Stimulant shortage in children with ADHD: greater vulnerability among those with comorbidity

Abstract

Background

The aim of this study was to examine stimulant access difficulties among school-aged children with attention-deficit/hyperactivity disorder (ADHD) in Turkey, family strategies to obtain medications, and access-related medication changes, and to evaluate their associations with irritability, emotional, behavioral, social, academic, and sleep difficulties by psychiatric comorbidity.

Methods

A cross-sectional study was conducted with 149 children aged 6–16 years diagnosed with ADHD and treated with methylphenidate-based stimulants, the only stimulant medications available for pediatric ADHD in Turkey, for at least three months. Data were collected using a sociodemographic form, the Medication Shortage Experience Assessment Form, and standardized parent-report scales, including the DSM-5 Level 2 Irritability Scale, Strengths and Difficulties Questionnaire (SDQ), and Sleep Disturbance Scale for Children (SDSC). Group comparisons were performed according to medication change and comorbidity status, followed by multivariable Generalized Linear Models (GZLM) to evaluate interaction effects between these variables.

Results

Nearly all parents (97.3%) reported difficulties, and 55.7% required medication switching due to shortages. Medication changes were associated with significantly greater perceived impacts on physical and mental health (77.1% vs. 42.4%, p < .001) and on academic and social functioning (69.9% vs. 51.5%, p = .022). In children who underwent medication changes, those with psychiatric comorbidities showed significantly higher irritability, emotional symptoms, conduct problems, peer relationship issues, and total SDQ difficulty scores compared with non-comorbid peers. GZLM interaction analyses formally confirmed these findings, showing that the combination of medication change and psychiatric comorbidity significantly predicted higher irritability (B = 2.65, p = .017), sleep arousal disorders (B = 1.12, p = .028), and total sleep disturbances (B = 9.56, p = .043). Notably, interaction coefficients were positive across nearly all psychometric scales, indicating a synergistic worsening of symptoms, except for prosocial behavior, which showed an expected negative coefficient.

Conclusions

Stimulant shortage is highly prevalent and disrupt treatment continuity in children with ADHD in Turkey. Those with psychiatric comorbidities appear particularly sensitive to medication changes, with our findings formally demonstrating a synergistic interaction that amplifies clinical vulnerability. These results highlight the need for coordinated supply systems and targeted psychosocial support to mitigate the emotional and functional consequences of stimulant unavailability.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12888-026-07958-6.

Introduction

Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders of childhood [1]. ADHD manifests in children as symptoms of hyperactivity, impulsivity, and/or inattention [2]. These symptoms impact cognitive, academic, behavioral, emotional, and social functioning [3]. Treatment for individuals with ADHD may be pharmacological, non-pharmacological, or a combination of both. Medications approved by the U.S. Food and Drug Administration (FDA) include stimulants (amphetamines and methylphenidate) and non-stimulants (atomoxetine, extended-release clonidine, and guanfacine) [3]. For school-aged children, evidence-based treatment typically involves a combination of pharmacotherapy and behavioral interventions, with behavioral therapies emphasized for younger children and pharmacotherapy becoming the primary modality in adolescents (≥ 12 years) [4]. Stimulants, including methylphenidate and amphetamines, are considered first-line pharmacological treatments for ADHD in most international guidelines [5].

Significant challenges have emerged in the global supply of stimulant medications, including both methylphenidate- and amphetamine-based formulations, in recent years. FDA announced a nationwide shortage of mixed amphetamine salts (commercially known as Adderall and Mydayis) in October 2022 [6]. Subsequently, access to other prescription stimulant medications, such as methylphenidate and lisdexamfetamine, has also become increasingly difficult [7]. The national safety alert issued by NHS England in 2023 and the subsequent supply problems have highlighted the critical importance of the continuous availability of these medications, as well as inadequacies within healthcare systems [8]. A similar trend is becoming evident in Turkey as well. In Turkey, methylphenidate is the only stimulant medication approved and available for pediatric ADHD treatment; atomoxetine and guanfacine are used exclusively as non-stimulant options. These supply issues have significant implications for children with ADHD. Limited accessibility to these medications negatively affects the continuity of treatment and, consequently, the overall health status of children with ADHD [9].

The global impact of these shortages is profound, with reports indicating that approximately 10% to 18% of the ADHD pediatric population has experienced medication interruptions or forced switches [8, 10]. Emerging evidence suggests that this crisis exacerbates socioeconomic and geographic disparities, as families with limited resources face greater challenges in navigating pharmacy searches and travel [11]. Despite extensive documentation of prescription trends and qualitative experiences [9, 12], there remains a critical research gap regarding how these shortages specifically interact with clinical profiles, such as psychiatric comorbidity, particularly in regions such as Turkey, where pharmacological options are strictly limited.

This research gap is especially pertinent to the Turkish clinical landscape, where the absence of amphetamine-based alternatives significantly limits pharmacological flexibility when methylphenidate supplies are disrupted. Although stimulant medication shortages have become an increasingly common clinical concern in recent years, their real-world impact on children with ADHD and their families has not been systematically examined in Turkey. Identifying how such access difficulties and forced medication changes affect children’s functioning and well-being is therefore of particular clinical importance. The aim of this study was to investigate the extent of difficulties experienced by school-aged children diagnosed with ADHD in Turkey in accessing stimulant medications, the strategies used to obtain them, and the frequency of medication changes resulting from access problems. Furthermore, the study aimed to compare the levels of social, academic, emotional, and behavioral difficulties, sleep disturbances, and irritability among children who frequently changed medications due to stimulant access problems, and to examine whether these associations varied according to the presence of psychiatric comorbidity.

