Symptom epidemiology, demographic correlates, and differentiation between cognitive disengagement syndrome symptoms and ADHD symptoms in a large nonprobability sample of Iranian adolescents and adults

Abstract

Background

Cognitive disengagement syndrome (CDS) is an emerging cognitive-attentional construct characterized by excessive daydreaming, mental slowness, drowsiness, and reduced engagement with external demands. Although CDS symptoms are substantially associated with attention-deficit/hyperactivity disorder (ADHD) symptoms, accumulating psychometric and external-validity evidence supports their conceptualization as related yet distinguishable symptom dimensions. However, large-scale evidence regarding the distribution and demographic correlates of elevated CDS symptoms, as well as their differentiation from ADHD symptoms, remains limited, particularly in non-Western contexts.

Methods

In this large-scale cross-sectional study, 8,075 Iranian participants aged 15–55 years, recruited through convenience and snowball sampling, completed the Persian Adult Concentration Inventory as a self-report measure of CDS symptoms. A subsample of 2,012 participants also completed the Adult ADHD Self-Report Scale. The study examined the distribution and demographic correlates of elevated CDS symptoms and the extent to which CDS and ADHD symptom dimensions showed overlap and differentiation. Sample-based percentile thresholds were used to identify elevated symptom levels. Analyses included descriptive statistics, logistic regression, correlation and overlap analyses, discriminant function analysis, and leave-one-out cross-validation.

Results

Using the sample-based 95th-percentile threshold, 5.8% of participants exceeded the threshold for elevated CDS symptoms, while 11.3% exceeded the 90th-percentile threshold. Females and younger participants were more likely to exceed the elevated-symptom threshold. CDS and ADHD symptom scores were strongly correlated (r = .69), indicating substantial overlap, although differences were observed across their symptom dimensions. An exploratory discriminant function analysis yielded an original classification accuracy of 95.3% and a leave-one-out cross-validated accuracy of 93.9%; however, these findings reflect within-sample differentiation based on the current self-report measurement framework rather than diagnostic separation.

Conclusion

In this large nonprobability Iranian sample, elevated CDS symptoms showed age- and sex-related differences. CDS and ADHD symptom dimensions demonstrated substantial overlap while also showing meaningful differences in their symptom profiles within the present self-report measurement framework. Because the thresholds were sample-based and no clinical diagnostic interviews or assessments of functional impairment were conducted, the reported percentages should not be interpreted as estimates of clinical or population prevalence, and the classification findings should not be considered evidence of diagnostic separation. These findings extend cross-cultural knowledge of CDS symptomatology and highlight the need for future representative, longitudinal, and multimethod research.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s12888-026-08346-w.

Introduction

Over recent decades, clinical psychology has shown growing interest in cognitive-attentional symptoms that are not fully captured by the diagnostic criteria for attention-deficit/hyperactivity disorder (ADHD). One prominent construct in this area is cognitive disengagement syndrome (CDS), formerly referred to as sluggish cognitive tempo. CDS is characterized by symptoms including excessive daydreaming, mental confusion, slowed thinking and behavior, drowsiness, and reduced engagement with external demands [1]. Importantly, CDS is not currently recognized as a formal diagnostic category in major classification systems such as the DSM-5-TR or ICD-11. Rather, it remains an emerging research construct whose nosological status, conceptual boundaries, and functional significance continue to be investigated.

Early research often examined CDS symptoms within samples of individuals with ADHD, leading to questions about whether CDS represented a subtype of ADHD, an associated feature, or a distinct dimension of attention-related difficulties [1–3]. Subsequent psychometric research has increasingly suggested that CDS and ADHD symptoms, although substantially correlated, represent related yet distinguishable symptom dimensions. In particular, factor-analytic studies have generally shown that CDS symptoms load separately from ADHD inattention and hyperactivity/impulsivity symptoms across different samples and assessment approaches [3, 4]. These findings provide evidence of structural differentiation, while also indicating that CDS and ADHD symptoms should not be regarded as completely independent or unrelated constructs.

From a measurement perspective, CDS-specific instruments have been developed and refined to assess symptoms such as mental slowness, excessive daydreaming, drowsiness, mental confusion, and cognitive disengagement, while improving differentiation from ADHD-related inattention. For adults, the Adult Concentration Inventory (ACI) is a self-report instrument developed to assess core CDS symptoms and has demonstrated evidence of convergent and discriminant validity in relation to ADHD-inattention and other psychopathology dimensions [5, 6]. For children and adolescents, the CDS scale of the Child and Adolescent Behavior Inventory (CABI) is available in parent-, teacher-, and self-report formats and assesses symptoms involving daydreaming, mental confusion, and hypoactivity [3, 7]. Despite these conceptual and measurement advances, large-scale evidence concerning the symptom epidemiology and demographic distribution of CDS remains limited. Most early investigations focused on clinical samples of children with ADHD [8, 9], whereas large-scale studies involving adults and community samples remain scarce. Becker’s [10] systematic review showed that fewer than ten of more than seventy published CDS studies used epidemiological designs, and most were conducted in the United States or Europe. Consequently, the distribution of elevated CDS symptoms and their demographic correlates remain insufficiently understood across diverse cultural contexts.

The limited available population-based evidence reveals notable variability in the distribution and co-occurrence of elevated CDS and ADHD symptoms. In a nationally representative U.S. sample, Burns and Becker [4] found that approximately 2.6% of children displayed elevated CDS symptoms without elevated ADHD symptoms, 4.5% displayed elevated ADHD symptoms without elevated CDS symptoms, and 2.4% exceeded the symptom thresholds for both constructs. These percentages were based on sample-derived elevated-symptom thresholds and should therefore be understood as symptom classifications rather than clinically diagnosed prevalence estimates. Collectively, these findings indicate substantial but incomplete overlap between elevated CDS and ADHD symptom profiles. However, the occurrence of separate elevated-symptom groups should not be interpreted as evidence of diagnostic independence; rather, it suggests that elevated CDS and ADHD symptoms may occur separately as well as concurrently.

