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Article

Determining Predictors of Academic Performance in Children and Adolescents with Sickle Cell Disease and Comparing It with Siblings in Benin

by
Bonaventure G. Ikediashi
1,2,
Selma Gomez
3,4,
Edwige Dedjinou
3,
Alban Zohoun
5,6,
Roukiyath Adjile Edjide Amoussa
3,4,
Bernice Quenum
3,
Gisela Michel
1,
Eva De Clercq
1,† and
Katharina Roser
1,*,†
1
Faculty of Health Sciences and Medicine, University of Lucerne, Alpenquai 4, 6005 Lucerne, Switzerland
2
Swiss School of Public Health, 8001 Zurich, Switzerland
3
National Sickle Cell Disease Centre (CPMI-NFED), National University Hospital Centre—Hubert Koutoukou Maga (CNHU-HKM), Cotonou 01 BP 386, Benin
4
Faculty of Sciences and Technology, University of Abomey Calavi, Cotonou 01 BP 526, Benin
5
Clinical Haematology Department, National University Hospital Centre—Hubert Koutoukou Maga (CNHU-HKM), Cotonou 01 BP 386, Benin
6
Faculty of Health Sciences, University of Abomey Calavi, Cotonou 01 BP 526, Benin
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Adolescents 2025, 5(3), 30; https://doi.org/10.3390/adolescents5030030
Submission received: 27 February 2025 / Revised: 27 June 2025 / Accepted: 30 June 2025 / Published: 2 July 2025
(This article belongs to the Section Adolescent Health and Mental Health)
Browse Figures
Versions Notes

Abstract

Background: One of the major challenges for children and adolescents with sickle cell disease (SCD) is academic performance. Objectives: Our study aimed to evaluate the academic performance of children and adolescents with SCD in Benin and compare it to the academic performance of their healthy siblings and paediatric comparisons. Furthermore, we aimed to explore the associations between socio-demographic factors, clinical characteristics, and depressive symptoms, and the academic performance of children and adolescents with SCD. Methods: The study was a cross-sectional study that used convenient sampling. Academic scores were collected during the 2021–2022 academic year. Patients with SCD and paediatric comparisons were recruited during routine hospital consultations. The Children’s Depression Inventory (CDI-S) tool was used to assess depressive symptoms. We compared academic performance scores (ranging from 0 to 20) using independent t-tests and explored associations through linear regression analyses. Results: This study included 209 participants: 100 patients with SCD (aged 6 to 17 years), 46 siblings, and 63 paediatric comparisons. The academic performance of patients with SCD (mean academic score = 13.29) was similar to that of the combined comparison group (mean academic score = 12.8, p = 0.196). Younger patients showed poorer academic performance (coef = −0.169, p = 0.019), and depressive symptoms (‘pessimism’, ‘self-hate’, ‘lack of friends’, and ‘fatigue’) were associated with poorer academic performance as well. Patients with SCD who were treated in Benin performed academically as well as their healthy siblings and peers. Conclusions: Children and adolescents with SCD performed on par academically with their healthy siblings and peers. While overall depressive symptoms were not significantly associated with academic performance, certain symptoms were more common among lower-performing students and should therefore be explored in greater detail.

1. Introduction

Sickle cell disease (SCD) is a prevalent genetic condition, standing as one of the most common hemoglobinopathies in sub-Saharan Africa, where around 236,000 children born per year are affected [1]. This genetic disorder is characterised by four primary complications: vaso-occlusive episodes, manifesting as recurrent and unpredictable acute pain attacks; haemolytic anaemia; susceptibility to repeated infections; and impaired growth [2]. In children and adolescents with SCD, common manifestations include pain, infections, acute splenic sequestration, acute chest syndrome (ACS), and stroke [3]. Managing such complications often involves emergency hospital visits and prolonged periods of hospitalizations that pose considerable financial and psychosocial challenges to patients and their families [4].
One of the major challenges for children and adolescents with sickle cell disease (SCD) is academic performance [5]. Academic performance refers to an individual’s achievements within an educational environment, commonly assessed through grades and examination scores [6,7,8]. It encompasses the ability to grasp and apply subject knowledge [6], active participation in class activities, the completion of assignments, and points earned in examinations [7,8]. It has been found that compared to healthy peers or healthy siblings, children with SCD have poorer academic performance assessed by average school examination scores [9,10,11]. This can be linked to the frequent episodes of pain experienced by patients with SCD, which in turn can hinder an individual’s ability to maintain regular attendance and active participation in classroom activities and focus during lessons [12]. Other reasons include cerebral infarcts, one of the major complications of SCD causing learning difficulties [1,13], and depressive symptoms [9], which could be due to social isolation [14]. Several studies have reported depression as a common problem in children and adolescents with SCD.
The National Sickle Cell Disease Centre of Benin (Centre de Prise en charge Médicale Intégrée du Nourrisson et de la Femme Enceinte atteints de Drépanocytose, CPMI-NFED) is a national reference institution for the research and care for children, adolescents, and pregnant women with SCD. While the centre has successfully implemented medical and social interventions and thereby considerably reduced mortality rates [15,16], the academic and psychosocial profiles of these individuals have remained undocumented. Recognizing this gap, the primary objective of this study was to evaluate the academic performance of children and adolescents with SCD treated at the CPMI-NFED. More specifically, we aimed to I) measure the academic performance of children and adolescents with SCD and compare it with the academic performance of their healthy siblings and another paediatric comparison group; and II) explore the associations between socio-demographic factors, clinical characteristics, and depressive symptoms and academic performance of children with SCD.