Methods

Study design, date, setting and ethics

This study was designed as a single-center, cross-sectional study and was conducted at the Department of Child and Adolescent Psychiatry, Ankara Etlik City Hospital between April 2025 and August 2025. Prior to participation, written informed consent was obtained from the parents and verbal assent was obtained from the children. All study procedures were conducted in accordance with the Declaration of Helsinki and local laws and regulations.

Participants and study sample

The sample size was determined using G*Power 3.1. A medium effect size of 0.5, an alpha value of 0.05, and a statistical power of 80%, the minimum required sample size was calculated to be 128 participants.

Inclusion criteria were as follows: participants had to be between 6 and 16 years of age, have a diagnosis of ADHD by a child psychiatrist according to DSM-5 criteria, be currently receiving stimulant medication (methylphenidate-based, which is the only stimulant medication available for pediatric ADHD treatment in Turkey) for at least three months, and provide informed consent by a parent or legal guardian to participate in the study. Exclusion criteria included the presence of a physical and/or mental illness in the parent that would prevent completion of the study forms (e.g., severe visual or hearing impairment, neurological disorders affecting motor or cognitive functioning, or active psychiatric conditions including major depressive disorder, psychosis, or intellectual disability), as well as illiteracy. These exclusionary criteria for parents were assessed based on their self-reported clinical history, current psychiatric treatment status, and direct clinical observation of their ability to comprehend and complete the study forms during the initial interview. Psychiatric comorbidities were not grounds for exclusion. All comorbid diagnoses were current and confirmed via clinical interviews and relevant K-SADS-PL modules. Participants with at least one comorbid condition were assigned to the comorbid group for primary analyses. To maintain internal validity, the reasons for any potential medication changes were meticulously investigated through a review of psychiatric clinical interview notes and medical records. Cases involving complex adjustments necessitated by routine clinical factors, such as dose optimization or side effects, were not included in the study, thereby ensuring that the analyzed data primarily reflect disruptions associated with the medication shortage.

During the study period, 168 children diagnosed with ADHD attended the study center. Of these, four children did not meet the age inclusion criteria, and seven children had been receiving medication for less than three months. Three children were being followed with non-pharmacological interventions. Two parents were illiterate, and two parents were unable to complete the forms due to illness. One child declined to participate. As a result, 149 children who met all inclusion criteria were included in the study.

Measures

Sociodemographic Data Form

This researcher-developed form collected data on the child’s age, gender, ADHD treatments, physical disorders, and parental characteristics (age, education, and psychiatric history).

Medication Shortage Experience Assessment Form: This form was developed to systematically document families’ experiences during the national stimulant medication shortage. The items were adapted from the semi-structured interview framework used by Johnson et al., with modifications to reflect the clinical and pharmaceutical context in Turkey [9]. To ensure content validity, the draft form was independently reviewed by two child and adolescent psychiatrists for clarity and clinical relevance. Subsequently, a pilot study (cognitive testing) was conducted with 10 parents of children with ADHD to identify and resolve any ambiguities in the questions; minor linguistic adjustments were made based on their feedback. The form consists of 27 items covering the following domains: (1) demographic and clinical characteristics of the child; (2) access to stimulant medications and frequency of medication changes; (3) effects of shortages on ADHD symptoms, academic functioning, emotions, and peer relationships; (4) coping strategies used by families; (5) interactions with the healthcare system; and (6) parental perceptions and concerns about future shortages. All items specifically referred to a defined six-month time frame to capture cumulative experience. The form includes multiple-choice, checkbox, and open-ended questions. It is not a scale and does not yield a total score or cutoff value; instead, each item was analyzed individually and reported descriptively in the Results section. The full instrument is provided as Supplementary Material.

Schedule for Affective Disorders and Schizophrenia for School-Age Children—Present and Lifetime Version (K-SADS-PL)

The K-SADS-PL is a semi-structured diagnostic interview used to assess past and current psychopathology in children and adolescents [13]. It is administered to both the parents and the child. The Turkish DSM-5 adaptation of the instrument has demonstrated strong psychometric properties, with consensual validity coefficients ranging from κ = 0.67 to 1.00, inter-rater reliability between κ = 0.63 and 1.00, and test–retest reliability between κ = 0.63 and 0.82 [14].

The DSM-5 Level 2 Irritability Scale-Parent Form

This 7-item parent-report scale measures emotional reactivity in children and adolescents aged 6–17 years [15]. Items are rated on a 3-point scale (0–2), with higher scores indicating greater irritability and emotional reactivity [16]. The Turkish version, validated by Yalın Sapmaz et al., demonstrated strong psychometric properties, including high internal consistency (Cronbach’s α = 0.886). Factor analysis revealed a single-factor structure explaining 59.9% of the total variance, with a Kaiser-Meyer-Olkin coefficient of 0.897. Furthermore, concurrent validity was supported by a significant correlation with the irritability item of the Parent Young Mania Rating Scale (r = .522, p < .0001) [17].

The Strengths and Difficulties Questionnaire-Parent Form (SDQ)

The SDQ is a widely used screening tool for identifying mental health problems in children and adolescents [18]. It includes 25 items covering five subscales. The sum of the first four subscales yields a total difficulties score, with higher scores (except in the prosocial domain) indicating greater behavioral problems. The Turkish version has demonstrated good validity and reliability (Cronbach’s α = 0.73) [19].

