This was a descriptive and analytical cross-sectional study conducted from January 22 to March 6, 2026, among students of the paramedical schools of Dapaong, in northern Togo. The manuscript was prepared in accordance with the STROBE guidelines for cross-sectional studies [13].

The source population comprised all 192 students enrolled in the two participating paramedical schools of Dapaong during the study period: the “École Nationale des Auxiliaires Médicaux de Dapaong” (ENAM-Dapaong; 105 nursing students) and the “École Nationale des Sages-Femmes de Dapaong” (ENSF-Dapaong; 87 midwifery students).

Census sampling was used: all students in the source population were invited to participate. The project was presented and explained to students during classroom visits, and a link to the electronic questionnaire was then made available to them. In total, 118 questionnaires were collected. One questionnaire was excluded for absence of consent, yielding 117 analyzed participants. The completion rate was 118/192 (61.5%), and the analyzed proportion was 117/192 (60.9%). Of the 117 analyzed participants, 74 (63.2%) were enrolled at ENAM-Dapaong and 43 (36.8%) at ENSF-Dapaong, corresponding to participation of 74/105 (70.5%) among nursing students and 43/87 (49.4%) among midwifery students.

Data were collected using a self-administered electronic questionnaire developed on KoboToolbox. Information about the study and an informed-consent form were presented before access to the questions, with access conditional on prior consent. The questionnaire captured sociodemographic and academic characteristics, lifestyle habits, selected medical history, headache characteristics, triggers, self-medication, psychological symptoms, and headache impact.

Included were students enrolled in the participating schools during the study period who agreed to participate after being informed. Students in the source population who did not take part in data collection were not included. Any questionnaire without informed consent was excluded.

Sociodemographic and academic characteristics:age; sex; program; year of study; years since baccalaureate; distance of residence; academic status; on-call duty during placement.

Lifestyle and environmental factors:daily sleep duration; sleep regularity; daily screen time; nighttime screen exposure; coffee consumption; energy-drink consumption; frequency of fasting.

Medical history and clinical characteristics:family history of migraine; chronic illness; head trauma; corrective lenses.

Headache characteristics:attack frequency; pain intensity; attack duration; topography; pain quality; triggers; self-medication; medications used. Participants were instructed to report the characteristics of their usual headache attacks, reflecting the most frequent pattern of their headaches rather than a single isolated episode. Attack duration was recorded as a categorical item (<4 h; 4 to 72 h; >72 h; highly variable or undetermined) and was used descriptively only; it did not enter the classification algorithm.

Psychological dimensions and impact:perceived stress, assessed with the PSS-10 [14]; anxiety symptoms, assessed with the GAD-2 [15]; depressive symptoms, assessed with the PHQ-2 [16]; headache impact, assessed with the HIT-6 [10]; migraine-related disability, assessed with the MIDAS [12], an instrument with established reliability [17].

Headache was defined as the report of at least one headache episode during the six months preceding the survey. Headache types were not assigned by clinical examination but were derived algorithmically from self-reported attack features, using operational criteria based on the ICHD-3 [18]. Algorithmic assignment of headache type from a structured diagnostic question set, rather than clinician interview, is the established method for headache classification in large-sample and population-based surveys, in which individual clinical assessment is not feasible [19]. Throughout this article, the terms “migraine” and “tension-type headache” denote these questionnaire-based, algorithm-derived categories, not clinician-confirmed ICHD-3 diagnoses. Types were assigned in a fixed precedence order, migraine being evaluated before tension-type headache.

Migraine. Classification required at least two of the following four features: unilateral location, pulsating quality, intensity ≥ 4/10, and aggravation by physical activity; together with either nausea or vomiting, or the combination of photophobia and phonophobia. Attacks meeting these criteria were classified as migraine irrespective of reported duration.

Tension-type headache. In participants not meeting the migraine criteria: bilateral location, pressing or tightening quality, intensity ≤ 6/10, no aggravation by physical activity, absence of nausea, and no more than one of photophobia or phonophobia.

Other or undifferentiated headache. Headache meeting neither operational set. A residual, undifferentiated category is an expected and recognized feature of questionnaire-based headache classification [19].

Categorical variables were described as counts and percentages. Continuous variables were presented as mean ± standard deviation, median [Q1 - Q3], and range; the median was preferred for skewed distributions. Normality was assessed with the Shapiro-Wilk test [20], supplemented by inspection of skewness and kurtosis.

Prevalences were reported with exact binomial 95% confidence intervals using the Clopper-Pearson method [21]. Bivariate comparisons used Pearson’s χ² test or Fisher’s exact test for categorical variables, and Student’s t test or the Mann-Whitney U test for continuous variables, depending on distribution.

