Treating ADHD in a Time of COVID-19

During the covid-19 era, APSARD has been able to connect and lean on our partnerships with other ADHD organizations. CADDRA, the Canadian ADHD Resource Alliance, has partnered with APSARD in the past and present to share information in the ADHD field. APSARD is proud to work alongside CADDRA and encourages its members to utilize the resources highlighted in the CADDRA submitted blog below.

Treating ADHD in a Time of COVID-19

COVID-19 has created a range of challenges for clinicians, including those treating patients with ADHD.

At the end of March, CADDRA – Canadian ADHD Resource Alliance – surveyed its members regarding the impact the continued spread of the virus and subsequent public health measures had on their practices. We heard about their concerns for patients, the impact on practices, and how they are making patient care work during this time.

Not surprisingly, Canadian practices were morphing into virtual care centres and figuring out ways to adapt to a new work environment while the survey also revealed a substantial financial impact on practices.

Respondents to the CADDRA member survey were representative of different disciplines, practice settings and locations.

Rate the extent to which you agree with the following statement: “My ADHD practice has been impacted by COVID-19

The majority (85%) reported their practice was impacted or very impacted by the pandemic. Additionally, 80% reported a financial impact on their practice.

Has the COVID-19 outbreak had a financial impact on your practice?

Several respondents indicated that the biggest difficulty they were facing was the ability to properly assess patients, some citing an inability collect biometrics virtually.

Are you continuing to see patients with ADHD?

New patient consultations have generally reduced, with roughly half (45%) reporting that they were no longer able to see new patients, and 17% seeing existing patients only.

Most respondents (80%) – have switched to virtual care only, while 8.5% continue to provide some in-person with virtual care.

What type of virtual care are you providing?

Switching to virtual care was achieved through a combination of phone, video and email support for just over a third of respondents (35%); just under a third were using phone only (30%) and the same number were using video only; a small number were using email only.

Of those using video, almost half (46%) were using alternative video-conferencing platforms (e.g. Zoom, Skype); 19% were using provincial telemedicine platforms and the same percentage were using private virtual care solutions; other videoconferencing options (FaceTime, WhatsApp) were used by 16%.

More than half reported that the care they are providing patients with ADHD had changed.

Challenges facing practices & patients

Assessments were the biggest problem area identified. However, respondents also discussed issues with accessibility of the virtual tools for patients, and difficulties faced when patients had to conduct an interview in a more distracting home environment.

Asked about what they perceived to be the biggest challenges facing their patients with ADHD, many respondents discussed how anxiety was generally high among patients and families now facing new challenges and increased stress.

Additionally, many patients are dealing with a loss of their routine and now face a much more unstructured schedule. Dealing with boredom and managing to stay productive or active was a common comment – not just for patients, but also for the healthcare professionals surveyed.

How are healthcare professionals staying healthy?

Asked about their personal strategies for navigating this situation, many respondents stressed the importance of staying connected – talking with friends or colleagues, spending time with family (or simply walking the dog more).
Others are taking the time to do yoga or practice mindfulness. A common theme was the importance of maintaining some form of routine.

Strategies for navigating COVID-19

The survey respondents also told us what resources better support patient care during this time would. In response, CADDRA has compiled the following evidence-based information and resources for clinicians and their patients:

In the last few weeks, many of our members sent in ADHD resources, and wellness tips or provided general feedback and we will continue to update our resource pages in the coming weeks based on this information. We invite APSARD members to utilize our resources.

Keep safe, keep healthy.
CADDRA – Canadian ADHD Resource Alliance

ADHD and Race in the School Setting

ADHD and Race in the School Setting

Catherine L. Montgomery & Kevin Antshel, Ph.D.
Department of Psychology
ADHD Lifespan Treatment, Education, and Research (ALTER) Program
Syracuse University

The prevalence rate of ADHD in the United States varies by race/ethnicity; notably, rates of ADHD diagnoses in Black children are estimated to be 65% to 75% of rates of diagnosis in White children of similar SES and symptom severity. (See (Miller, Nigg, & Miller, 2009) for a review of this literature.) ADHD diagnostic practices rely on collecting multiple informant (i.e., parent, teacher, and child) ratings of symptoms. These ratings may be impacted by the actual ADHD symptoms, the context (school v. home) or characteristics about the informant (Kraemer et al., 2003). Over 80% of primary and secondary school teachers are White (U.S. Department of Education, 2017). Thus, one potential contributor to the identified ADHD racial discrepancy rates may be differences in how Black parents and White teachers consider a child’s behaviors.