Sleep Disturbance Scale for Children (SDSC)

Developed by Bruni et al. (1996), the SDSC is a parent-report Likert-type scale assessing sleep disturbances in children aged 6–16 years during the past six months [20]. Each item is rated on a five-point scale, with higher scores indicating more severe sleep disturbances [20, 21]. The Turkish version of the scale was validated by Ağadayı et al. (2020) following a rigorous translation process, including forward-translation, expert panel review, back-translation, and pilot testing [21]. The Turkish adaptation demonstrated acceptable psychometric properties, with a Cronbach’s α of 0.79 and adequate fit indices in confirmatory factor analysis (RMSEA = 0.055, CFI = 0.845, GFI = 0.875, X²/ df = 2.003) [21].

Statistical analysis

All analyses were conducted using IBM SPSS Statistics 27.0 (IBM Corp., Armonk, NY, USA). The distribution of continuous variables was evaluated using histograms and the Shapiro–Wilk test. Data are presented as mean ± SD or median (25th–75th percentile), and categorical variables as frequencies and percentages. Group comparisons were performed using Pearson’s chi-square, independent samples t, or Mann–Whitney U tests as appropriate. Effect sizes were calculated to estimate the magnitude of differences: Cohen’s d for t-tests, r (Z/√N) for Mann–Whitney U tests, and Cramer’s V for chi-square tests. Generalized Linear Models (GZLM) were employed to examine the associations between medication change, psychiatric comorbidity, and psychometric scale scores (DSM-5 Level 2 Irritability, SDQ, and SDSC). Models were adjusted for relevant covariates, including child age, sex, family income, maternal education, medication duration, and concomitant psychotropic use. Interaction terms (medication change × psychiatric comorbidity) were included to evaluate synergistic impacts. GZLM analyses utilized Huber-White robust standard errors to account for non-normality or heteroscedasticity. Finally, to investigate daily functioning, coping strategies, and healthcare-related perceptions, separate multivariable binary logistic regression models were conducted based on the presence or absence of each reported symptom/experience. These models included medication change as the primary predictor, adjusted for relevant covariates and the interaction term. For all multivariable models, standard assumptions, including absence of multicollinearity, linearity of the logit for continuous variables, and adherence to the events per variable criterion to ensure model stability, were tested and met [22, 23]. Statistical significance was defined as p < .05, with nominal p-values reported without adjustment for multiple comparisons due to the exploratory nature of the study.

Results

Sociodemographic and clinical characteristics

The participants had a mean age of M = 10.68 years (SD = 3.13), and most were male (n = 108, 72.5%). Regarding peer relationships, n = 43 (28.9%) of participants reported having many friends, n = 58 (38.9%) had few friends, and n = 48 (32.2%) reported difficulty maintaining friendships. The mean maternal and paternal ages were M = 38.9 years (SD = 6.45) and M = 42.48 years (SD = 7.67), respectively. A high education level (> 8 years, WHO classification) was reported for mothers (n = 104, 70.7%) and fathers (n = 103, 72.0%). According to Hollingshead socioeconomic status criteria [24], family income was low in n = 27 (18.1%), middle in n = 77 (51.7%), and high in n = 45 (30.2%).

The combined ADHD presentation was most common (n = 120, 80.5%), followed by inattentive (n = 22, 14.8%) and hyperactive/impulsive (n = 7, 4.7%) presentations. Psychiatric comorbidity was present in n = 85 (57.0%) of participants, most frequently specific learning disorder (n = 39, 45.9%), oppositional defiant disorder (n = 13, 15.3%), and speech disorder (n = 11, 12.9%). Detailed sociodemographic and clinical characteristics are presented in Table 1.

Table 1.

Sociodemographic and clinical characteristics of children with ADHD (n = 149)

Variable	n (%) or mean ± SD
Age, years	10.68 ± 3.13
Gender
Male	108 (72.5)
Female	41 (27.5)
Peer relationship
Many friends	43 (28.9)
Few friends	58 (38.9)
Difficulty maintaining	48 (32.2)
Mother’s age	38.90 ± 6.45
Mother’s education level*
Low education	43 (29.3)
High education	104 (70.7)
Father’s age	42.48 ± 7.67
Father’s education level*
Low education	40 (28.0)
High education	103 (72.0)
Family income level
Low	27 (18.1)
Middle	77 (51.7)
High	45 (30.2)
ADHD presentation
Combined presentation	120 (80.5)
Inattentive presentation	22 (14.8)
Hyperactive/impulsive presentation	7 (4.7)
Psychiatric comorbidity
No comorbidity	64 (43.0)
Single comorbidity	71 (47.7)
≥2 comorbidities	14 (9.3)
Types of psychiatric comorbidity
Specific learning disorder	39 (45.9)
Oppositional defiant disorder	13 (15.3)
Speech disorder	11 (12.9)
Anxiety disorder	10 (11.8)
Conduct disorder	9 (10.6)
Intellectual disability	9 (10.6)
Autism spectrum disorder	4 (4.7)
Depression	3 (3.5)
Tic disorder	2 (2.4)
Other	4 (4.7)

Note. Values are presented as n (%) or mean ± SD. The numbers in parentheses (%) indicate frequencies. n indicates the number of participants

*Maternal and paternal education categorized as low (≤ 8 years) and high (> 8 years) according to WHO classification

SD, standard deviation; ADHD, attention deficit/hyperactivity disorder

Parental reports on stimulant medication shortages and their impact on treatment

Among 149 parents of children with ADHD, n = 145 (97.3%) reported difficulty accessing stimulant medications. The most commonly experienced access problems included pharmacy stock-outs (n = 122, 81.9%), the need to call multiple pharmacies (n = 116, 77.9%), and driving long distances to obtain medication (n = 88, 59.1%). Some parents reported obtaining medications from another city by shipment (n = 48, 32.2%), encountering partial availability of prescribed drugs (n = 68, 45.6%), or switching to an alternative medication (n = 37, 24.8%) (Fig. 1). Overall, a total of 83 participants (55.7%) had to change their child’s medication at least once due to stimulant shortage. Among these participants, n = 37 (24.8%) switched once, n = 24 (16.1%) twice, and n = 22 (14.8%) three or more times between stimulant medication formulations. Despite these challenges, most parents (n = 124, 83.2%) indicated that their child was currently using the most beneficial medication. Regarding treatment effectiveness following medication changes, n = 30 (36.1%) reported decreased treatment benefit, n = 26 (31.3%) reported no change, n = 18 (21.7%) reported adverse effects, n = 12 (14.5%) reported no benefit, and n = 11 (13.3%) reported increased benefit (Table 2).

