Complementary and Alternative Medicine Use by ADHD Patients: A Systematic Review

Abstract

Objective:

This study aimed to review the prevalence of complementary and alternative medicine (CAM) use and its different used types, characteristics of the studied cohorts, the reasoning for CAM use, and possible predictive factors for its use amongst ADHD patients.

Method:

The Web of Science Core Collection, PubMed, and Scopus were searched from inception to 10 February 2022. All of the original papers published in English which report data on CAM use by patients with ADHD were included.

Results:

Twelve original researches including 4,447 patients were included. The prevalence of CAM use varied from 7.5% to 67.6%. The most-reported CAM modalities were dietary modifications and natural products. Moreover, higher parental education should be considered as a predictive factor for CAM use.

Conclusion:

CAM use by ADHD patients seems to be prevalent. Healthcare providers should be trained about the most commonly used CAM therapies and their possible adverse events.

Keywords

ADHD complementary and alternative medicine traditional medicine prevalence systematic review

Introduction

ADHD is one of the most common neurodevelopmental disorders. It is characterized by chronic hyperactive-impulsive and/or inattentive symptoms. The symptoms should be observed in different settings (i.e., not only in school or home) (American Psychiatric Association, 2013; Gualtieri & Johnson, 2005). Boys are significantly affected more than girls. Different cross-sectional and population-based surveys showed its prevalence from 5% in children to 2.2% to 2.8% in adults (Dobrosavljevic et al., 2020; Fayyad et al., 2017; Polanczyk et al., 2007). The genetic background has an important role in its development. Polygenic risk for ADHD has been suggested (Demontis et al., 2019; Taylor et al., 2019). Moreover, there are several environmental correlates of ADHD. Different toxicant and medication exposures (Chen et al., 2019; Nilsen & Tulve, 2020), deficiency of several nutrients (Sucksdorff et al., 2021; Wang et al., 2017), abnormal pregnancies (Ge et al., 2020; Maher et al., 2020), deprivation and poverty (Ouyang et al., 2008; Østergaard et al., 2016), and several other risk factors were determined. A wide variety of non-psychiatric diseases such as obesity (Chen et al., 2018), asthma (Cortese et al., 2018), and epilepsy (Brikell et al., 2018) are known for their association with ADHD. Additionally, ADHD is a known risk factor for many psychiatric and mental disorders, including substance use disorders (Wimberley et al., 2020), antisocial behaviors (Retz et al., 2021), emotional problems (Han et al., 2020; Stern et al., 2020), self-harm (Ward & Curran, 2021), and suicide (Fuller-Thomson et al., 2020).

ADHD and its adverse outcomes make a substantial burden on patients and their families, healthcare systems, and governments. For instance, an Australian study estimated an annual $20 billion for direct and indirect costs (Sciberras et al., 2022). Daley et al. (2019), found that ADHD adult patients have a €20,000 economic burden per year. There are several standardized protocols for ADHD treatment. Medical treatments are divided into two main categories of stimulants (e.g., amphetamine and its derivatives, and methylphenidate) and non-stimulant drugs (e.g., extended-release clonidine and atomoxetine). Medications can significantly reduce oppositional behavior, emotional dysregulation, aggression, and other symptoms. Also, parent-reported quality of life and teacher-rated behavior can be improved after a period of drug use (Lenzi et al., 2018; Maneeton et al., 2015; Schwartz & Correll, 2014). Also, there is a wide variety of non-medical treatments, usually depending on the patient’s age. Cognitive behavior therapy, social skills training, organizational skills interventions, and neurofeedback are some of the well-known options (Bikic et al., 2017; Cortese et al., 2016; Knouse et al., 2017; Willis et al., 2019). However, a collection of adverse events due to these medications was reported. Sleep disturbances, cardiovascular events, anorexia, primary hypertension, abdominal pain, and congenital cardiac malformation were reported in some users (Dalsgaard et al., 2014; Kidwell et al., 2015; Koren et al., 2020; Solmi et al., 2020). In addition, most non-medical treatments have limited availability, and are time-consuming (De Crescenzo et al., 2017; Sierawska et al., 2019).

