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. 2024 Apr 18;19(4):e0300763. doi: 10.1371/journal.pone.0300763

Cervical cancer screening knowledge and associated factors among Eswatini women: A cross-sectional study

Phinda G Khumalo 1,2,*, Mariko Carey 2,3, Lisa Mackenzie 1,2, Rob Sanson-Fisher 1,2
Editor: Gulzhanat Aimagambetova4
PMCID: PMC11025751  PMID: 38635684

Abstract

Background

Over recent years, cervical cancer incidence and related mortality have steadily increased in Eswatini. Low cervical cancer screening uptake partly explains the situation. Cervical cancer screening-related knowledge is positively associated with screening uptake. Little is known about women’s cervical cancer screening-related knowledge in Eswatini.

Objective

This study aimed to assess cervical cancer screening knowledge and associated factors among Eswatini women eligible for screening.

Methods

A cross-sectional study involving three hundred and seventy-seven women aged 25 to 59 selected from four primary healthcare clinics in Eswatini was conducted. A paper and pen survey assessed knowledge about cervical cancer risk factors, benefits of screening, the meaning of screening results, recommended screening intervals, and socio-demographics. Descriptive analyses were performed to assess participants’ sociodemographic characteristics. Linear regression was applied to examine associations between cervical cancer screening-related knowledge and participants’ sociodemographic characteristics.

Results

Two hundred and twenty-nine (61%) participants answered 80% or more knowledge questions correctly. Compared to HIV-positive participants, HIV-negative participants had 0.61 times lower cervical cancer screening knowledge scores (β = -0.39, 95% CI: -0.56, -0.19, p = 0.03). Participants who travelled more than 30 minutes to the clinic had 0.3 times lower cervical cancer screening knowledge scores (β = -0.70, 95% CI: -1.15, -0.25, p < 0.01) compared to participants who travelled less than 30 minutes to the clinic.

Conclusions

Relatively high overall cervical cancer screening knowledge levels were observed among the study participants. Findings from the current study may inform future educational programs to create and sustain an accurate understanding of cervical cancer screening in Eswatini communities.

Introduction

Over recent years, the number of Swati women with cervical cancer has steadily increased [1]. In 2018, Eswatini became the country with the world’s highest age-standardised incidence rate (84.5 per 100 000 female population) [2]. Approximately 6.5% of women develop cervical cancer before turning 75 years [3]. Mortality trends are similar to incidence trends in the country, with cervical cancer-related mortality estimated at 55.7 per 100 000 female population [2].

The World Health Organisation (WHO) recommends a comprehensive cervical cancer prevention program that involves reducing human papillomavirus (HPV) infections through vaccination and detection and treatment of cervical pre-cancer lesions through screening [4]. Without a vaccination program in Eswatini, screening remains the primary method of cervical cancer prevention. The Ministry of Health in Eswatini has implemented an opportunistic cervical cancer screening program that relies on women presenting at primary health clinics for screening. Visual inspection with acetic acid (VIA) is the screening method of choice. Other techniques, like cytology-based screening and HPV testing, are currently not feasible because of a shortage of financial, infrastructure, human resources and technology investments required to sustain such methods [5]. Unfortunately, the uptake of cervical cancer screening is generally low in Eswatini. A cross-sectional study conducted in 2017 found that only 5.2% of women of ages 30 to 65 years old reported having ever screened [6].

Previous research suggests that knowledge is positively associated with screening uptake [7–9]. Knowledge of cervical cancer risk factors and the benefits of cervical cancer screening is associated with higher screening participation rates [10, 11]. Correct information on these aspects helps develop positive cervical cancer screening attitudes and perceptions that influence whether a woman participates in cancer screening [12]. Also, the probability of promptly seeking screening and follow-up care may be higher among women informed about recommended screening intervals and the meaning of screening results [13, 14].

Little is known about women’s cervical cancer screening-related knowledge levels in Eswatini. Ngwenya and Huang’s study assessed cervical cancer screening knowledge among Swati men and women. It was found that 58.1% of the participants had misconceptions about the causes of cervical cancer. For example, a majority believed that cervical cancer is a disease caused by witchcraft, cervical cancer is caused by having back street abortion, only women with multiple partners get cervical cancer, and that cervical cancer is a disease for rich people only [6].

The Eswatini cervical cancer screening guidelines recommend that women participate in screening between the ages of 25 and 59. Ngwenya and Huang’s study only included women 30 – 59 years old [6]. Therefore, its results may not be representative of women eligible for screening in Eswatini. Also, the scope of knowledge domains in the study was limited to knowledge regarding symptoms and risk factors. Other important domains (such as knowledge of screening eligibility, benefits of cervical cancer screening and the meaning of cervical cancer screening results) previously assessed in other African studies [15, 16] were not examined. Therefore, the current study seeks to provide improvements on these methodological weaknesses.

