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Although family physicians frequently encounter dermatological conditions, the effect of dermatology rotations on their diagnostic competency remains underexplored. We aimed to determine the effect of a mandatory 1-month dermatology rotation on the diagnostic accuracy of family medicine (FM) residents for skin lesions.
Methods
We conducted a cross-sectional study among FM residents from September 1 to December 1, 2023. We assessed participants’ ability to identify 54 dermatological lesions using a structured, face-to-face questionnaire. A multivariable linear regression model was used to identify independent predictors of diagnostic knowledge scores.
Results
A total of 260 residents participated; 121 (46.5%) had completed the dermatology rotation, whereas 139 (53.5%) had not. Mean diagnostic knowledge scores were significantly higher among residents who completed the rotation (79.17±8.69 vs. 73.06±8.94; P<0.001). In the multivariable model, completing the dermatology rotation was the only independent predictor of higher diagnostic scores (P<0.001).
Conclusion
Completing a dermatology rotation improves the diagnostic accuracy of FM residents for skin lesions, underscoring the value of structured dermatological training within FM curricula.
Dermatological diseases constitute a substantial global burden, accounting for 12% to 14% of primary care consultations and ranking as the fourth leading cause of non-fatal disability [1-6]. Family physicians (FPs) must manage a wide range of dermatological presentations; however, diagnostic accuracy in primary care remains suboptimal, with reported rates ranging from 48% to 77% [7-9]. The rising prevalence of skin cancers makes timely and accurate diagnosis essential, underscoring the need to strengthen dermatological competency within primary care [3].
The literature consistently emphasizes the need for improved dermatology training for FPs [5,7-10]. Limited training and clinical exposure impair the accurate diagnosis of skin lesions—a challenge documented in numerous international studies [11-13]. This deficiency often reduces physicians’ confidence during skin examinations and increases referrals to dermatology clinics [12]. Collectively, these findings reveal a persistent educational gap that undermines diagnostic confidence and influences clinical decision-making, including referral patterns.
Despite the high prevalence of skin conditions in family medicine (FM) practice, training in dermatology is often limited. Didactic or blended educational approaches have been assessed, but structured clinical dermatology rotations have been insufficiently evaluated [11,14,15]. This gap highlights the importance of determining whether supervised clinical exposure during residency enhances diagnostic competency.
The mandatory 1-month dermatology rotation for FM residents in Türkiye offers an ideal setting to evaluate the educational effect of this intervention. This study therefore aimed to determine whether FM residents who completed this rotation demonstrate diagnostic accuracy superior to that of their peers.
Methods
We conducted this cross-sectional study at two university hospitals and three training and research hospitals from September 1 to December 1, 2023. All FM residents at these institutions were eligible for inclusion. The sample comprised all FM residents available and willing to participate during the study period. Of the 600 eligible residents, 260 consented to participate and were included in the final sample. Data were collected via a questionnaire administered face-to-face. As the dermatology rotation is a mandatory component of the national FM curriculum, group assignment was determined by residents’ schedules rather than by their preference. Participants were categorized into two groups based on dermatology rotation status: Group 1 comprised residents who had completed the rotation, and Group 2 comprised those who had not.
A structured questionnaire consisting of 59 items across two sections was administered. The first section collected demographic data, including age, sex, year of residency, professional experience, rotation status, and time elapsed since rotation (Table 1). The second section comprised 54 dermatological lesion images. Each image was accompanied by a four-option multiple-choice question. Although the questionnaire had not undergone prior formal psychometric validation, a board-certified dermatologist reviewed and approved all items and images for content validity.