Fig. 1.

Parent-reported types of access difficulties in obtaining stimulant medications among children with ADHD. Note: Multiple responses were permitted; therefore, percentages do not sum to 100%

Table 2.

Parent-reported experiences regarding stimulant medication shortages and their impact on treatment (n = 149)*

Variable	n (%)
Stimulant medication access difficulty	145 (97.3)
Type of access difficulties**
Pharmacy stock-outs	122 (81.9)
Multiple pharmacy calls	116 (77.9)
Long-distance travel	88 (59.1)
Out-of-city shipments	48 (32.2)
Partial prescription fills	68 (45.6)
Medication switching	37 (24.8)
Medication change due to shortage	83 (55.7)
Frequency of medication change due to shortage
Once	37 (24.8)
Twice	24 (16.1)
Three times or more	22 (14.8)
Current use of the most beneficial medication
Yes	124 (83.2)
No	25 (16.8)
Impact of medication shortage on treatment effectiveness***
No change	26 (31.3)
Decreased benefit	30 (36.1)
Increased benefit	11 (13.3)
No benefit	12 (14.5)
Adverse effects	18 (21.7)

Note. Values are presented as n (%). The numbers in parentheses (%) indicate frequencies. n indicates the number of participants

* Stimulant medications refer to methylphenidate formulations prescribed for ADHD

** Multiple responses were allowed for items under “Type of access difficulties” and “Impact of medication shortage on treatment effectiveness”

*** Data in this section refer to participants who experienced at least one medication change due to stimulant shortage (n = 83)

ADHD, attention deficit/hyperactivity disorder

Impact of stimulant medication shortage on daily functioning, coping strategies, and healthcare perceptions

The impact of stimulant medication shortage on children’s daily lives, coping strategies, and healthcare-related perceptions is summarized in Table 3. Compared with parents whose children did not experience medication changes, those whose children required medication switching reported significantly greater perceived impact on their child’s physical or mental health (77.1% vs. 42.4%, p < .001, r = .35), and on peer relationships and academic performance (69.9% vs. 51.5%, p = .022, r = .19). Beyond these significant findings, a consistent trend was observed across other daily life domains; although not reaching statistical significance, the medication-changed group reported higher rates of adverse experiences, including worsening of ADHD symptoms (61.4% vs. 47.0%), academic decline (55.4% vs. 48.5%), and emotional dysregulation (51.8% vs. 37.9%) compared to the unchanged group. The overall distribution of these reported impacts and the utilized coping methods across the entire sample are further illustrated in Figs. 2 and 3, respectively.

Table 3.

Impact of stimulant medication shortage on daily functioning, coping strategies, and related perceptions*

Variable n (%) or median (25th–75th)	Medication changed (n = 83)	Medication unchanged (n = 66)	P-value	Effect size
Impact of medication shortage on daily life**
Worsening ADHD symptoms	51 (61.4)	31 (47.0)	0.078	0.15
Academic decline	46 (55.4)	32 (48.5)	0.400	0.07
Emotional dysregulation	43 (51.8)	25 (37.9)	0.090	0.14
Problems in peer relationships	27 (32.5)	15 (22.7)	0.186	0.11
Difficulty maintaining social activities	21 (25.3)	11 (16.7)	0.202	0.10
Perceived health impact (physical/mental)	64 (77.1)	28 (42.4)	< 0.001	0.35
Perceived social & academic impact	58 (69.9)	34 (51.5)	0.022	0.19
Coping methods during medication shortage**
Encouraging physical activity	38 (45.8)	22 (33.3)	0.124	0.13
Supplements/ Alternative remedies	21 (25.3)	13 (19.7)	0.418	0.07
Non-medical interventions	4 (4.8)	6 (9.1)	0.301	0.09
Healthcare system-related barriers**
Lack of stock info	64 (77.1)	51 (77.3)	0.981	0.01
Restrictive renewal policies	38 (45.8)	24 (36.4)	0.247	0.10
Healthcare-related stigma	13 (15.7)	7 (10.6)	0.368	0.07
Perceptions and future concerns related to stimulant shortage
Feeling hopeless about the healthcare system	73 (88.0)	49 (74.2)	0.031	0.18
Level of hopelessness (0–7 scale)	5 (3–7)	4 (2–6)	0.025	0.19

Note. Values are presented as n (%) or median (25th–75th). The numbers in parentheses (%) indicate frequencies. n indicates number of the participants. Pearson’s chi-square test was used to compare categorical variables, and the Mann–Whitney U test was used for non-normally distributed continuous variables. Effect sizes were calculated using r (Z/√N) for Mann–Whitney U tests and Cramer’s V for chi-square tests (0.1 = small, 0.3 = medium, 0.5 = large)

Statistical significance was defined as p < .05 (indicated in bold), with nominal p-values reported without adjustment for multiple comparisons due to the exploratory nature of the study

* Stimulant medications refer to methylphenidate formulations prescribed for ADHD

** Multiple responses were allowed

ADHD, attention deficit/hyperactivity disorder

Fig. 2.