Recent studies have begun to examine possible neurocognitive and neurobiological correlates of CDS, including altered engagement of attention- and vigilance-related systems [11, 12]. However, this evidence remains preliminary and does not establish a specific cognitive or neural hypoactivation mechanism. Because the present study relied exclusively on self-report symptom measures, these neurobiological accounts are considered only as part of the broader theoretical background and were not directly tested. Direct comparative evidence regarding the neurobiological overlap and differences between CDS and ADHD remains limited, and further multimethod research is required before specific mechanistic differences can be established [1, 3].

Beyond attentional symptoms, CDS has been associated with a range of emotional, social, and functional difficulties across cultural contexts. Studies conducted in Turkey, South Korea, Iran, and the United States have linked elevated CDS symptoms to depression, anxiety, social withdrawal, sleep-related problems, and reduced academic and everyday functioning [2, 4, 6, 7, 13, 14]. Comparative findings further suggest that CDS symptoms tend to show stronger associations with internalizing symptoms, conflicted shyness, social withdrawal, and sleep difficulties, whereas ADHD symptoms are more consistently associated with executive-function difficulties, impulsivity, oppositional behavior, and broader externalizing problems [2, 4, 14]. These differences concern the relative strength and pattern of associations rather than an absolute separation between the two symptom dimensions.

Nevertheless, current knowledge remains limited by important methodological and contextual constraints. Many CDS studies have relied on clinical, student, convenience, or otherwise homogeneous samples, and large-scale research from non-Western cultural settings remains comparatively scarce [1, 3]. Although CDS assessment instruments have been validated among Persian-speaking children, adolescents, and adults [6, 7], evidence regarding the distribution of elevated CDS symptoms, their demographic correlates, and their overlap with ADHD symptoms in large Iranian samples remains limited. Accordingly, large-scale Iranian data can contribute valuable descriptive symptom-epidemiological evidence, while not replacing the need for future probability-based studies designed to estimate population prevalence.

From a symptom-epidemiological perspective, examining the distribution of CDS symptoms across age and sex groups may clarify whether elevated symptom levels are concentrated within particular demographic segments. Previous research suggests that age and sex may be relevant demographic correlates of CDS symptoms, although the direction and magnitude of these associations have not been fully consistent across studies [1, 2, 4].However, these patterns have not been examined consistently across cultural settings, and findings from Western probability-based samples may not generalize directly to non-Western convenience samples. Accordingly, examining age- and sex-related differences in a large Iranian sample may provide useful descriptive evidence while requiring cautious interpretation because of the sample’s demographic composition and nonprobability recruitment.

Against this background, the present study aimed to examine the symptom epidemiology of CDS in a large nonprobability sample of Iranian adolescents and adults.The first objective was to describe the distribution of self-reported CDS symptoms and to examine their demographic correlates, particularly differences associated with age and sex. The second objective was to estimate the proportions of participants exceeding alternative sample-based thresholds for elevated CDS symptoms. These thresholds were used as descriptive indicators of elevated symptom levels rather than as clinically validated diagnostic criteria or estimates of population prevalence. The third objective was to examine the association, overlap, and differentiation between CDS and ADHD symptom dimensions in the subsample of participants who completed both measures. Given the substantial conceptual and empirical overlap between CDS and ADHD symptoms, the analyses were intended to evaluate whether the two symptom dimensions showed distinguishable patterns within the present self-report measurement framework, rather than to establish diagnostic separation.

Methods

Study design and objectives

This study employed a large-scale cross-sectional descriptive design to examine the distribution and demographic correlates of self-reported CDS symptoms in a nonprobability sample of Iranian adolescents and adults. Elevated CDS symptom levels were identified using sample-based thresholds and were interpreted as descriptive indicators of symptom elevation rather than clinical diagnoses or estimates of population prevalence. In a second phase, the study examined the association, overlap, and exploratory symptom-level differentiation between CDS and ADHD symptom dimensions among the subsample of participants who completed both self-report measures.

Participants and sampling procedure

Participants were Iranian adolescents and adults aged 15 to 55 years who were recruited using nonprobability convenience and snowball sampling. Recruitment was conducted in Tehran, Tabriz, Mashhad, and Isfahan through schools, universities, workplaces, and public centers, as well as through online survey distribution. Data collection took place between 2021 and 2024 using both in-person and online administration. Approximately 30% of the questionnaires were collected in person and 70% were collected online.

A total of 8,500 CDS questionnaires were initially collected. After removing incomplete or invalid responses, 8,075 valid cases were retained for the main analyses. The mean age of the final sample was 24.8 years (SD = 7.4; range = 15–55). The sample was predominantly female, with 29.2% male and 70.8% female participants, and was largely composed of adolescents and young adults. Therefore, the sample should be considered a large nonprobability sample rather than a nationally representative Iranian population sample.

Among the full sample, 2,200 participants additionally completed the Adult ADHD Self-Report Scale. Following data-quality screening, 2,012 valid cases were retained for the symptom-level comparative analyses involving CDS and ADHD symptom dimensions.

The demographic variables collected for the present analyses were age and sex. No additional demographic variables were included in the current statistical analyses.

Inclusion and exclusion criteria

Participants were eligible if they were between 15 and 55 years of age, fluent in Persian, able to read and write, and provided informed consent. For participants younger than 18 years, parental or legal guardian consent and participant assent were required. As part of the eligibility screening, participants were asked to self-report whether they had a history of major psychiatric disorder; those who reported such a history were not eligible for inclusion.

Cases were excluded if they had more than 10% missing data, patterned or careless responses, out-of-range age values, or inconsistent demographic information. Information regarding psychiatric history was based solely on participant self-report. No structured diagnostic interview, clinician-administered assessment, medical record review, or independent verification of psychiatric or medical history was conducted. Therefore, these criteria should be interpreted as self-reported eligibility and data-quality screening procedures rather than clinical diagnostic screening.