Complementary and alternative medicine (CAM) has an increasing use worldwide among different patient populations and healthy people (Kalantar Motamedi et al., 2018; Maghbool et al., 2020; Moeini et al., 2021; Nayebi et al., 2019; Seyed Hashemi et al., 2021). Also, its use for patients with different psychological disorders, including ADHD patients is increasing (Afrasiabian et al., 2019; Sadiq, 2007). The chronicity of ADHD makes patients more likely to use CAM (Pellow et al., 2011). Different Herbal remedies and medicinal herbs, minerals, a variety of food interventions, and massage are some of the recommended modalities by CAM practitioners (Baziar et al., 2019; Behdad & Hashem-Dabaghian, 2020; Mostajeran et al., 2020; Motaharifard et al., 2019; Searight et al., 2012). In addition, physical exercise, omega-3 fatty acid supplementation, and meditation-based therapies can be listed as some popular evidence-based CAM modalities for ADHD patients (Puri & Martins, 2014; Zang, 2019; Zhang et al., 2018).

CAM use by patients with ADHD has been studied in different countries and cultures. However, authoritative data on different aspects of its use is lacking. Therefore, this study aimed to summarize the prevalence of CAM use and its different used types, characteristics of the studied cohorts, the most important points about the used questionnaires and ways of surveying, the reasoning for CAM use, and possible predictive factors for its use.

Methods

Literature Search

This systematic review was conducted according to PRISMA (Preferred Reported Items for Systematic Reviews and Meta-Analysis) guidelines (Moher et al., 2009). The Web of Science Core Collection, PubMed, and Scopus was searched from inception to 10 February 2022. For this purpose, Medical Subject Headings (MeSH) terms and free text terms (in combination) were used appropriately. Use, prevalence, complementary and alternative medicine, complementary therapies, herbal medicine, medicinal herbs, herbal product, herbal therapy, herbal remedies, medicinal plants, herbal supplements, traditional therapy, and traditional medicine were the used keywords.

Inclusion and Exclusion Criteria

Studies’ titles and abstracts were screened by two independent researchers for possible inclusion in the next steps of the review. Any discrepancies were resolved by group discussion. They were included if reported original research on patients with ADHD for assessment of any type of CAM use. Only papers published in English were considered for review. References of the included papers were searched to find other relevant articles which may not be found by the systematic search. Duplicate studies were omitted from the review.

Quality Appraisal

All of the included studies were assessed for their main quality indicators. The used quality assessment checklist was made by Bishop et al. (2010) based on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist for observational research. Then, it has been used in many systematic reviews regarding CAM use in a wide variety of patient populations (Grant et al., 2012; Höfer et al., 2017; Italia et al., 2014).

Data Extraction

The full-text papers of the included studies were carefully examined for data extraction. The main information (about the used questionnaires, studied cohorts, study setting, and main findings) which were recorded for this systematic review were: first author’s name, country of the study, publication year, study setting, responder to the questions, mode of data collection (e.g., self-reported questionnaire, interview), type of questions (e.g., multiple-choice, Likert scale), time of data collection, period of time for CAM use, eligibility criteria with a special focus on age, sample size, response rate, mean age, participants’ gender, percent of patients who currently received conventional medications for ADHD, reported prevalence of any CAM use, the three most reported CAM modalities and their prevalence, variables which seems as predictive factors for CAM usage, and reported reasons for CAM Use. If some of the mentioned questions were not addressed in the study, it was reported as “not mentioned” in the resulted tables.

Results

Study Selection

Figure 1 shows the flowchart of the main steps of the study selection. Search in databases resulted in 428 studies, of which 107 duplicated ones were excluded. Of records that were screened by title and abstract, 202 were irrelevant and not included. In the next step, the investigators assessed 119 left articles for their eligibility. Finally, 12 original pieces of research—including a total of 4,447 patients—were included in this systematic review.

Figure 1.

PRISMA flow chart of the study.

Surveys’ Characteristics

Table 1 summarizes some of the main characteristics of each of the reviewed studies. Three of the studies used national survey information. All of the patients were younger than 18 years old. Additionally, regarding ADHD diagnosis there is a wide heterogeneity. It was based on different versions of the Diagnostic and Statistical Manual of Mental Disorders (DSM) in five of them. Although, some of them were based on parent reporting or not mentioned in several studies. Self-reported questionnaires were the most used way for data gathering. In addition, seven of the surveys asked about lifetime CAM use; of them, two asked about current use, too. Four of the studies asked about CAM use during the past 12 months before the study. The smallest sample size was 41, while the biggest study had 986 participants.

Table 1.

Characteristics of Included Studies and Their Data Gathering Information.

