Attention Deficit Hyperactivity Disorder (ADHD) and mood disorders in Peruvian Human Medicine students: a nationwide pilot test.

INTRODUCTION

Attention deficit hyperactivity disorder, also known by its acronym ADHD, is considered a neurodevelopmental disorder, which usually presents its first manifestations before the age of 12, whose symptoms can persist into adult life.(1)

The literature reports that this pathology presents a relatively uncertain prevalence, since there are different classifications with different diagnostic criteria, and according to each of them there would be a different prevalence. Based on the criteria of the DSM in its fourth edition (DSM-IV) the estimated prevalence would be 3-7% of the child population. While according to the International Classification of Diseases in its tenth edition (ICD-10) it would be 1.5%, these cases would be with severity characteristics compatible with the mixed subtype of the classification according to DSM. Currently, it is estimated that its prevalence in the adult population is 4 to 5%, higher figures compared to schizophrenia, or bipolar disorder, positioning it as one of the most frequent psychiatric disorders in the adult population.(2,3)

Several studies report that the persistence of symptoms during adulthood occurs in 50-70% of children with ADHD, of these, 40 to 50% have significant symptoms, and 10 to 15% severe. In the adult population, the persistence of these symptoms affects different areas of their daily lives, such as academic performance, work performance, interpersonal relationships, and other areas such as substance use and abuse.(4)

The academic area is one of the dimensions with the greatest importance for the development of a person, since it generates the main tools for survival during adult life. Studies indicate that the prevalence of this pathology in the university population ranges from 10 to 25% of students, in particular those of human medicine. In the case of Peru, Chambi (2018) observed that in a particular Lima university, 23.3% of human medicine students were found with symptoms suggestive of ADHD, of which 30% belonged to the lower third, associating this pathology with poor academic performance.(5-7)

Other research has indicated the presence of other associated pathologies such as mood disorders, different types of dependencies (tobacco, alcohol, and internet use). Regarding mood disorders, we find depression, in some cases to a severe degree with suicidal ideation. Anxiety and stress.(8-10)

The objective of the present study was to develop a pilot test with which it was sought to obtain initial estimates for the calculation of the sample size (prevalences, relationship between the variables), in addition to testing the forms in the sample context to correct possible errors or improve the process during the sample of the final study.

MATERIALS AND METHODS

Methodological design

The pilot test followed the methodological design of the original study, which consisted of an observational cross-sectional study, also known as an analytical or prevalence cross-sectional study. The objectives of the study were to know an approximate prevalence of attention deficit hyperactivity disorder (ADHD), the approximate prevalence of mood disorders (depression, anxiety, and stress) in Peruvian human medicine students, in addition to the relationship between these disorders. And with this, obtain the initial estimates for the calculation of the sample size for the original study.

Target population, instruments, and data collection technique

The study was designed to explore the variables mentioned in human medicine students throughout the Peruvian territory. All students from the first to the last cycle of the degree were included, in addition to those who were in the process of titling at the time of the invitation to participate in the study. Participants who did not study or reside in Peru, as well as those who did not wish to participate or provide informed consent, were excluded.

The instruments used were the “Attention Deficit Hyperactivity Disorder Self-Report Scale in Adults (ASRS V1.1)” and the “Abbreviated Depression, Anxiety and Stress Scale (DASS-21)”, for the variable ADHD and for mood disorders respectively.

For a viable management of the number of participants regarding their geographical location of study and residence, the departments were grouped into 5 macroregions: Lima macroregion, North, South, Center, and East. (Figure 1)

The sampling developed was of the non-probabilistic type of the “snowball” type.

The instruments used were compiled into a virtual form of the Google platform (Google Form), which was disseminated through the main social networks (Facebook, Instagram) and WhatsApp groups. This dissemination was supported by the various scientific societies of Peruvian medical students.

Information Processing

The data collected were processed using the following statistical packages: Epidat v4.2 (for randomization and subsequent calculation of the sample size), and R Studio v4.1 for data analysis.

Ethical aspects

This pilot study was approved by an institutional ethics committee of the UPSJB, ensuring that all bioethical criteria were met before the start of the field stage. In addition, an informed consent was requested from each participant where all the pertinent information regarding the study was made known to them. At the time of filling out the database, each participant was encrypted, to hide the identity and respect the privacy of each participant.

