Sage Journals: Discover world-class research

Abstract

Background:

Cervical cancer (CC) remains a leading cause of death among women worldwide despite the availability of effective preventive strategies. In Ecuador, CC is the second most prevalent cancer among women. However, many women in rural areas remain inadequately screened, resulting in both underscreening and overscreening patterns.

Objective:

To identify the determinants associated with under- and overscreening for CC among women in rural areas of Cuenca, Ecuador.

Methods:

A cross-sectional, door-to-door survey was conducted between September and December 2023 in the rural parishes of Nulti and Chiquintad. A total of 1692 women aged 18 years and older were included. Participants were categorized as under-, optimally, or overscreened based on self-reported Pap test frequency according to the World Health Organization (WHO) recommended 3-to-5-year screening intervals. Odds ratio (OR) with 95% confidence intervals (CI) were calculated to identify associated factors.

Results:

Among the participants, 42.7% were underscreened, 19.3% optimally screened, and 37.9% overscreened. Underscreening was associated with being older than 45 years, having a low educational level, being single, experiencing embarrassment during genital examination, and lack of time. Overscreening was associated with being younger than 45 years, having higher education, and a strong willingness to undergo screening.

Conclusions:

Targeted interventions should address informational and emotional barriers contributing to underscreening while discouraging unnecessary overscreening. Strengthened counseling, public education, and standardized guidelines could improve the efficiency and equity of CC screening programs.

Keywords

cervical cancer screening behavior Pap test HPV

Introduction

Cervical cancer (CC) is the fourth most commonly diagnosed cancer and the fourth leading cause of cancer-related deaths among women worldwide, with over 662 000 new cases and more than 300 000 deaths reported in 2022.^1,2 According to the World Health Organization (WHO), CC is largely preventable through early detection and appropriate treatment. Nevertheless, it remains a major contributor to female cancer mortality.³

In Ecuador, CC ranks second in incidence among women, with nearly 2000 new cases and over 800 deaths reported in 2020.⁴ Prevention relies mainly on 2 key approaches: human papillomavirus (HPV) vaccination and routine cervical cancer screening through the Papanicolaou (Pap) tests conducted every 3-to-5 years, yet coverage remains suboptimal in rural regions.^1,3 Screening is recommended starting at age 21, regardless of the onset of sexual activity.⁵ The WHO recommends HPV vaccination among both girls and boys between the ages of 9 and 13 to effectively reduce CC incidence.³ However, until 2023, only 9-year-old girls were included in the national vaccination program in Ecuador. In 2024, the Ministry of Public Health (MSP) expanded the program to include boys, representing a significant public health milestone.⁶ Similar initiatives have been adopted by neighboring countries: Colombia included boys in October 2023,⁷ and Peru launched HPV vaccination for boys aged 9 to 13 in 2024.⁸

Beyond Ecuador, research from Colombia and Peru shows parallel trends. Cordoba-Sanchez et al⁹ documented that reluctance to vaccinate is associated with information gaps, concerns regarding vaccine safety, and prevailing social beliefs that influence parental attitudes toward adolescent vaccination. Consistent findings have been reported in Peru, where Juárez-Leon et al¹⁰ identified similar determinants affecting HPV vaccination uptake.

Despite the availability of preventive measures, many women in rural areas remain inadequately screened for CC.^5,11 In addition, although the WHO recommends Pap testing every 3 to 5 years, some healthcare facilities in Ecuador continue to offer annual testing, which may lead to unnecessary procedures and resource misallocation.³ Several barriers contribute to suboptimal screening practices, including limited knowledge, fear of results, embarrassment, and geographic inaccessibility.^5,12-16

Similarly, a study by Vega et al¹⁶ evaluated cervical cancer screening practices among rural Ecuadorian women, revealing substantial discrepancies between recommended guidelines and actual practices. Their findings identified fear of results, logistical barriers, and misconceptions about Pap testing as major factors contributing to both under- and overscreening phenomena.

Collectively, these studies demonstrate that while progress has been made in CC prevention, significant gaps remain, especially in rural and underserved populations. Building on previous work, the present study aims to contribute localized evidence to design interventions that are culturally sensitive and contextually appropriate for rural women in Cuenca, Ecuador.

These challenges lead to 2 contrasting yet coexisting issues: underscreening, where eligible women are not screened according to guidelines, and overscreening, where women undergo testing more frequently than recommended. This study aims to identify the determinants associated with both under- and overscreening for CC among women in rural areas of Cuenca, Ecuador. By addressing these factors, the study seeks to inform evidence-based public health interventions to improve access, align screening practices with global recommendations, and ultimately reduce the burden of CC in underserved populations.

Methods

Study Design

This study employed a descriptive, analytical, cross-sectional design with a 2-arm structure. A door-to-door survey was conducted to collect data on risk factors, barriers, and beliefs related to CC screening and HPV vaccination.

Study Population

The study was conducted between September 08 and December 30, 2023, in 2 rural communities of Cuenca, Ecuador: Chiquintad and Nulti. These communities were selected due to their similar sociodemographic characteristics,¹⁷ low CC screening coverage, and comparable distances from Cuenca, the capital of Azuay province.