Author, publishing year, and country	Study setting	Responder	Mode of data collection	Type of questions	Period of data collection	Period of time for CAM use	Eligibility	Sample size (% response rate)
Wang et al. (2020), U.S.	Data from the 2012 and 2017 National Health Interview Survey	A family member	Interview	Multiple-choice questions	2017	Within the past 12 months	Patients aged 4–17 years	628 (Not reported)
Chou et al. (2020), Taiwan	Psychiatric outpatient clinics of two medical centers in Kaohsiung	A family member who spent the most time with the patient	Self-report questionnaire	Likert scale and multiple-choice questions	June 2018–April 2019	Lifetime	Patients aged under 18 years who were diagnosed with ADHD according to DSM-5	400 (97.80)
Wang et al. (2018), U.S.	Data from the 2012 National Health Interview Survey	A family member	Interview	Multiple-choice questions	2012	Within the past 12 months	Patients aged 4–17 years	986 (Not reported)
Huang et al. (2013), U.S.	A patient panel of the Division of Child Neurology and Neurodevelopmental Disabilities at the University of Medicine and Dentistry of New Jersey–Robert Wood Johnson Medical School	Parents or caregivers	Self-reported questionnaire	Multiple choice and open-ended questions	Not reported	Not reported	Patients with parent-reported ADHD	41 (31)
Kemper et al. (2013), U.S.	Data from the 2007 National Health Interview Survey	A family member	Interview	Multiple choice questions	Not reported	Within the past 12 months	Patients aged 7 to 17 years old with self-reported ADHD	483 (Not reported)
Snyman and Truter (2010), South Africa	Patients referred to ninety-four pharmacies in the Eastern Cape	Parents	Self-reported questionnaire	Not reported	October 2006–January 2007	Lifetime and current use	Not reported	51 (9.77)
Sinha and Efron (2005), Australia	Outpatients of the Royal Children’s Hospital, Melbourne	Parents	Self-reported questionnaire	Multiple choice questions	May to September 2003	Lifetime	Patients aged 5–17 years old who were diagnosed with ADHD according to DSM-5	75 (71.40)
Cala et al. (2003), U.S.	Five community mental health centers in Texas	Parents or caregivers	Self-reported questionnaire	Multiple choice and open-ended questions	October 2000–July 2001	Lifetime, within the past 12 months, and current use	Patients aged under 18 years old who were diagnosed with ADHD according to DSM-IV	117 (Not reported)
Gross-Tsur et al. (2003), Israel	Neuropediatric Unit in Shaare Zedek Medical Center	Parents	Interview	Multiple-choice questions	Not reported	Lifetime and current use	Patients who were diagnosed with ADHD according to DSM-IV and standardized behavioral questionnaires	120
Chan et al. (2003), U.S.	Developmental Medicine Center at a major urban children’s hospital	Parents	Self-reported questionnaire or interview	Likert scale and multiple-choice questions	January–December 1999	Within the past 12 months	Patients with a referral or final diagnosis of ADHD, attention-deficit disorder, or attention problem	114 (56)
Bussing et al. (2002), U.S.	A north-central Florida public school district	Parents	Interview	Multiple-choice questions	October–December 1998	Lifetime	Patients with a diagnosis of ADHD or at risk of having ADHD, not receiving special education services for mental retardation or autism, and Caucasian or African-American ethnicity	822 (79)
Stubberfield and Parry (1999), Australia	State Child Development Centre in Perth	Not reported	Self-reported questionnaire	Multiple-choice questions	June 1993	Lifetime	Patients with ADHD based on DSM-III-R	305 (76)

Note. DSM = Diagnostic and Statistical Manual of Mental Disorders.

CAM Use

The prevalence of CAM use varied from 7.5% to 67.6%. In detail, for lifetime CAM use a range of 12% to 67.6% was reported. Also, 7.5% and 54% were the lowest and highest rate for recent CAM use, respectively. The most-reported CAM modalities were dietary modifications, natural products (including herbs, vitamins, and minerals), and mind-body practices. Also, the most common reasons for CAM use were natural therapies preferring, synergistic effects with conventional medicine, and treatment of co-morbidities. Moreover, the higher parental education and female sex were variables that emerge as predictive factors for its use (Table 2).

Table 2.

Patients’ Characteristics and CAM Use by Them.