Parent-reported impact of stimulant medication shortage on daily life among children with ADHD. Note: Multiple responses were permitted; therefore, percentages do not sum to 100%

Fig. 3.

Parent-reported coping methods and healthcare system-related barriers during stimulant medication shortage. Note: Multiple responses were permitted; therefore, percentages do not sum to 100%

Regarding healthcare perceptions, hopeless attitudes about the healthcare system were significantly more prevalent among those who experienced a medication change (88.0% vs. 74.2%, p = .031), with these individuals also reporting higher overall hopelessness levels [median 5 (3–7) vs. 4 (2–6), p = .025].

Multivariable logistic regression models, adjusted for relevant covariates and including interaction terms, confirmed these primary findings (detailed results are provided in Table S3). In addition, detailed comparisons of daily functioning, coping strategies, and related perceptions, further categorized by the presence of psychiatric comorbidity, are provided in the Supplementary Material (Table S4).

Comparison of DSM-5 level 2 irritability, SDQ, and SDSC scores by medication change and comorbidity status in children with ADHD

Direct comparisons between children with and without medication changes revealed no statistically significant differences in DSM-5 Level 2 Irritability, SDQ, or SDSC total and subscale scores (Table 4). However, a more granular analysis accounting for psychiatric comorbidity status identified significant clinical variations within the medication-changed group. Specifically, within the medication-changed cohort, children with psychiatric comorbidities exhibited significantly higher DSM-5 Level 2 Irritability total scores (p = .003, r = .32), SDQ emotional symptoms (p = .026, r = .24), conduct problems (p = .014, r = .27), and peer relationship problems (p = .002, r = .34) compared to those without comorbidities. Furthermore, the total difficulties score was significantly elevated in comorbid children who experienced medication changes (M = 17.0, SD = 5.5 vs. M = 12.9, SD = 6.1, p = .003, Cohen’s d = 0.71), whereas no such differences were observed in the medication-unchanged group. Detailed scores for these clinical measures across comorbidity and medication status are provided in Table 5.

Table 4.

Comparison of DSM-5 Level 2 Irritability scale, SDQ and SDSC scores between children with and without stimulant medication changes*

Variable median (25th–75th)	Medication changed (n = 83)	Medication unchanged (n = 66)	P-value	Effect size
DSM-5 level 2- irritability scale
Total score	5 (2–8)	6 (2–9)	0.362	0.08
Strengths and difficulties questionnaire
Emotional symptoms	3 (1–4)	3 (2–5)	0.760	0.03
Conduct problems	2 (1–4)	3 (2–5)	0.203	0.10
Hyperactivity/inattention	7 (5–8)	6 (5–8)	0.829	0.02
Peer relationship problems	4 (2–5)	4 (2–5)	0.867	0.01
Prosocial behavior	8 (6–9)	7 (5–9)	0.191	0.11
Total difficulties score	16 (9)	15 (9)	0.826	0.02
Sleep disturbance scale for children
Disorders of initiating and maintaining sleep	14 (10–18)	14 (10–18)	0.609	0.04
Sleep breathing disorders	3 (3–5)	4 (3–5)	0.295	0.09
Disorders of arousal	3 (3–4)	3 (3–4)	0.405	0.07
Sleep–wake transition disorders	9 (6–13)	9 (6–12)	0.548	0.05
Disorders of excessive somnolence	6 (5–9)	6 (5–9)	0.358	0.08
Sleep hyperhidrosis	2 (2–4)	2 (2–4)	0.670	0.04
Total score	40 (32–51)	40 (34–49)	0.873	0.01

Note. Values are presented as median (25th–75th). n indicates number of the participants. Mann–Whitney U test was used for non-normally distributed continuous variables. Effect sizes were calculated using r (Z/√N) for Mann–Whitney U tests (0.1 = small, 0.3 = medium, 0.5 = large)

Statistical significance was defined as p < .05 (indicated in bold), with nominal p-values reported without adjustment for multiple comparisons due to the exploratory nature of the study

* Stimulant medications refer to methylphenidate formulations prescribed for attention deficit/hyperactivity disorder.

SDQ, Strengths and Difficulties Questionnaire; SDSC, Sleep Disturbance Scale for Children

Table 5.

Comparison of DSM-5 Level 2 Irritability, SDQ, and SDSC scores by psychiatric comorbidity among children with ADHD who did and did not experience medication change due to stimulant shortage*

Variable median (25th–75th) or mean ± SD	Medication changed				Medication unchanged
	Comorbidity (+) (n = 56)	Comorbidity (–) (n = 27)	P-value	Effect size	Comorbidity (+) (n = 29)	Comorbidity (–) (n = 37)	P-value	Effect size
DSM-5 level 2- irritability scale
Total score	6 (3–8)	4 (1–7)	0.003	0.32	6 (3–8)	6 (2–10)	0.785	0.03
Strengths and difficulties questionnaire
Emotional symptoms	3 (2–5)	2 (1–4)	0.026	0.24	3.3 ± 2.2	3.6 ± 2.3	0.514	0.16
Conduct problems	3 (1–4)	2 (0–3)	0.014	0.27	3 (2–5)	2 (1–4)	0.520	0.08
Hyperactivity/inattention	7 (5–8)	5 (4–8)	0.113	0.17	6.1 ± 2.4	6.6 ± 2.1	0.467	0.18
Peer relationship problems	4 (3–5)	2 (2–4)	0.002	0.34	4 (3–5)	4 (2–5)	0.280	0.13
Prosocial behavior	7 (6–9)	8 (6–10)	0.090	0.19	6 (5–8)	7 (5–9)	0.315	0.12
Total difficulties score	17.0 ± 5.5	12.9 ± 6.1	0.003	0.71	16.5 ± 6.2	16.6 ± 5.8	0.954	0.01
Sleep disturbance scale for children
Disorders of initiating and maintaining sleep	14 (9–19)	13 (12–15)	0.818	0.03	13 (10–18)	15 (11–20)	0.213	0.16
Sleep breathing disorders	3 (3–5)	3 (3–5)	0.345	0.11	4 (3–5)	4 (3–5)	0.907	0.02
Disorders of arousal	3 (3–5)	3 (3–3)	0.065	0.21	3 (3–4)	3 (3–3)	0.900	0.02
Sleep–wake transition disorders	9 (6–14)	8 (6–11)	0.193	0.15	9 (6–11)	8 (6–12)	0.699	0.05
Disorders of excessive somnolence	7 (5–11)	5 (5–8)	0.064	0.21	6 (5–9)	6 (5–9)	0.591	0.07
Sleep hyperhidrosis	2 (2–4)	2.0 (2–3)	0.385	0.10	2 (2–3)	2 (2–4)	0.644	0.06
Total score	43 (32–53)	37 (32–46)	0.185	0.15	40 (33–48)	40 (34–50)	0.431	0.10