After screening, 8,075 participants were retained for the main CDS symptom analyses, and 2,012 participants were retained for the comparative analyses involving CDS and ADHD symptom dimensions.

Measures

Adult concentration inventory

CDS symptoms were assessed using the Persian version of the Adult Concentration Inventory (ACI), a self-report symptom measure originally developed by Becker et al. [5] to assess core dimensions of cognitive disengagement. The ACI assesses symptoms related to attention problems, slowness, and imagination/mind-wandering. The inventory consists of 16 items rated on a four-point Likert scale ranging from 0, “not at all true,” to 3, “very true.” Total scores range from 0 to 48, with higher scores indicating higher levels of self-reported CDS symptoms. The ACI was used in the present study as a dimensional symptom measure and not as a clinical diagnostic instrument. The Persian version of the Adult Concentration Inventory was validated in an Iranian sample by Abdolmohamadi and Alimohamadi [15]. Their findings supported a three-factor structure comprising attention problems, sluggishness, and mind-wandering, with adequate model fit indices (RMSEA = 0.050, CFI = 0.95, TLI = 0.94, IFI = 0.95, SRMR = 0.03). The scale demonstrated acceptable internal consistency, with Cronbach’s alpha of 0.864 for the total score and subscale alphas ranging from 0.723 to 0.851.

Adult ADHD self-report scale

ADHD symptoms were assessed using the Adult ADHD Self-Report Scale (ASRS-v1.1), developed by Kessler et al. [16] in collaboration with the World Health Organization. The ASRS-v1.1 is a self-report screening measure designed to assess adult ADHD symptoms. It includes 18 items across two symptom dimensions: inattention and hyperactivity/impulsivity, with 9 items for each dimension. Items are rated on a five-point Likert scale ranging from 1, “never,” to 5, “very often.” Higher scores indicate higher levels of self-reported ADHD symptoms. In the present study, the ASRS was used to assess ADHD symptom dimensions and not to establish a clinical diagnosis of ADHD. The Persian version of the ASRS-v1.1 was validated by Mousavi et al. [17], who reported a Cronbach’s alpha of 0.85. In the present sample, Cronbach’s alpha for the ASRS total score was 0.92.

Procedure

Data were collected through both in-person and online administration. In the in-person format, questionnaires were completed individually in settings such as classrooms, universities, workplaces, and public centers. In the online format, participants completed the questionnaires through a secure survey platform accessible by smartphones and computers. Before completing the questionnaires, participants received information about the study purpose, voluntary participation, anonymity, and confidentiality of responses.

All questionnaires were completed as self-report measures without assistance from clinicians or trained interviewers. Responses were recorded electronically and screened for completeness and data quality before statistical analysis.

Ethics approval and consent to participate

All participants received a full explanation of the study objectives and procedures before participation, and participation was voluntary. Informed consent was obtained from adult participants. For participants younger than 18 years, informed consent was obtained from a parent or legal guardian, and assent was obtained from the participants themselves.

Data were collected anonymously, and no personally identifiable information was recorded. The study involved non-interventional, questionnaire-based self-report data collection and did not include clinical diagnostic interviews, clinician-administered assessments, biological sampling, or experimental procedures.

The study protocol was reviewed by the Ethics Committee of Azarbaijan Shahid Madani University. Given the anonymous, non-interventional, self-report nature of the study and the absence of anticipated risk to participants, the committee determined that formal ethics approval and an ethics reference code were not required.

The study was conducted in accordance with the ethical principles of the Declaration of Helsinki and the American Psychological Association’s Ethical Principles of Psychologists and Code of Conduct.

Data analysis

Data were analyzed using SPSS version 26 and R version 4.3.1. SPSS was used for data screening, descriptive statistics, reliability analyses, chi-square tests, logistic regression, and primary tabular outputs. R was used to reproduce and supplement the inferential analyses, calculate effect sizes, and conduct the discriminant function analysis with leave-one-out cross-validation. In R, core statistical analyses were conducted using functions from the base stats package, including t.test(), chisq.test(), cor.test(), and glm(). Effect sizes were calculated using the effectsize package, including Cohen’s d for continuous variables and Cramér’s V for categorical variables. Discriminant function analysis was conducted using lda() from the MASS package, and leave-one-out cross-validation was implemented using the CV = TRUE option in lda(), whereby each case was classified using discriminant functions derived from all remaining cases.

Descriptive statistics, including mean, standard deviation, range, skewness, kurtosis, and Cronbach’s alpha, were calculated for all CDS symptom variables. Because no diagnostically validated clinical cutoffs based on structured clinical interviews are currently available for the Persian ACI in the present context, sample-based percentile thresholds were used to identify elevated CDS symptom levels. The 95th percentile was used as the primary threshold, and the 90th percentile and mean plus 1.5 standard deviations were used as sensitivity thresholds. These thresholds were interpreted as descriptive indicators of elevated self-reported CDS symptoms and not as clinical diagnostic criteria or estimates of population prevalence.

Sex and age-group differences in elevated CDS symptom status were examined using chi-square tests. Linear-by-linear association tests were used to examine ordered age-group trends where appropriate. Cramér’s V was reported as an effect size for categorical comparisons. Binary logistic regression was conducted to examine whether age and sex predicted elevated CDS symptom status, defined as scoring above the 95th-percentile threshold. Odds ratios, 95% confidence intervals, and Nagelkerke R² were reported for the logistic regression model.

To evaluate the comparability of the ASRS subsample, participants who completed both the CDS and ADHD symptom measures (n = 2,012) were compared with participants who completed only the CDS measure (n = 6,063). Welch’s t-tests were used for continuous variables, including age, CDS total score, and CDS subscale scores, with Cohen’s d and 95% confidence intervals reported as effect sizes. Chi-square tests were used for categorical variables, including sex, with Cramér’s V reported as the effect size. Mode of administration was described at the aggregate sample level but was not included in individual-level comparative analyses because it was not coded separately for each participant in the statistical dataset.