1.1. Methods

Sample and Procedure

For this study, we used a cross-sectional design and convenience sampling as this was the most practical means of reaching the target population in this context. The participants included patients with SCD who were treated at the CPMI-NFED and two comparison groups, namely (i) healthy siblings of patients with SCD (the “sibling group”) and (ii) children and adolescents attending the paediatric clinic at the University Teaching Hospital in Benin for acute conditions (malaria, typhoid, and fever; the “paediatric group”).
Patients with SCD and participants of both comparison groups were considered eligible for the study if they were (i) aged 6 to 17 years at the time of the study and (ii) currently enrolled in either primary or secondary school. Patients with SCD had to be treated at the CPMI-NFED.
The study was carried out in two stages. The first stage involved the recruitment of patients with SCD from the CPMI-NFED and their siblings. Parents were informed about the study by their treating physician while attending a consultation. Those who indicated interest in participating in the study were directed to a waiting room with their children where the study was explained to them in detail. They were handed an information note outlining the study details and the contact information of one of the researchers. Subsequently, those who were interested provided written informed consent for their children to participate, and the children themselves provided written assent. Considering that the study was carried out during the summer vacation, in some cases, healthy siblings accompanied their parents (or legal guardians) and children with SCD to the consultation, facilitating their participation. The parents/guardians without accompanying siblings were asked about the presence of other eligible healthy siblings of the child with SCD. Information regarding the age, sex, and school level of these children was collected at that time. Additionally, parents were invited to leave their contact information with the research assistant so that they could be reminded to provide details of the academic performance of their healthy children when they returned home, either by text message or over a phone call. If needed, follow-up was conducted by the research assistant to collect this information, ensuring a comprehensive and accurate assessment.
The second stage involved the recruitment of the paediatric group from the general paediatric unit of the University Teaching Hospital in Benin. Similarly, parents were approached while awaiting a doctor’s consultation at the paediatric clinic. The remaining procedure was the same for the children with SCD and their healthy siblings.

1.2. Measures

1.2.1. Outcome Measure

The outcome measure of interest was academic performance, measured by the participants’ summative scores on all subjects in the 2021/2022 academic year. In Benin, academic scores are commonly reported on a 20-point scale and are based on formal assessments, including standardised classroom tests and teacher evaluations. Higher scores indicate better academic performance. Others, especially those in primary schools, are evaluated on a 10-point rating. Scorings obtained using the 10-point rating were converted to the 20-point rating by multiplying the scores by two, allowing for uniformity in the comparison analysis. We categorised the academic performance into 3 groups: poor (<10 points), average (10 to 14 points), and good (>14 points). A minimum score of 10 is required to move to the next grade level.

1.2.2. Predictor Measures

Socio-Demographic, Socio-Economic, and Clinical Characteristics
Socio-demographic characteristics included the participants’ age (in years), sex (male, female), and mothers’ and fathers’ education level (primary [first seven years of schooling], secondary [junior and senior high school], tertiary [university or post-secondary education]). The following clinical characteristics were collected for the patient group: genotype (HbSS, HbSC, others), number of hospitalisations in the last 12 months, history of blood transfusion (yes, no), and frequency of vaso-occlusive crises in the last 12 months. This clinical information was retrieved from the patient’s medical dossiers.
Depressive Symptoms
Depressive symptoms in patients with SCD were measured using the short form of the Children’s Depression Inventory (CDI-S) [17] consisting of 10 items indicative of depressive symptoms (“sadness”, “pessimism”, “self-depreciation”, “self-hate”, “crying spells”, “irritability”, “negative body image”, “loneliness”, “lack of friends”, “feeling unloved”). For this study, we included 3 additional items from the original 27-item CDI questionnaire: “schoolwork”, “fatigue”, and “sleep”, giving a total of 13 items. A higher score indicates a greater severity of depressive symptoms. Each of these items comprises three different phrases that describe the degree to which the respondent experiences depressive symptoms. (e.g., “I feel lonely once in a while” (score = 0); “I feel lonely often” (score = 1); “I feel lonely all the time” (score = 2)). We calculated a total score for the CDI-S ranging from 0 to 20, with a cut-off score of ≥3 [18]. The additional three items were not included in the computed CDI-S score but were analysed separately.