The 54 lesion images were categorized into nine groups. The specific lesions in each category were as follows: (1) Benign dermatoses (n=15): acne vulgaris, acne rosacea, seborrheic dermatitis, diaper dermatitis, intertrigo, psoriasis (plaque type), nail psoriasis, lichen planus, pityriasis rosea, vitiligo, alopecia areata, oral aphthae, Behçet disease, pemphigus vulgaris, and bullous pemphigoid. (2) Allergic conditions (n=4): atopic dermatitis, urticaria, angioedema, and fixed drug eruption. (3) Benign, precancerous, and malignant skin tumors (n=5): seborrheic keratosis, actinic keratosis, basal cell carcinoma, squamous cell carcinoma, and melanoma. (4) Bacterial infections (n=9): impetigo, folliculitis, furuncle, carbuncle, lymphangitis, erysipelas, cellulitis, bacterial paronychia, and erythrasma. (5) Fungal infections (n=8): tinea capitis superficialis, tinea capitis profunda, tinea corporis, tinea inguinalis, tinea pedis (intertriginous), tinea pedis (vesiculobullous), onychomycosis, and tinea versicolor. (6) Viral infections (n=5): verruca vulgaris, verruca plana, herpes simplex, herpes zoster, and molluscum contagiosum. (7) Spirochetal diseases (n=2): syphilitic alopecia and syphilitic chancre. (8) Ectoparasitic diseases and insect bites (n=3): scabies tunnel, pediculosis capitis, and insect bite. (9) Diagnostic test interpretations (n=3): morphology of fungal elements under a microscope, erythrasma (image with Wood lamp), and the pathergy test.
All statistical analyses were performed using the SPSS ver. 11.5 (SPSS Inc.). Descriptive analyses included means, medians, and percentages. We compared groups using chi-square tests or Fisher exact tests for categorical variables and the Mann-Whitney U test for continuous variables. Univariate and multivariable linear regression analyses were conducted to identify predictors of diagnostic knowledge scores. Statistical significance was set at P<0.05.
We performed a multivariable linear regression analysis using the enter method. All covariates meeting the inclusion threshold in the univariate analysis (P<0.10)—including age, gender, and dermatology rotation status—were included in the final model to identify independent predictors of diagnostic knowledge scores.
The study was approved by Ankara Bilkent City Hospital Clinical Researches Ethics Committee (no., E1/3853/2023), and written informed consent was obtained from all participants.
Results
Of the 260 participating residents, 143 (55.0%) were women, and 121 (46.5%) had completed the mandatory dermatology rotation (Table 1). Among residents who had completed the rotation, most (75.2%) had done so within the preceding year.
Among all participants (n=260), the highest diagnostic accuracy was achieved for vitiligo (100%). Conversely, diagnostic accuracy was lowest for syphilitic alopecia, nail psoriasis, pemphigus vulgaris, seborrheic keratosis, squamous cell carcinoma, and basal cell carcinoma (Table 2).
Residents who completed the rotation demonstrated significantly higher diagnostic accuracy for fungal, bacterial, and viral infections, as well as for benign dermatoses, ectoparasites, insect bites, and diagnostic test interpretation (Table 3).
Univariate linear regression analysis identified both gender (P=0.040) and dermatology rotation status (P<0.001) as significant predictors of overall diagnostic scores (Table 4). In the multivariable model, however, only dermatology rotation status remained an independent predictor of diagnostic scores (β=5.863, P<0.001) (Table 5).
Discussion
This study demonstrates that completing a mandatory dermatology rotation improves diagnostic accuracy among FM residents. These findings align with prior research supporting structured clinical exposure as an effective strategy to enhance dermatological competency [14-16]. Given the substantially expanding spectrum of dermatological presentations in primary care [17], strengthening residents’ diagnostic proficiency is essential for ensuring timely and appropriate management. Previous studies consistently indicate that FPs encounter diagnostic challenges owing to the heterogeneity of dermatological diseases [5,7-13] and that non-dermatologists generally achieve lower diagnostic accuracy than dermatologists [5,12,14]. Consistent with this evidence, our results confirm that structured dermatology exposure significantly improves diagnostic competency among FM residents. The higher overall diagnostic scores observed in this study compared with previous reports [13,14,18,19] may reflect differences in participant characteristics, the broader selection of lesions in our assessment tool, and the design of our questionnaire.