In the ASRS subsample, Pearson correlations were calculated to examine associations between CDS and ADHD symptom dimensions. Percentile-based overlap analyses were then conducted using the 90th-percentile thresholds of the CDS and ADHD total scores to classify participants into four symptom-level groups: neither elevated, elevated CDS symptoms only, elevated ADHD symptoms only, or both elevated CDS and ADHD symptoms. These groups were used only for within-sample descriptive and exploratory comparison purposes.

An exploratory discriminant function analysis was conducted to examine whether symptom dimensions and demographic variables differentiated participants with elevated CDS-only and elevated ADHD-only symptom profiles within the present self-report measurement framework. Because the groups and predictors were derived from the same self-report symptom measures, the analysis was interpreted cautiously as an exploratory within-sample differentiation analysis rather than as evidence of diagnostic separation. To reduce potential optimistic bias in classification accuracy, leave-one-out cross-validation was conducted. Both original and cross-validated classification accuracies were reported.

A two-tailed significance level of p < .05 was used for all analyses.

Results

Demographic characteristics

Data from 8,075 participants were analyzed. Of these participants, 29.2% were male and 70.8% were female. The mean age was 24.8 years (SD = 7.4; range = 15–55). The age distribution indicates that the sample was predominantly composed of adolescents and young adults. Therefore, the findings should be interpreted primarily in relation to younger age groups within the broader Iranian community sample.

Descriptive indices of CDS Variables

Table 1 presents the descriptive statistics for the three CDS subscales—Attention, Slowness, and Imagination—and the total CDS score.

Table 1.

Descriptive statistics of CDS variables

Variable	N	Mean	SD	Median	Range	Skewness	Kurtosis	α / r
Attention	8,075	8.68	5.87	8	0–27	0.49	−0.27	α = 0.86 / r = .83
Slowness	8,075	4.55	2.64	4	0–13	0.58	−0.24	α = 0.79 / r = .77
Imagination	8,075	3.87	2.18	4	0–12	0.44	−0.29	α = 0.74 / r = .68
Total CDS	8,075	17.10	9.45	16	0–48	0.56	−0.26	α = 0.91

Note. CDS = Cognitive Disengagement Syndrome; SD = standard deviation; α = Cronbach’s alpha; r = corrected item–total/subscale correlation coefficient

As shown in Table 1, the mean total CDS score was 17.10 (SD = 9.45). The subscales showed comparable variability and approximately normal distributions, with skewness and kurtosis values falling within the acceptable ± 1 range. Cronbach’s alpha for the total scale was excellent (α = 0.91), and subscale reliabilities ranged from 0.74 to 0.86, indicating satisfactory internal consistency. Overall, these findings suggest that the CDS scores showed adequate distributional characteristics and acceptable reliability in the present sample.

Sample-based classification of elevated CDS symptoms

As shown in Table 2, 5.8% of participants exceeded the primary 95th-percentile threshold for elevated CDS symptoms, while 8.3% exceeded the mean + 1.5 SD threshold and 11.3% exceeded the 90th-percentile threshold. The conservative P95 cutoff indicated that approximately 1 in 17 participants showed elevated self-reported CDS symptoms within the present sample.

Table 2.

Overall and sensitivity-based classification of elevated CDS symptoms

Case Definition	Cutoff (Total CDS)	Cases (n)	Percentage exceeding threshold (%)	95% CI
Primary (P95)	34.00	466	5.77	5.28–6.28
Sensitivity 1 (Mean + 1.5 SD)	31.76	667	8.27	7.69–8.88
Sensitivity 2 (P90)	30.00	909	11.27	10.61–11.97

Note. CDS = Cognitive Disengagement Syndrome; CI = confidence interval; P95 = 95th percentile; P90 = 90th percentile; SD = standard deviation. The 95th percentile was used as the primary sample-based threshold for elevated CDS symptoms. Two additional sensitivity thresholds, mean + 1.5 SD and the 90th-percentile cutoff, were applied to examine the stability of elevated symptom classification across alternative sample-based definitions

As shown in Table 3, a higher percentage of females exceeded the P95 threshold for elevated CDS symptoms compared with males, 6.4% versus 4.3%. The percentage of participants exceeding the P95 threshold also decreased across age groups: adolescents aged 15–17 years showed the highest percentage, 9.1%, whereas adults aged 35–55 years showed the lowest percentages, approximately 1–2%. Collectively, these findings indicate that elevated CDS symptom levels were more frequently observed among females and younger participants in the present nonprobability sample, highlighting the importance of considering age- and sex-related factors when examining the demographic distribution of elevated CDS symptoms.

Table 3.

Elevated CDS symptoms based on the P95 threshold by sex and age group

Variable	Group	N	Cases (n)	Percentage exceeding threshold (%)	95% CI
Sex	Male	2,360	102	4.32	3.56–5.22
	Female	5,715	364	6.37	5.76–7.03
Age (years)	15–17	525	48	9.14	6.97–11.91
	18–24	5,080	305	6.00	5.38–6.69
	25–34	1,952	106	5.43	4.51–6.53
	35–44	333	4	1.20	0.47–3.05
	45–55	185	3	1.62	0.55–4.66

Note. Cognitive Disengagement Syndrome; CI = confidence interval; P95 = 95th percentile. Elevated CDS symptoms were defined using the conservative 95th-percentile threshold of the total CDS score

Predictors of CDS

A binary logistic regression was conducted to examine whether age and sex predicted the likelihood of exceeding the P95 threshold for elevated CDS symptoms. The overall model was statistically significant, χ²(2) = 84.21, p < .001, indicating that age and sex collectively contributed to the prediction of elevated CDS symptom classification. The model explained approximately 9.2% of the variance, Nagelkerke R² = 0.092. Although the model correctly classified 94.3% of participants, this classification rate should be interpreted cautiously given the relatively small proportion of participants exceeding the P95 threshold.

