Comorbidity and Factors Affecting Treatment Non-Persistence in ADHD

Abstract

Objective: The aim of the study was to identify factors for treatment non-persistence in patients with ADHD. Method: Data for 100 patients with ADHD aged 5 to 16 who completed the Kiddie-Schedule for Affective Disorders and Schizophrenia–Present and Lifetime Version–Korean Version (K-SADS-PL-K) and Korean Wechsler Intelligence Scale for Children (K-WISC) were obtained between 2008 and 2013. Patients were classified as treatment-persistent and treatment-non-persistent based on 6-month follow-up. Sociodemographic data, comorbidities, intelligence quotient (IQ), severity, and social/school functioning were compared. Results: Adolescence and poor parental spousal relationships significantly predicted treatment non-persistence. Although comorbid major depressive disorder and absence of transient tic disorder were associated with treatment non-persistence, there was no difference in overall psychiatric comorbidity. No differences existed for IQ, Clinical Global Impressions–Severity (CGI-S) score, peer relationships, and academic achievement. Conclusion: Lower treatment persistence was associated with adolescence, comorbid depression, absence of tics, and poor parental spousal relationships, but not with symptom severity or impairment of the disorder.

Keywords

ADHD comorbidity K-SADS treatment persistence

ADHD is a common neurobehavioral disorder with childhood onset characterized by diminished sustained attention and high levels of impulsivity. Despite having normal intelligence, individuals with ADHD experience impairment in academic, social, and family functioning due to deficits in executive function (Hechtman, 2005). In the past, ADHD was thought to be confined to childhood, but now, it is considered to be a more prevalent, persistent, and disabling condition with an increased risk for psychiatric comorbidity throughout adolescence and adulthood (Faraone, Biederman, & Mick, 2006; Turgay et al., 2012).

Globally, the prevalence of ADHD was reported to be 5.3% (Polanczyk, de Lima, Horta, Biederman, & Rohde, 2007), and its comorbidity rates were estimated to be more than 50% (Pliszka, 2003; Wilens et al., 2002). In South Korea, several epidemiologic studies have shown the prevalence and comorbidity rates to be 2% to 13% and 33% to 82%, respectively (Ahn & Yoo, 2009; Byun et al., 2006; J. Y. Kim, Ahn, & Shin, 1999; J. Y. Kim et al., 2005; S. J. Yang, Cheong, & Hong, 2006; Y. H. Yang, Kim, Kim, Cho, & Kim, 2008; Yoo et al., 2005).

Although the effectiveness of long-term use of psychostimulants has been shown to minimize developmental interference (Murray-Close et al., 2010) and lifelong problems, such as criminality, unemployment, and psychiatric comorbidity, a substantial portion of patients with ADHD remain untreated or sub-optimally treated (Froehlich et al., 2007). Many studies have shown variable and consistently disappointing compliance rates for medication and have demonstrated that the majority of treatment dropouts occurred within the first 6 months (Garbe et al., 2012; Y. J. Kim et al., 2010; Lawson, Johnsrud, Hodgkins, Sasané, & Crismon, 2012; Perwien, Hall, Swensen, & Swindle, 2004). In South Korea, studies have shown that only approximately 60% of patients complied with treatment for the first 6 to 12 months (Hwang, Kim, & Cho, 2004; Y. J. Kim et al., 2010).

Therefore, it is very important to take into account factors affecting treatment persistence to enhance favorable long-term outcomes. Although several factors have been identified, including socioeconomic status, age, sex, severity, comorbidity, parental status, and attitude toward diagnosis and treatment, results across studies are variable (Brinkman & Epstein, 2011; Brinkman et al., 2009; Gadow, Nolan, Sverd, Sprafkin, & Schwartz, 2002; Gajria et al., 2014; Hwang et al., 2004; Jensen et al., 2007; Y. J. Kim et al., 2010; Lee et al., 2002; McCarthy et al., 2009; Perring, 1997; Rieppi et al., 2002; Thiruchelvam, Charach, & Schachar, 2001). Among them, psychiatric comorbidity is associated with the likelihood of core symptoms persisting into adulthood (Spetie & Arnold, 2007) and may distinctly influence illness severity, prognosis, and treatment response, ultimately affecting treatment persistence (Biederman, 1998; Biederman, Faraone, Milberger, Guite, et al., 1996; Jensen et al., 2001). For example, ADHD patients with comorbid externalizing disorders, such as oppositional defiant disorder (ODD) or conduct disorder, often refuse treatment (Biederman, Faraone, Milberger, Curtis, et al., 1996; Thiruchelvam et al., 2001). The influence of comorbid depression and anxiety on treatment response and persistence has demonstrated contradictory results (Diamond, Tannock, & Schachar, 1999; DuPaul, Barkley, & McMurray, 1994; Gadow et al., 2002; Lee et al., 2002; MTA Cooperative Group, 1999; Pliszka, 1998; Thiruchelvam et al., 2001).