1.2.3. Analysis

We used t-tests and chi-squared tests to compare children with SCD with the two comparison groups regarding socio-demographic and socio-economic characteristics. For aim I, we used a one-way Analysis of Variance (ANOVA) alongside Welch’s t-tests to compare the mean academic performance between the patients with SCD and the two comparison groups (separately and in combination). These tests are robust for comparisons of groups of unequal sample sizes and heterogeneity of variances [19], which was the case in this study. Two comparisons were conducted in this study. Firstly, we compared the mean academic scores between the patient group and the separate and combined comparison groups (the combined group consisting of both the sibling group and the paediatric group). Subsequently, sub-group comparisons according to the school level (primary, secondary) were conducted.
For aim II, to examine the associations between academic performance in children and adolescents with SCD and socio-demographic, socio-economic, and clinical characteristics, and depressive symptoms (CDI-S score), we used linear regression models. First, we ran univariable regression analyses with academic performance being the outcome and socio-demographic and clinical characteristics being the explanatory variables, one by one. Second, the variables found to be significantly associated with the outcome (p ≤ 0.05) were included in the final multivariable regression model. In addition, we carried out exploratory correlation analyses to assess associations between depressive symptoms (single items; all 13 assessed items separately) and academic performance. Statistical analyses were conducted with Stata 17, College Station, TX and the Statistical Package for the Social Sciences (SPSS®) version 25 (IBM Corp., Armonk, NY, USA).

2. Results

2.1. Patients Characteristics

The socio-demographic and socio-economic characteristics of the patient and comparison groups are summarised in Table 1.
There were 209 participants enrolled in the study, including 100 patients diagnosed with SCD, 63 paediatric comparisons, and 46 healthy siblings (Table 1). About half of the patients diagnosed with SCD were female (54.0%) and attended primary school (53.0%). Their mean age was 11.1 years (SD = 3.3) and the mean age at inclusion for treatment at the CPMI-NFED was 3.5 years (SD = 2.6). In terms of the parental education level, 8.0% of fathers had a primary-level, 37.0% had a secondary-level, and 55.0% had a tertiary-level education, while 0.0% had no formal education. In the case of mothers, this was 22.0% (primary level), 43.0% (secondary level), and 27.0% (tertiary level), respectively, while 8.0% had no formal education. Most of the patients (71.0%) had the HbSS genotype and 68.0% had no history of blood transfusions.
In the sibling comparison group, the mean age was 11.9 years (SD = 3.20), and siblings were older than the patients with SCD (p = 0.03). Half of the siblings (50.0%) were male, and 53.0% attended primary school. The paediatric comparison group had a mean age of 12.2 years (SD = 3.01), and they were slightly older than the patient group (p = 0.03). In this group, 57.1% were male and 39.7% attended primary school.
In the group of patients with SCD, 71% had the HbSS genotype and 29% had the HbSC genotype. A history of blood transfusion was reported by 32%. Sixty-three percent of patients had no hospitalisations, while 20% were hospitalised more than twice during the previous 12 months. Vaso-occlusive crises were not reported by 60% of patients with SCD; 9% experienced more than two episodes during the last 12 months. The mean CDI-S depression score was 3.8 (SD = 3.1).

2.2. Academic Performance

The distribution of participants by the level of academic performance is shown in Figure 1. A minority of the patients with SCD (9%) and the joint comparison group reported poor academic performance.
The overall mean academic score of the patient group was 13.3 (SD = 2.8), while the overall mean score of the combined comparison group (i.e., the siblings and paediatric group combined) was 12.8 (SD = 2.6).
The sibling group had a mean score of 13.1 (SD = 3.2) and the paediatric group had a mean score of 12.6 (SD = 2.1).
There were no statistically significant differences observed between the patient group and either the combined comparison group (t = 1.297, p = 0.20) or the individual comparison groups (sibling group: t = 0.331, p = 0.74; paediatric group: t = 1.750, p = 0.082).
Figure 2 illustrates the comparison of the mean academic performance between the patient group and the sibling and paediatric groups, categorised by education level (primary, secondary). Mean academic performance did not differ significantly among the three groups and by academic level (t-value = 2.051, p = 0.081). At the primary education level, the mean academic score for the patient group was 14.0 (SD = 3.1), for the sibling group it was 12.9 (SD = 4.1), and for the paediatric group it was 12.4 (SD = 2.3). Similarly, at the secondary education level, the mean academic score for the patient group was 12.5 (SD = 2.15), for the sibling group it was 13.2 (SD = 2.67), and for the paediatric group it was 12.50 (SD = 1.97).

2.3. Depressive Symptoms in Patients with SCD

The CDI-S demonstrated good reliability with a Cronbach’s alpha of 0.81 in our study. The mean depression score in patients with SCD was 5.27 (SD = 3.7). More than half (59%) of the participants scored ≥3, indicating a high level of depressive symptoms.