Author, publishing year, and country	Patients’ mean age	Patients’ gender (% females)	Patients who received medication for ADHD, %	Prevalence of any CAM use, %	Prevalence of the three most reported CAM modalities, %	Variables that emerge as predictive factors for CAM use	Reasons for CAM use, %
Wang et al. (2020), U.S.	4–11 years: 54.75%; 12–17 years: 45.25%	38.43	Not reported	19.35	Meditation (10.80), yoga (9.60), breathing exercise (7.30)	Males (p = .0007)	Would help treat ADHD symptoms when combined with conventional treatment (60); focusing on the whole person (47.40); preferring natural remedies (45.30)
Chou et al. (2020), Taiwan	10.7 ± 3.2	16.0	85.30	Not reported	Sensory integration (30.30), exercise training (29.30), sugar restriction (20.50)	Males (p = .004, OR 0.405 (CI 95% 0.22–0.74)) for sensory integration; affiliate stigma (p = .02, OR 1.02 (CI 95% 1–1.04)) for exercise training; affiliate stigma (p = .004, OR 1.04 (CI 95% 1.01–1.07) for omega fatty acids supplement. *All of the mentioned variables for caregivers’ characteristics (not children themselves)	Not reported
Wang et al. (2018), U.S.	Not reported	28.6	Not reported	14.80	Herbs (9), chiropractic (3.20), deep breathing (2.50)	Female (p < .001, OR 2.16 (CI 95% 1.56–2.99)0; income ≥ $75,000 (p < .001, OR 2.84 (CI 95% 1.67–4.82); having sleep problems (p = .001, OR 1.76 (CI 95% 1.22–2.54); income $35,000–$74,999 (p = .002, OR 2.01 (CI 95% 1.29–3.13); having asthma or respiratory allergy (p = .005, OR 1.69 (CI 95% 1.17–2.45); parents’ education at least a bachelor’s degree (p = .005, OR 2.31 (CI 95% 1.28–4.15)	Would help treat ADHD symptoms when combined with conventional treatment (69.20); preferring natural remedies (55.90); preferring a holistic approach (44.70)
Huang et al. (2013), U.S.	10.9 ± 3.2	24.0	93	19.50	Dietary supplements (15), sensory integration (2), facilitated communication (2), kinesiology (2), behavior modification (2)	Not reported	Not reported
Kemper et al. (2013), U.S.	Not reported	Not reported	Not reported	24.70	Mind-body practices (15), biologically based therapies (9.30), body-based practices and manipulation (6.60)	Having other chronic health conditions (OR 2.19 (CI 95% 1.21–3.97); prescription medication use (OR 1.80 (CI 95% 1.18–2.74)); difficulty affording mental health counseling (OR 2.63 (CI 95% 1.35–5.11)); higher parental education (OR 3.04 (CI 95% 1.76–5.26))	Not reported
Snyman and Truter (2010), South Africa	10.27 ± 2.54	26.42	96.08	Lifetime use 66.67; current use 21.57	Natural products (79.41), diet modifications (64.71), occupational therapy (45.88)	Not reported	Not reported
Sinha and Efron, (2005), Australia	11.1 ± 2.9	13.30	92	67.60	Modified diet (66), vitamins and/or minerals (32), dietary supplements (24)	None of the assessed factors were found to be associated with CAM use.	Minimizing ADHD symptoms (80); increasing conventional medicines’ benefits (60); minimizing conventional medicines’ side effects (58)
Cala et al. (2003), U.S.	10.9 ± 3.1	24	94	Lifetime use 20; past year use 15	Ginkgo biloba (26), Echinacea (22), St. John’s wort (22)	Not reported	Decreasing ADHD symptoms (35), for treatment of other conditions such as rashes, colds, fever, and asthma (no percent reported)
Gross-Tsur et al. (2003), Israel	11 ± 3.1	Not reported	81	Lifetime use 28; current use 7.5	Dietary intervention (14.4% of CAM users)	Not reported	Not reported
Chan et al. (2003), U.S.	Not reported	27	51	54	Expressive (21), vitamins (21), dietary manipulation (14)	Females (p = .01)	Preferring natural remedies, having more control over treatment (no percent reported)
Bussing et al. (2002), U.S.	8.1 ± 1.6	30.77	88.80	12	Homeopathy (3), massage (2.40), chiropractic (1.70)	Lesser use of the internet as a source of information about ADHD (p < .001); better knowledge score about ADHD (p < .01); parents’ SNAP-IV rating greater than two standard deviations from the mean (p < .01); receiving special education and treatment for ADHD (p < .05); African-American ethnicity, subsidized lunch, and uninsured were greater in non-users (p < .05).	Not reported
Stubberfield and Parry (1999), Australia	10.2 ± 5.8	14.28	69	64	Restricting diet (60), multivitamin supplementation (13), occupational therapy (12)	Not reported	Not reported

Note. CAM = complementary and alternative medicine; OR = odds ratio; CI 95% = confidence interval 95%; SNAP-IV = Swanson, Nolan, and Pelham, version IV rating scale.