The rotation improved recognition of common and clinically relevant dermatological conditions, particularly in the benign, infectious, and fungal categories. This finding contrasts with previous studies showing that FPs often struggle to recognize frequently encountered dermatological diseases [13,20,21]. However, diagnostic accuracy remained low for less common or visually subtle lesions such as pemphigus vulgaris, squamous cell carcinoma, and basal cell carcinoma—an expected finding consistent with specialist literature [20,22-25]. Such discrepancies may reflect well-recognized disparities in clinical exposure between primary and specialist care settings. FPs typically encounter benign, infectious, and inflammatory lesions far more frequently than malignant or atypical ones, a pattern that likely shapes their diagnostic focus [20,26]. Consequently, variations in clinical exposure likely account for some of the observed variability across studies, underscoring the importance of structured dermatology education tailored to the primary care context.
The lack of an association with demographic characteristics suggests that structured dermatology training itself, rather than years of experience, is the primary driver of improved diagnostic accuracy. Previous research indicates that short-term or isolated educational interventions may not ensure long-term retention of dermatological knowledge [27,28]. In contrast, educational models combining clinical rotations with structured theoretical learning generate more sustained and meaningful improvements in diagnostic accuracy [11]. Therefore, incorporating longitudinal strategies—such as case-based learning, reinforcement sessions, simulation-based practice, and exposure to diverse presentations—may sustain and strengthen residents’ diagnostic skills. Such strategies may also reduce unnecessary referrals, improve patient outcomes, and enhance the role of FPs as frontline providers in dermatology.
Although existing studies have examined dermatology education in primary care, evidence directly comparing diagnostic performance based on rotation status remains limited. Restricting the study to five institutions may limit the generalizability of our findings. Additionally, the image-based assessment lacked clinical context (e.g., patient history), which typically aids diagnostic decision-making. The multiple-choice format may have favored pattern recognition over comprehensive clinical reasoning, whereas convenience sampling introduces the risk of selection bias. Despite these limitations, these findings offer significant implications for residency training curricula. Specifically, they support the integration of longitudinal dermatology education, targeted modules on tumors and rare conditions, dermoscopy-supported case simulations, and periodic refresher sessions to promote retention and strengthen diagnostic competency. Implementing such strategies may reduce unnecessary referrals and solidify the role of FPs as frontline providers in dermatological care.
In conclusion, completing a mandatory dermatology rotation significantly improves the diagnostic accuracy of FM residents. While these findings underscore the educational value of the rotation, future longitudinal studies are needed to determine whether these improvements translate into real-world clinical proficiency and better patient outcomes.
Notes
Conflict of interest
No potential conflict of interest relevant to this article was reported.
Acknowledgments
The authors would like to thank our gratitude to all the participants for their cooperation and support.
Funding
None.
Data availability
The data supporting the findings of this article are available upon request from the corresponding author.
Author contribution
Conceptualization: SD, ÜG, CA. Methodology: SD, ÜG, CA. Validation: SD, ÜG, CA. Visualization: SD, ÜG, CA. Formal analysis: SD, ÜG, CA. Investigation: SD, ÜG, CA. Resources: SD, ÜG, CA. Data curation: SD, ÜG, CA. Project administration: SD, ÜG, CA. Supervision: SD, ÜG, CA. Writing–original draft: SD. Writing–review & editing: SD, ÜG, CA. Final approval of the manuscript: all authors
Table 1.
Demographic characteristics of participants by rotation status
Characteristic
Value
Sex
Female
143 (55.0)
Male
117 (45.0)
Age (y)
Mean±SD
33.69±7.94
Median (range)
31.00 (25.00–57.00)
≤30
129 (49.6)
>30
131 (50.4)
Year of family medicine residency
1st year
111 (42.7)
2nd year
75 (28.8)
3rd year
74 (28.5)
Years of professional experience (y)
≤5
136 (52.3)
>5
124 (47.7)
Values are presented as number (%), mean±SD, or median (range).