Given the existing research, the aim of the present study was to identify factors related to treatment persistence in children and adolescents with ADHD. We did so through a review of medical records of patients who completed the Kiddie-Schedule for Affective Disorders and Schizophrenia–Present and Lifetime Version–Korean Version (K-SADS-PL-K; Y. S. Kim et al., 2004) and the Korean Wechsler Intelligence Scale for Children (K-WISC; Kwak, Park, & Kim, 2001). To our knowledge, this is the first time the K-SADS-PL-K, a semi-structured interview extensively used to assess psychiatric morbidity in children and adolescents, has been used to investigate factors affecting treatment persistence in Korea.

Method

This study was a retrospective analysis. Participants included 113 patients with ADHD who completed the K-SADS-PL-K and K-WISC-III or -IV between 2008 and 2013, whose data were extracted from the medical records of a university hospital. Diagnoses were made by a child and adolescent psychiatrist based on the Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; DSM-IV-TR; American Psychiatric Association, 2000). Inclusion criteria included being aged 5 to 16 at the time the K-SADS-PL-K was completed, and treatment was initiated. In addition, 13 patients with neurological disorders, mental retardation, or schizophrenia were excluded, leading to our final sample size of 100 (Figure 1). We obtained institutional review board (IRB) approval from Inje University Sanggye Paik Hospital to review, analyze, and report these findings.

Figure 1.

Sample distribution of patients with ADHD.

Procedure

Patients were classified into either the treatment-persistent (n = 43) or treatment-non-persistent group (n = 57). The treatment-non-persistent group was defined as those who discontinued clinic visits prior to 6 months after their first visit to the hospital. This cutoff is based on prior research suggesting that treatment discontinuation was highest in the first 6 months of treatment and that this is a critical period for treatment persistence (Garbe et al., 2012; Y. J. Kim et al., 2010; Lawson et al., 2012). Data analysis included group comparisons regarding sociodemographic data, comorbidities, IQ, symptom severity, and school and social functioning.

Measures

The K-SADS-PL-K (Y. S. Kim et al., 2004) is a comprehensive, semi-structured interview used to objectively assess prior and current psychopathology in children and adolescents (32 psychiatric disorders) according to DSM-IV (APA, 1994) criteria. Y. S. Kim et al. translated the K-SADS-PL-K into Korean in 2004 and showed good to excellent reliability and validity for diagnosing ADHD, ODD, and tic disorders. An unstructured introductory interview to collect sociodemographic information, such as family status, school adaptation, and social relationships, is also included in the K-SADS-PL-K. Based on the answers to the open-ended questions in the unstructured introductory interview, spousal relationships of parents were classified as good, usual, or poor; academic achievement as high, moderate, or low; and peer relationships as good or poor. All interviews were conducted with participants and their parents at the first or second visit. Interviewers were psychiatry residents who received a 1-hr lecture as training in the use of the K-SADS-PL-K.

The K-WISC-III is a test to assess intelligence of children and adolescents aged 6 to 16. It was developed by Kwak et al. (2001) and was based on the Wechsler Intelligence Scale for Children–III (WISC-III). The K-WISC-III was used in Sanggye Paik hospital until it was replaced by the K-WISC-IV in December 2012. The K-WISC-IV was developed based on the WISC-IV in 2011. In this revision, three subtests were eliminated from the WISC-III, and five new subtests were introduced (Kwak, Oh, & Kim, 2011). Interviewers were master’s-level clinical psychologists.