Quality of the Studies

Detailed descriptions of the quality assessment of the included studies were reported in Table 3. Regarding “study methods,” the main flaw of almost all of the studies was “not piloting the study” (before the main data gathering step). Quality assessment of the “sampling” comprised of two important factors. Regarding the “response rate report” about 40% of the studies could not pass the required standard. However, about 60% of the studies applied a “representative sampling strategy.” “Reporting of individuals’ characteristics” consists of six items with a weight of about 25% of the total weight of the quality appraisal. “Time since diagnosis” was reported in only one of the studies. Although, age and gender were reported in almost all of the studies (92% and 83%, respectively). Moreover, most of the studies had an acceptable quality in the field of “CAM usage.”

Table 3.

Quality Appraisal of the Included Studies.

Study	Study methods (6 pt.)					Sampling (2 pt.)		Reporting of individuals’ characteristics (3.5 pt.)						CAM usage (4 pt.)			Total score (out of 15.5)
Study	Recall bias—low risk (2)	Recall bias—some risk (1)	Piloted questionnaire (or interview schedule) (1)	Describe efforts to address potential sources of bias (1)	Adjust for potential confounders in statistical analysis (1)	Response rate reporter (1)	Representative sampling strategy (1)	Specific diagnosis (1)	Time since diagnosis (0.5)	Indicator of socioeconomic Status (0.5)	Age (0.5)	Ethnicity (0.5)	Gender (0.5)	CAM clearly defined to Respondents (2)	Definition of CAM reported in Article (1)	Use of CAM modalities assessed (1)
Wang et al. (2020), U.S.	-	+	-	+	+	-	+	-	-	+	+	+	+	+	+	+	10
Chou et al. (2020), Taiwan	-	+	-	+	+	+	-	+	-	+	+	-	+	+	+	+	10.5
Wang et al. (2018), U.S.	-	+	-	+	+	-	+	-	-	+	+	+	+	+	+	+	10
Huang et al. (2013), U.S.	-	-	-	+	+	+	-	+	-	+	+	+	+	+	+	+	10
Kemper et al. (2013), U.S.	-	+	-	+	+	-	+	-	-	+	+	+	-	+	+	+	9.5
Snyman and Truter (2010), South Africa	-	+	-	-	-	+	+	+	-	-	+	-	+	+	+	+	9
Sinha and Efron (2005), Australia	-	-	-	-	+	+	-	+	-	+	+	-	+	+	+	+	8.5
Cala et al. (2003), U.S.	-	+	-	-	-	-	+	+	+	+	+	+	+	-	+	+	7.5
Gross-Tsur et al. (2003), Israel	-	+	-	-	+	-	-	+	-	+	+	-	-	+	-	+	7
Chan et al. (2003), U.S.	-	+	+	-	-	+	-	+	-	-	-	-	+	+	+	+	8.5
Bussing et al. (2002), U.S.	-	-	-	+	+	+	+	-	-	+	+	+	+	-	+	+	8
Stubberfield and Parry (1999), Australia	-	-	-	+	-	+	+	+	-	-	+	-	+	-	+	+	7

Discussion

This paper reports the first systematic review on CAM use by patients with ADHD. There were no reviews that systematically examine the research on the prevalence, possible determinants, and type of used CAM by patients with ADHD. The significant heterogeneity amongst individual research made us unable for pooling the rate of CAM use for meta-analysis.

There is a wide range of CAM use by these patients (i.e., 7.5%–67.6%) which may be due to a cluster of cultural context, design-related issues, the definition of CAM, and different time range for asking about CAM use. Most of the studies reported CAM use about 15% to 25% within the last 12 months before the patients’ recruitment. Only one of them reported the last year’s prevalence of CAM use as 54%. However, CAM use during the life (i.e., its lifetime use) was much greater in most of the reviewed papers. In fact, more than 60% of the participants reported lifetime CAM use. Although, in one study it was reported as low as 12%. The relatively high rate of CAM use by patients with ADHD is not an unexpected finding. As we mentioned in the introduction section, ADHD is a chronic and lifelong disease that has no effective causal treatment. These two aspects are well-known items in the current literature for higher CAM use (Höfer et al., 2017).