The community of Chiquintad has a population of 5738 inhabitants (2683 men and 3055 women), while Nulti has 6707 inhabitants (3304 men and 3403 women).¹⁷ A total of 1692 women were included in the study based on the criteria outlined below.

Selection Criteria

Inclusion Criteria

Women aged 18 years or older, residing in either Chiquintad or Nulti, and willing to sign the informed consent were eligible for participation.

Exclusion Criteria

Women who were unable or unwilling to provide informed consent were excluded.

Recruitment Procedure

Prior to data collection, each community participated in an outreach and socialization phase where the research objectives were explained, and the research team was introduced. Following this, door-to-door data collection began at the center of each community and proceeded outward to ensure full geographic coverage.

Data Collection

Data were collected using the Kobo toolbox platform (https://www.kobotoolbox.org/). The survey included sections on sociodemographic data, family history, socioeconomic status, perceived barriers and beliefs regarding CC screening, and knowledge about CC, HPV, and vaccination. All data were anonymized and stored securely on a project computer accessible only to the principal and lead investigators.

Data Analysis

The dataset initially included 1897 responses and 133 variables derived from the “COENCA Project Quantitative Data” survey—48 related to metadata and 85 to survey items. Incomplete or erroneous responses were excluded, resulting in a final sample of 1692 participants.

Participants were classified into 3 screening categories—underscreened, optimally screened, and overscreened—based on their age and their response to question 15 (“How many Papanicolaou tests have you undergone in your lifetime?”). The expected number of screenings for each participant was calculated using the recommended screening initiation at age 21 and a recommended screening interval of 3-to-5 years.

The optimal number of screenings was determined using the following formula:

\begin{array}{l} O p t i m a l N u m b e r o f S c r e e n i n g s \\ = 1 + ((A g e - 21) / / S c r e e n i n g I n t e r v a l) \end{array}

where:

“//” represents integer division.

Results

A total of 1692 women from both communities agreed to participate in the study.

Screening Categories

Table 1 summarizes the classification of participants into 3 categories—underscreened, optimally screened, and overscreened—based on the recommended Pap test interval of 3 to 5 years. Most women were underscreened (n = 723; 42.7%), followed by overscreened (n = 642; 37.9%), while only 19.3% (n = 327) were optimally screened according to national guidelines.

Table 1.

Distribution of Screening Categories Among Participating Women Based on a 3- to 5-year Pap Test Interval.

Category	Number (n)	Percentage
Underscreened	723	42.7
Optimally screened	327	19.3
Overscreened	642	37.9

n, sample size.

Sociodemographic Characteristics

Table 2 presents the sociodemographic characteristics of participants according to screening category. Significant differences were observed in age, educational level, and civil status (P < .05). Women aged 20 to 29 years showed the highest proportion of overscreening (24.3%), whereas those aged ≥60 years were mostly underscreened (25.3%). Educational level varied across groups: 58.1% of underscreened women had completed only elementary school, compared with 48.3% in the optimally screened group, and 51.1% of overscreened women who had completed high school. In terms of civil status, a greater proportion of married women were found in all 3 categories: 60% among underscreened, 67.6% among optimally screened, and 65.1% among overscreened participants.

Table 2.

Sociodemographic Characteristics by Screening Category.

Variables	Underscreened (n = 723)	Optimal screened (n = 327)	Overscreened (n = 642)	P value*
Age
≤ 19 years old	0%	0%	(7%) 18.6 ± 0.5	P > .05
20-29 years old	(16.2%) 25.2 ± 2.5	(15.6%) 24.2 ± 2.8	(24.3%) 24.2 ± 3.2	P < .05
30-39 years old	(18.4%) 34.7 ± 3.0	(27.5%) 35.1 ± 2.7	(28.7%) 34.3 ± 2.8	P > .05
40-49 years old	(17.8%) 44.7 ± 2.9	(20.5%) 44.1 ± 2.7	(21.7%) 44.5 ± 2.8	P > .05
50-59 years old	(22.3%) 54.4 ± 2.9	(17.7%) 54.1 ± 2.4	(12.8%) 53.8 ± 2.9	P > .05
≥ 60 years old	(25.3%) 65.2 ± 3.4	(18.7%) 64.8 ± 3.5	(5.6%) 64.2 ± 2.6	P > .05
Educational level
None	34 (4.7%)	11 (3.4%)	7 (1.1%)	P < .05
Elementary school	420 (58.1%)	158 (48.3%)	200 (31.2%)	P < .05
High school	202 (27.9%)	113 (34.6%)	328 (51.1%)	P < .05
College	65 (9.0%)	45 (13.8%)	99 (15.4%)	P < .05
Master’s degree	2 (0.3%)	0%	8 (1.2%)	P < .05
Civil status
Single	180 (24.9%)	68 (20.8%)	181 (28.2%)	P > .05
Married	434 (60%)	221 (67.6%)	418 (65.1%)	P > .05
Divorced	50 (6.9%)	19 (5.8%)	32 (5.0%)	P > .05
Widow	59 (8.2%)	19 (5.8%)	11 (1.7%)	P < .05
Do you work?
No	192 (26.6%)	84 (25.7%)	164 (25.5%)	P > .05
Yes	531 (73.4%)	243 (74.3%)	478 (74.5%)	P > .05

Abbreviations: M (SD), Mean and standard deviation; n, sample size.