SD, standard deviation.
Table 2.
Comparative analysis of the distribution of correct answers in the questionnaire overall and by subgroup
Values are presented as number (%). Group 1: physicians who had completed dermatology rotation; Group 2: physicians who had not completed dermatology rotation.
*P<0.05 (statistical significance).
a)By Fisher exact test.
b)By chi-square test.
Table 3.
Comparison of skin disorders groups and knowledge levels by dermatology rotation status
Group 1: physicians who had completed dermatology rotation; Group 2: physicians who had not completed dermatology rotation.
CI, confidence interval; SE, standard error; Ref, reference.
*P<0.05 (statistical significance).
Table 5.
Multivariable linear regression analysis of independent predictors of overall diagnostic scores
Variable
β (95% CI)
SE
P-value
R2
Constant
75.933 (71.239 to 80.627)
2.384
<0.001*
0.107
Age (y)
≤30
Ref
>30
–0.241 (–2.492 to 2.009)
1.143
0.833
Sex
Female
Ref
Male
–1.651 (–3.866 to 0.565)
1.125
0.143
Dermatology rotation status
Group 2
Ref
Group 1
5.863 (3.639 to 8.087)
1.129
<0.001*
Group 1: physicians who had completed dermatology rotation; Group 2: physicians who had not completed dermatology rotation.
CI, confidence interval; SE, standard error; Ref, reference.
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Effect of dermatology rotation on the diagnostic accuracy of family medicine residents for skin lesions: a cross-sectional study in Türkiye
Graphical abstract
Graphical abstract
Effect of dermatology rotation on the diagnostic accuracy of family medicine residents for skin lesions: a cross-sectional study in Türkiye
Characteristic
Value
Sex
Female
143 (55.0)
Male
117 (45.0)
Age (y)
Mean±SD
33.69±7.94
Median (range)
31.00 (25.00–57.00)
≤30
129 (49.6)
>30
131 (50.4)
Year of family medicine residency
1st year
111 (42.7)
2nd year
75 (28.8)
3rd year
74 (28.5)
Years of professional experience (y)
≤5
136 (52.3)
>5
124 (47.7)
Lesion
Correct answer rate
Group 1 (n=121)
Group 2 (n=139)
P-value
Vitiligo
260 (100.0)
121 (100.0)
139 (100.0)
-
Syphilitic chancre
257 (98.8)
121 (100.0)
136 (97.8)
0.251a)
Tinea pedis (intertriginous)
256 (98.5)
119 (98.3)
137 (98.6)
>0.999a)
Oral aphthae
256 (98.5)
119 (98.3)
137 (98.6)
>0.999a)
Angioedema
256 (98.5)
120 (99.2)
136 (97.8)
0.626a)
Lymphangitis
256 (98.5)
119 (98.3)
137 (98.6)
>0.999a)
Bacterial paronychia
256 (98.5)
120 (99.2)
136 (97.8)
0.626a)
Herpes zoster
253 (97.3)
118 (97.5)
135 (97.1)
>0.999a)
Herpes simplex
252 (96.9)
117 (96.7)
135 (97.1)
>0.999a)
Insect bite
251 (96.5)
120 (99.2)
131 (94.2)
0.040a),*
Tinea inguinalis
249 (95.8)
119 (98.3)
130 (93.5)
0.054b)
Psoriasis (plaque type)
248 (95.4)
116 (95.9)
132 (95.0)
0.729b)
Diaper dermatitis
247 (95.0)
118 (97.5)
129 (92.8)
0.082b)
Scabies tunnel