The Clinical Global Impressions–Severity scale (CGI-S) is a single-item instrument used by clinicians to assess the global severity of illness based on the clinician’s total experience with the patient (Guy, 1976). It is rated using a 7-point scale from 1 (not at all ill) to 7 (extremely ill). The CGI-S score was given at the time of diagnosis.

Statistical Analysis

All analyses were performed using SAS Enterprise 4.2 (SAS Institute Inc., Cary, North Carolina, USA), and p < .05 was considered statistically significant. Characteristics between the treatment-persistent and treatment-non-persistent groups were compared using student’s t tests and chi-square tests. Fisher’s exact test was used in cases that did not satisfy the smallest expected frequencies.

Results

Sociodemographics and Clinical Characteristics

Participants included 25 adolescents aged 12 to 16 and 75 children aged 5 to 11. The mean age (± SD) was 9.38 ± 2.82 years. The mean age (± SD) of the treatment-persistent and treatment-non-persistent groups was 8.88 ± 2.52 and 9.75 ± 2.99 years, respectively. The treatment-non-persistent group (n = 57) had a significantly higher proportion of adolescents (33.3% vs. 14.0% [χ² = 4.91, p = .03]) than the treatment-persistent group (n = 43), although age differences at the time of the first visit were not statistically significant between groups (Table 1).

Table 1.

Comparison of Variables in the Treatment-Persistent and Non-Persistent Groups.

Variables	Total patients (n = 100)	Treatment-persistent (n = 43)	Treatment-non-persistent (n = 57)	p value	χ²
Age, M ± SD	9.38 ± 2.82	8.88 ± 2.52	9.75 ± 2.99	.13
Children (age 5-11)	75	37 (86.05%)	38 (66.67%)
Adolescents (age 12-16)	25	6 (13.95%)	19 (33.33%)	.03	4.91
Sex				.18	1.80
Boys	88	40 (93.02%)	48 (84.21%)
Girls	12	3 (6.98%)	9 (15.79%)
Total IQ, M ± SD	94.76 ± 12.93	96.79 ± 13.89	93.23 ± 12.05	.17
Comorbidity				.49	0.52
Non-comorbid ADHD	47	22 (51.16%)	25 (43.86%)
Comorbid ADHD	53	21 (48.84%)	22 (56.14%)
Number of comorbid disorders, M ± SD	0.72 ± 0.79	0.60 ± 0.66	0.81 ± 0.88	.21
Peer relations				.44	0.60
Good	67	27 (62.79%)	40 (70.18%)
Poor	33	16 (37.21%)	17 (29.82%)
Family state (n = 94)
Living with one parent	7	2 (5.26%)	5 (8.93%)	.50	0.44
Living with both parents	87	36 (94.74%)	51 (91.07%)
Parental relationship (n = 87)
Good	55 (63.2%)	22 (61.11%)	33 (64.71%)
Usual	15 (17.2%)	10 (27.78%)	5 (9.80%)
Poor	17 (19.5%)	4 (11.11%)	13 (25.49%)	.04	6.23
Father’s age (n = 83), M ± SD	41.9 ± 4.83	40.97 ± 5.28	42.57 ± 4.41	.13
Mother’s age (n = 85), M ± SD	39.4 ± 4.92	39.31 ± 4.66	39.44 ± 5.14	.91
Academic achievement (n = 89)				.98	0.03
High	20 (22.5%)	8 (21.62%)	12 (23.08%)
Middle	50 (56.2%)	21 (56.76%)	29 (55.77%)
Low	19 (21.3%)	8 (21.62%)	11 (21.15%)
CGI-S (n = 82)				.91	0.01
Low (1-4)	21 (25.6%)	9 (25.00%)	12 (26.09%)
High (5-7)	61 (74.4%)	27 (75.00%)	34 (73.91%)
Months from onset to the first visit (n = 95), M ± SD	36.39 ± 27.76	34.63 ± 24.19	37.67 ± 30.24	.60

Note. IQ = intelligence quotient; CGI-S = Clinical Global Impressions–Severity scale.