P-value was calculated using the ANOVA test.

Factors Associated with Underscreening and Overscreening

Table 3 summarizes the results of the bivariate logistic regression analysis. Several factors were found to be significantly associated with underscreening. Among sociodemographic characteristics, women aged ≥45 years were more likely to be underscreened compared with those <45 years (OR: 1.57; 95% CI: 1.21-2.03). Similarly, having a lower educational level (OR: 1.58; 95% CI: 1.21-2.06) and being single, divorced, or widowed (OR: 1.39; 95% CI: 1.05-1.83) were significant predictors of underscreening. With respect to healthcare access barriers, lack of time to undergo a Pap smear test was strongly associated with underscreening (OR: 2.17; 95% CI: 1.62-2.94). Cultural and emotional barriers also played an important role. Feelings of embarrassment when undergoing a genital examination were significantly associated with underscreening (OR: 2.12; 95% CI: 1.59-2.85). Among knowledge gaps and misconceptions, several factors showed strong associations: lack of knowledge about the recommended frequency of Pap smear testing (OR: 1.81; 95% CI: 1.33-2.50), the belief that Pap smears are unnecessary in the absence of symptoms (OR: 1.65; 95% CI: 1.05-2.68), lack of knowledge about the appropriate age to initiate screening (OR: 1.48; 95% CI: 1.12-1.96), and the belief that cervical cancer may not require chemotherapy or radiotherapy (OR: 1.88; 95% CI: 1.03-3.42). In terms of motivation and risk perception, lack of health awareness (OR: 2.46; 95% CI: 1.31-4.63), not receiving a doctor’s recommendation (OR: 1.75: 95% CI: 1.15-2.67), not receiving a nurse’s recommendation (OR: 1.44; 95% CI: 1.09-1.91), and the absence of information through newspapers, television, radio, or social media (OR: 2.04: 95% CI: 1.55-2.67) were significantly associated with underscreening. Social influence also played a role: lack of a family member’s recommendation (OR: 1.89; 95% CI: 1.08-3.50), not knowing someone with cervical cancer (OR: 1.40; 95% CI: 1.01-1.93), and lack of desire to undergo screening (OR: 1.58: 95% CI: 1.06-2.35) were significant predictors.

Table 3.

Bivariate Logistic Regression Analysis of Risk Factors Associated With Underscreening (n = 723) and Overscreening (n = 642).

