Comparative Assessments of Psychological Outcome of Mental Health Issues Among Adolescent Student

Research design

This study employed a comparative cross-sectional survey design to assess the psychological outcomes of mental health issues among adolescent students in the FCT, Abuja, Nigeria. The design was chosen because it allows for the systematic collection of quantitative data at a single point in time, enabling comparisons across key variables such as school type (private vs. public) and school location (urban vs. rural). A comparative approach was particularly relevant, as it facilitated statistical testing of differences in mental health outcomes between subgroups, while providing insights into the prevalence, patterns, and psychological challenges among adolescents.

Study area

The study was conducted in the FCT, Abuja, Nigeria’s administrative capital, and a cosmopolitan city with a diverse population. Abuja is a strategic choice for this research due to its mix of urban and rural communities, as well as the availability of both public and private secondary schools. This diversity allowed for robust comparisons of mental health outcomes across different socio-demographic and educational contexts.

Study population

The target population comprised adolescent students aged 10– 19 years attending secondary schools (both junior and senior) in the FCT. Adolescence was defined in line with the WHO’s classification of 10–19 years. This group was chosen because adolescence is a critical developmental stage where individuals experience rapid cognitive, social, and emotional changes that may predispose them to mental health challenges.

Sample size determination

A total of 424 adolescents participated in the study. The sample size was determined using Cochran’s formula for finite populations, with assumptions of a 95% confidence interval, 5% margin of error, and a prevalence estimate of 50% (since no prior prevalence data were available for adolescent mental health outcomes in the FCT). The initial sample size was increased by 10% to account for non-response or incomplete questionnaires, ensuring representativeness.

Sampling technique

A multistage sampling technique was employed:

• Stage one – school selection: Schools were stratified by type (private and public) and location (urban and rural). From this stratification, schools were randomly selected to ensure balanced representation.

• Stage two – class selection: Within each selected school, classes from junior and senior levels were randomly chosen.

• Stage three – student selection: Students within the eligible age range (10–19 years) were selected using simple random sampling, ensuring gender balance and representation across socio-demographic characteristics.

This sampling approach enhanced representativeness and minimized selection bias.

Inclusion criteria

• Adolescent students aged 10–19 years, in line with the WHO definition of adolescence.

• Students enrolled in public or private secondary schools (junior and senior) within the Federal Capital Territory, Abuja.

• Students who provided assent and whose parents/guardians gave informed consent.

• Adolescents present in school at the time of data collection and willing to participate voluntarily.

Exclusion criteria

• Students younger than 10 years or older than 19 years.

• Adolescents not formally enrolled in the selected schools, such as out-of-school youths.

• Students who declined to participate or whose parents/guardians did not provide consent.

• Adolescents with severe cognitive or communication impairments that could hinder their ability to complete the self-administered questionnaire.

Data collection instrument

Data were collected using a structured, self-administered questionnaire, which was divided into three sections:

• Socio-demographic characteristics – including age, gender, school type, residence, ethnicity, religion, sibling number, and parents’ education.

• Psychological outcome assessment – measured using a validated self-assessment tool for adolescent mental health, adapted from internationally recognized screening instruments such as the strengths and difficulties questionnaire (SDQ) and the general health questionnaire (GHQ-12). Items covered emotional symptoms, behavioral difficulties, self-perception, social relationships, and coping strategies. The study did not employ the full standardized SDQ scale. Rather, items were adapted from the adolescent self-report version of the SDQ, alongside GHQ-12, to suit the study context.

• Signs of mental health challenges – including concentration difficulties, withdrawal, mood swings, sleep pattern changes, and feelings of isolation.

The instrument was pre-tested on 20 adolescents in a non-study school within Abuja to ensure clarity, cultural appropriateness, and reliability. Cronbach’s alpha was used to test internal consistency, and coefficients above 0.70 confirmed reliability. Adolescents’ mental health status was classified based on a composite psychological outcome score derived from the self-assessment questionnaire adapted from the SDQ and GHQ-12 domains. Individual item responses covering emotional symptoms, behavioral difficulties, self-perception, social relationships, and coping were aggregated to generate an overall mental health score. Participants with scores above the established cut-off (indicating fewer symptoms and better functioning) were categorized as having good mental health, while those scoring at or below the cutoff were classified as having poor mental health

Data collection procedure

Data collection was carried out by trained research assistants with backgrounds in psychology and public health. The assistants administered the questionnaires in classrooms after obtaining permission from school authorities. Respondents were assured of confidentiality, anonymity, and voluntary participation. Completed questionnaires were collected immediately to minimize data loss.