The majority of participants were boys (n = 88), and the mean number of months from onset to the first visit was 36.69 ± 4.92. The mean period of treatment persistence (±SD) in the treatment-persistent group was 550.91 days (±465.13), whereas it was 62.47 days (±45.81) in the treatment-non-persistent group. Mean total IQ (±SD) was 94.76 ± 12.93. Mean total IQ of the treatment-persistent group was higher than that of the treatment-non-persistent group, but these differences were not statistically significant. Of the 100 patients in our study, we identified 82 with CGI-S ratings. Among them, 61 (74.4%) were rated as having a score of 5 (markedly ill) or higher, and there was no significant correlation between treatment persistence and CGI-S score. In addition, there was no significant difference between the two groups with regard to sex, parental age, marital status of parents, peer relationships, and academic achievement. However, there were significantly greater numbers of patients who had parents with poor spousal relationships in the treatment-non-persistent group (25.5% vs. 11.1% [χ² = 6.23, p = .04]; Table 1).

Patterns of Comorbidity

In our sample, 52 of the 100 patients had at least one comorbid psychiatric disorder. The comorbidity rates of the treatment-persistent group and treatment-non-persistent group were 48.84% and 56.14%, respectively, and this difference was not statistically significant. The mean number of comorbid disorders was not significantly different between the treatment-persistent and treatment-non-persistent groups (Table 1). The most common comorbid disorder was ODD (n = 16), followed by transient tic disorder (n = 13). Patients with comorbid transient tic disorder were more likely to be treatment-persistent (7.0% vs. 20.9% [χ² = 4.19, p = .04]). Major depressive disorder (n = 7) was the third most common comorbid disorder, all of which were found in the treatment-non-persistent group (12.3% vs. 0%, p = .02). Otherwise, there was no significant difference with respect to other major psychiatric comorbidity (Table 2).

Table 2.

Differences in Psychiatric Comorbidity Variables Between the Treatment-Persistent and Treatment-Non-Persistent Groups.

Psychiatric diagnoses	Total patients (n = 100)	Treatment-persistent (n = 43)	Treatment-non-persistent (n = 57)
Psychiatric diagnoses	n (%)	n (%)	n (%)	p value	χ²
Diagnosis based on K-SADS-PL-K
Tic disorders	16 (16.00)	9 (20.93)	7 (12.28)	.24	1.36
Chronic motor or vocal tic disorder	2 (2.00)	0 (0.00)	2 (3.51)	.50	^a
Transient tic disorder	13 (13.00)	9 (20.93)	4 (7.02)	.04	4.19
Tourette’s disorder	1 (1.00)	0 (0.00)	1 (1.75)	1.00	^a
Mood disorders
Major depressive disorder	7 (7.00)	0 (0.00)	7 (12.28)	.02	^a
Disrupted behavior disorders	17 (17.00)	6 (13.95)	11 (19.30)	.48	0.50
ODD	16 (16.00)	5 (11.63)	11 (19.30)	.30	1.07
Conduct disorder	1 (1.00)	1 (2.33)	0 (0.00)	.43	^a
Anxiety disorders	11^b (11.00)	3 (6.98)	8 (14.04)	.26	1.25
Separation anxiety disorder	3^b (3.00)	1 (2.33)	2 (3.51)	1.00	^a
Acute stress disorder	1 (1.00)	0 (0.00)	1 (1.75)	1.00	^a
PTSD	4^b (4.00)	1 (2.33)	3 (5.26)	.63	^a
Social phobia	3 (3.00)	1 (2.33)	2 (3.51)	1.00	^a
GAD	1 (1.00)	0 (0.00)	1 (1.75)	1.00	^a
Elimination disorders
Enuresis	3 (3.00)	1 (2.33)	2 (3.51)	1.00	^a
Diagnosis not covered by K-SADS-PL-K
Learning disorder	4 (4.00)	0 (0.00)	4 (7.02)	.13	^a
Communication disorder	5 (5.00)	3 (6.98)	2 (3.51)	.65	^a
Impulse-control disorder not elsewhere classified	3 (3.00)	1 (2.33)	2 (3.51)	1.00	^a
Somatoform disorder	2 (2.00)	0 (0.00)	2 (3.51)	.50	^a
Sleep disorder	1 (1.00)	1 (2.33)	0 (0.00)	.43	^a

Note. K-SADS-PL-K = Kiddie-Schedule for Affective Disorders and Schizophrenia–Present and Lifetime Version–Korean Version; ODD = oppositional defiant disorder; PTSD = posttraumatic stress disorder; GAD = generalized anxiety disorder.