2.4. Determinants of Academic Performance in Patients with SCD

The results of the univariable and multivariable linear regression models for patients diagnosed with SCD are displayed in Table 2. In the univariable regression analyses, younger patients (coef = −0.309, p < 0.001), and those at the primary education level (compared to secondary education: coef = −0.528, p = 0.006) had better academic performance. In the final multivariable regression model, only younger age (coef = −0.263, p = 0.046) remained significantly associated with better academic performance (Table 2). The depression scores did not differ significantly with respect to the academic performance (χ2 = 2.128, p = 0.345; Figure 3). As part of exploratory analyses, four items (‘pessimism’, ‘self-hate’, ‘lack of friends’, and ‘fatigue’) showed significant negative correlations with academic performance (Table S1 in the Supplementary Material).

3. Discussion

In this study, we compared the academic performance of children and adolescents aged 6 to 17 years with SCD to their healthy siblings and a paediatric comparison group, and investigated associations between demographic factors, clinical characteristics, depressive symptoms, and academic performance in patients with SCD. Our study revealed that the majority of patients with SCD achieved average-to-good academic performance. Overall, patients performed similarly to their healthy siblings and their peers. Patients who were older and had a high level of depressive symptoms had poorer academic performance.
In two separate Nigerian studies involving children and adolescents with SCD, academic performance comparisons revealed no significant differences between children and adolescents with SCD and their peers [20,21]. In contrast, a meta-analysis including studies in the United States [9], found poorer academic performance in children with SCD partly due to the complications of SCD, leading to micro-infarcts, repeated ischemia, and frequent school absences. Similarly, studies from Europe reported that children with SCD performed worse than their peers in tasks in a preschool executive task assessment [22] and executive functioning [23], attributing this to the direct effects of the disease itself. The Nigerian studies noted increased school absences in patients with SCD compared to the controls, despite no overall academic performance differences. In our study, comparable academic performance between patients with SCD and the comparisons might be attributed to the CPMI-NFED’s care regimen. At the CPMI-NFED, managing SCD emphasises infection prevention, which is crucial for minimizing painful crises that disrupt school attendance. This involves nutritional support, essential micronutrient supplementation [23], and infection prophylaxis [24], including controlled doses of penicillin V, oral chloroquine, impregnated mosquito nets, hygiene education, and vaccinations. Adherence to this regimen reduces acute events, leading to a substantial reduction in hospitalizations [16]. We believe this is likely to have a positive influence on the growth and development of children with SCD, thereby contributing to improved academic outcomes.
Participants in the control groups (both the sibling and paediatric groups) were, on average, older and more likely to be attending secondary school compared to participants with SCD. Additionally, a larger proportion of children in the paediatric control group had fathers with a university-level education. We found that age was the only significant predictor of academic performance in our regression analysis, with older children demonstrating lower academic achievement. This finding is consistent with previous research suggesting that the cumulative effects of SCD, such as silent cerebral infarcts, recurrent ischemia, and school absences, can lead to progressive neuropsychological complications [12]. These complications place adolescents at an increased risk of limited educational attainment, with older children often showing worse cognitive performance than their younger peers [25]. Our study did not reveal any significant associations between academic performance and the children’s sex. This finding is in line with previous research [20,21], which has also reported no substantial sex-related differences in academic achievements among children and adolescents with SCD. Furthermore, our study also found no significant associations between academic performance and parents’ education level. This outcome was unexpected given that previous studies in general populations have consistently shown that children of parents with higher levels of education tend to exhibit superior academic performance [26,27,28,29]. These findings are often attributed to factors such as increased access to educational resources and support, higher expectations for academic performance, and greater parental involvement in children’s education. Similarly, studies of children with SCD have shown that children whose parents have a higher education level tend to perform better academically [20,21]. The influence of parental education on academic performance is likely complex and multifaceted [27,30], and our study may not have captured all of the relevant factors.
Surprisingly, we did not find any associations between academic performance and the assessed clinical characteristics: genotype, frequency of hospitalisations, history of blood transfusion, and frequency of vaso-occlusive crises. Patients with SCD with the HbSS genotype tend to have more-severe manifestations of the disease, including frequent hospital admissions, frequent vaso-occlusive crises episodes, and severe acute anaemia requiring blood transfusions [31,32,33]. Considering that more-severe SCD has been found to negatively affect academic performance [10], an association between these characteristics and academic performance was expected. One possible explanation for this unexpected observation in our study could be that most patients in our study exhibited less-severe manifestations of SCD, evidenced by few hospital admissions and episodes of vaso-occlusive crises, indicating an overall relatively good health status among the participants [30].
This study unexpectedly found no differences in academic performance based on the recommended cut-off score of >3 for depressive symptoms. However, assessments showed that a high level of depressive symptoms correlated with poorer academic performance, specifically with ‘pessimism’, ‘self-hate’, ‘lack of friends’, and ‘fatigue’. Among those with poor academic performance, the majority (six out of nine) scored above the recommended cut-off of >3. Caution is warranted in interpreting these findings. While no statistically significant association was found between depressive symptoms and overall academic performance (based on the chosen cut-off score) in the patient group, a substantial proportion of those with poor academic performance scored above the cut-off value. Depression, a common issue, notably impacts academic performance, especially in individuals with chronic diseases like SCD [14,34].
This study is not without limitations and our results should be interpreted in this context. Firstly, we took a snapshot of the academic performance of the 2021/2022 academic year. This may not capture the evolution of academic performance over a more extended period; however, this nonetheless provides information on the academic performance in this population. Secondly, a sample bias might be present: our participants were recruited during routine hospital consultations. This recruitment approach may inadvertently exclude individuals with SCD who do not regularly seek medical care or who receive treatment elsewhere. Thirdly, we could also not collect data on school absences as we did not have access to the school dossier of the participants during the timeframe in which data was collected. However, we believe that parents’ reports reasonably reflect the actual academic performance of their children. Significant group differences in age and education level were observed, which could confound comparisons and should be considered when interpreting the results. We did not evaluate depressive symptoms in the siblings and the paediatric group and therefore were not able to investigate the association between depressive symptoms and academic performance in these groups Finally, our study possesses a modest sample size, prompting the consideration of larger-scale investigations in the future. Such studies should encompass an expanded participant pool and seek to encompass data on academic performance within the context of schoolmates, thereby offering a more comprehensive evaluation and comparison with peers. Despite these limitations, in this study, we assessed the academic performance of children and adolescents with SCD in comparison to their healthy siblings and paediatric peers within the context of Benin. Moreover, we were able to retrieve information on the clinical characteristics from the medical dossiers, ensuring the accuracy and reliability of the data.