Data analysis

Data were entered into SPSS version 28 for analysis, and both descriptive and inferential statistics were applied. Descriptive statistics, including frequencies, percentages, means, and standard deviations, were used to summarize socio-demographic characteristics and the prevalence of psychological outcomes. Inferential statistics involved the use of independent samples t-tests to compare mean psychological outcome scores between private and public schools, as well as urban and rural schools. Chi-square tests were employed to examine associations between categorical socio-demographic variables and mental health status, while effect sizes (Cohen’s d) were calculated to determine the magnitude of differences. Confidence intervals at 95% were applied to assess the precision of estimates, and a significance level of p < 0.05 was adopted.

Ethical considerations

Approval for this study was obtained from school Federal Capital Territory Health Research Ethic Committee with an approval number FHREC/2025/01/12/31-01-01-25. Also, approval was sought from the relevant authorities of the selected schools. Informed consent was sought from parents/guardians, while assent was obtained from adolescent participants. Confidentiality was strictly maintained by anonymizing all data, and respondents were informed that participation was voluntary with the right to withdraw at any time. Students showing severe psychological distress during the survey were referred to school counselors for appropriate support.

Comparison of adolescent psychological mental health outcome across private and public schools

Table 2 compares the mental health status of adolescents attending private and public schools. A larger proportion of adolescents with poor mental health were from public schools (58.6%) compared to private schools (41.4%). In contrast, a higher percentage of adolescents with good mental health attended private schools (59.1%) compared to public schools (40.9%). Statistically, the mean mental health score for private school students was 0.80 (SD = 0.40), which was significantly higher than the 0.66 (SD = 0.474) reported for public school students. The mean difference of 0.138 was statistically significant (t = 3.195, p = 0.002), with a 95% confidence interval ranging from 0.054 to 0.221. Additionally, the effect size (Cohen’s d = 0.435) suggests a moderate difference.

Comparison of adolescent mental health across urban and rural school areas

Table 3 presents the distribution and statistical comparison of mental health among adolescents in urban and rural school areas. A total of 230 adolescents from urban schools and 194 from rural schools participated. In terms of mental health status, 54.1% of urban students reported poor mental health compared to 45.9% of rural students, while 54.3% of urban and 45.7% of rural students reported good mental health. The mean mental health scores were nearly identical for both groups (mean = 0.74), with similar standard deviations (SD = 0.440 for urban, SD = 0.441 for rural). The slight mean difference of 0.002 was not statistically significant, as indicated by a t-value of 0.047 and a p-value of 0.963. The 95% confidence interval for the difference ranged from -0.082 to 0.086, indicating no statistically significant difference between the two groups. Cohen’s d effect size was 0.441

Common signs of mental health challenges among adolescents

Figure 1 shows the most frequently observed signs of mental health challenges among adolescents. The most reported symptom was difficulty concentrating, cited by 151 (35.6%), indicating that cognitive disruption is a key early warning sign. Following this, withdrawal from activities was reported by 90 (21.2%), and mood swings by 88 (20.8%), both of which reflect emotional and social impacts of mental health issues. Changes in sleeping patterns were also notable, identified by 80 (18.9%), highlighting the impact of mental health on physical routines. A small portion of the participants, 15 (3.5%), identified other signs, suggesting that while the core symptoms are well-recognised, some individual experiences may vary.

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Figure 1: Common signs of mental health challenges

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Prevalence of mental health outcomes among adolescents in FCT Abuja, Nigeria

Figure 2 illustrates the prevalence of mental health status among adolescents in the FCT, Abuja, Nigeria. Out of a total of 424 adolescents surveyed, 111 (26.2%) were identified as having poor mental health, while 313 (73.8%) were classified as having good mental health. Mental health outcome was determined using a composite psychological score derived from the self-assessment items. Scores were dichotomized using the sample mean as the cut-off, with scores below the mean classified as good mental health and scores at or above the mean classified as poor mental health

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Figure 2: Prevalence of mental health outcomes among adolescents in FCT Abuja, Nigeria. n (%), FCT: Federal Capital Territory

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Mental health psychological self-assessment among adolescents