Note. Values are presented as median (25th–75th) or mean ± SD, as appropriate. n indicates the number of participants. Mann–Whitney U and independent samples t-tests were used to compare groups. Effect sizes were calculated as Cohen’s d for parametric and r = Z/√N for non-parametric tests (0.2 = small, 0.5 = medium, 0.8 = large)

Statistical significance was defined as p < .05 (indicated in bold), with nominal p-values reported without adjustment for multiple comparisons due to the exploratory nature of the study

* Stimulant medications refer to methylphenidate formulations prescribed for ADHD

SD, Standard Deviation; SDQ, Strengths and Difficulties Questionnaire; SDSC, Sleep Disturbance Scale for Children; ADHD, attention deficit/hyperactivity disorder

Generalized Linear Models (GZLM) further confirmed these associations by evaluating the interaction effects between medication change and psychiatric comorbidity (Table 6). While main effects varied, the interaction term was a significant predictor of the DSM-5 Level 2 Irritability total score (B = 2.65, 95% CI: 0.48–4.83, p = .017), SDSC disorders of arousal (B = 1.12, 95% CI: 0.12–2.12, p = .028), and SDSC total score (B = 9.56, 95% CI: 0.29–18.84, p = .043). Notably, B coefficients for the interaction term were positive across nearly all psychometric scales, indicating a synergistic worsening of symptoms, with the exception of prosocial behavior, which showed a negative coefficient (B = − 0.57) consistent with decreased positive social functioning.

Table 6.

Generalized Linear Models evaluating the interaction effects between stimulant medication change and psychiatric comorbidity on DSM-5 Level 2 Irritability, SDQ, and SDSC scores*

Scale scores (dependent variables)	B (95% CI) for medication change	p for medication change	B (95% CI) for psychiatric comorbidity	p for psychiatric comorbidity	B (95% CI) for interaction**	p for interaction
DSM-5 level 2- irritability scale
Total score	-2.01 (-3.72 to -0.30)	0.021	-0.51 (-2.24 to 1.21)	0.559	2.65 (0.48 to 4.83)	0.017
Strengths and difficulties questionnaire
Emotional symptoms	-0.57 (-1.77 to 0.62)	0.345	-0.40 (-1.49 to 0.70)	0.479	1.03 (-0.46 to 2.51)	0.175
Conduct problems	-0.79 (-1.63 to 0.05)	0.064	0.16 (-0.80 to 1.12)	0.745	0.76 (-0.43 to 1.94)	0.210
Hyperactivity/inattention	-0.36 (-1.42 to 0.70)	0.503	-0.13 (-1.15 to 0.88)	0.795	1.05 (-0.43 to 2.53)	0.163
Peer relationship problems	-0.54 (-1.42 to 0.34)	0.228	0.54 (-0.37 to 1.45)	0.242	0.54 (-0.70 to 1.78)	0.394
Prosocial behavior	1.10 (0.05 to 2.14)	0.039	-0.62 (-1.68 to 0.44)	0.253	-0.57 (-1.95 to 0.80)	0.414
Total difficulties score	-2.27 (-5.30 to 0.77)	0.143	0.17 (-2.68 to 3.02)	0.906	3.38 (-0.66 to 7.41)	0.101
Sleep disturbance scale for children
Disorders of initiating and maintaining sleep	-1.43 (-4.10 to 1.23)	0.292	-1.96 (-4.64 to 0.72)	0.152	2.74 (-0.68 to 6.17)	0.116
Sleep breathing disorders	-1.01 (-2.23 to 0.22)	0.107	-0.89 (-2.18 to 0.40)	0.175	1.07 (-0.34 to 2.48)	0.137
Disorders of arousal	-0.48 (-1.34 to 0.38)	0.273	-0.46 (-1.26 to 0.33)	0.253	1.12 (0.12 to 2.12)	0.028
Sleep–wake transition disorders	-0.82 (-2.75 to 1.10)	0.401	-0.91 (-2.80 to 0.99)	0.347	2.19 (-0.26 to 4.64)	0.080
Disorders of excessive somnolence	-1.50 (-3.18 to 0.18)	0.081	-0.30 (-2.42 to 1.83)	0.783	1.67 (-0.81 to 4.15)	0.187
Sleep hyperhidrosis	-0.61 (-1.42 to 0.21)	0.146	-0.14 (-1.17 to 0.88)	0.785	0.78 (-0.52 to 2.07)	0.242
Total score	-5.85 (-13.13 to 1.42)	0.115	-4.67 (-12.48 to 3.14)	0.241	9.56 (0.29 to 18.84)	0.043