Variables	Underscreening N = 723	P-value	Overscreening N = 642	P-value
Variables	OR (95% CI)	P-value	OR (95% CI)	P-value
Sociodemographic factors
Age
≥45 years	1.57 (1.21-2.03)	<.05	2.10 (1.60-2.77)	<.05
<45 years	1.57 (1.21-2.03)	<.05	2.10 (1.60-2.77)	<.05
Educational level
No education/primary school	1.58 (1.21-2.06)	<.05	2.25 (1.69-2.98)	<.05
Secondary, higher education, postgraduate	1.58 (1.21-2.06)	<.05	2.25 (1.69-2.98)	<.05
Marital status
Single/divorced/widowed	1.39 (1.05-1.83)	<.05	1.12 (0.84-1.48)	.44
Married	1.39 (1.05-1.83)	<.05	1.12 (0.84-1.48)	.44
Healthcare access barriers
Lack of time to undergo a Pap smear
Yes	2.17 (1.62-2.94)	<.05	1.41 (1.03-1.92)	<.05
No	2.17 (1.62-2.94)	<.05	1.41 (1.03-1.92)	<.05
Poor treatment at the health center
Yes	1.50 (0.93-2.48)	<.05	1.23 (0.74-2.05)	.42
No	1.50 (0.93-2.48)	<.05	1.23 (0.74-2.05)	.42
Long waiting times to receive care
Yes	1.37 (0.95-2.00)	<.05	1.27 (0.87-1.87)	.22
No	1.37 (0.95-2.00)	<.05	1.27 (0.87-1.87)	.22
Health centers open only at inconvenient hours
Yes	1.03 (0.67-1.60)	<.05	1.42 (0.91-2.21)	.12
No	1.03 (0.67-1.60)	<.05	1.42 (0.91-2.21)	.12
Difficulty obtaining an appointment
Yes	1.26 (0.90-1.76)	<.05	1.19 (0.84-1.67)	.32
No	1.26 (0.90-1.76)	<.05	1.19 (0.84-1.67)	.32
Cultural and emotional barriers
Embarrassment about undergoing a genital examination
Yes	2.12 (1.59-2.85)	<.05	1.48 (1.09-2.02)	<.05
No	2.12 (1.59-2.85)	<.05	1.48 (1.09-2.02)	<.05
Fear of knowing a cancer diagnosis
Yes	1.08 (0.63-1.93)	<.05	2.03 (1.09-3.77)	2.03
No	1.08 (0.63-1.93)	<.05	2.03 (1.09-3.77)	2.03
Religious beliefs preventing Pap smear uptake
Yes	7.78 (0.45-135.22)	.16	3.58 (0.18-69.61)	.40
No	7.78 (0.45-135.22)	.16	3.58 (0.18-69.61)	.40
Need for partner’s approval to undergo a Pap smear
Yes	1.28 (0.37-5.54)	<.05	1.55 (0.41-5.83)	.51
No	1.28 (0.37-5.54)	<.05	1.55 (0.41-5.83)	.51
Knowledge gaps and misconceptions
Lack of knowledge about the recommended frequency of Pap smears
Yes	1.81 (1.33-2.50)	<.05	1.22 (0.88-1.69)	.24
No	1.81 (1.33-2.50)	<.05	1.22 (0.88-1.69)	.24
Belief that Pap smears are unnecessary in the absence of symptoms
Yes	1.65 (1.05-2.68)	<.05	1.49 (0.90-2.47)	.12
No	1.65 (1.05-2.68)	<.05	1.49 (0.90-2.47)	.12
Belief that cervical cancer could lead women to undergo hysterectomy
Yes	1.32 (0.72-2.40)	.37	1.02 (0.50-1.99)	.96
No	1.32 (0.72-2.40)	.37	1.02 (0.50-1.99)	.96
Lack of knowledge about the age to initiate Pap smears
Yes	1.48 (1.12-1.96)	<.05	1.16 (0.87-1.54)	.30
No	1.48 (1.12-1.96)	<.05	1.16 (0.87-1.54)	.30
Belief that Pap smears are unnecessary for women without children
No	1.03 (0.63-1.67)	.91	1.65 (0.96-2.81)	.91
Yes	1.03 (0.63-1.67)	.91	1.65 (0.96-2.81)	.91
Belief that Pap smears are unnecessary for women without male sexual partners
Yes	1.09 (0.83-1.45)	<.05	1.06 (0.80-1.40)	0.80
No	1.09 (0.83-1.45)	<.05	1.06 (0.80-1.40)	0.80
Belief that cervical cancer can cause death
No	1.29 (0.50-3.30)	.60	1.58 (0.73-3.32)	<.05
Yes	1.29 (0.50-3.30)	.60	1.58 (0.73-3.32)	<.05
Belief that cervical cancer is a serious health problem
No	1.25 (0.39-3.95)	.71	1.31 (0.27-5.58)	.62
Yes	1.25 (0.39-3.95)	.71	1.31 (0.27-5.58)	.62
Belief that cervical cancer may require chemotherapy or radiotherapy
No	1.88 (1.03-3.42)	<.05	1.45 (0.77-2.70)	.25
Yes	1.88 (1.03-3.42)	<.05	1.45 (0.77-2.70)	.25
Motivation and risk perception
Perception that undergoing a Pap smear means caring for one’s health
No	2.46 (1.31-4.63)	<.05	1.38 (0.70-2.71)	.35
Yes	2.46 (1.31-4.63)	<.05	1.38 (0.70-2.71)	.35
Desire to maintain personal health
No	1.36 (0.44-4.26)	.59	1.02 (0.30-3.41)	.98
Yes	1.36 (0.44-4.26)	.59	1.02 (0.30-3.41)	.98
Belief that Pap smear can save one’s life
Yes	1.07 (0.50-2.17)	.90	1.17 (0.53-2.46)	.90
No	1.07 (0.50-2.17)	.90	1.17 (0.53-2.46)	.90
Doctor’s recommendation to undergo a Pap smear
No	1.75 (1.15-2.67)	.19	1.42 (0.92-2.19)	.12
Yes	1.75 (1.15-2.67)	.19	1.42 (0.92-2.19)	.12
Nurse’s recommendation to undergo a Pap smear
No	1.44 (1.09-1.91)	<.05	1.41 (1.06-1.88)	<.05
Yes	1.44 (1.09-1.91)	<.05	1.41 (1.06-1.88)	<.05
Mother’s recommendation to undergo a Pap smear
No	1.25 (0.86-1.81)	.23	1.90 (1.33-2.75)	<.05
Yes	1.25 (0.86-1.81)	.23	1.90 (1.33-2.75)	<.05
Family member’s recommendation to undergo a Pap smear
Yes	1.89 (1.08-3.50)	<.05	1.02 (0.69-1.54)	.88
No	1.89 (1.08-3.50)	<.05	1.02 (0.69-1.54)	.88
Exposure to information through newspapers, television, radio, or social media
No	2.04 (1.55-2.67)	<.05	1.06 (0.77-1.48)	.88
Yes	2.04 (1.55-2.67)	<.05	1.06 (0.77-1.48)	.88
Knowing someone who had cervical cancer
No	1.40 (1.01-1.93)	<.05	1.06 (0.77-1.48)	<.05
Yes	1.40 (1.01-1.93)	<.05	1.06 (0.77-1.48)	<.05
Desire to undergo pap smear
No	1.58 (1.06-2.35)	<.05	1.75 (1.12-2.70)	<.05
Yes	1.58 (1.06-2.35)	<.05	1.75 (1.12-2.70)	<.05

Abbreviations: CI, confidence intervals; OR, odds ratio.