Factors associated with the presence of headache (among the 117 participants) and then with substantial impact (among the 82 participants with headache, HIT-6 ≥ 56) were examined by logistic regression. Variables associated at p < 0.20 in bivariate analysis were candidates for the multivariate model. The number of variables was limited according to the rule of at least ten events per variable [22]. Final selection relied on backward elimination guided by the Akaike information criterion (AIC) and the likelihood-ratio test; results were expressed as adjusted odds ratios (aOR) with 95% CIs. Collinearity was assessed with the variance inflation factor (VIF), calibration with the Hosmer-Lemeshow test [23], and discrimination with the area under the ROC curve (AUC). Among participants with migraine, disability (MIDAS) was described only descriptively given the small sample size. The significance threshold was set at p < 0.05 (two-sided).

The study protocol was not reviewed by a formal research ethics committee, as no such committee was available to the investigators for this survey; the study was nonetheless conducted in accordance with the principles of the Declaration of Helsinki. Administrative authorization to conduct the survey was obtained from the directors of the two participating schools. Participation was voluntary; all students received information about the study and provided electronic informed consent before accessing the questionnaire.

Of the 192 students invited, 118 questionnaires were collected and 117 analyzed after exclusion of one questionnaire for absence of consent (Figure 1). The analyzed population comprised 68/117 (58.1%) men, for a male-to-female sex ratio of 1.4. Nursing students accounted for 74 (63.2%) participants. The median age was 21 years [20 - 22]. Details are provided in Table 1.

Figure 1. Study flow chart.

The median PSS-10 score was 18 [15 - 21]. A positive screen was found in 34/117 (29.1%) participants for anxiety (GAD-2 ≥ 3) and 38/117 (32.5%) for depressive symptoms (PHQ-2 ≥ 3) (Table 1).

The prevalence of headache during the previous six months was 82/117 (70.1%; 95% CI 60.9 - 78.2). Tension-type headache was the most frequent category, affecting 32/82 (39.0%; 95% CI 28.4 to 50.4) of participants with headache (Table 2). Migraine affected 19/82 (23.2%; 95% CI 14.6 to 33.8) of participants with headache, corresponding to 16.2% (95% CI 10.1 to 24.2) of the overall sample.

Table 1. Characteristics of the study population (n = 117).

Continuous variables: mean ± SD; median (IQR: Q1 - Q3); range. Categorical variables: n (%).

Among the 82 participants with headache, the median frequency was 5 attacks per month [3 - 8], the median intensity 5 [4 - 7], and the median HIT-6 score 55 [48 - 60]. Other characteristics are presented in Table 2.

Table 2. Clinical characteristics of headache in participants with headache (n = 82).

Continuous variables: mean ± SD; median (IQR: Q1-Q3); range (MIDAS: median (IQR: Q1-Q3); range). Categorical variables: n (%). MIDAS rows refer to the migraine subgroup (n = 19). Headache-type prevalences are shown with exact (Clopper-Pearson) 95% CIs. Substantial or severe impact (HIT-6 ≥ 56): 40/82 (48.8%; 95% CI 37.6 to 60.1).

Substantial or severe impact (HIT-6 ≥ 56) affected 40/82 (48.8%; 95% CI 37.6 to 60.1) of participants with headache (Table 2). Self-medication was reported by 44/82 (53.7%) participants (Table 3). The most frequently reported triggers were lack of sleep (64/82; 78.0%) and study-related stress (46/82; 56.1%) (Table 3).

Table 3. Self-medication and reported triggers in participants with headache (n = 82).

Multiple-response items: percentages are based on the relevant denominator (medications, n = 44; triggers, n = 82) and do not sum to 100%.

Among the 19 participants with migraine, the median MIDAS score was 17 [10 - 58], with values ranging from 0 to 80. Severe disability was observed in 8/19 (42.1%; 95% CI 20.3 to 66.5) (Table 2).

3.7.1. Bivariate Analysis

In bivariate analysis, variables associated with the presence of headache at the p < 0.20 threshold were years since baccalaureate (p = 0.040), sleep duration (p = 0.130), screen time (p = 0.081), GAD-2 (p = 0.001), PHQ-2 (p = 0.036), and family history of migraine (p = 0.081) (Table 4).

Table 4. Bivariate analysis of factors associated with the presence of headache (n = 117).

Continuous variables: median (IQR: Q1 - Q3). Categorical variables: n (row %). Candidates for the multivariate model: p < 0.20.

3.7.2. Multivariate Analysis

After adjustment, only the GAD-2 score was independently associated with the presence of headache (aOR 1.66; 95% CI 1.20 - 2.30; p = 0.002). Years since baccalaureate and sleep duration did not retain a statistically significant association. The model showed satisfactory calibration (Hosmer-Lemeshow p = 0.93), an AUC of 0.73, and a VIF close to 1.0 (Table 5).

Table 5. Factors associated with the presence of headache: multivariate model (n = 117).

Hosmer-Lemeshow p = 0.93; AUC = 0.73; VIF ≈ 1.0.