4. Conclusions

In conclusion, this study evaluated the academic performance of children and adolescents with SCD under the comprehensive care regimen of the CPMI-NFED, in comparison to their healthy siblings, and found that they performed as well as their siblings and the paediatric group. While these findings highlight encouraging parity in the academic performance of patients with SCD, they underscore the need to monitor the impact of depressive symptoms, as our exploratory findings suggest that certain symptoms may be more common in patients with poorer academic performance. Therefore, it remains important to provide adequate psychosocial support to patients with SCD, particularly to those who experience challenges with their academic performance. At the CPMI-NFED, psychosocial care such as counselling services provided by mental health professionals and support groups should be included in the services provided to children and adolescents.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/adolescents5030030/s1, Table S1: Correlations between depressive symptoms and academic performance in SCD patients.

Author Contributions

Funding for this project was secured by G.M., A.Z., S.G., E.D., B.Q., K.R., E.D.C. and B.G.I. The project protocol was drafted by S.G., E.D. and B.Q. The study was designed by S.G., E.D., B.Q., B.G.I., K.R. and E.D.C. Data collection was carried out by B.G.I., S.G., E.D., R.A.E.A. and B.Q. Data analysis was carried out by B.G.I. and K.R. B.G.I. drafted the manuscript with contributions from all of the authors. All authors have read and agreed to the published version of the manuscript.

Funding

This project was funded by a “Leading House Africa Lectureships and Prolonged Research Stays at African Higher Education Institutions for Research Groups of Swiss Higher Education Institutions” grant in 2022.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethics Committee of CPMI-NFED (CSI/001/2022, August 2022) for studies involving humans.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The datasets used for the current study are available from the corresponding author upon reasonable request.

Conflicts of Interest

The authors declare that they have no competing interests.