In contrast, overscreening was primarily associated with younger age and higher educational level. Women aged <45 years were more likely to be overscreened compared with those ≥45 years (OR: 2.10; 95% CI: 1.60-2.77), and women with higher educational levels (secondary, higher education, or postgraduate) also showed increased odds of overscreening (OR: 2.25; 95% CI: 1.69-2.98). Among healthcare access barriers, women who did not report lack of time to undergo screening were more likely to be overscreened (OR: 1.41; 95% CI: 1.03-1.92). Cultural and emotional factors were also significant. Women who did not feel embarrassed about undergoing a genital examination (OR: 1.48; 95% CI: 1.09-2.02) and those who did not fear a cancer diagnosis (OR: 2.03; 95% CI: 1.09-3.77) had higher odds of overscreening. No significant associations were found between knowledge gaps or misconceptions and overscreening. In the domain of motivation and risk perception, significant predictors of overscreening included not receiving a nurse’s recommendation (OR: 1.41; 95% CI: 1.06-1.88), receiving a mother’s recommendation (OR: 1.90; 95% CI: 1.33-2.75), and willingness to undergo screening (OR: 1.75; 95% CI: 1.12-2.70).

Discussion

These findings underscore significant sociodemographic differences between underscreened and overscreened women, which may influence screening behaviors and access to healthcare services. This study identified 2 contrasting screening behaviors in rural Ecuador: underscreening and overscreening, each with distinct determinants and implications.

In this study, 42.7% of women were underscreened, a behavior also reported as predominant by Laowjan et al.¹⁸ Older, less educated, and single women were at greater risk of being underscreened, and nearly half of participants did not adhere to national guidelines for routine Pap testing, consistent with findings from Akinlotan et al¹⁹ and Narcisse et al.²⁰

In contrast, only 19.3% of women demonstrated optimal screening behavior, revealing a significant gap in preventive adherence. This low percentage of adequately screened women may suggest systemic challenges such as limited education about cervical cancer, and the recommended screening frequency, as well as logistical barriers to accessing healthcare services. These results align with the barriers and factors described by OPS²¹ and Heberer et al.²²

Interestingly, 37.9% of participants were considered overscreened, meaning they underwent Pap tests more frequently than recommended. Although overscreening has been less frequently studied, it can also burden healthcare systems and expose women to unnecessary procedures. As highlighted by Torres et al,²³ overscreening may show fragmentation within the healthcare system, heightened disease anxiety, or limited understanding of screening guidelines. Women who attend multiple health facilities may experience redundant testing, contributing to inefficiencies and resource strain.

Our results indicate that being over 45 years of age, having no formal education or only primary education, and being single, divorced, or widowed were significantly associated with underscreening. These findings are consistent with previous studies by Akinlotan et al,¹⁹ Narcisse et al,²⁰ Chao et al,²⁴ White et al,²⁵ and Chavez,²⁶ which similarly reported lower Pap testing rates among women with less education. Moreover, insufficient knowledge may foster a false sense of security in which women perceive Pap smears as unnecessary or unbeneficial,²³ a misconception reflected in our findings.

Our results also parallel those of Binka et al,⁵ Torres Ulloa et al,²³ Vega Crespo et al,²⁷ Vasudevan et al,²⁸ Bando et al,²⁹ and Marques et al,³⁰ who identified structural and psychosocial barriers, including lack of time and feelings of shame, as major determinants of underscreening in Ecuadorian populations. Notably, lack of awareness regarding the recommended frequency of Pap testing was a common factor, similar to findings by Vega Crespo et al,²⁷ Bando et al,²⁹ Marques et al,³⁰ Torres et al²³ Chavez et al,²⁶ Gomes et al³¹ Vasudevan et al²⁸ Urrutia et al³² and Desta et al.³³

Moreover, the perception of not being at risk, absence of symptoms, limited knowledge regarding the appropriate age to initiate screening, and lack of recommendations from healthcare providers or family members were also key contributors to underscreening. These factors, reported by Marques et al,³⁰ Vega Crespo et al,²⁷ Torres et al,²³ Urrutia et al,³² Ortiz et al,³⁴ emphasize how structural barriers and personal beliefs, such as perceiving Pap tests as unnecessary in the absence of symptoms, discourage participation in screening programs.

Furthermore, the lack of exposure to health messages through mass media or social networks, combined with limited proactive communication from healthcare professionals, further exacerbates screening gaps. Similar trends have been documented in both high- and low-income settings,^{12,18,20,26,27,31-33,35-38} Among our participants, feelings of embarrassment or shame associated with genital examinations emerged as a particularly strong barrier, echoing reports from Kirubarajan et al,³⁹ Vega et al,²⁷ Laowjan et al,¹⁸ Vasudevan et al,²⁸ Torres et al,²³ and Desta et al.³³ Additionally, a lack of motivation or desire to undergo a Pap test was another major obstacle, as also noted by Gomes et al,³¹ Urrutia et al,³² and Guartambel et al.⁴⁰

Regarding overscreening, our findings indicate that being younger than 45 years, having higher educational attainment, not perceiving time as a barrier, lack of embarrassment during the exam, and the absence of fear of a cancer diagnosis were all associated with more frequent screening. These results align with observations from Torres et al²³ and Becerra et al.⁴¹ Overscreening, while less explored, appears more common among younger and more educated women who are highly proactive about their health or receive care across multiple institutions.

A substantial proportion of overscreening in this population may also relate to inconsistent recommendations from nurses or family members regarding appropriate screening intervals, a phenomenon similarly reported by Akinlotan et al,¹⁹ Narcisse et al,²⁰ Chao et al,²⁴ and Franklin et al⁴² national initiatives should therefore aim not only to reduce underscreening but also to prevent excessive or unnecessary testing.