3.8.1. Bivariate Analysis

Among the 82 participants with headache, 42/82 (51.2%) had a HIT-6 < 56 and 40/82 (48.8%) a HIT-6 ≥ 56. Pain intensity (p < 0.001) and perceived stress (p = 0.002) were associated with impact; attack frequency (p = 0.052), GAD-2 (p = 0.053), PHQ-2 (p = 0.141), on-call duty (p = 0.191), and headache type (p = 0.139) also met the preselection threshold (Table 6).

Table 6. Bivariate analysis of factors associated with substantial impact (HIT-6 ≥ 56; n = 82).

Continuous variables: median (IQR: Q1 - Q3). Categorical variables: n (row %). Candidates for the multivariate model: p < 0.20.

3.8.2. Multivariate Analysis

In the final model, two factors were independently associated with substantial impact: pain intensity (aOR 1.53; 95% CI 1.21 - 2.02; p < 0.001) and perceived stress (aOR 1.19; 95% CI 1.06 - 1.37; p = 0.006). The model showed satisfactory calibration (Hosmer-Lemeshow p = 0.43), an AUC of 0.79, and a VIF close to 1.1 (Table 7).

Table 7. Factors associated with substantial impact: multivariate model (n = 82).

Hosmer-Lemeshow p = 0.43; AUC = 0.79; VIF ≈ 1.1.

Of the 192 students invited, 118 completed the questionnaire (completion rate 61.5%) and 117 were analyzed (60.9%). The population was predominantly male (58.1%) and enrolled in nursing (63.2%), with a median age of 21 years. The median sleep duration was 5 hours per night and the median daily screen time 3 hours. These characteristics describe a young population in paramedical training, exposed to academic demands and to a relatively short sleep duration.

A positive screen for anxiety symptoms was found in 29.1% of participants and for depressive symptoms in 32.5%. These findings are consistent with data reported among health-science students, in whom anxiety, depressive symptoms, and sleep disturbances are common [7,8], and underscore the importance of considering psychological dimensions in the study of headache.

The prevalence of headache during the previous six months was 70.1%, close to the estimate of 70.4% reported among medical students [6]. It should be noted that differences in prevalence periods, diagnostic criteria, and recruitment methods may bias this comparison. Migraine affected 23.2% of participants with headache; relative to the whole sample, its prevalence was 16.2% (19/117). The questionnaire-based migraine estimate (16.2% of the sample) is of the same order as figures reported among university students, 16.1% [4] and 19% [5], and the 14.9% reported in African student cohorts [9]. These estimates are not directly comparable, however, because they rest on differing case definitions, ascertainment methods, and prevalence periods; the present figure should be read as an approximation derived from a self-administered algorithm rather than as an ICHD-3-equivalent prevalence.

Among participants with headache, the median frequency was five attacks per month and the median intensity 5/10, with pain most often pulsating and a predominantly frontal topography. These features indicate potentially recurrent headaches liable to limit academic and daily activities. Because classification relied on a self-administered questionnaire rather than a neurological examination, generalization and firm conclusions may be limited.

Substantial or severe impact (HIT-6 ≥ 56) affected 48.8% of participants with headache, despite a moderate median frequency (5 attacks per month). The functional burden of headache is therefore not captured by frequency alone, which the HIT-6 is specifically designed to quantify [10]. Self-medication was reported by 53.7% of participants with headache, with paracetamol largely predominant; this frequent use, in a population expected to enter the health professions, underscores the value of education on the rational use of analgesics. Lack of sleep and study-related stress were the triggers most frequently reported by participants. This predominance is consistent with the high level of exposure to stress and sleep disturbance documented among health-science students [7][8], although these merely self-reported factors cannot be regarded as established risk factors.

Among the 19 participants with migraine, the median MIDAS score was 17 and severe disability affected 42.1%, indicating potentially substantial disability in a considerable proportion of those affected. The small subgroup size warrants a descriptive interpretation, a specific multivariate analysis not being feasible.

After adjustment, only the GAD-2 remained independently associated with the presence of headache, each additional point increasing the odds (aOR 1.66; 95% CI 1.20 - 2.30). This association is consistent with the high frequency of anxiety symptoms among health-science students [7] and with the recognized role of psychological factors in headache [24]. Several mechanisms may be involved: stress-related physiological arousal, sleep disruption, hypervigilance to painful symptoms, and bidirectional interactions between anxiety and pain. However, the cross-sectional design does not allow the temporality of this association to be determined.

In the final model, pain intensity (aOR 1.53) and perceived stress (aOR 1.19) remained independently associated with impact. The association between pain intensity and impact is consistent with the very design of the HIT-6, an instrument developed to capture the functional impact of headache pain [10]. The association with perceived stress complements the finding for anxiety: anxiety was associated with the presence of headache, whereas perceived stress was associated with its impact. This twofold observation aligns with the recognized role of psychological factors, which may operate at different levels of the headache phenomenon—occurrence, frequency, and disability [24]. These associations, measured concurrently, do not, however, allow any direction of causality to be established.