Table 4 presents a detailed psychological self-assessment of adolescent students in private and public schools. Private school students reported higher frequencies of negative emotional states than public school students across all five emotional parameters. They experienced more unexplained sadness (M = 2.39 vs. 2.07, p = 0.003), nervousness/anxiety (M = 2.63 vs. 2.31, p = 0.003), emotional instability (M = 2.36 vs. 2.03, p = 0.005), feelings of being overwhelmed (M = 2.42 vs. 2.17, p = 0.025), and hopelessness (M = 2.54 vs. 2.27, p = 0.044). These differences were all statistically significant, indicating worse emotional well-being among private school adolescents. Private school students also exhibited more behavioral difficulties, including trouble focusing (M = 2.65 vs. 2.28, p = 0.002), risky behaviors (M = 2.55 vs. 2.28, p = 0.020), rule-breaking (M = 2.72 vs. 2.28, p < 0.001), impulsivity (M = 2.46 vs. 2.15, p = 0.005), and irritability/anger (M = 2.57 vs. 2.01, p < 0.001). All were statistically significant. Public school students reported higher self-confidence (M = 2.70 vs. 2.46, p = 0.041) and greater satisfaction with physical appearance (M = 2.73 vs. 2.47, p = 0.018). However, private school students reported more frequent negative self-comparisons (M = 2.45 vs. 2.16, p = 0.012), despite also reporting more frequent positive self-image (M = 2.50 vs. 2.50, p = 0.003 – although the means are equal, the p-value indicates a significant variance). Private school students experienced more bullying or social exclusion (M = 2.69 vs. 2.38, p = 0.007) and greater loneliness or isolation (M = 2.48 vs. 2.09, p = 0.001). Other social support metrics (e.g., feeling supported, discussing feelings) showed no significant difference between the two groups. Most coping-related parameters did not differ significantly between the school types. However, private school students were more likely to rely on unhealthy stress responses (M = 2.33 vs. 2.06, p = 0.011).

Table 5 presents a psychological self-assessment of adolescent students in urban and rural areas of the Federal Capital Territory, analyzing emotional health, behavior, self-esteem, social support, and coping strategies. Urban students reported more frequent feelings of being overwhelmed (M = 2.41 vs. 2.18, p = 0.036) and hopelessness about the future (M = 2.54 vs. 2.27, p = 0.041), both of which were statistically significant. Other emotional indicators, like sadness, anxiety, and difficulty managing emotions, showed no significant differences. Urban adolescents experienced greater difficulty staying focused on tasks (M = 2.64 vs. 2.30, p = 0.003), which was the only significant behavioral difference. Other behaviors, such as impulsivity, rule-following, and risky activities, showed no meaningful variation between urban and rural students. Urban students reported more frequent negative self-comparisons than rural students (M = 2.45 vs. 2.16, p = 0.020), indicating lower self-esteem in this aspect. Other self-image variables, such as self-confidence and physical appearance, did not show any significant differences. Urban adolescents reported feeling lonelier or more isolated than their rural counterparts (M = 2.43 vs. 2.14, p = 0.012). Other metrics, such as family support, emotional support, and experiences with bullying, did not differ significantly. Across all coping parameters, use of stress management, physical activity, communication, and confidence, no significant differences were observed between urban and rural students. Both groups reported similar resilience patterns.

Adolescent psychological mental health outcome across private and public schools

This study's findings show a statistically significant difference in Psychological mental health outcomes by school type, with public school students exhibiting a higher proportion of poor mental health outcomes (58.6%) compared to private school students (41.4%), despite the latter reporting more frequent emotional symptoms. This disparity is may be attributed to higher academic pressure, fewer resources, and less individualized support in public schools, which can negatively impact students’ well-being, life satisfaction, and self-esteem.^[17,18] High school students, particularly in public settings, tend to underperform in measures of general well-being and self-evaluation compared to those in technical or private schools, likely due to the greater expectations and stress they face.^[18] Additionally, factors such as poverty, family disputes, and lack of awareness about mental health further contribute to the higher prevalence of mental health problems among public school students.^[17,19] The limited availability of mental health services and professionals in public schools, especially in rural areas, exacerbates these Psychological challenges.^[20] Addressing these disparities requires targeted interventions, increased funding, and comprehensive mental health support systems within public schools to promote student Psychological well-being and academic success.^[20,21] Conversely, no significant difference was observed in overall Psychological mental health outcome between urban and rural adolescents, with both groups showing nearly identical distributions of poor and good mental health. This suggests that geographical location may not be as influential a factor in determining overall mental health outcomes among adolescents in the FCT.

Prevalence of mental health outcomes and recognition of mental health symptoms

The overall prevalence of poor mental health among adolescents in the FCT stands at 26.2%. This figure aligns closely with the WHO's global estimates, which suggest that approximately one in seven adolescents worldwide experience mental health conditions.^[22] The relatively high proportion of adolescents with good mental health (73.8%) may reflect growing awareness, resilience, or coping capacities,^[23] but the concerning 26.2% rate of poor mental health suggests the need for targeted school-based interventions and mental health integration into routine educational policies.