As shown in Table 4, both predictors showed significant effects. Females had higher odds than males of exceeding the P95 threshold for elevated CDS symptoms, OR = 1.46, p = .001. Each one-year increase in age was associated with a 6% decrease in the odds of exceeding the P95 threshold, OR = 0.94, p < .001. These findings indicate that younger age and female sex were associated with higher odds of elevated self-reported CDS symptoms in the present nonprobability sample. Developmental and psychosocial explanations for these demographic patterns require further investigation.

Table 4.

Binary logistic regression predicting elevated CDS symptoms based on the P95 threshold

Predictor	β (SE)	Wald	p	OR	95% CI (OR)
Female (vs. Male)	0.38 (0.12)	10.9	0.001	1.46	1.17–1.83
Age (years)	−0.065 (0.008)	60.0	< 0.001	0.94	0.92–0.95
Constant	−1.55 (0.21)	52.4	< 0.001	—	—

Note. Note. CDS = Cognitive Disengagement Syndrome; P95 = 95th percentile; SE = standard error; OR = odds ratio; CI = confidence interval. Elevated CDS symptoms were defined as scoring at or above the P95 threshold on the total CDS score

Phase II: Overlap and distinction between CDS and ADHD

In the second phase of the study, the relationship between CDS and ADHD symptom dimensions was examined to determine their degree of association, overlap, and exploratory symptom-level differentiation. Data were obtained from 2,012 participants who completed both the CDS and ADHD self-report measures. The primary objective of these analyses was to examine whether CDS and ADHD symptom dimensions showed distinguishable patterns within the present self-report measurement framework, while also considering their expected overlap. Accordingly, descriptive indices and intercorrelations between the two symptom dimensions were first analyzed, followed by percentile-based overlap analyses. Finally, an exploratory discriminant function analysis was conducted to examine symptom-level features that differentiated elevated CDS-only and elevated ADHD-only profiles.

Comparability of the ASRS subsample

Before conducting the CDS–ADHD symptom comparison analyses, the ASRS subsample was compared with participants who completed only the CDS measure to evaluate the comparability of the two groups. Participants in the ASRS subsample were slightly older than participants in the CDS-only group, p = .013, although the effect size was negligible, d = 0.07. No statistically significant differences were observed between the two groups in CDS attention, slowness, imagination, or total CDS scores, and all effect sizes were negligible. The sex distribution was also highly similar between the ASRS subsample and the CDS-only group, χ² = 0.10, p = .753, Cramér’s V = 0.003. Overall, these findings indicate that the ASRS subsample was broadly comparable to the CDS-only group in terms of self-reported CDS symptom levels and sex distribution, although a very small age difference was observed. Detailed results are presented in Supplementary Table S1.

As shown in Table 5, all CDS and ADHD symptom variables demonstrated acceptable distributional indices, with skewness and kurtosis values falling within the ± 1 range. The descriptive statistics indicated variability across both CDS and ADHD symptom dimensions. Because the two instruments differ in item content, scoring structure, response format, and score ranges, direct comparison of raw mean scores across CDS and ADHD measures should be avoided. Therefore, these descriptive results were interpreted as preliminary indicators of score variability and were examined further through correlational, overlap, and exploratory discriminant analyses.

Table 5.

Descriptive statistics of CDS and ADHD variables (N = 2,012)

Variable	Mean	SD	Min	Max	Skewness	Kurtosis
CDS – Attention	8.64	5.86	0	27	0.71	0.2
CDS – Slowness	4.52	2.66	0	12	0.6	0.12
CDS – Imagination	3.82	2.21	0	9	0.42	0.18
CDS – Total Score	17.04	9.64	0	48	0.58	0.02
ADHD – Inattention	22.16	6.25	9	45	0.29	0.01
ADHD – Hyperactivity/Impulsivity	22.53	6.06	9	45	0.31	0.03
ADHD – Total Score	44.69	11.29	18	90	0.27	0.04

Note. CDS = Cognitive Disengagement Syndrome; ADHD = attention-deficit/hyperactivity disorder; SD = standard deviation; Min = minimum; Max = maximum. Descriptive statistics are based on the subsample of participants who completed both CDS and ADHD measures

As shown in Table 6, significant positive correlations were observed among all CDS and ADHD symptom dimensions, p < .001. The total CDS and ADHD symptom scores showed a strong association, r = .69, indicating substantial overlap between the two constructs at the self-report symptom level. CDS attention showed the strongest association with ADHD inattention, r = .67, and a more moderate association with ADHD hyperactivity/impulsivity, r = .46. This pattern indicates that CDS and ADHD symptoms share considerable variance, particularly in the attentional domain. At the same time, the correlations were not sufficiently high to indicate redundancy, and the weaker association with hyperactivity/impulsivity suggests some differentiation in symptom profiles. Thus, the findings support the view that CDS and ADHD symptoms are closely related but distinguishable symptom dimensions rather than completely separate or identical constructs.

Table 6.

Intercorrelations between CDS and ADHD symptom dimensions

Variables	1	2	3	4	5	6	7
1. CDS – Attention	—
2. CDS – Slowness	0.51**	—
3. CDS – Imagination	0.40**	0.45**	—
4. CDS – Total	0.87**	0.81**	0.73**	—
5. ADHD – Inattention	0.67**	0.49**	0.35**	0.70**	—
6. ADHD – Hyperactivity/Impulsivity	0.46**	0.42**	0.28**	0.53**	0.75**	—
7. ADHD – Total	0.59**	0.50**	0.36**	0.69**	0.93**	0.92**	—

Note. CDS = Cognitive Disengagement Syndrome; ADHD = attention-deficit/hyperactivity disorder. Values are Pearson correlation coefficients. ** p < .001

Summary of descriptive and correlational findings

Taken together, the descriptive analyses indicated variability across CDS and ADHD symptom dimensions, while the correlational analyses demonstrated a strong association between total CDS and ADHD symptom scores. These findings indicate substantial symptom-level overlap, particularly between CDS attention and ADHD inattention. However, the pattern of correlations also suggests that CDS and ADHD symptoms were not fully redundant, especially given the comparatively weaker association between CDS dimensions and ADHD hyperactivity/impulsivity. These results support the conceptualization of CDS and ADHD symptoms as closely related yet distinguishable symptom dimensions within the present self-report measurement framework. They also provided a basis for subsequent overlap and exploratory differentiation analyses, while requiring cautious interpretation because both constructs were assessed using self-report symptom measures.