It is important to note that the literature on overscreening remains scarce. This study contributes valuable evidence to this underexplored topic and highlights the need for further research to develop evidence-based guidelines and educational strategies that promote adherence to optimal screening intervals.

One limitation of this study is that all data were self-reported, which introduces potential recall and social-desirability bias, particularly regarding sensitive issues such as personal health practices and beliefs. These biases may have led to either under- or overestimation of associations. Another limitation is that some reported Pap tests may have been diagnostic or follow-up procedures rather than routine screenings, potentially leading to an overestimation of overscreening prevalence. This limitation aligns with previous findings by Althubaiti⁴³ and Amin et al,⁴⁴ who noted that self-reported information is prone to recall and social-desirability bias.

Conclusion

This study identified key determinants associated with both underscreening and overscreening for cervical cancer among women in rural communities of Cuenca, Ecuador. Being over 45 years of age, having a low educational level, and holding persistent misconceptions or emotional barriers were significantly associated with reduced screening uptake. Conversely, the absence of these barriers, along with higher education, perceived risk, and proactive health behavior, was linked to more frequent screening than recommended.

These findings underscore the need for differentiated public health strategies: one aimed at addressing barriers and misinformation that hinder screening, and another focused on promoting adherence to evidence-based intervals to prevent unnecessary procedures. Tailored communication, health education, and provider training are essential to achieving equis and effective cervical cancer prevention across diverse populations.

Footnotes

Acknowledgements

Project supported by the Scientific and Technological Equipment Projects Competition, year 2024, code LE24-03, Universidad Tecnológica Metropolitana (JVQ and RCC), Project supported by the Competition for Research Regular Projects, year 2023, code LPR23-17, Universidad Tecnológica Metropolitana (RCC and JVQ), This research was supported by the Cluster Faraday UTEM (FONDEQUIP EQM180180) (JVQ and RCC), and Project ANID Fondecyt de Iniciación en Investigación 2025 #11250867 (RCC).

ORCID iDs

Dayanara Delgado López

Juan Pozo-Palacios

Jorge Vergara Quezada

Raúl Caulier-Cisterna

Bernardo Vega Crespo

Veronique Verhoeven

Vivian Alejandra Neira

Ethical Considerations

The study protocol was approved by the Ethics Committee for Health Research at the University of Cuenca (COBIAS), approval number 2024-001EO-VIUC, under the oversight of the Ministry of Public Health. All participants provided written informed consent prior to participation.

Consent to Participate

Written informed consent was obtained from all participants before their participation in the study.

Consent to Publication

Consent for publication was also obtained from all participants.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: VLIR-UOS

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The data are available from the corresponding author upon reasonable request. Due to privacy and ethical concerns, data are not publicly available in a repository but will be shared with qualified researchers under specific conditions.

References

Sung

Ferlay

Siegel

, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209-249. doi:10.3322/caac.21660

Ferlay

Ervik

Lam

, et al. Global Cancer Observatory: Cancer Today. International Agency for Research on Cancer. 2024. Accessed July 12, 2024. https://gco.iarc.who.int/media/globocan/factsheets/cancers/23-cervix-uteri-fact-sheet.pdf

World Health Organization. Global Strategy to Accelerate the Elimination of Cervical Cancer as a Public Health Problem. World Health Organization; 2020.

Ferlay

Ervik

Lam

, et al. Ecuador Fact Sheets 2020: IARC. International Agency for Research on Cancer. 2022. Accessed July 12, 2024. https://gco.iarc.who.int/media/globocan/factsheets/populations/218-ecuador-fact-sheet.pdf

Binka

Nyarko

Awusabo-Asare

Doku

DT.

Barriers to the uptake of cervical cancer screening and treatment among rural women in Ghana. Biomed Res Int. 2019;2019:6320938. doi:10.1155/2019/6320938

Ministerio de Salúd Pública. MSP y OPS impulsan campaña para proteger a más de 500 mil niñas y niños del cáncer de cuello uterino – Ministerio de Salud Pública. Ministerio de Salúd Pública. 2024. Accessed July 12, 2024. https://www.salud.gob.ec/msp-y-ops-impulsan-campana-para-proteger-a-mas-de-500-mil-ninas-y-ninos-del-cancer-de-cuello-uterino/

Ministerio de Salud y Protección Social. Minsalud fortalece esquema de vacunación ante alertas por picos de enfermedades prevenibles. Ministerio de Salud y Protección Social. 2023. Accessed July 12, 2024. https://www.minsalud.gov.co/Paginas/Minsalud-fortalece-esquema-de-vacunacion-ante-alertas-por-picos-de-enfermedades-prevenibles.aspx

Ministerio de Salud. Resolución Ministerial N.° 218-2024-MINSA. República Del Perú. Ministerio de Salud. March 27, 2024. Accessed July 12, 2024. https://cdn.www.gob.pe/uploads/document/file/6124416/5412702-resolucion-ministerial-n-218-2024-minsa.pdf?v=1711686334

Cordoba-Sanchez

Lemos

Tamayo-Lopera

Sheinfeld Gorin

HPV-vaccine hesitancy in Colombia: a mixed-methods study. Vaccines. 2022;10(8):1187. doi:10.3390/vaccines10081187

10.