Note. Statistical significance was defined as p < .05 (indicated in bold), with nominal p-values reported without adjustment for multiple comparisons due to the exploratory nature of the study

*All models included child age, sex, family income, maternal education, duration of medication use, concomitant psychotropic use, medication change, and psychiatric comorbidity as main effects

**Interaction Term refers to medication change × psychiatric comorbidity

SDQ, Strengths and Difficulties Questionnaire; SDSC, Sleep Disturbance Scale for Children

Discussion

Stimulant shortage has emerged as a growing global concern affecting children with ADHD. In Turkey, amphetamine-based stimulants are not available, and the stimulant shortage exclusively involves methylphenidate formulations. In this study, we aimed to investigate the extent of this problem among school-aged children with ADHD in Turkey, focusing on families’ challenges in accessing stimulant medications, their coping strategies and perceptions, and the frequency of medication changes due to access difficulties. Furthermore, we examined how these challenges influenced social, academic, emotional, behavioral, and sleep-related functioning, as well as irritability levels, particularly in relation to the presence of psychiatric comorbidity. Our findings revealed that stimulant access difficulties were highly prevalent within our study clinical sample, leading to medication changes in more than half of the participants. While these results reflect the experiences of a specific clinical population in Turkey, they highlight a significant challenge that warrants broader investigation. A considerable proportion of parents reported reduced treatment benefits following these medication changes. Beyond their impact on children’s functional outcomes, the stimulant shortage also appeared to undermine parental confidence in the healthcare system. Moreover, children with psychiatric comorbidities were found to be more adversely affected by these disruptions, suggesting that this subgroup may be particularly vulnerable to the consequences of medication instability.

Global data indicate that the stimulant shortage has led to significant delays in prescription continuity. Using 3.8 million pediatric records from the United States, He et al. (2025) reported an 8% increase in medication switching and a 1.2% increase in discontinuation after the 2022 Adderall shortage [10]. Similarly, Bohm et al. (2024) reported a 15–22% decline in amphetamine prescriptions and a reduction in average medication supply duration during 2022–2023 [25]. Nawaz et al. (2024) likewise observed increased prescription fills outside patients’ home regions, underscoring geographic disparities [11]. In the United Kingdom, Lewis and Khong (2024) reported that national guidelines recommending clinicians avoid initiating new stimulant treatments during supply crises exacerbated treatment delays [8]. While these global trends are comparable, the rate of medication switching in our sample was notably higher (55.7%). This discrepancy might be attributable to local factors, such as the potentially simultaneous scarcity of various long-acting methylphenidate formulations in the Turkish market or challenges related to national reimbursement policies, which may have necessitated more frequent rotations to maintain treatment continuity. Our findings, representing the first clinical documentation of this crisis in Turkey, suggest that local regulatory and supply chain dynamics could potentially intensify the clinical impact of global shortages.

The access difficulties reported in our study parallel the qualitative findings of Johnson et al. (2025) and Shrestha et al. (2025), which highlighted the emotional strain and uncertainty associated with stimulant shortage [9, 26]. Families in our sample similarly reported visiting numerous pharmacies, facing stock unpredictability, and feeling anxious about treatment continuity. In our study’s open-ended responses, one parent reported visiting nearly 60 pharmacies and noted that their anxiety intensified as the refill date approached. These experiences reflect not only logistical barriers but also psychological exhaustion and declining trust in the healthcare system. Notably, parents of children who experienced medication changes reported greater hopelessness about the future, suggesting that repeated disruptions may damage confidence in long-term care. Our results empirically capture the frustration and uncertainty previously described qualitatively, underscoring the psychosocial toll of stimulant shortage on families.

Although both the global questions and the standardized scales in our study were based on parental reports, they appeared to capture different aspects of parental perception and clinical reality. Parents of children who experienced medication changes reported greater functional impairments, particularly in academic and social domains, compared with those whose treatment remained stable. However, no significant group differences emerged in irritability, sleep, or total difficulty scores. This discrepancy likely reflects a measurement mismatch rather than a true gap in parental appraisal. While standardized tools such as the SDQ and irritability scales capture recent symptom burden, our study-specific form was designed to assess the cumulative psychosocial impact experienced across the entire six-month shortage period. Consequently, parents may be reporting a long-term, aggregated experience of instability, reflecting the sustained burden of medication access, that standardized “snapshot” assessments are less sensitive to detect. While it remains possible that parents who shoulder the burden of securing medication might anticipate challenges more acutely, the temporal difference between instruments provides a more robust methodological explanation for these findings. Consistent with this interpretation, He et al. (2025) and Romba (2025) noted that stimulant switching without adequate titration can undermine treatment stability [10, 27].

Our most striking finding was that emotional and behavioral consequences of medication changes were particularly pronounced among children with psychiatric comorbidities. In this subgroup, irritability, emotional symptoms, conduct problems, peer relationship problems, and total difficulty scores were significantly higher compared with non-comorbid peers, whereas no such differences were observed among children whose medication regimen remained unchanged. This disparity was formally supported by our interaction analyses, which demonstrated a clear synergistic impact: the coexistence of medication instability and psychiatric comorbidity created a “compounding effect” on clinical outcomes. Specifically, the consistent direction of our interaction models across nearly all psychometric scales, indicating worsening symptoms and diminished social functioning, suggests that the medication shortage did not merely cause isolated disruptions, but rather amplified the inherent clinical vulnerabilities of these children. These results suggest that comorbidities may amplify sensitivity to pharmacologic disruptions, leading to greater emotional dysregulation and behavioral reactivity. Similar patterns of “fragile stability” have been described in qualitative studies such as Johnson et al. (2025) and Shrestha et al. (2025), where families reported that children with co-occurring conditions experienced heightened emotional fluctuation during periods of stimulant unavailability [9, 26]. From a clinical perspective, these findings underscore the importance of ensuring treatment continuity for vulnerable subgroups, as even short-term medication instability may have disproportionate psychosocial consequences.