Overlap analysis between elevated CDS and ADHD symptom levels

Analytical procedure

To examine the degree of overlap between elevated CDS and ADHD symptom levels, sample-based percentile cutoffs were applied to the total scores of both measures. As shown in Table 7, participants scoring at or above the 90th percentile on each respective scale were classified as having elevated symptom levels for that measure, corresponding to cutoff scores of ≥ 30 for CDS and ≥ 59 for ADHD. These thresholds were used for descriptive within-sample classification and should not be interpreted as clinically validated diagnostic cutoffs.

Table 7.

90th-percentile cutoffs for elevated CDS and ADHD symptoms

Scale	Cutoff (P90)	Definition of “High Score”
CDS Total	30	≥ 30 = CDS High
ADHD Total	59	≥ 59 = ADHD High

Note. CDS = Cognitive Disengagement Syndrome; ADHD = attention-deficit/hyperactivity disorder; P90 = 90th percentile. Elevated symptom classification was based on sample-derived 90th-percentile thresholds

A four-group cross-tabulation was then computed to identify participants with neither elevated symptom level, elevated CDS symptoms only, elevated ADHD symptoms only, or both elevated CDS and ADHD symptoms. This approach was intended to describe the extent to which elevated CDS and ADHD symptom levels occurred separately or concurrently within the ASRS subsample. The overlap results are presented in Table 8.

Table 8.

Cross-classification of elevated CDS and ADHD symptom levels

Group	Count (n)	Percent (%)
Neither High	1701	84.54
Only CDS High	105	5.22
Only ADHD High	107	5.32
Both High	99	4.92

Note. CDS = Cognitive Disengagement Syndrome; ADHD = attention-deficit/hyperactivity disorder. Groups represent symptom-level classifications based on the P90 cutoffs shown in Table 7

As shown in Table 8, the majority of participants, 84.5%, did not show elevated symptom levels on either the CDS or ADHD measure. Elevated CDS symptoms only were observed in 5.2% of participants, while elevated ADHD symptoms only were observed in 5.3%. In addition, 4.9% of participants exceeded the sample-based threshold for both CDS and ADHD symptoms. This pattern indicates meaningful co-occurrence between elevated CDS and ADHD symptom levels, while also showing that elevated symptoms in each domain occurred separately in comparable proportions. Thus, the overlap findings are consistent with the view that CDS and ADHD symptoms are closely related but not fully redundant within the present self-report measurement framework.

Exploratory discriminant function analysis

An exploratory discriminant function analysis was conducted to examine whether CDS symptom dimensions and demographic variables differentiated participants with elevated CDS-only and elevated ADHD-only symptom profiles. The analysis was restricted to participants who exceeded the P90 threshold on one symptom domain but not the other. Attention, slowness, imagination, age, and sex were entered as predictors.

The discriminant function was statistically significant, Wilks’ Λ = 0.374, F(5, 206) = 68.99, p < .001, indicating that the included variables differentiated the elevated CDS-only and elevated ADHD-only symptom profiles within the present sample. Participants with elevated CDS-only profiles showed relatively higher slowness and imagination scores, whereas participants with elevated ADHD-only profiles showed relatively higher attention-related difficulties. Age and sex contributed less strongly to the discriminant function.

Figure 1 presents the distribution of participants along the discriminant function. The figure illustrates separation between the elevated CDS-only and elevated ADHD-only symptom-profile groups, although this separation should be interpreted as exploratory and symptom-based.

Fig. 1.

Distribution of elevated CDS-only and ADHD-only symptom profiles along the discriminant function

The standardized canonical discriminant function coefficients are presented in Table 9.

Table 9.

Standardized discriminant function coefficients

Predictor	Coefficient
Attention	-0.61
Slowness	0.79
Imagination	0.66
Age	-0.15
Sex (Male = 1, Female = 2)	0.08

Note. Positive coefficients indicate stronger association with the elevated CDS-only symptom profile, whereas negative coefficients indicate stronger association with the elevated ADHD-only symptom profile

As shown in Table 9, slowness and imagination contributed most strongly to the elevated CDS-only symptom profile, whereas attention contributed more strongly to the elevated ADHD-only symptom profile. Age and sex made comparatively smaller contributions. This pattern suggests that elevated CDS-only profiles were characterized more by cognitive slowing and imagination/mind-wandering features, whereas elevated ADHD-only profiles were characterized more by attention-related difficulties within the present symptom-based framework.

Classification results for the original and cross-validated discriminant models are presented in Table 10.

Table 10.

Original and cross-validated classification accuracy

Classification method	Overall accuracy	CDS-only correctly classified	ADHD-only correctly classified
Original classification	95.3%	100.0%	90.7%
Leave-one-out cross-validation	93.9%	100.0%	87.9%

Note. CDS-only = participants scoring at or above the 90th percentile on CDS but below the 90th percentile on ADHD; ADHD-only = participants scoring at or above the 90th percentile on ADHD but below the 90th percentile on CDS. Leave-one-out cross-validation classified each case using discriminant functions derived from all remaining cases

As shown in Table 10, the original classification accuracy was 95.3%, with 100.0% of elevated CDS-only cases and 90.7% of elevated ADHD-only cases correctly classified. Leave-one-out cross-validation yielded a similar overall classification accuracy of 93.9%, with 100.0% of elevated CDS-only cases and 87.9% of elevated ADHD-only cases correctly classified.These findings suggest that elevated CDS-only and elevated ADHD-only symptom profiles could be differentiated with high accuracy within the present dataset. However, because the grouping variables and predictors were derived from the same self-report symptom measures, the classification results should be interpreted cautiously. They are best understood as exploratory evidence of symptom-profile differentiation rather than evidence of diagnostic separation. Overall, the discriminant findings are consistent with the overlap analyses in suggesting that CDS and ADHD symptoms are closely related but not fully redundant.