Juárez-Leon

Calderón-Solano

Poterico

Ybaseta-Medina

Azañedo

Torres-Román

JS.

Factors associated with parental acceptance of the HPV vaccine in girls from metropolitan Lima, Peru. BMC Public Health. 2025;25(1):2334. doi:10.1186/s12889-025-23228-8

11.

Petersen

Jaca

Ginindza

, et al. Barriers to uptake of cervical cancer screening services in low-and-middle-income countries: a systematic review. BMC Womens Health. 2022;22(1):486. doi:10.1186/s12905-022-02043-y

12.

Daley

Alio

Anstey

Chandler

Dyer

Helmy

Examining barriers to cervical cancer screening and treatment in Florida through a socio-ecological lens. J Community Health. 2011;36(1):121-131. doi:10.1007/s10900-010-9289-7

13.

Bustamante

Almeida

Jaramillo

Palacios

Breaking barriers: acceptability and feasibility of HPV self-sampling for cervical cancer prevention in rural communities of Ecuador. Environ Health Perspect. 2024;2024(1):6-8. doi:10.1289/isee.2024.0801

14.

Guerrero

Zumarraga

DAA

Rojas

HM.

Prevención y atención del cáncer cervicouterino en Ecuador. Rev cuba investig bioméd. 2023;42(2):10, 16. Accessed October 28, 2024. https://revibiomedica.sld.cu/index.php/ibi/article/view/3030

15.

Delgado López

Acosta Bedón

Rivas-Párraga

, et al. Assessing the acceptability of a vaginal self-sampling device in a rural parish of Cuenca, Ecuador. J Prim Care Community Health. 2025;16:21501319251320172. doi:10.1177/21501319251320172

16.

Vega-Crespo

Neira

Maldonado-Rengel

, et al. Barriers and advantages of self-sampling tests, for HPV diagnosis: a qualitative field experience before implementation in a rural community in Ecuador. Int J Womens Health. 2024;16:947-960. doi:10.2147/IJWH.S455118

17.

INEC. Censo Ecuador. Censo Ecuador. INEC. 2022. Accessed April 15, 2024. https://censoecuador.ecudatanalytics.com/

18.

Laowjan

Maichonklang

Permpool

Talungchit

Jareemit

Factors associated with cervical cancer screening overuse and underuse, and attitude towards human Papillomavirus self-sampling among hospital staffs. Siriraj Med J. 2023;75(3):200-207. doi:10.33192/smj.v75i3.260868

19.

Akinlotan

Bolin

Helduser

Ojinnaka

Lichorad

McClellan

Cervical cancer screening barriers and risk factor knowledge among uninsured women. J Community Health. 2017;42(4):770-778. doi:10.1007/s10900-017-0316-9

20.

Narcisse

McElfish

Hallgren

Pierre-Joseph

Felix

HC.

Non-use and inadequate use of cervical cancer screening among a representative sample of women in the United States. Front Public Health. 2024;12:1321253. doi:10.3389/fpubh.2024.1321253

21.

Organización Panamericana de la Salud. [Synthesis of evidence and recommendations: guidelines for cervical cancer screening, detection, and treatmentSíntese de evidências e recomendações: diretrizes para rastreamento, detecção e tratamento do câncer do colo do útero]. Rev Panam Salud Publica. 2023;47:e72. doi:10.26633/RPSP.2023.72

22.

Heberer

Komenaka

Nodora

, et al. Factors associated with cervical cancer screening in a safety net population. World J Clin Oncol. 2016;7(5):406-413. doi:10.5306/wjco.v7.i5.406

23.

Torres Ulloa

Peñafiel Saavedra

Vega Crespo

BJ.

Adherencia y factores asociados al tamizaje de cáncer de cérvix. Guarainag-Paute. 2021. Rev Fac Cien Med Univ Nac Cordoba. 2022;40(3):33-40. Accessed July 18, 2024. https://publicaciones.ucuenca.edu.ec/ojs/index.php/medicina/article/view/4137/3674

24.

Chao

Chubak

Beaber

, et al. Gaps in the screening process for women diagnosed with cervical cancer in four diverse US health care settings. Cancer Med. 2023;12(3):3705-3717. doi:10.1002/cam4.5226

25.

White

Shoemaker

Benard

VB.

Cervical cancer screening and incidence by age: unmet needs near and after the stopping age for screening. Am J Prev Med. 2017;53(3):392-395. doi:10.1016/j.amepre.2017.02.024

26.

Chavez Andrade

. Factores que influyen en la cobertura de Papanicolaou en mujeres rurales en edad fértil, 2021. MED-FMENT Salud Públ Acción. 2024;5(1):1-11. doi:10.53287/flfg3174wy88m

27.

Vega Crespo

Neira

Ortíz Segarra

, et al. Barriers and facilitators to cervical cancer screening among under-screened women in Cuenca, Ecuador: the perspectives of women and health professionals. BMC Public Health. 2022;22(1):2144. doi:10.1186/s12889-022-14601-y

28.

Vasudevan

Stinnett

Mizelle

, et al. Barriers to the uptake of cervical cancer services and attitudes towards adopting new interventions in Peru. Prev Med Rep. 2020;20(101212):101212. doi:10.1016/j.pmedr.2020.101212

29.