References

  1. Schatz, J.; Brown, R.T.; Pascual, J.M.; Hsu, L.; DeBaun, M.R. Poor school and cognitive functioning with silent cer-ebral infarcts and sickle cell disease. Neurology 2001, 56, 1109–1111. [Google Scholar] [CrossRef] [PubMed]
  2. Piel, F.B.; Patil, A.P.; Howes, R.E.; Nyangiri, O.A.; Gething, P.W.; Dewi, M.; Temperley, W.H.; Williams, T.N.; Weatherall, D.J.; Hay, S.I. Global epidemiology of sickle haemoglobin in neonates: A contemporary geostatistical model-based map and population estimates. Lancet 2013, 381, 142–151. [Google Scholar] [CrossRef]
  3. Ballas, S.K.; Lieff, S.; Benjamin, L.J.; Dampier, C.D.; Heeney, M.M.; Hoppe, C.; Johnson, C.S.; Rogers, Z.R.; Smith-Whitley, K.; Wang, W.C.; et al. Definitions of the Phenotypic Manifestations of Sickle Cell Disease. Am. J. Hematol. 2010, 85, 6–13. [Google Scholar] [CrossRef]
  4. Schnog, J.B.; Duits, A.J.; Muskiet Fa, J.; ten Cate, H.; Rojer, R.A.; Brandjes, D.P.M. Sickle cell disease; a general over-view. Neth. J. Med. 2004, 62, 364–374. [Google Scholar]
  5. Adegboyega, L.O. Psycho-social problems of adolescents with sickle-cell anaemia in Ekiti State, Nigeria. Afr. Health Sci. 2021, 21, 775–781. [Google Scholar] [CrossRef]
  6. Narad, A.; Abdullah, B. Academic Performance of Senior Secondary School Students: Influence of Parental Encouragement and School Environment. Rupkatha J. Interdiscip. Stud. Humanit. 2016, 8, 12–19. [Google Scholar] [CrossRef]
  7. Choi, N. Self-efficacy and self-concept as predictors of college students’ academic performance. Psychol. Sch. 2005, 42, 197–205. [Google Scholar] [CrossRef]
  8. Gallardon, J. Facteurs Prédictifs de Retard Scolaire Chez le Patient Drépanocytaire. Médecine Humaine et Pathologie. Ph.D. Thesis, University Post-Viva Dissertation Deposit, Lyon, France, 2017. [Google Scholar]
  9. Heitzer, A.M.; Hamilton, L.; Stafford, C.; Gossett, J.; Ouellette, L.; Trpchevska, A.; King, A.A.; Kang, G.; Hankins, J.S. Academic Performance of Children with Sickle Cell Disease in the United States: A Meta-Analysis. Front. Neurol. 2021, 12, 786065. [Google Scholar] [CrossRef]
  10. Alhazmi, A.; Hakami, K.; Abusageah, F.; Jaawna, E.; Khawaji, M.; Alhazmi, E.; Zogel, B.; Qahl, S.; Qumayri, G. The Impact of Sickle Cell Disease on Academic Performance among Affected Students. Children 2021, 9, 15. [Google Scholar] [CrossRef]
  11. Abid, F.; Hassan, M.; Ahmed, B. School performance of children with sickle cell disease in Basra, Iraq. Iraqi J. Hematol. 2019, 8, 29–37. [Google Scholar] [CrossRef]
  12. Haridasa, N.; DeBaun, M.R.; Sanger, M.; Mayo-Gamble, T.L. Student perspectives on managing sickle cell disease at school. Pediatr. Blood Cancer 2019, 66, e27507. [Google Scholar] [CrossRef] [PubMed]
  13. Crosby, L.E.; Joffe, N.E.; Irwin, M.K.; Strong, H.; Peugh, J.; Shook, L.; Kalinyak, K.A.; Mitchell, M.J. School Performance and Disease Interference in Adolescents with Sickle Cell Disease. Phys. Disabil. Educ. Relat. Serv. 2015, 34, 14–30. [Google Scholar] [CrossRef] [PubMed]
  14. Hurtig, A.L.; Park, K.B. Adjustment and coping in adolescents with sickle cell disease. Ann. N. Y. Acad. Sci. 1989, 565, 172–182. [Google Scholar] [CrossRef] [PubMed]
  15. Rahimy, M.C.; Gangbo, A.; Ahouignan, G.; Alihonou, E. Newborn screening for sickle cell disease in the Republic of Benin. J. Clin. Pathol. 2009, 62, 46–48. [Google Scholar] [CrossRef]
  16. Rahimy, M.C.; Gangbo, A.; Ahouignan, G.; Adjou, R.; Deguenon, C.; Goussanou, S.; Alihonou, E. Effect of a comprehensive clinical care program on disease course in severely ill children with sickle cell anemia in a sub-Saharan African setting. Blood 2003, 102, 834–838. [Google Scholar] [CrossRef]
  17. Kovacs, M. Children’s Depression Inventory (CDI and CDI 2). In The Encyclopedia of Clinical Psychology; John Wiley & Sons, Ltd.: Hoboken, NJ, USA, 2015; pp. 1–5. ISBN 978-1-118-62539-2. [Google Scholar]
  18. Allgaier, A.-K.; Frühe, B.; Pietsch, K.; Saravo, B.; Baethmann, M.; Schulte-Körne, G. Is the Children’s Depression Inventory Short version a valid screening tool in pediatric care? A comparison to its full-length version. J. Psychosom. Res. 2012, 73, 369–374. [Google Scholar] [CrossRef]
  19. Derrick, B.; White, P. Why Welch’s test is Type I error robust. Quant. Methods Psychol. 2016, 12, 30–38. [Google Scholar] [CrossRef]
  20. Olatunya, O.S.; Oke, O.J.; Kuti, B.P.; Ajayi, I.A.; Olajuyin, O.; Omotosho-Olagoke, O.; Taiwo, A.B.; Faboya, O.A.; Ajibola, A. Factors Influencing the Academic Performance of Children with Sickle Cell Anaemia in Ekiti, South West Nigeria. J. Trop. Pediatr. 2018, 64, 67–74. [Google Scholar] [CrossRef]
  21. Ezenwosu, O.U.; Emodi, I.J.; Ikefuna, A.N.; Chukwu, B.F.; Osuorah, C.D. Determinants of academic performance in children with sickle cell anaemia. BMC Pediatr. 2013, 13, 189. [Google Scholar] [CrossRef]
  22. Downes, M.; Kirkham, F.J.; Berg, C.; Telfer, P.; de Haan, M. Executive performance on the preschool executive task assessment in children with sickle cell anemia and matched controls. Child Neuropsychol. 2019, 25, 278–285. [Google Scholar] [CrossRef]
  23. Arfé, B.; Montanaro, M.; Mottura, E.; Scaltritti, M.; Manara, R.; Basso, G.; Sainati, L.; Colombatti, R. Selective difficulties in lexical retrieval and nonverbal executive functioning in children with HbSS sickle cell disease. J. Pediatr. Psychol. 2018, 43, 666–677. [Google Scholar] [CrossRef]
  24. Koury, M.J.; Ponka, P. NEW INSIGHTS INTO ERYTHROPOIESIS: The Roles of Folate, Vitamin B12, and Iron. Annu. Rev. Nutr. 2004, 24, 105–131. [Google Scholar] [CrossRef] [PubMed]
  25. Zeba, A.N.; Sorgho, H.; Rouamba, N.; Zongo, I.; Rouamba, J.; Guiguemdë, R.T.; Hamer, D.H.; Mokhtar, N.; Ouedraogo, J.-B. Major reduction of malaria morbidity with combined vitamin A and zinc supplementation in young children in Burkina Faso: A randomized double blind trial. Nutr. J. 2008, 7, 7. [Google Scholar] [CrossRef]