Discussion

Summary of main findings

The present study provides large-scale descriptive symptom-epidemiological evidence on elevated CDS symptoms in a nonprobability sample of Iranian adolescents and adults, integrating demographic, psychometric, and symptom-level differential analyses. Using a conservative sample-based 95th-percentile threshold, 5.8% of participants exceeded the threshold for elevated self-reported CDS symptoms; this percentage should be interpreted as a sample-based indicator of elevated symptomatology rather than as a clinical or population prevalence estimate. Consistent with previous research, elevated CDS symptoms were more frequently observed among females and younger participants, and the percentage exceeding the threshold decreased across older age groups. Importantly, CDS and ADHD symptom scores showed substantial overlap, as reflected in the strong correlation between total scores. Nevertheless, the overlap was not complete: the pattern of correlations, the distribution of elevated CDS-only and ADHD-only symptom profiles, and the exploratory discriminant findings collectively suggested that CDS and ADHD symptoms were empirically distinguishable at the symptom-profile level within the present self-report measurement framework. Thus, the findings support the view that CDS is a closely related but not redundant cognitive-attentional construct in relation to ADHD, rather than merely an ADHD subtype, while avoiding any claim of diagnostic separation [1].

Comparison with previous research

The sample-based elevated-symptom percentages observed in the present study are broadly consistent with international community-based findings, where elevated CDS symptom levels have generally been reported in the approximate range of 2–10%, depending on the measure, informant, sample, and cutoff strategy used [1, 4]. The observed higher percentage of elevated CDS symptoms among females parallels findings from Turkey [14] and South Korea [13], suggesting that sociocultural, developmental, or biological factors may contribute to individual differences in attentional disengagement tendencies. Similarly, the lower percentage of elevated CDS symptoms in older age groups is consistent with developmental perspectives proposing that CDS symptoms may be more prominent during periods in which attentional control and self-regulatory capacities are still maturing [2, 3]. Taken together, these findings extend prior research by providing large-scale evidence from a Middle Eastern context and suggest that elevated CDS symptom patterns may show meaningful cross-cultural similarities.

Theoretical and neurocognitive implications

The observed symptom pattern—particularly mental slowness, daydreaming, cognitive fogginess, and hypoactivity-related features—is consistent with theoretical accounts that conceptualize CDS as involving reduced cognitive engagement and low task-directed activation. However, this interpretation should be limited to the phenomenological and symptom-profile level. Because the present study relied exclusively on cross-sectional self-report questionnaires, it did not directly assess cognitive performance, physiological arousal, or neural activation. Therefore, the findings should be understood as symptom-level evidence compatible with reduced-engagement or hypoactivation-related accounts, rather than as direct evidence for cognitive, physiological, or neural hypoactivation mechanisms.

Within this cautious framework, the findings may be interpreted as consistent with the view that CDS symptoms are characterized more prominently by mental slowness, daydreaming, cognitive fogginess, and low task-directed engagement, whereas ADHD symptoms, particularly hyperactivity/impulsivity, reflect a different pattern of attentional and behavioral difficulties. This contrast should not be understood as evidence of clinical or diagnostic separation, especially given the substantial overlap observed between CDS and ADHD symptom scores. Rather, the present results support a symptom-profile distinction: CDS and ADHD symptoms appear to be closely related and partially overlapping, but not fully redundant, within the present self-report measurement framework.

Future multimethod studies are needed to determine whether the symptom-profile differences observed in the present study correspond to measurable differences in cognitive performance, arousal regulation, or neural functioning. Behavioral attention tasks, processing-speed paradigms, physiological indices, electrophysiological measures, and neuroimaging methods could help clarify whether elevated CDS symptoms are associated with distinct cognitive or neurobiological correlates. Until such evidence is available, the present findings should be interpreted as symptom-level and psychometric evidence of partial differentiation between CDS and ADHD symptoms, rather than as evidence for a specific neurocognitive mechanism.

Cultural and epidemiological considerations

This study represents one of the first large-scale descriptive reports of elevated CDS symptoms in Iran, thereby contributing cross-cultural evidence to the emerging international literature on CDS symptomatology. The relatively higher percentage of elevated CDS symptoms observed among females may reflect gender-related differences in symptom expression, reporting tendencies, sociocultural expectations around concentration and passivity, or broader developmental and contextual factors, as suggested by cross-national comparisons [1, 14]. Similarly, the lower percentage of elevated CDS symptoms in older age groups is consistent with developmental perspectives suggesting that attentional control and self-regulatory capacities may change across adolescence and adulthood, although longitudinal research is needed to clarify developmental trajectories.

Beyond demographic patterns, the present findings may have potential practical relevance for understanding elevated CDS symptoms in educational and occupational contexts. Although elevated CDS symptoms do not necessarily indicate clinical impairment in all individuals, previous research has linked persistent CDS symptoms with emotional dysregulation, depressive symptoms, motivational difficulties, sleep-related problems, and academic underachievement [6, 18]. Accordingly, the present findings may inform future research on screening and early identification of individuals who experience cognitive under-engagement and related functional difficulties, particularly if combined with clinical assessment and measures of impairment.

Limitations and future directions

Several limitations should be acknowledged. First, the cross-sectional design precludes causal inference and limits conclusions regarding developmental change. Although elevated CDS symptoms were less frequent in older age groups, this pattern should not be interpreted as evidence of within-person developmental decline. Longitudinal studies are needed to examine the developmental trajectories of CDS symptoms from adolescence to adulthood and to determine whether elevated CDS symptoms predict later emotional, motivational, academic, occupational, or functional difficulties.

