People with ADHD often struggle to sustain focus, filter out distractions, and regulate their attention.
This can manifest as difficulty completing tasks, forgetfulness, frequent shifts in attention, overlooking details, and trouble organizing thoughts or activities.
These challenges can impact various aspects of daily life, including work, relationships, and personal goals.
Xiang, J., Wang, X., & Feng, T. (2024). The attention network characteristics of adults with high ADHD traits: Low stability, boost accuracy by sacrificing response time. Frontiers in Psychology, 15, 1477581. https://doi.org/10.3389/fpsyg.2024.1477581
Key Points
- Adults with high ADHD traits (H-ADHD) exhibit deficits in sustained attention (alerting network), attentional stability, and overall attentional performance.
- H-ADHD-I (inattentive subtype) shows a unique “high accuracy-slow response” pattern in overall attentional performance.
- Attentional variability mediates the impact of ADHD symptoms on overall attentional performance more significantly than the alerting network.
- All H-ADHD groups (inattentive, hyperactive-impulsive, and combined subtypes) show higher intra-individual coefficient of variation (ICV) compared to control groups.
- The study emphasizes the importance of considering attentional variability in adult ADHD research and interventions.
- No significant differences were found in the executive control network between H-ADHD groups and controls, contrary to some previous findings in children with ADHD.
- The study suggests that alerting network, ICV, and balanced integration score (BIS) could be potential supplementary diagnostic indicators for ADHD in adults.
Rationale
Attention-Deficit/Hyperactivity Disorder (ADHD) affects 8.0% of children and adolescents worldwide, with about 2.58% continuing to have symptoms into adulthood (Ayano et al., 2023; Song et al., 2021).
Adult ADHD often presents with more prominent inattention symptoms, leading to challenges in various life domains (Kooij et al., 2019; Faraone et al., 2015).
Despite the prevalence of attention deficits in adult ADHD, understanding their specific patterns remains a critical area of investigation.
The Attention Network Model, proposed by Posner and colleagues, categorizes attention into three networks: alerting, orienting, and executive control (Posner and Petersen, 1990; Fan et al., 2005).
The Attention Network Test (ANT) developed by Fan et al. (2002) offers a comprehensive approach to assessing these networks.
However, findings regarding the performance of adults with ADHD on the ANT have been inconsistent, particularly concerning the executive control network (Oberlin et al., 2005; Kim and Kim, 2021; Lundervold et al., 2011; Coll-Martin et al., 2021).
This study aims to examine the attentional characteristics of adults with high ADHD traits using the ANT and investigate how specific attentional qualities influence overall attentional performance.
By focusing on high ADHD traits in adults, the research contributes to understanding potential issues and improving diagnostic accuracy and treatment planning.
Method
The study employed the Attention Network Test (ANT) to assess attention network performance in adults with high ADHD traits.
Participants completed the Adult ADHD Self-Report Scale (ASRS) and were categorized into high ADHD traits groups and control groups based on their scores.
The study analyzed three major metrics: attention network efficiency (ANE), balanced integration score (BIS), and intra-individual coefficient of variation (ICV).
Procedure
Participants completed the ASRS either online or offline. Those who passed the deception check were invited to complete the ANT task.
The ANT involved a 10-minute task with different cue conditions and target stimuli. Participants responded to targets while different cues were presented, allowing for the measurement of alerting, orienting, and executive control networks.
Sample
The initial sample consisted of 430 participants recruited in Chongqing, China. After exclusions based on various criteria, the final sample sizes were:
- 339 participants for attention network analysis
- 335 participants for speed-accuracy balance analysis
- 325 participants for reaction time variability analysis
- 317 participants for mediation analysis
Participants were aged 18-24 years (mean age = 21.00, SD = 0.91), with 101 males and 282 Han-Chinese.
Measures
- Adult ADHD Self-Report Scale (ASRS): Used to assess current ADHD symptoms.
- Attention Network Test (ANT): Used to evaluate alerting, orienting, and executive control networks.
- Intra-individual coefficient of variation (ICV): Calculated to measure attentional variability.
- Balanced integration score (BIS): Used to assess overall attentional performance.
Statistical measures
The study used bootstrap tests for group comparisons, cluster analysis for reaction time and accuracy patterns, correlation analysis, and parallel mediation models.