  26. Schatz, J.; Finke, R.L.; Kellett, J.M.; Kramer, J.H. Cognitive functioning in children with sickle cell disease: A meta-analysis. J. Pediatr. Psychol. 2002, 27, 739–748. [Google Scholar] [CrossRef]
  27. Davis-Kean, P.E. The influence of parent education and family income on child achievement: The indirect role of parental expectations and the home environment. J. Fam. Psychol. 2005, 19, 294–304. [Google Scholar] [CrossRef] [PubMed]
  28. Sirin, S.R. Socioeconomic Status and Academic Achievement: A Meta-Analytic Review of Research. Rev. Educ. Res. 2005, 75, 417–453. [Google Scholar] [CrossRef]
  29. Dornbusch, S.M.; Ritter, P.L.; Leiderman, P.H.; Roberts, D.F.; Fraleigh, M.J. The Relation of Parenting Style to Adolescent School Performance. Child Dev. 1987, 58, 1244–1257. [Google Scholar] [CrossRef] [PubMed]
  30. Hill, N.E.; Tyson, D.F. Parental involvement in middle school: A meta-analytic assessment of the strategies that promote achievement. Dev. Psychol. 2009, 45, 740–763. [Google Scholar] [CrossRef]
  31. da Guarda, C.C.; Yahouédéhou, S.C.M.A.; Santiago, R.P.; Neres, J.S.D.S.; Fernandes, C.F.D.L.; Aleluia, M.M.; Figueiredo, C.V.B.; Fiuza, L.M.; Carvalho, S.P.; de Oliveira, R.M.; et al. Sickle cell disease: A distinction of two most frequent genotypes (HbSS and HbSC). PLoS ONE 2020, 15, e0228399. [Google Scholar] [CrossRef]
  32. Joly, P.; Pondarré, C.; Bardel, C.; Francina, A.; Martin, C. The alpha-globin genotype does not influence sickle cell disease severity in a retrospective cross-validation study of the pediatric severity score. Eur. J. Haematol. 2012, 88, 61–67. [Google Scholar] [CrossRef]
  33. Diop, S.; Pirenne, F. Transfusion and sickle cell anemia in Africa. Transfus. Clin. Biol. 2021, 28, 143–145. [Google Scholar] [CrossRef] [PubMed]
  34. Anie, K.A. Psychological complications in sickle cell disease. Br. J. Haematol. 2005, 129, 723–729. [Google Scholar] [CrossRef] [PubMed]
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Figure 1. Distribution of participants by academic performance for the patient group and the comparison groups (separately and in combination).
Figure 1. Distribution of participants by academic performance for the patient group and the comparison groups (separately and in combination).
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Figure 2. Academic performance of the three groups (patient group, sibling group, paediatric group) by education level (primary, secondary), and in total.
Figure 2. Academic performance of the three groups (patient group, sibling group, paediatric group) by education level (primary, secondary), and in total.
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Figure 3. Distribution of academic performance by depression score groups in the patient group.
Figure 3. Distribution of academic performance by depression score groups in the patient group.
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Table 1. Socio-demographic and socio-economic characteristics of the patient and comparison groups.
Table 1. Socio-demographic and socio-economic characteristics of the patient and comparison groups.
Patients with SCDSibling ComparisonsPaediatric Comparisons
Total number10046 63
Mean (SD)Mean (SD)(t, p-value)Mean (SD)(t, p-value)
Age a11.1 (3.3)11.9 (3.20)(−1.346, 0.180)12.2 (3.01)(−2.126, 0.035)
Age at Inclusion b3.5(2.6)
N (%)N (%)(χ p-value)N (%)(χ, p-value)
Sex 0.202 (0.653) 1.920 (0.166)
Male46 (46.0)23 (50.0) 36 (57.1)
Female54(54.0)23 (50.0) 27(42.9)
Education Level c 3.249 (0.071) 3.957 (0.047)
Primary53 (53.0)17 (37.0) 25 (39.7)
Secondary47 (47.0)29 (63.0) 38 (60.3)
Father’s Education 3.248 (0.197) 9.643 (0.022)
Level c
Primary8(8.0)8 (17.4) 9 (14.3)
Secondary37 (37.0)16 (34.8) 11 (17.5)
Tertiary55(55.0)22 (47.8) 42 (66.7)
None0 (0.0)0 (0.0) 1 (1.6)
Mother’s Education 2.165 (0.539)  1.188 (0.756)
Level c
Primary22 (22.0)14 (30.4) 13 (20.6)
Secondary43 (43.0)20 (43.5) 26 (41.3)
Tertiary27 (27.0)8 (17.4) 21 (33.3)
None8 (8.0)4 (8.7) 3 (4.8)
Abbreviations: SD, standard deviation; CDI, Children’s Depression Inventory. a = Independent t-test applied; b = Inclusion at the CPMI-NFED for treatment; c = Chi-square test applied; significant values are in bold.
Table 2. Associations between socio-demographic, socio-economic, and clinical characteristics, and depressive symptoms and academic performance in children with SCD.
Table 2. Associations between socio-demographic, socio-economic, and clinical characteristics, and depressive symptoms and academic performance in children with SCD.
Univariable Regression AnalysesMultivariable Regression Analysis
Coefficient 95% CIp-ValueCoefficient95% CIp-Value
Age (years)−0.309−0.469, −0.149<0.001 **−0.263−0.521, −0.0050.046 *
Age inclusion (years)−0.09−0.307, 0.1290.416
Gender (male)
   Female−0.127−1.248, 0.9950.823
Education (primary)
   Secondary−1.528−2.605, −0.0040.006 *0.201−1.44, 1.8450.808
Father’s education (primary)
 Secondary0.258−1.849, 2.3640.809
 Tertiary1.755−0.287, 3.7960.091
   No formal education a
Mother’s education (primary)
 Secondary1.188−0.236, 2.6120.1011.058−0.275, 2.3920.118
 Tertiary2.0830.523, 3.6420.009 *1.376−0.125, 2.8780.072
 No formal education0.262−1.980, 2.5040.817−0.109−2.211, 1.9920.918
Genotype (HbSS)
   HbSC0.919−0.299, 2.1370.138
Hospitalisation (none)
 1 to 20.996−0.514, 2.5070.194
 3 and above−0.648−2.066, 0.7700.367
Transfusion history (no)
(yes)−0.011−1.255, 1.2340.987
Vaso-occlusive crises (none)
1 to 20.675−0.560, 1.9100.281
3 and above0.299−1.697, 2.2960.767
CDI score (less than 3)
3 and above−0.635 −1.765, −0.494 −0.267
Abbreviations: SD, standard deviation; CDI, Children’s Depression Inventory; CI, confidence interval. a = coefficient unavailable, because none of the fathers had no formal education; * p < 0.05; ** p < 0.001; statistically significant associations are indicated in bold.
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MDPI and ACS Style