242 (93.1)
116 (95.9)
126 (90.6)
0.098b)
Tinea versicolor
241 (92.7)
116 (95.9)
125 (89.9)
0.066b)
Onychomycosis
241 (92.7)
114 (94.2)
127 (91.4)
0.379b)
Molluscum contagiosum
236 (90.8)
115 (95.0)
121 (87.1)
0.026b),*
Urticaria
235 (90.4)
112 (92.6)
123 (88.5)
0.267b)
Impetigo
232 (89.2)
114 (94.2)
118 (84.9)
0.016b),*
Behçet disease
230 (88.5)
114 (94.2)
116 (83.5)
0.007b),*
Carbuncle
227 (87.3)
106 (87.6)
121 (87.1)
0.894b)
Seborrheic dermatitis
225 (86.5)
105 (86.8)
120 (86.3)
0.916b)
Alopecia areata
222 (85.4)
101 (83.5)
121 (87.1)
0.415b)
Acne vulgaris
217 (83.5)
109 (90.1)
108 (77.7)
0.007b),*
Fixed drug eruption
217 (83.5)
106 (87.6)
111 (79.9)
0.094b)
Pathergy test
214 (82.3)
107 (88.4)
107 (77.0)
0.016b),*
Pediculosis capitis
211 (81.2)
103 (85.1)
108 (77.7)
0.127b)
Intertrigo
204 (78.5)
103 (85.1)
101 (72.7)
0.015b),*
Atopic dermatitis
201 (77.3)
96 (79.3)
105 (75.5)
0.466b)
Tinea capitis profunda
198 (76.2)
93 (76.9)
105 (75.5)
0.803b)
Fungal elements
196 (75.4)
95 (78.5)
101 (72.7)
0.275b)
Cellulitis
194 (74.6)
94 (77.7)
100 (71.9)
0.288b)
Melanoma
183 (70.4)
89 (73.6)
94 (67.6)
0.296b)
Bullous pemphigoid
183 (70.4)
85 (70.2)
98 (70.5)
0.964b)
Folliculitis
181 (69.6)
94 (77.7)
87 (62.6)
0.008b),*
Lichen planus
172 (66.2)
83 (68.6)
89 (64.0)
0.438b)
Erythrasma
170 (65.4)
85 (70.2)
85 (61.2)
0.124b)
Verruca plana
170 (65.4)
87 (71.9)
83 (59.7)
0.039b),*
Tinea capitis superficialis
169 (65.0)
86 (71.1)
83 (59.7)
0.055b)
Furuncle
163 (62.7)
88 (72.7)
75 (54.0)
0.002b),*
Acne rosacea
163 (62.7)
85 (70.2)
78 (56.1)
0.019b),*
Erythrasma (Wood’s lamp)
162 (62.3)
85 (70.2)
77 (55.4)
0.014b),*
Tinea pedis (vesiculobullous)
162 (62.3)
76 (62.8)
86 (61.9)
0.876b)
Tinea corporis
155 (59.6)
86 (71.1)
69 (49.6)
<0.001b),*
Actinic keratosis
153 (58.8)
78 (64.5)
75 (54.0)
0.086b)
Verruca vulgaris
153 (58.8)
81 (66.9)
72 (51.8)
0.013b),*
Pityriasis rosea
138 (53.1)
71 (58.7)
67 (48.2)
0.091b)
Erysipelas
136 (52.3)
72 (59.5)
64 (46.0)
0.030b),*
Basal cell carcinoma
134 (51.5)
69 (57.0)
65 (46.8)
0.099b)
Squamous cell carcinoma
120 (46.2)
60 (49.6)
60 (43.2)
0.300b)
Seborrheic keratosis
113 (43.5)
48 (39.7)
65 (46.8)
0.250b)
Pemphigus vulgaris
74 (28.5)
33 (27.3)
41 (29.5)
0.692b)
Nail psoriasis
71 (27.3)
39 (32.2)
32 (23.0)
0.096b)
Syphilitic alopecia
52 (20.0)
27 (22.3)
25 (18.0)
0.384b)
Level of knowledgea)
Group 1
Group 2
P-valueb)
Mean±SD
Median (range)
Mean±SD
Median (range)
Benign dermatosis
77.25±10.94
80.00 (33.33–100.00)
72.33±12.35
73.33 (33.33–93.33)
0.003*
Allergic condition
89.67±16.98
100.00 (50.00–100.00)
85.43±19.94
100.00 (25.00–100.00)
0.083
Benign, precancerous, and malignant skin tumor
56.86±25.95
60.00 (0.00–100.00)
51.65±24.19
60.00 (0.00–100.00)
0.123
Bacterial infection
81.91±16.92
88.89 (33.33–100.00)
73.78±17.29
77.78 (33.33–100.00)