To investigate this hypothesis, Kang and Harvey (Kang & Harvey, 2019) recently compared ADHD ratings of 71 Black parents (92% female) to those of 60 White teachers (68% female) and 65 White parents (75% female) recruited through Amazon’s Mechanical Turk (MTurk). Participants watched ten 1-minute video clips of children in actual preschool, Kindergarten, 2nd grade and 3rd grade classrooms which were posted publicly on YouTube. Within each classroom, one child served as the target child for participants to rate. Two Black boys, two Black girls, two White boys, two White girls, one Asian boy and one Latina girl served as targets with the order of the children counterbalanced between participants. All participants watched the same 10, 1-minute video clips. Following each video, participants completed Vanderbilt ADHD symptom checklists and rated the likelihood of the target child having ADHD (1 = Very Unlikely – 6 = Very Likely). Only 11 items were used from the Vanderbilt. These 11 items were chosen based off of what could be readily observed from a video. Importantly, the parent and teacher ratings were compared against each other and not an external “gold standard”. Thus, conclusions about the accuracy of a reporter’s ratings could not be reached. Finally, the authors’ also examined beliefs about ADHD stigma, verve (movement expressiveness), experiences with racial discrimination, and racial attitudes as potential explanations for racial differences.

Results indicated:

  • White teachers rated Black boys’ ADHD behaviors (d = .33) and ADHD likelihood (d = .44) higher than Black parents. No differences emerged between White teachers and White parents for Black boys’ ADHD behaviors and ADHD likelihood.
  • No group differences emerged for Black girls, White boys or White girls.
  • Black and White parents aligned well in their ratings of all children except for Black boys.
  • White teachers with more negative racial attitudes gave significantly higher ADHD behavior (r = -.30) and likelihood (r = -.45) ratings to Black boys than those with less negative racial attitudes. Teacher’s racial attitudes were not related to any other child’s ADHD ratings or likelihood.
  • There was a positive relationship between Black parents’ experiences with racial discrimination and ratings of all children’s ADHD behaviors.
  • No group differences emerged for ADHD stigma beliefs.
  • Neither ADHD stigma beliefs nor verve were related to any group’s ratings.

Kang and Harvey reported significant racial differences in ratings of Black boys’ ADHD behaviors and likelihood, a finding which other studies have similarly reported (Harvey, Fischer, Weieneth, Hurwitz, & Sayer, 2013; Lawson, Nissley-Tsiopinis, Nahmias, McConaughy, & Eiraldi, 2017). Kang and Harvey held the context constant (all actual classrooms) and suggest that these differences are due, at least in part, to racial differences in adult perception as opposed to contextual differences present in different settings (e.g., home versus school). Kang and Harvey concluded that it remains unclear if these discrepancies are due to Black parents underestimating Black boys’ symptoms or White teachers overestimating Black boys’ symptoms.

These findings may help to explain the lower rates of ADHD diagnosis in Black children. The DSM-5 criteria emphasize the importance cross-situational symptoms when diagnosing ADHD. If parents and teachers are not reporting the same symptoms at the same severity, then a diagnosis is less likely. Kang and Harvey offered several clinical and practical implications such as the implementation of teacher interventions to reduce the role of racial biases, the provision of more explicit instructions for completing ADHD rating scales, and bringing awareness of these racial discrepancies to clinicians. Additional research on this topic is necessary to further explain the variation in the rates of diagnosis. For example, Black teachers were not recruited for the current study, and including Black teachers may reveal more about the discrepancy. Future research could also consider additional mechanisms that might explain the observed racial differences in adults’ perceptions of ADHD behaviors in Black boys. Finally, a design which includes more than 1-minute of child behavior may enhance the ecological validity of the ratings.

For further reading on this topic, please consider DuPaul’s excellent commentary on this study (DuPaul, 2020).