Analysis of covariance (ANCOVA) was used in supplementary analyses to control for anxiety and depression.
Results
H1: Adults with high ADHD traits will show impairments in the alerting network, executive control network, attentional variability (ICV), and overall attentional performance (BIS).
Results: Partially supported. All H-ADHD groups showed deficits in the alerting network and higher ICV. H-ADHD-I and H-ADHD-C groups demonstrated lower BIS. However, no significant differences were found in the executive control network.
H2: More severe ADHD symptoms will lead to poorer attentional qualities and, consequently, diminished overall attentional performance (BIS).
Results: Supported. Attentional variability (ICV) mediated the relationship between ADHD symptoms and overall attentional performance (BIS). The alerting network did not show a significant mediating effect.
Insight
The study reveals distinct attentional deficits in adults with high ADHD traits, primarily in sustained attention and attentional stability.
Interestingly, the H-ADHD-I group showed a unique “high accuracy-slow response” pattern, suggesting they can achieve high accuracy by sacrificing response time.
This finding challenges the notion that individuals with ADHD always perform poorly and highlights their potential to excel when given sufficient time.
The absence of significant differences in the executive control network between H-ADHD groups and controls contrasts with some previous findings in children with ADHD.
This suggests that adults may develop compensatory mechanisms for executive control deficits over time, while foundational functions like sustained attention remain challenging to naturally compensate for in adulthood.
The study emphasizes the importance of attentional variability in understanding ADHD symptoms’ impact on overall performance.
This insight could lead to more targeted interventions focusing on improving attentional stability rather than solely on specific attention networks.
Future research could explore the development of cognitive training programs based on ICV and the alerting network to help adults with ADHD enhance their attention persistence and stability.
Additionally, investigating the relationship between attentional characteristics and various life outcomes (e.g., academic performance, job satisfaction) in adults with high ADHD traits could provide valuable insights for tailored support strategies.
Implications
The findings have significant implications for clinical practice and future research:
- Diagnostic tools: The study suggests that alerting network efficiency, ICV, and BIS could serve as supplementary diagnostic indicators for adult ADHD, potentially improving the accuracy of assessments.
- Intervention strategies: The “high accuracy-slow response” pattern observed in the H-ADHD-I group implies that providing extended time for task completion could be an effective strategy in educational and occupational settings.
- Treatment focus: The importance of attentional variability in mediating ADHD symptoms’ impact on overall performance suggests that interventions targeting attentional stability might be particularly beneficial.
- Career counseling: Understanding the attentional characteristics of individuals with high ADHD traits can inform career counseling, helping to design suitable work environments and task schedules that leverage their strengths.
- Research direction: The study highlights the need for more research on attentional variability in adult ADHD, potentially leading to new theoretical frameworks and intervention approaches.
- Educational accommodations: The findings support the use of extended time accommodations for students with ADHD traits in academic settings, as they can achieve high accuracy when given sufficient time.
- Workplace adaptations: Employers could use these insights to create more ADHD-friendly work environments, potentially improving job performance and satisfaction for employees with high ADHD traits.
Strengths
The study had many methodological strengths including:
- Comprehensive assessment of attention using multiple metrics (ANE, ICV, BIS)
- Large sample size for robust statistical analyses
- Inclusion of supplementary analyses controlling for anxiety and depression
- Use of advanced statistical techniques like bootstrap tests and mediation models
- Consideration of different ADHD subtypes (inattentive, hyperactive-impulsive, combined)
- Integration of both categorical (group comparisons) and dimensional (correlation and mediation) approaches to ADHD symptoms
Limitations
This study also had several methodological limitations, including:
- The study focused on adults with high ADHD traits rather than clinically diagnosed ADHD, which may limit generalizability to clinical populations.
- The sample was predominantly young adults (18-24 years) from a single geographical location (Chongqing, China), potentially limiting generalizability to other age groups and cultures.
- The use of self-report measures for ADHD symptoms may be subject to reporting biases.
- The cross-sectional design limits causal inferences about the relationships between ADHD symptoms, attentional qualities, and overall performance.
- The study did not include measures of functional outcomes (e.g., academic or occupational performance), which could have provided additional context for the attentional findings.
- The ANT, while comprehensive, may not capture all aspects of real-world attentional demands.
These limitations suggest the need for future studies with clinically diagnosed ADHD populations, diverse age groups and cultural contexts, and longitudinal designs to confirm and extend the current findings.