RESULTS

Enrolment and final sample size

The sampling process was carried out during the months of July and August of the year 2021. 350 participants were enrolled (70 for each macroregion), randomly selecting 50 participants representing each macroregion, forming a total sample of 250 participants for the pilot test. (Figure 1)

Descriptive analysis

Population characteristics

Of the 250 participants, the average age was 23 years, with an age range ranging from 17 to 40 years. Regarding gender, 64% of the sample reported belonging to the female gender. Depending on the type of university they attend, 57.2% reported studying at a state university. Regarding the cycle of studies, 88% of the sample were from the first to the last cycle prior to the medical internship, 20 reported being in the medical internship, and 10 were in the process of titling. Regarding psychiatric history, 34.4% reported having one. Of these, only 7 reported having a history of ADHD, the rest was divided between depression, anxiety, and stress. (See Table 1).

Attention deficit hyperactivity disorder and mood disorders

Regarding ADHD, it was observed that of the total sample collected, 33.6% presented results suggestive of this disorder. (Table 2)

Of the 250 participants, the prevalence of mood disorders was 81.6%. Of these, the most prevalent disorder was anxiety with 70.4%, followed by depression (62.8%) and stress (57.6%). Among the participants who presented a diagnosis suggestive of depression, it was observed that most presented moderate symptoms (39.4%). Of the participants with suggestive anxiety, 85.2% had symptoms of moderate to extremely severe intensity. Regarding participants with symptoms suggestive of stress, 73.6% were classified as mild to moderate stress.

When analyzing the data collected according to macro region, it was observed that at the level of the Macro Region lima, 16 (32%) students presented a diagnosis suggestive of ADHD, while 34 did not (n = 50 per macro region). 76% (38 participants) had some type of mood disorder (depression, anxiety, and stress). Of the participants with suggestive ADHD, only 6% (1 participant) did not have any mood disorder. Regarding the group of students who presented a non-suggestive diagnosis for ADHD, 23 of them (6%) had some type of mood disorder. (Figure 2)

Regarding the Northern macroregion, it was observed that 30% were suggestive of ADHD, and 90% some mood disorder. Of the participants with suggestive ADHD, all gave a suggestive diagnosis of mood disorder, compared to the non-suggestive ADHD group with 85%. (Figure 2)

The Southern macroregion observed the following figures: suggestive ADHD in 34%, and 82% for mood disorder. Of the participants with suggestive ADHD, only 5% did not have any mood disorder. Compared to the negative ADHD group, in which 75% had some mood disorder.

In the case of the central macroregion, the proportion of suggestive ADHD with respect to non-suggestive ADHD was 36%, and for mood disorders the proportion was 80%. The suggestive ADHD group presented 5% with absence of mood disorder, compared to the non-suggestive group, which presented 71% with mood

disorder.

Finally, in the East macroregion it was observed that 36% presented a suggestive diagnosis for ADHD, of which all presented some mood disorder. Of the total sample, 80% presented some type of mood disorder. Only in the non-suggestive ADHD group were participants found who did not present some type of mood disorder (31%).

Analytical statistics

Association between ADHD and mood disorders.

The associative analysis between the variables of interest mentioned consisted of two stages: The initial analysis was based on the calculation of the association using Pearson’s chi-square test with its respective p-value, for statistical significance. The second stage consisted of the statistical quantification of the association using association measures. Due to the study design presented (Cross-sectional) the appropriate association measure is the Prevalence Ratio; however, the use of the Odds ratio has also been considered to observe the overestimation of this test in this type of studies.

The associative analysis was carried out with the entire sample (250 participants), grouping it as a national reference.

ADHD and Mood Disorder

With respect to the Chi-square test, it was first analyzed that our data met the test of the expected values as a prerequisite. The value of the chi-square test was 17.07 (p<0.001), considering statistically significant association.

The prevalence ratio (PR) obtained was 1.3 (CI (95%): 1.18 – 1.44), confirming the association demonstrated by p value.

The calculated OR was 9.44 (CI (95%): 2.83 – 31.45), with a clear overestimation when compared with the PR. (Table 2)

ADHD and depression

The association of ADHD and depression was statistically meaning: (p<0.001) using Pearson’s Chi-square test (16,692). PR equal to 1.51 (CI (95%): 1.27 – 1.80) and OR of 3.68 (CI (95%): 1.97 – 6.86). (Table 2)

ADHD and anxiety

The association of ADHD and anxiety was statistically meaning: (p<0.001) using Pearson’s Chi-square test (20,309). PR equal to 1.47 (CI (95%): 1.27 – 1.69) and OR of 5.36 (CI (95%): 2.51 – 11.45). (Table 2)

ADHD and stress

The association between ADHD and stress was statistically meaning: (p<0.001) using Pearson’s Chi-square test (32,733). PR equal to 1.87 (CI (95%): 1.54 – 2.27) and OR of 6.22 (CI (95%): 3.24 – 11.91). (Table 2)

DISCUSSION

The findings of this pilot study give us a glimpse of the picture regarding mental health in our human medicine students.