Fisher’s exact test was used.

One patient had both separation anxiety disorder and PTSD.

Discussion

In our study, the treatment persistence rate at 6-month follow-up was 43.0%. This is substantially lower than results of previous studies in South Korea, which found rates of 62.0% in the first year and 62.3% during the first 6 months (Hwang et al., 2004; Y. J. Kim et al., 2010). One reason for this may be the prospective design of previous studies, which promoted treatment engagement in patients and/or their parents. The rate found in our study is comparable with results of retrospective studies conducted in the United States (Ahmed & Aslani, 2013; Marcus, Wan, Kemner, & Olfson, 2005; Perwien et al., 2004; van den Ban et al., 2010). Considering differences in outcome by sites across studies, further investigation is necessary to examine site differences, as treatment settings, prescriber, cost, and health insurance have also been identified as factors affecting ADHD treatment persistence (van den Ban et al., 2010).

Consistent with previous studies, we found that adolescence is associated with lower persistence. It is well documented that adolescents show rebellious behavior and disagreement with parents or authority (Tebbi, 1993). As in other childhood illness, parental attitude toward ADHD plays an important role in initiating and continuing treatment (Brinkman et al., 2009). However, as adolescents develop autonomy, parents are less involved in their child’s disease management. This developmental evolution from parental dependency to autonomy often causes poorer outcomes in many chronic illnesses, showing higher rates of non-compliance for adolescents compared with children or adults (Gavin, Wamboldt, Sorokin, Levy, & Wamboldt, 1999; Tebbi, 1993). Distinct symptom profiles of adolescents with ADHD also might play a role for treatment non-persistence. Patients and parents of higher rates of hyperactivity report a higher degree of satisfaction with medication (B. S. Kim & Park, 2005), but overt symptoms of hyperactivity decline with increasing age. It might make adolescent patients underestimate their symptoms and finally doubt their diagnosis and treatment (Turgay et al., 2012; Wolraich et al., 2005).

In addition, compared with patients who had parents of usual spousal relationships, patients who had parents of poor spousal relationships had a greater likelihood of treatment non-persistence. Having parents with poor spousal relationships is assumed to substantially impact family functioning. As previously outlined, parents play a key role in decision making for the treatment of their child or adolescent (Brinkman et al., 2009), and positive family communication is associated with adherence to treatment (Bobrow, AvRuskin, & Siller, 1985; Miller & Drotar, 2007; Wysocki, 1993). Thus, parental conflict may impede consideration with regard to treatment initiation and continuity and, consequently, weaken parental influence on children and adolescents who naturally lack insight into the illness. Although other parental factors, such as age, education level, and socioeconomic status, were suggested in prior studies, those correlations with treatment persistence were not identified nor investigated in this study.

In contrast to prior research (Ahmed & Aslani, 2013; Gadow et al., 2002; Y. J. Kim et al., 2010) suggesting that psychiatric comorbidity and ADHD severity lead patients and parents to become more adherent to treatment, we observed no significant differences between groups with regard to overall rates or numbers of comorbid disorders or illness severity. Consistent with previous research, ODD was the most prevalent comorbid disorder in our study (Byun et al., 2006; Wilens et al., 2002), but we did not find a relationship between the presence of ODD and treatment persistence. Comorbid ODD has been identified as a factor related to poor medication adherence in adolescents (Thiruchelvam et al., 2001); however, in childhood, when parents have a greater responsibility in decision making, it may be a predictor of increased adherence (Charach & Fernandez, 2013).