References
Primary reference
Xiang, J., Wang, X., & Feng, T. (2024). The attention network characteristics of adults with high ADHD traits: Low stability, boost accuracy by sacrificing response time. Frontiers in Psychology, 15, 1477581. https://doi.org/10.3389/fpsyg.2024.1477581
Other references
Ayano, G., Demelash, S., Gizachew, Y., Tsegay, L., & Alati, R. (2023). The global prevalence of attention deficit hyperactivity disorder in children and adolescents: An umbrella review of meta-analyses. Journal of affective disorders, 339, 860-866. https://doi.org/10.1016/j.jad.2023.07.071
Coll‐Martín, T., Carretero‐Dios, H., & Lupiáñez, J. (2021). Attentional networks, vigilance, and distraction as a function of attention‐deficit/hyperactivity disorder symptoms in an adult community sample. British Journal of Psychology, 112(4), 1053-1079. https://doi.org/10.1111/bjop.12513
Fan, J., McCandliss, B. D., Fossella, J., Flombaum, J. I., & Posner, M. I. (2005). The activation of attentional networks. Neuroimage, 26(2), 471-479. https://doi.org/10.1016/j.neuroimage.2005.02.004
Fan, J., McCandliss, B. D., Sommer, T., Raz, A., & Posner, M. I. (2002). Testing the efficiency and independence of attentional networks. Journal of Cognitive Neuroscience, 14, 340-347.
Faraone, S. V., Asherson, P., Banaschewski, T., Biederman, J., Buitelaar, J. K., Ramos-Quiroga, J. A., … & Franke, B. (2015). Attention-deficit/hyperactivity disorder. Nature Reviews Disease Primers, 1, 1-23.
Kim, K., & Kim, H. J. (2021). Normal executive attention but abnormal orienting attention in individuals with sluggish cognitive tempo. International Journal of Clinical and Health Psychology, 21(1), 100199. https://doi.org/10.1016/j.ijchp.2020.08.003
Kooij, J. J. S., Bijlenga, D., Salerno, L., Jaeschke, R., Bitter, I., Balazs, J., … & Asherson, P. (2019). Updated European Consensus Statement on diagnosis and treatment of adult ADHD. European psychiatry, 56(1), 14-34.
Lundervold, A. J., Adolfsdottir, S., Halleland, H., Halmøy, A., Plessen, K., & Haavik, J. (2011). Attention Network Test in adults with ADHD-the impact of affective fluctuations. Behavioral and Brain Functions, 7, 1-8. https://doi.org/10.1186/1744-9081-7-27
Oberlin, B. G., Alford, J. L., & Marrocco, R. T. (2005). Normal attention orienting but abnormal stimulus alerting and conflict effect in combined subtype of ADHD. Behavioural brain research, 165(1), 1-11. https://doi.org/10.1016/j.bbr.2005.06.041
Posner, M. I., & Petersen, S. E. (1990). The attention system of the human brain. Annual Review of Neuroscience, 13, 25-42.
Song, P., Zha, M., Yang, Q., Zhang, Y., Li, X., & Rudan, I. (2021). The prevalence of adult attention-deficit hyperactivity disorder: A global systematic review and meta-analysis. Journal of Global Health, 11, 04009. https://doi.org/10.7189/jogh.11.04009
Keep Learning
Socratic questions for a college class to discuss this paper:
- How might the “high accuracy-slow response” pattern observed in adults with high inattentive ADHD traits influence our understanding of ADHD’s impact on academic and professional performance?
- What ethical considerations should be taken into account when using attentional measures as diagnostic tools for ADHD in adults?
- How might cultural differences affect the manifestation and assessment of ADHD symptoms in adults? How could future research address this?
- Given the findings on attentional variability, how might we redesign educational or work environments to better support individuals with high ADHD traits?
- What are the potential implications of the lack of significant differences in the executive control network between H-ADHD groups and controls? How does this challenge or support existing theories about ADHD?
- How might the insights from this study inform the development of more effective cognitive training programs or interventions for adults with ADHD?
- Considering the limitations of the study, what would be the most crucial next steps in researching adult ADHD and attention networks?
- How might the findings of this study influence public perception and policies regarding accommodations for individuals with ADHD in educational and professional settings?