In this systematic review, the most reported used CAMs were dietary modifications and natural products. Their easier accessibility seems to be one of the most important reasons that they are first ranked. Additionally, they are usually cheaper than several other options (Höfer et al., 2017). Parents’ belief in the important role of dietary modification for disease control in ADHD patients should be considered as another important reason (Searight et al., 2012). This belief is supported by scientific evidence in some cases. For instance, Feingold showed that a wide range of food colorings in different diets, natural salicylates, and most preservatives may cause some sensitivities in 50% of children with ADHD (Feingold, 1975). It was a controversial issue that was approved by more recent studies (Kavale & Forness, 1983; McCann et al., 2007).

Our study revealed that the most common reason for CAM use was natural therapies preferring. Previous studies showed that people who value natural healing paradigms use CAM more than others (Doering et al., 2013; Emmerton et al., 2012; Fjær et al., 2020; Tabish, 2008), . Belief in CAM’s synergistic effects with conventional medicine is another main reason for its use in patients with ADHD. Many healthy people and patients with chronic diseases look at CAM options as a booster for conventional medicines which improve their therapeutic outcomes (Bahall & Edwards, 2015; Peng & Xie, 2021; Ritenbaugh et al., 2011).

In this study, the higher parental education was associated with higher CAM use by participants. The positive role of parents’ education on CAM use is similar to the findings of other researchers worldwide and in different settings. It seems that parents with higher education are more open-minded. Additionally, they usually try internet sources, books, and even yellow magazines and other sources of information for the treatment of their children (Davis et al., 2004; Italia et al., 2014; Menniti-Ippolito et al., 2002; Ottolini et al., 2001; Ozturk & Karayagiz, 2008).

The female gender of patients was another variable that emerge as a predictive factor for CAM use in a significant part of the reviewed studies. This finding is also consistent with many of the previously published research (Bishop & Lewith, 2010; Steinsbekk et al., 2008). One of the most important reasons for the higher CAM use in patients of the female gender is the fact that they usually employ more health services than males (Lorber & Moore, 2002). Regarding CAM therapies, there are some specific researches on the gender difference for its use which confirm our findings (Alwhaibi & Sambamoorthi, 2016; Chao et al., 2006; Kristoffersen et al., 2014).

Limitations

There are some limitations to this review. Articles in non-English languages were not included in this study. Thus, there is a possibility that some important papers were missed from our review. Most of the studies were from the U.S. and Australia. There was no data from Europe, Asia (excluding one from Taiwan), and Africa (excluding one from South Africa). Therefore, it should be mentioned as an important limitation for the generalizability of our findings. Due to a significant heterogeneity amongst individual research, pooling the rate of CAM use for quantitative analysis and meta-analysis was impossible. Finally, it should be noted that regarding quality assessment, most of the studies had some important pitfalls. Resulted findings should be considered cautiously.

Conclusion

The prevalence of CAM use by ADHD patients varied from 7.5% to 67.6%. As most of the studies reported, it seems to be prevalent. Dietary modifications and natural products (e.g., herbs and vitamins) were the most reported CAM modalities. Also, the most common reasons for CAM use were natural therapies preferring, synergistic effects with conventional medicine, and treatment of comorbidities. Healthcare providers should be trained about the most commonly used CAM therapies, their possible adverse events, and interactions with conventional medications. They should have a deeper and more informed dialog about this matter with ADHD patients which encourages them to disclose their CAM use.

Footnotes

Correction (April 2025):

The article has been updated with the detailed affiliations.

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) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by a grant entitled “Metagenomics and metabolomics study of gut microbiota in Han children with autism spectrum disorder in Sichuan, China” (2021YFS0113).

ORCID iD

You Lu

Author Biographies

Jinhui Wu, nurse in charge of the child health department of West China Second Hospital of Sichuan University. Master of hospital management (in school), mainly focusing on children's growth and development, children's nutrition and developmental behavior diseases.

Ping Li, doctor in Pediatrics, deputy chief physician, Department of child health, West China Second Hospital, Sichuan University. The main research interests are children's growth and development, children's nutrition, children's endocrine and developmental behavior diseases.

Hong Luo, nurse of the child health department of West China Second Hospital of Sichuan University, has been engaged in child care for many years, has rich experience in child care, child development behavior test and evaluation, infant sports evaluation and early sports intervention, feeding guidance, etc.

You Lu, chief physician of Child Health Department of West China Second Hospital of Sichuan University. Master of Pediatrics, whose main research interests are children's growth and development, children's nutrition, children's endocrine and developmental behavior diseases.

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