<0.001*
Fungal infection
83.57±13.41
87.50 (37.50–100.00)
77.52±14.99
75.00 (37.50–100.00)
0.001*
Viral infection
85.62±13.96
80.00 (60.00–100.00)
78.56±17.63
80.00 (40.00–100.00)
0.001*
Spirochetal disease
61.16±20.90
50.00 (50.00–100.00)
57.91±19.28
50.00 (0.00–100.00)
0.201
Ectoparasitic diseases and insect bite
93.39±14.02
100.00 (33.33–100.00)
87.53±22.08
100.00 (0.00–100.00)
0.042*
Diagnostic test
79.06±24.01
100.00 (0.00–100.00)
68.35±26.72
66.67 (0.00–100.00)
0.001*
General knowledge level
79.17±8.69
79.63 (51.85–98.15)
73.06±8.94
72.22 (44.44–90.74)
<0.001*
Variable
β (95% CI)
SE
P-value
R2
Age (y)
≤30
Ref
>30
–1.923 (–4.191 to 0.346)
1.152
0.096
0.011
Sex
Female
Ref
Male
–2.378 (–4.652 to –0.105)
1.155
0.040*
0.016
Years of professional experience (y)
≤5
Ref
>5
–1.844 (–4.115to 0.428)
1.154
0.111
0.010
Dermatology rotation status
Group 2
Ref
Group 1
6.109 (3.949 to 8.269)
1.097
<0.001*
0.107
Time since rotation (y)
≤1
Ref
>1
0.611 (–3.024 to 4.245)
1.836
0.740
0.001
Variable
β (95% CI)
SE
P-value
R2
Constant
75.933 (71.239 to 80.627)
2.384
<0.001*
0.107
Age (y)
≤30
Ref
>30
–0.241 (–2.492 to 2.009)
1.143
0.833
Sex
Female
Ref
Male
–1.651 (–3.866 to 0.565)
1.125
0.143
Dermatology rotation status
Group 2
Ref
Group 1
5.863 (3.639 to 8.087)
1.129
<0.001*
Table 1. Demographic characteristics of participants by rotation status
Values are presented as number (%), mean±SD, or median (range).
SD, standard deviation.
Table 2. Comparative analysis of the distribution of correct answers in the questionnaire overall and by subgroup
Values are presented as number (%). Group 1: physicians who had completed dermatology rotation; Group 2: physicians who had not completed dermatology rotation.
P<0.05 (statistical significance).
By Fisher exact test.
By chi-square test.
Table 3. Comparison of skin disorders groups and knowledge levels by dermatology rotation status
Group 1: physicians who had completed dermatology rotation; Group 2: physicians who had not completed dermatology rotation.
SD, standard deviation.
P<0.05 (statistical significance).
The knowledge level was calculated out of 100 based on the answers given to 54 questions.
By Mann-Whitney U test.
Table 4. Univariate linear regression analysis of predictors of overall diagnostic scores
Group 1: physicians who had completed dermatology rotation; Group 2: physicians who had not completed dermatology rotation.
CI, confidence interval; SE, standard error; Ref, reference.
P<0.05 (statistical significance).
Table 5. Multivariable linear regression analysis of independent predictors of overall diagnostic scores
Group 1: physicians who had completed dermatology rotation; Group 2: physicians who had not completed dermatology rotation.
CI, confidence interval; SE, standard error; Ref, reference.