Second, the study used nonprobability convenience and snowball sampling, and the sample was predominantly female and largely composed of adolescents and young adults. Therefore, the findings should be generalized cautiously and should be interpreted as descriptive evidence from a large nonprobability Iranian sample rather than as estimates of population prevalence. In addition, the demographic information available for the present analyses was limited to age and sex. Future studies should use probability-based or stratified sampling designs and include broader demographic, socioeconomic, educational, clinical, and regional variables to clarify the distribution and correlates of elevated CDS symptoms across more representative populations.

Third, elevated CDS symptom status was defined using sample-based percentile thresholds rather than diagnostically validated clinical cutoffs. These thresholds were useful for describing elevated symptom levels within the present sample, but they do not represent clinical diagnostic criteria. Moreover, the study did not include structured diagnostic interviews, clinician-administered assessments, or direct evaluation of functional impairment. As a result, the reported percentages should be interpreted as elevated self-reported CDS symptom levels, not as clinical or epidemiological prevalence estimates of CDS as a disorder or diagnostic condition.

Fourth, all measures were based on self-report questionnaires. Although the instruments used in the present study have demonstrated acceptable psychometric properties, self-report data may be influenced by response bias, shared-method variance, differences in symptom awareness, and individual differences in reporting style. In addition, psychiatric history was based solely on participants’ self-report, and no medical record review, clinician-administered assessment, or independent verification of psychiatric or medical history was conducted. Therefore, unrecognized psychiatric, sleep-related, neurological, or medical conditions may have influenced symptom reporting. Future research should incorporate multi-informant and multimethod assessment strategies, including clinician ratings, structured interviews, collateral reports, and objective measures of impairment.

Fifth, the present study did not include behavioral attention tasks, neuropsychological tests, physiological indices, electrophysiological measures, or neuroimaging data. Consequently, the findings cannot directly test mechanisms related to arousal regulation, cognitive activation, vigilance, processing speed, or neural functioning. Any interpretation of the findings in relation to reduced cognitive engagement or hypoactivation should therefore remain limited to the symptom-profile level. Future studies using behavioral, physiological, and neurobiological methods are needed to determine whether elevated CDS symptoms are associated with distinct cognitive or neural correlates.

Finally, the discriminant function analysis should be interpreted cautiously. The elevated CDS-only and ADHD-only groups were defined using the same symptom measures from which several discriminant predictors were derived. This conceptual and measurement overlap may have inflated classification accuracy, even though leave-one-out cross-validation was used to reduce optimistic bias. Therefore, the discriminant findings should be understood as exploratory evidence of symptom-profile differentiation within the present self-report measurement framework, not as diagnostic accuracy or evidence of diagnostic separation between CDS and ADHD. Future studies should test the differentiation of CDS and ADHD symptoms using independent clinical assessments, external validators, longitudinal outcomes, and multimethod indicators of functioning.

Conclusion

In summary, this study provides large-scale descriptive evidence on elevated CDS symptoms in a nonprobability sample of Iranian adolescents and adults. Using sample-based thresholds, elevated CDS symptom levels were observed in a meaningful minority of participants and showed age- and sex-related differences. In the subsample that completed both CDS and ADHD symptom measures, CDS and ADHD symptoms showed substantial overlap, particularly in the attentional domain. Nevertheless, the correlational pattern, overlap analyses, and exploratory discriminant findings indicated that CDS and ADHD symptom profiles were not fully redundant within the present self-report measurement framework. These findings support the view that CDS is closely related to ADHD symptomatology but retains a partially distinguishable symptom profile, rather than representing merely an ADHD subtype. At the same time, the results should not be interpreted as estimates of clinical prevalence, diagnostic separation, or evidence for a specific neurocognitive mechanism. Future representative, longitudinal, and multimethod studies incorporating clinical assessment, impairment measures, and external validators are needed to clarify the developmental course, functional significance, and cognitive or neurobiological correlates of elevated CDS symptoms.

Supplementary Information

Below is the link to the electronic supplementary material.

Abbreviations

ACI

Adult Concentration Inventory

ADHD

Attention-deficit/hyperactivity disorder

ASRS-v1.1

Adult ADHD Self-Report Scale version 1.1

CDS

Cognitive Disengagement Syndrome

CFI

Comparative Fit Index

CI

Confidence interval

DSM-5-TR

Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision

ICD-11

International Classification of Diseases, 11th Revision

IFI

Incremental Fit Index

OR

Odds ratio

P90

90th percentile

P95

95th percentile

RMSEA

Root Mean Square Error of Approximation

SD

Standard deviation

SE

Standard error

SPSS

Statistical Package for the Social Sciences

SRMR

Standardized Root Mean Square Residual

TLI

Tucker–Lewis Index

WHO

World Health Organization

Author contributions

KA. conceptualized and designed the study, supervised data analysis, and prepared the original manuscript draft. AA. contributed to statistical analyses and interpretation of the findings. DS. provided methodological and theoretical input and contributed to manuscript editing. SB. critically reviewed and revised the manuscript for intellectual content. All authors read and approved the final version of the manuscript.

Funding

This study received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Data availability

The data supporting the findings of this study are available from the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participate

All participants received a full explanation of the study objectives and procedures before participation, and participation was voluntary. Informed consent was obtained from adult participants. For participants younger than 18 years, informed consent was obtained from a parent or legal guardian, and assent was obtained from the participants themselves. Data were collected anonymously, and no personally identifiable information was recorded. The study involved non-interventional, questionnaire-based self-report data collection and did not include clinical diagnostic interviews, clinician-administered assessments, biological sampling, or experimental procedures. The study protocol was reviewed by the Ethics Committee of Azarbaijan Shahid Madani University. Given the anonymous, non-interventional, self-report nature of the study and the absence of anticipated risk to participants, the committee determined that formal ethics approval and an ethics reference code were not required. The study was conducted in accordance with the ethical principles of the Declaration of Helsinki and the American Psychological Association’s Ethical Principles of Psychologists and Code of Conduct.

Consent for publication

Not applicable. The manuscript does not contain any individual person’s identifiable data, images, or videos.

Competing interests

The authors declare no competing interests.