First, they provide and reinforce the little knowledge available in the scientific literature on attention deficit hyperactivity disorder (ADHD) in adults, particularly human medicine students, both internationally and nationally. It is common knowledge that the career of human medicine is one of the most academically demanded, so it is not expected to find cases of this pathology in this population. Contrary to this, various research studies have observed that the prevalence ranges from 16 to 37%.(8,11-14)

Regarding this, there is little national scientific literature, a study by Regalado-Rodríguez, Fernández-Mogollón and Alipázaga-Pérez (2015) reported that in two universities in the city of Chiclayo the prevalence was 14.6%. While, in the city of Lima, Chambi (2018) described that the prevalence in a capital university was 23.3%. Although the results obtained are higher than the figures mentioned at the national level, these are within the range observed in international studies.(7,15)

Within the pilot study, there was also the participation of recent graduates who did not yet have an academic degree in medicine (bachelor’s degree or professional degree), observing that in this group there was also suggestive ADHD (5 participants), so it could be thought that for this group resilience and the desire to overcome predominated, thus avoiding academic desertion.

Regarding mood disorders, the scientific literature has shown the high prevalence in human medicine students, this shows how the mental health of our students, even doctors, has been increasingly diminished over the years. A study published in 2016 by Vilchez-Cornejo et al mentions that in 8 faculties of human medicine nationwide the prevalence of mood disorders in the form of depression, anxiety and stress was 32.5%, 52.9% and 34.6% respectively. The findings evidenced in the following pilot study are considerably higher (70.4%, 62.8% and 57.6%), and all of them accounted for 81% of the sample. These results may be due to the new pandemic context in which we are living, the change in lifestyle, classes, virtuality, etc. In addition, academic demands increase every year.(16)

It is described in the literature that ADHD can be accompanied by other disorders such as mood disorders, especially depression. However, the association between both pathologies has not been quantified, so the present study gives us an estimate of this. ADHD is a factor associated with a 30% more likely to present some type of mood disorder.(9,10)

Secondly, it allowed us to estimate the figures required to establish the sample size of the final study, knowing the proportion of exposed with the outcome of interest (suggestive ADHD with mood disorder) and the proportion of not exposed with the outcome of interest (non-suggestive ADHD with mood disorder).

Finally, it allowed to test and observe the correct development of the instrument during the field work and to observe possible limitations in the sampling.

Within the limitations of the pilot study, the main limitation was to carry out a non-probabilistic sampling, which sought to reduce the possible biases presented when carrying out a process of randomization of the sample. Another limitation presented was the reluctance of some students to participate in the study. The main strength that we consider the study presents is the representativeness of the sample, since by grouping the various departments into macro regions it could be more viable to collect samples for each macro region.

In conclusion, the present pilot study has allowed us to satisfactorily test the performance of the instrument and the technique proposed by the methodological design in the primary study. Confirmed with the obtaining of estimated figures consistent with what is described by the literature, contributing to clarify a little the panorama regarding these disorders in our students of human medicine. It is recommended to encourage more research on this disorder, as scientific publications to date are limited and a wide range of research topics are glimpsed.