We did discover a relationship between treatment persistence and transient tic disorder and major depressive disorder, the second and third most common comorbid disorders, respectively. It might be reasonable to assume that these comorbid disorders influence patient treatment motivation. More patients with transient tic disorder persisted with treatment. Comorbid tic disorder is known to have only a limited impact on the course, outcome, and treatment of ADHD (Spencer et al., 2001). However, tics are characterized by abnormal movements or vocalizations that are easily observed by others and might cause embarrassment or distress at school. These symptomatic features may motivate children and adolescents with tics to persist in treatment. However, this pattern disappeared when analyzing patients with a chronic motor or vocal tic disorder or Tourette’s disorder, which require more than 1 year of symptom duration for diagnosis. All patients with ADHD and comorbid major depressive disorder discontinued treatment before 6 months. Depression is one of the well-known adherence influencing factors in chronic medical illnesses such as asthma and diabetes mellitus, especially among adolescents, sometimes leading to deaths (Baucom et al., 2015; Bender, 2006). Loss of energy, cognitive decline, and pessimistic expectations aggravated by depression might diminish patients’ willingness to take responsibility for their treatment and erode illness self-management (DiMatteo, Lepper, & Croghan, 2000; Wing, Phelan, & Tate, 2002). This adherence behavior has been proposed as an important mediator between depression and poorer treatment outcome in many diseases.

It was surprising that illness severity and functional impairment were not significantly correlated with treatment persistence. However, this may have been related to methodological concerns, as these factors were rated based on indirect information such as the CGI-S and unstructured questions from the K-SADS-PL-K about peer relationships and academic achievement. Thus, results are based on subjective clinical impressions and open-ended self-reports, and lack objective assessment. Although the influence of symptom severity on treatment persistence is inconsistent across studies, we propose that ADHD severity is not critical for treatment persistence in children and adolescents, given that they usually have limited insight into their illness. In fact, the majority of patients with ADHD visit psychiatric clinics at the request of others and persisting in treatment may not be acceptable for them. Therefore, additional effort or obedience to parents or doctors is required for long-term treatment. In this context, adolescence, comorbid depression, and poorer parental support may produce a negative effect on parental influence and willingness of children and adolescents to continue visiting psychiatric clinics and adhering to medication. Thus, clinicians should focus on patients’ developmental status and motivation as well as family or parental functioning in addition to the therapeutic alliance. Indeed, there is evidence that children and adolescents with high levels of family distress are more likely to be interested in physician’s aid with the proposition of the so-called compensatory alliance (Gavin et al., 1999; Hahn, Feiner, & Bellin, 1988).

There are several limitations to this study. First, data were obtained retrospectively without the use of a structured protocol, and there were some missing reports in the medical records leading to missing data. This could negatively affect the accuracy of our results, particularly as the sample size was not large. Further research with a larger sample size is required for more adequate analysis. Second, our findings cannot be generalized, as all diagnoses and severity ratings were made by only one child and adolescent psychiatrist with possible personal bias. Likewise, K-SADS-PL-K interviews were performed by many psychiatric residents with unknown inter-rater reliability. Third, because data were not available for parental factors other than their age and marital status, we could not examine the impact of other factors that may have influenced treatment persistence, including parental education level, socioeconomic status, and attitude toward diagnosis and treatment. Fourth, the K-WISC-III was used until December 2012, and the K-WISC-IV was used thereafter. This might have had some, although probably minimal, impact on our data. Finally, we did not consider formulation type, efficacy, side effects, and adherence to prescribed medication. Future prospective studies should encompass multi-sites with larger sample sizes and be designed using structured interviews at the time of an initial hospital visit, to analyze factors affecting treatment persistence.

Conclusion

This study suggests that adolescence, comorbid depression, absence of tics, and poor parental relationships are associated with lower persistence of ADHD treatment. We hypothesize that those factors affect patients’ motivation for treatment more than the severity of symptoms or impairment of the disorder does. Thus, clinicians should focus on patients’ developmental status and comorbidity, as well as family or parental functioning, to make an adequate treatment plan and achieve higher persistence of treatment in children and adolescents with ADHD.

Footnotes

Declaration of Conflicting Interests

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

Funding

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

Author Biographies

Jiung Park, MD, is a resident physician in Department of Psychiatry at Inje University Sanggye Paik Hospital.

Bongseog Kim, MD, PhD, is a professor of child and adolescent psychiatry in the Department of Psychiatry at Inje University Sanggye Paik Hospital.

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