Bando

Said

MSM

Sansuwito

Cervical cancer screening among women: a systematic literature review. Malahayati Int J Nurs Health Sci. 2024;7(8):963-975. doi:10.33024/minh.v7i8.685

30.

Marques

Gama

Santos

Heleno

Vermandere

Dias

Understanding cervical cancer screening barriers among migrant women: a qualitative study with healthcare and community workers in Portugal. Int J Environ Res Public Health. 2021;18(14):7248. doi:10.3390/ijerph18147248

31.

Gomes Martins

Bezerra Pinheiro

Moreira Vasconcelos

Pinto Falcão Júnior

JS.

Examen de papanicolaou: factores que influyen a las mujeres a no recibir el resultado. Enferm Glob. 2010;20:1-11. Accessed April 11, 2025. https://scielo.isciii.es/scielo.php?script=sci_abstract&pid=S1695-61412010000300007&lng=es&nrm=iso&tlng=es

32.

Urrutia

Gajardo

Características del Papanicolaou y de la atención recibida como factores para adherir (o no) al tamizaje. Estudio cualitativo en mujeres chilenas. Rev Chil Obstet Ginecol. 2018;83(5):471-477. doi:10.4067/s0717-75262018000500471

33.

Desta

Getaneh

Yeserah

, et al. Cervical cancer screening utilization and predictors among eligible women in Ethiopia: a systematic review and meta-analysis. PLoS ONE. 2021;16(11):e0259339. doi:10.1371/journal.pone.0259339

34.

Ortiz-Segarra

Vega Crespo

Lorena

NVA

Guerra-Astudillo

Ortiz-Mejia

Pérez-Paredes

View of Knowledge and practices of cervical cancer prevention among women with histopathological lesions. Cuenca, Ecuador 2021. MASKANA. 2021;12(2):4-10. Accessed August 11, 2024. https://publicaciones.ucuenca.edu.ec/ojs/index.php/maskana/article/view/3820/2846

35.

Vinodhini

Shanmughapriya

Das

Natarajaseenivasan

Prevalence and risk factors of HPV infection among women from various provinces of the world. Arch Gynecol Obstet. 2012;285(3):771-777. doi:10.1007/s00404-011-2155-8

36.

Jordá

Ramos

Mosmann

Lopez

Wegert

Cuffini

[Prevalence of human papillomavirus and associated risk factors in women affiliated with state health insurance in Posadas, Misiones (Argentina)]. Rev Chilena Infectol. 2020;37(2):111-116. doi:10.4067/s0716-10182020000200111

37.

Godoy

Reyes

Social representations of gynecologic cancer screening assessment a qualitative research on Ecuadorian women. Rev Esc Enferm USP. 2016;50 Spec:68-73. doi:10.1590/S0080-623420160000300010

38.

Aranguren

Burbano

González

Mojica

Plazas

Prieto

Barreras para la prevención y detección temprana de cáncer de cuello uterino. Inv Enf. 2017;19(2):129-144. doi:10.11144/javeriana.ie19-2.bpdt

39.

Kirubarajan

Leung

Yau

Sobel

WITHDRAWN: barriers and facilitators for cervical cancer screening among young women: a systematic review. Research Square. Published online September 24, 2020. doi:10.21203/rs.3.rs-64439/v1

40.

Guartambel Cajamarca

Guerrero Cevallos

Guapisaca Gaona

Armijos Ayala

AD.

Conocimiento y factores asociados a la detección de cáncer de cuello uterino. Salud Cienc Tecnol. 2022;2(S1):211. doi:10.56294/saludcyt2022211

41.

Becerra

Campos

Atuncar

Cáceres

Prevalencia y factores asociados al tamizaje preventivo del cáncer cervical en una región de Perú. Medwave. 2023. Accessed September 12, 2024. https://www.medwave.cl/investigacion/estudios/2709.html

42.

Franklin

Webel

Kaelber

Evans

Kelley

Prevalence of cervical cancer overscreening: review of a wellness registry. Comput Inform Nurs. 2020;38(9):459-465. doi:10.1097/CIN.0000000000000610

43.

Althubaiti

Information bias in health research: definition, pitfalls, and adjustment methods. J Multidiscip Healthc. 2016;9:211-217. doi:10.2147/JMDH.S104807

44.

Amin

Kolahi

Jahanmehr

Abadi

Sohrabi

MR.

Disparities in cervical cancer screening participation in Iran: a cross-sectional analysis of the 2016 nationwide STEPS survey. BMC Public Health. 2020;20(1):1594. doi:10.1186/s12889-020-09705-2

Factors Associated with Under- and Over-Screening for Cervical Cancer in Rural Areas of Cuenca,Ecuador

Abstract

Background:

Objective:

Methods:

Results:

Conclusions:

Keywords

Introduction

Methods

Study Design

Study Population

Selection Criteria

Inclusion Criteria

Exclusion Criteria

Recruitment Procedure

Data Collection

Data Analysis

Results

Screening Categories

Sociodemographic Characteristics

Factors Associated with Underscreening and Overscreening

Discussion

Conclusion

Footnotes

Acknowledgements

ORCID iDs

Ethical Considerations

Consent to Participate

Consent to Publication

Funding

Declaration of Conflicting Interests

Data Availability Statement

References