REFERENCES

1. 1. Ortiz León S, Jaimes Medrano AL. Attention deficit disorder in adulthood and in university students. Journal of the Faculty of Medicine of the UNAM. 2016 ;59(5):6–14. Available in: https://www.medigraphic.com/pdfs/facmed/un-2016/un165b.pdf
2. 2. Hidalgo Vicario MI, Soutullo Esperón C. Attention deficit hyperactivity disorder. Clinical manifestations and evolution. Diagnosis from scientific evidence. Integral Pediatrics. 2014 ;18(9):609–23. Available in: https://www.pediatriaintegral.es/wp-content/uploads/2014/xviii09/03/n9-609-623_Ines%20Hidalgo.pdf
3. 3. Reyes Ticas JA, Reyes Ochoa E. Attention deficit hyperactivity disorder (ADHD) in adults. Rev méd hondur. 2010 ;196–202. Available in: http://www.bvs.hn/RMH/pdf/2010/pdf/Vol78-4-2010-10.pdf
4. 4. Barkley RA, Fischer M, Edelbrock CS, Smallish L. The adolescent outcome of hyperactive children diagnosed according to research criteria: An 8-year prospective follow-up study. J Am Acad Adolescent Child Psychiatry. 1990 ;29(4):546–57. Available in: https://pubmed.ncbi.nlm.nih.gov/2387789/
5. 5. Shen Y, Zhang Y, Chan BSM, Meng F, Yang T, Luo X, et al. Association of ADHD symptoms, depression and suicidal behaviors with anxiety in Chinese medical college students. BMC Psychiatry. 2020 Apr 22; 20(1). Disponible en: https://pubmed.ncbi.nlm.nih.gov/32321462/
6. 6. Shi M, Liu L, Sun X, Wang L. Associations between symptoms of attention-deficit/ hyperactivity disorder and life satisfaction in medical students: The mediating effect of resilience. BMC Medical Education . 2018 Jul 13;18(1). Disponible en: https://pubmed.ncbi.nlm.nih.gov/30005708/
7. 7. Chambi Infantas FN. Prevalence of attention deficit and hyperactivity disorder in students of the Faculty of Human Medicine of the University of San Martín de Porres; March 2018 [Thesis]. [Lima]; 2018. Available in: https://repositorio.usmp.edu.pe/bitstream/handle/20.500.12727/3863/chambi_ifn.pdf?sequence=3&isAllowed=y
8. 8. Njuwa KF, Simo LP, Ntani LL, Forchin AN, Parviel C, Tianyi Tianyi FL, et al. Factors associated with the symptoms of attention deficit hyperactivity disorder among medical students in Cameroon: a web-based cross-sectional study. BMJ Open. 2020 May 7 ;10(5):1–7. Available in: https://pubmed.ncbi.nlm.nih.gov/32385066/
9. 9. Cienfuegos-Meza J, Gaytán-Magaña JJ, Hermosillo-Pérez SN, Martínez-Sánchez AE, Oropeza-Prieto A, Rodríguez-Mendoza RL, et al. Attention deficit hyperactivity disorder and its prevalence in medical students of the Autonomous University of Aguascalientes. Lux Medical. 2012; 20(1):55–9. Available in: https://revistas.uaa.mx/index.php/luxmedica/article/view/1578/1468
10. 10. Shen Y, Chan BSM, Liu J, Meng F, Yang T, He Y, et al. Estimated prevalence and associated risk factors of attention deficit hyperactivity disorder (ADHD) among medical college students in a Chinese population. Journal of Affective Disorders . 2018 Dec 1; 241:291–6. Disponible en: https://pubmed.ncbi.nlm.nih.gov/30142587/
11. 11. Santander JT, Enrique Berner JG, María Contreras AS, Gómez TD. Prevalence of attention deficit in medical students at the Pontificia Universidad Católica de Chile. Chilean Journal of Neuro-Psychiatry. 2013; 51(3):169–74. Available in: www.sonepsyn.cl
12. 12. Atwoli L, Owiti P, Manguro G, Ndambuki D. Attention deficit hyperactivity disorder symptom self-report among medical students in Eldoret, Kenya. African Journal of Psychiatry (South Africa). 2011 Sep;14(4):286–9. Disponible en: https://pubmed.ncbi.nlm.nih.gov/22038426/
13. 13. Mattos P, Nazar BP, Tannock R. By the book: ADHD prevalence in medical students varies with analogous methods of addressing DSM items. Revista Brasileira de Psiquiatria. 2018 Oct 1; 40(4):382–7. Disponible en: https://pubmed.ncbi.nlm.nih.gov/29451590/
14. 14. Ashor AW. Variable influence of the degree of smoking dependence on adult attention deficit/hyperactivity disorder in Iraqi medical students. Vol. 17, Neurosciences. 2012. Disponible en: www.neurosciencesjournal.org
15. 15. Regalado-Rodríguez MA, Fernández-Mogollón J, Alipázaga-Pérez P. Attention deficit hyperactivity disorder in medical students of the Universidad Nacional Pedro Ruiz Gallo and Universidad de San Martin de Porres – Filial Norte, 2015. Rev body medid HNAAA . 2017; 10(1):35–9. Available in: https://docs.bvsalud.org/biblioref/2020/03/1052237/rcm-v10-n1-2017_pag35-39.pdf
16. 16. Vilchez-Cornejo J, Quiñones-Laveriano D, Failoc-Rojas V, Acevedo-Villar T, Larico-Calla G, Mucching-Toscano S, et al. Mental health and sleep quality in students from eight human medicine schools in Peru. Chilean Journal of Neuro-Psychiatry. 2016 Dec 1; 54(4):272–81. Available in: https://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-92272016000400002&lng=p&nrm=iso&tlng=p
17.