Citations

DuPaul, G. J. (2020). Adult Ratings of Child ADHD Symptoms: Importance of Race, Role, and Context. J Abnorm Child Psychol. doi:10.1007/s10802-019-00615-5

Harvey, E. A., Fischer, C., Weieneth, J. L., Hurwitz, S. D., & Sayer, A. G. (2013). Predictors of discrepancies between informants’ ratings of preschool-aged children’s behavior: An examination of ethnicity, child characteristics, and family functioning. Early Child Res Q, 28(4), 668-682. doi:10.1016/j.ecresq.2013.05.002

Kang, S., & Harvey, E. A. (2019). Racial Differences Between Black Parents’ and White Teachers’ Perceptions of Attention-Deficit/Hyperactivity Disorder Behavior. J Abnorm Child Psychol. doi:10.1007/s10802-019-00600-y

Kraemer, H. C., Measelle, J. R., Ablow, J. C., Essex, M. J., Boyce, W. T., & Kupfer, D. J. (2003). A new approach to integrating data from multiple informants in psychiatric assessment and research: mixing and matching contexts and perspectives. Am J Psychiatry, 160(9), 1566-1577. doi:10.1176/appi.ajp.160.9.1566

Lawson, G. M., Nissley-Tsiopinis, J., Nahmias, A., McConaughy, S., & Eiraldi, R. (2017). Do parent and teacher report of ADHD symptoms in children differ by SES and racial status? Journal of Psychopathology and Behavior Assessment, 39, 426-440.

Miller, T. W., Nigg, J. T., & Miller, R. L. (2009). Attention deficit hyperactivity disorder in African American children: what can be concluded from the past ten years? Clin Psychol Rev, 29(1), 77-86. doi:10.1016/j.cpr.2008.10.001

U.S. Department of Education, National Center for Education Statistics, Schools and Staffing Survey (SASS), “Public School Teacher Data File,” 2003–04; and National Teacher and Principal Survey (NTPS), “Public School Teacher Data File,” 2015–16. (2017). Public School Teacher Data File, 2003–04 and National Teacher and Principal Survey (NTPS), Public School Teacher Data File, 2015–16. Washington, DC.

 

Do Academic Attainment and Peer Relationships Mediate the Relationship Between ADHD and Depression in Adolescence?

Do Academic Attainment and Peer Relationships Mediate the Relationship Between ADHD and Depression in Adolescence?

Jessica Simmons, M.A.
Kevin Antshel, Ph.D.
Department of Psychology
ADHD Lifespan Treatment, Education and Research (ALTER) program
Syracuse University

Studies have found that nearly 25-30% of youth with ADHD meet criteria for depression, however the mechanisms behind this association are less understood. In work by Meinzer and colleagues1, two pathways explaining this association have been suggested. The first pathway suggests that the ADHD and depression comorbidity is based upon similar etiological variables which contribute to both disorders (e.g., complex interactions between contextual, genetic, biological, cognitive, and interpersonal variables). The second pathway posits that depression comorbidities are secondary to the associated functional impairments commonly reported in ADHD. For example, youth with ADHD will most likely experience a number of functional impairments which mediate the relationship between ADHD symptoms and depression.

Two areas of functional impairments that are widely studied in children with ADHD are their peer relationships and academic functioning. It has been well-established that youth with ADHD struggle with a host of social deficits. Specifically, research has shown that problems with inattention can limit opportunities to learn social skills through observational learning and attend to social cues needed to fit in with their peers. Likewise, hyperactive and impulsive behaviors may be interpreted as overbearing, annoying, and aggressive by peers. Additionally, research on academic problems among children with ADHD has shown that these youth tend to have difficulty attending to class content, often forget to record homework assignments, fail to turn-in classwork, and struggle with time management when completing long-term projects and studying for exams.

Recently, a longitudinal study by Powell and colleagues2   examined whether ADHD symptoms in children would predict late-adolescent onset of depressive symptoms, and also, if academic attainment and peer problems mediated this relationship. Data were collected from an ongoing prospective population-based study based in the UK. For the primary relationship between ADHD and depression, data from 2,950 individuals were analyzed. ADHD symptoms were collected when the children were 7.5 years old and depressive symptoms were collected at 17.5 years old. Results confirmed that childhood ADHD symptoms predicted later depressive symptoms. While there was not a significant interaction between ADHD symptoms and sex in predicting depression symptom scores, the relationship was slightly stronger in females than males.

Next, to assess whether academic attainment and peer problems mediated the relationship between childhood ADHD and adolescent depression, data from 2,161 individuals were analyzed. Academic attainment, measured using formal end-of-school-year evaluations, and mother-reported peer problems were both collected when the child was 16 years old. Analyses were adjusted for mother’s socioeconomic status (determined by occupation and maternal age at birth) and child’s sex to account for the potential of these variables confounding all three pathways tested in the mediation model. Results of the mediation model analyses indicated that both academic attainment and peer problems mediated the association of ADHD symptoms and depressive symptoms, explaining 12.5% and 14.7% of the association respectively. Notably, peer problems remained a mediator of this relationship even when one item in the peer problems measure, which assessed for bullying victimization, was removed, suggesting that children identified as bullying victims were not the only children with ADHD at risk for depressive symptoms.

