

Swanson

J. M.

Hechtman

L. T.

Molina

B. S. G.

Mitchell

J. T.

Arnold

L. E.

Caye

Kennedy

T. M.

Roy

Stehli

, & for the Multimodal Treatment Study of Children with ADHD (MTA) Cooperative Group. (2018). Late-onset ADHD reconsidered with comprehensive repeated assessments between ages 10 and 25. American Journal of Psychiatry, 175(2), 140–149. https://doi.org/10.1176/appi.ajp.2017.17030298

32.

Solanto

M. V.

(2019). The prevalence of “late-onset” ADHD in a clinically referred adult sample. Journal of Attention Disorders, 23(9), 1026–1034. https://doi.org/10.1177/1087054718765672

33.

Stroop

J. R.

(1935). Studies of interference in serial verbal reactions. Journal of Experimental Psychology, 18(6), 643–662. https://doi.org/10.1037/h0054651

34.

Taylor

L. E.

Kaplan-Kahn

E. A.

Lighthall

R. A.

Antshel

K. M.

(2022). Adult-onset ADHD : A critical analysis and alternative explanations. Child Psychiatry & Human Development, 53(4), 635–653. https://doi.org/10.1007/s10578-021-01159-w

35.

Toulouse

Masseguin

Lafont

McGurk

Harbonn

A Roberts

Granier

Dupeyron

Bazin

J. E.

(2018). French legal approach to clinical research. Anaesthesia Critical Care & Pain Medicine, 37(6), 607–614. https://doi.org/10.1016/j.accpm.2018.10.013

36.

Wechsler

(2012). Wechsler Adult Intelligence Scale—fourth edition [Data set]. American Psychological Association. https://doi.org/10.1037/t15169-000

37.

Whiteside

S. P.

Lynam

D. R.

Miller

J. D.

Reynolds

S. K.

(2005). Validation of the UPPS impulsive behaviour scale : A four-factor model of impulsivity. European Journal of Personality, 19(7), 559–574. https://doi.org/10.1002/per.556

38.

World Health Organization. (s. d.). WHOQOL: Measuring quality of life. https://www.who.int/healthinfo/survey/whoqol-qualityoflife/en/index1.html

39.

Zimmermann

Fimm

(1992). Testbatterie zur Aufmerksamkeitsprüfung:(TAP). Psytest.