Ikediashi, B.G.; Gomez, S.; Dedjinou, E.; Zohoun, A.; Amoussa, R.A.E.; Quenum, B.; Michel, G.; De Clercq, E.; Roser, K. Determining Predictors of Academic Performance in Children and Adolescents with Sickle Cell Disease and Comparing It with Siblings in Benin. Adolescents 2025, 5, 30. https://doi.org/10.3390/adolescents5030030

AMA Style

Ikediashi BG, Gomez S, Dedjinou E, Zohoun A, Amoussa RAE, Quenum B, Michel G, De Clercq E, Roser K. Determining Predictors of Academic Performance in Children and Adolescents with Sickle Cell Disease and Comparing It with Siblings in Benin. Adolescents. 2025; 5(3):30. https://doi.org/10.3390/adolescents5030030

Chicago/Turabian Style

Ikediashi, Bonaventure G., Selma Gomez, Edwige Dedjinou, Alban Zohoun, Roukiyath Adjile Edjide Amoussa, Bernice Quenum, Gisela Michel, Eva De Clercq, and Katharina Roser. 2025. "Determining Predictors of Academic Performance in Children and Adolescents with Sickle Cell Disease and Comparing It with Siblings in Benin" Adolescents 5, no. 3: 30. https://doi.org/10.3390/adolescents5030030

APA Style

Ikediashi, B. G., Gomez, S., Dedjinou, E., Zohoun, A., Amoussa, R. A. E., Quenum, B., Michel, G., De Clercq, E., & Roser, K. (2025). Determining Predictors of Academic Performance in Children and Adolescents with Sickle Cell Disease and Comparing It with Siblings in Benin. Adolescents, 5(3), 30. https://doi.org/10.3390/adolescents5030030

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