The results of the Powell et al. study are important for understanding the association between ADHD and depression. For many years, the connection between ADHD and depression has been acknowledged, however, a lack of longitudinal and mediation studies have stifled our ability to identify causal mechanisms. Powell and colleagues’ study not only contributes to the ADHD literature by showing that academic attainment and peer problems in young people with ADHD contribute to the later development of depressive symptoms, but it also encourages us to individualize prevention techniques in our clinical work, and design longitudinal research studies to further expand our understanding of the relationship between ADHD and depression.

1Meizner, M. C., Pettit, J. W., & Viswesvaran, C. (2014). The co-occurrence of attention-deficit/hyperactivity disorder and unipolar depression in children and adolescents: A meta-analytic review. Clinical Psychology Review, 34, 595-607. doi: 10.1016/j.cpr.2014.10.002

2 Powell, V., Riglin, L., Hammerton, G., Eyre, O., Martin, J., Anney, R., … & Rice R. (2020). What explains the link between childhood ADHD and adolescent depression? Investigating the role of peer relationships and academic attainment. European Child & Adolescent Psychiatry. https://doi-org.libezproxy2.syr.edu/10.1007/s00787-019-01463-w

 

Can Computers Train the Brain to Cure ADHD?

Can Computers Train the Brain to Cure ADHD?

It sound like science fiction, but scientists have been testing computerized methods to train the brains of ADHD people with the goal of reducing both ADHD symptoms and cognitive deficits such as difficulties with memory or attention.   Two main approaches have been used: cognitive training and neurofeedback.

Cognitive training methods ask patients to practice tasks aimed at teaching specific skills such as retaining information in memory or inhibiting impulsive responses.  Currently, results from ADHD brain studies suggests that the ADHD brain is not very different from the non-ADHD brain, but that ADHD leads to small differences in the structure, organization and functioning of the brain.  The idea behind cognitive training is that the brain can be reorganized to accomplish tasks through a structured learning process.  Cognitive retraining helps people who have suffered brain damage so was logical to think it might help the types of brain differences seen in ADHD people.  Several software packages have been created to deliver cognitive training sessions to ADHD people.  You can read more about these methods here: Sonuga-Barke, E., D. Brandeis, et al. (2014). “Computer-based cognitive training for ADHD: a review of current evidence.” Child Adolesc Psychiatr Clin N Am 23(4): 807-824.

Neurofeedback was applied to ADHD after it had been observed, in many studies, that people with ADHD have unusual brain waves as measured by the electroencephalogram (EEG).  We believe that these unusual brain waves are caused by the different way that the ADHD brain processes information.  Because these differences lead to problems with memory, attention, inhibiting responses and other areas of cognition and behavior, it was believed that normalizing the brain waves might reduce ADHD symptoms.  In a neurofeedback session, patients sit with a computer that reads their brain waves via wires connected to their head.  The patient is asked to do a task on the computer that is known to produce a specific type of brain wave.   The computer gives feedback via sound or a visual on the computer screen that tells the patient how ‘normal’ their brain waves are.  By modifying their behavior, patients learn to change their brain waves.  The method is called neurofeedback because it gives patients direct feedback about how their brains are processing information.

Both cognitive training and neurofeedback have been extensively studied.  If you’ve been reading my blogs about ADHD, you know that I play by the rules of evidenced based medicine.  My view is that the only way to be sure that a treatment  ‘works’ is to see what researchers have published in scientific journals.   The highest level of evidence is a meta-analysis of randomized controlled clinical trials.   For my lay readers, that means that that many rigorous studies have been conducted and summarized with a sophisticated mathematical method.   Although both cognitive training and neurofeedback are rational methods based on good science, meta-analyses suggest that they are not helpful for reducing ADHD symptoms.  They may be helpful for specific problems such as problems with memory, but more work is needed to be certain if that is true.

The future may bring better news about these methods if they are modified and become more effective.  You can learn more about non-pharmacologic treatments for ADHD from a book I recently edited: Faraone, S. V. & Antshel, K. M. (2014). ADHD: Non-Pharmacologic Interventions. Child Adolesc Psychiatr Clin N Am 23, xiii-xiv.