This study also showed some common signs of mental health challenges among adolescents. Adolescents commonly recognized difficulty concentrating (35.6%), withdrawal from activities (21.2%), and mood swings (20.8%) as signs of mental health challenges. These are consistent with typical early symptoms of anxiety, depression, and stress-related disorders. Recognition of these signs is crucial for early intervention. This pattern also aligns with broader research, which shows that while adolescents often identify some key symptoms of mental health issues, such as changes in mood, social withdrawal, and problems with focus, they may still underrecognize other important signs, like persistent sadness or anxiety.^[24,25] Studies indicate that recognition is generally higher for more visible or disruptive symptoms, such as those associated with depression, but less so for conditions like social anxiety or internalizing disorders.^[24,25] Mental health literacy programs, such as Mental Health First Aid, have been shown to improve adolescents’ ability to recognize a wider range of symptoms and increase their confidence in seeking help for themselves or peers.^[26] However, less recognition was given to changes in sleeping patterns (18.9%) and other physical or behavioral changes, which may indicate that some symptoms remain under-identified. The pattern observed is in line with a study by Li et al. (2025), which noted that cognitive and emotional symptoms are more likely to be recognized by adolescents than somatic or behavioral signs.^[27]

Differences in psychological well-being by school type and area

The results reveal that adolescents in private schools reported significantly higher levels of emotional distress across multiple domains. Private school students experienced more frequent episodes of unexplained sadness (mean = 2.39), nervousness or anxiety (2.63), difficulty controlling emotions (2.36), feelings of being overwhelmed (2.42), and hopelessness (2.54) compared to their public-school counterparts. All differences were statistically significant (p < 0.05). Similarly, in the behavioral dimension, private school students reported greater difficulty staying focused, higher engagement in risky behaviors, greater impulsivity, and extreme irritability or anger. These findings suggest that despite their often-perceived privilege, adolescents in private schools may face intense psychological strain. A plausible explanation for this pattern is the heightened academic and social pressures common in private institutions. Many private school students are enrolled in highly competitive environments with elevated parental expectations and limited downtime. These conditions can contribute to chronic stress, emotional dysregulation, and behavioral challenges. Studies by Li et al. (2024 and Schnyder et al. (2025) Similarly, elevated stress levels and anxiety among students in elite private schools were identified due to performance demands and societal pressure.^[27,28]

In terms of self-esteem and self-perception, private school students reported more frequent negative self-comparisons and lower satisfaction with physical appearance, although they displayed slightly higher scores on positive self-image. This paradox may reflect a growing exposure to social media and image-based comparisons in private school populations, aligning with findings from who noted increased body dissatisfaction and lower self-esteem in students attending affluent schools due to social comparison dynamics.

Notably, private school students also reported a higher prevalence of bullying or social exclusion and a greater frequency of loneliness or isolation. This could be related to fragmented peer relationships or competitive academic culture, which may inhibit social bonding. Although private school environments are often assumed to offer better emotional support, the data suggest that the emotional strain may be masked by external appearances and socio-economic privilege.

When comparing urban and rural areas, there were fewer significant differences. Urban adolescents experienced higher levels of being overwhelmed and hopeless (p = 0.036 and 0.041, respectively), along with more difficulty staying focused (p = 0.003) and increased feelings of loneliness (p = 0.012). While these effects were statistically significant, the overall differences across most psychological indicators between urban and rural students were marginal. These results could reflect the stressors associated with urban living, such as social isolation, academic competition, and exposure to digital and peer pressures.^[29] Adolescents in urban settings may also have greater awareness of their challenges, leading to more accurate self-reporting. This is supported by previous studies, which identified urban residency as a risk factor for certain mental health problems due to exposure to psychosocial stressors and fragmented family structures.^[30–32]

Interestingly, while rural students reported slightly better emotional scores in some areas, they did not significantly differ in their self-esteem, coping strategies, or access to support. This suggests that mental health vulnerabilities are widespread and not confined to geographical settings alone, although their triggers may differ.

Limitations and mitigation strategies

One limitation of this study is its reliance on self-reported questionnaires, which may introduce social desirability bias or underreporting of sensitive psychological symptoms. To mitigate this, participants were assured of anonymity and confidentiality, and questionnaires were self-administered without teacher interference to encourage honest responses.

Another limitation is the cross-sectional design, which restricts the ability to establish causal relationships between socio-demographic factors and psychological outcomes. This was mitigated by using comparative statistical analyses (t-tests, chi-square tests, and effect size calculations) to strengthen the interpretation of associations between variables.

The study also faced the possibility of sample bias, as only students present during the survey were included, potentially excluding adolescents absent due to severe mental health challenges. To address this, a multistage sampling approach was used to ensure broad representativeness across school types, locations, and socio-demographic groups.

Finally, the study was limited to students in formal schools, thereby excluding out-of-school adolescents who may have different mental health experiences. This limitation was acknowledged, and findings were interpreted strictly within the school-going adolescent population. Future studies can adopt a mixed-methods design or extend coverage to out-of-school youths for a more comprehensive understanding.