From a systems perspective, stimulant shortage stems from both clinical and policy-level deficiencies. Rising and Califf (2025) noted that Drug Enforcement Administration (DEA) quota restrictions, fragmented supply chains, and poor production transparency have prolonged shortages in the United States [28]. Comparable structural issues may exist in Turkey, where limited production planning and weak communication between pharmacies and regulators intensify uncertainty for families and clinicians. Consistent with our findings, Lewis and Khong (2024) described these shortages as “not merely a supply problem but a policy failure.” [8]. Strengthening coordination among health authorities, pharmacies, and manufacturers is essential to ensure consistent availability and prevent recurrence.

During the shortage period, various individualized and pragmatic adjustments were observed in clinical practice to maintain treatment continuity, although these should not be interpreted as standardized clinical recommendations. Families often undertook logistical strategies, such as checking local pharmacy stocks before renewals. When primary formulations were unavailable, dose-equivalent substitutions, such as combining multiple lower-dosage capsules or switching to a different methylphenidate formulation, were sometimes utilized, although these adjustments often increased the pill burden and parental stress. In some instances, clinicians discussed alternative long-term strategies with families, including transitions to non-stimulants like atomoxetine or utilizing weekend drug holidays to conserve limited supplies. In more complex cases involving prominent externalizing symptoms, adjunctive treatments such as low-dose antipsychotics or combination therapies were occasionally employed. It is critical to note that such off-label or adjunctive strategies were based on individual clinical judgment in the absence of evidence-based shortage guidelines and require careful safety monitoring. These real-world observations highlight the significant variability in practice and underscore the urgent need for formal, evidence-based protocols to manage medication instability during supply crises.

Strengths and limitations

This study has several strengths and limitations. Its main strength lies in being the first to clinically document the multifaceted effects of stimulant shortage on children with ADHD in Turkey. Combining quantitative data with open-ended parental feedback provided a deeper understanding of families’ experiences with medication access difficulties. However, several limitations should be noted. Firstly, the cross-sectional design precludes establishing causal relationships or the direction of observed associations. Secondly, reliance on self-reported parental data may introduce recall or severity bias; for instance, unassessed parental factors like anxiety or burnout could influence evaluations of child functioning. Additionally, medication change likely serves as a surrogate for complex clinical and systemic factors, making it challenging to isolate its effects from unmeasured confounding variables. Furthermore, while significant interactions were identified, the sample size limited more nuanced subgroup analyses across diverse comorbidities. The single-center nature of the study may also restrict the generalizability of findings to the broader pediatric ADHD population. Finally, multiple comparison corrections were not applied due to the exploratory nature of this study. While this increases the risk of Type I errors, the remarkable consistency of findings across almost all psychometric domains, following a uniform clinical trend, reinforces our results’ internal validity. Nonetheless, these preliminary associations require validation in future confirmatory studies.

Conclusions

In conclusion, this study provides the first clinical-level evidence from Turkey on the multifaceted impact of stimulant medication shortages on children with ADHD and their families. The findings highlight that medication access difficulties are highly prevalent, with children who have psychiatric comorbidities showing greater sensitivity to the emotional and behavioral effects of medication changes. These results underscore the need for health system preparedness, including reliable supply chain coordination, transparent communication between pharmacies and regulatory authorities, and psychosocial support for affected families. Future research should employ longitudinal and mixed-method approaches to better capture the long-term developmental and psychosocial consequences of stimulant shortage and to guide sustainable policy responses.

Supplementary Information

Below is the link to the electronic supplementary material.

Abbreviations

ADHD

Attention deficit/hyperactivity disorder

FDA

U.S. Food and Drug Administration

SDQ

Strengths and Difficulties Questionnaire

SDSC

Sleep Disturbance Scale for Children

SD

Standard Deviation

Author contributions

Tuğba Acehan, MD, PhD Candidate conceptualized and designed the study, coordinated and supervised all stages of the project, performed/overseen data analysis and interpretation, drafted the initial manuscript, and is the corresponding author.Esra Güngör Bağlıcakoğlu, MD; Ecem Selin Akbaş Aliyeva, MD; Huriye Berna Devecioğlu, MD; Merve Canlı, MD; Yusuf Selman Çelik, MD contributed to study planning, participant recruitment and data collection, data entry/management, and interpretation of findings; they critically reviewed and revised the manuscript.Ayşegül Efe, MD; Yusuf Öztürk, MD contributed at every stage of the study, including design, clinical oversight, data acquisition, and interpretation, and they critically reviewed and substantially revised the manuscript for important intellectual content.All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Data availability

The study and analysis plan were not formally registered. Deidentified data are not available in a public archive. Deidentified data will be made available as allowable according to institutional IRB standards by emailing the corresponding author. No analytic code is associated with this study. Materials used to conduct the study will be made available by emailing the corresponding author.

Declarations

Ethics approval and consent to participate

This study was designed as a single-center, cross-sectional study and was conducted at the Department of Child and Adolescent Psychiatry, Ankara Etlik City Hospital between April 2025 and August 2025. IRB approval was obtained from the Ankara Etlik City Hospital Scientific Research Evaluation and Ethics Committee (Date: 09.04.2025, No: AEŞH-BADEK-2025-0641). Informed consent was obtained from all participants and their parents prior to inclusion in the study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.