In another study, 78% of women aged 18–69 years attending clinics in three regions of Eswatini reported having never heard of VIA [17]. Despite half the sample being HIV-positive, the study did not examine knowledge about the different screening intervals recommended for HIV-positive and HIV-negative women. Eswatini guidelines recommend that HIV-positive women are screened yearly due to their increased risk of cervical cancer, while HIV-negative women are screened every two years.

The current study was conducted to assess the level of knowledge regarding cervical cancer and screening among women aged 25 to 59 years in Eswatini. The study considered knowledge domains, including risk factors of cervical cancer, recommended screening intervals, benefits, and the meaning of cervical cancer screening results. The study also explored the extent to which participants’ sociodemographic characteristics are associated with knowledge level. We hypothesised that age, being married, education, HPV-positive status, socioeconomic status (estimated using electricity availability), and the number of clinic visits in the last six months would be positively correlated with knowledge and travel time to the nearest clinic negatively correlated. This study’s findings may inform future educational programmes aimed at increasing knowledge levels among women in Eswatini.

Materials and methods

Design and setting

A cross-sectional survey was conducted from October to December 2021 among women aged 25 to 59 from four selected primary healthcare clinics in Eswatini. Located in Southern Africa, Eswatini shares its borders with South Africa and Mozambique [18]. Eswatini is a lower middle-income country with a per capita Gross Domestic Product (GDP) of US$2,776 [19] and a population of 1.2 million people [20]. Much of the population lives in rural areas, with only 22% in urban areas [19]. The population of Eswatini is generally young, with 47% aged less than 18 years [21]. About half of the Emaswati are female (52.6%) [21]. Healthcare services are delivered in both private and public sectors. Public healthcare is organised in a four-tiered system. The system consists of a network of community-based services, primary healthcare facilities, secondary healthcare facilities (health centres and regional hospitals), and tertiary healthcare facilities (referral hospitals) [22]. Primary healthcare clinics provide first-line curative and emergency interventions to the rural population. They also offer promotive and preventative services [23]. Among other preventive services, primary healthcare clinics in Eswatini offer health screening, including cervical cancer screening [24]. HPV vaccination is not available in Eswatini [25].

Clinics were eligible if they provided care to at least 50 women aged 25 to 59 per week. Clinics that exclusively served HIV-positive women were not eligible to participate in the study. At the time of data collection, 94 clinics attended to more than 50 women per week [26]. One eligible clinic from each of the four regions of Eswatini (Hhohho, Lubombo, Manzini, and Shiselweni) was selected using convenience sampling.

Sampling and recruitment

Participants were women meeting the following inclusion criteria: (i) attending one of the selected clinics, (ii) being aged between 25 and 59 years, and (iii) having no history of cervical cancer or hysterectomy. Consecutive sampling was used to select women until the target sample size was reached.

Women in the eligible age range were approached at the clinic, informed about the study and invited to participate. Those who agreed to participate were asked to sign a consent form (available in English and siSwati) before completing a paper copy of the study survey. A study log sheet was used to document the age of both consenting and non-consenting eligible women.

Survey development and data collection

Three steps were implemented to produce survey items. The first step involved reviewing previous African research, World Health Organisation guidelines for screening and treating precancerous lesions for cervical cancer prevention [4], and Eswatini standardised cancer guidelines [5]. Twenty-five items were identified. The second step involved a review of identified items by six health behaviour experts. The panel of experts dropped one item about the benefits of cervical cancer screening because it was similar to another. An English version of the survey was developed based on these items.

The English survey was translated into siSwati using the forward-backward translation method [27]. A native bi-lingual siSwati translator independently translated the English survey into siSwati. This was followed by synthesising the forward translation, by the first author and the translator, into a satisfactory version. Afterwards, a second bilingual translator independently translated the synthesised forward translation into English. This translator was not permitted to see the original English version. After the backward translation was completed, both translators identified and resolved differences between the original and back-translated versions through discussions. A satisfactory version was reached after one round of backward-forward translation and discussions.

The 24-item survey was piloted before use in the current study. Bonett’s formula [28] was used to calculate the minimum sample size required to test the reliability of the survey. Twenty-five eligible women were recruited to participate in the pilot study involving completing the siSwati version of the survey. To test the reliability, the internal consistency of the questionnaire was assessed by Cronbach’s alpha coefficient. Content validity was evaluated by the panel of six health behaviour experts during survey development. Since the survey items were mainly derived from WHO and Eswatini screening guidelines, construct validity was not assessed.

As part of the feedback, women were asked to indicate whether: the instructions were easy to follow, the questions and/or response choices were easy to understand, whether they felt comfortable answering all the questions and whether they would be willing to complete a similar survey at future appointments (yes/no). Following piloting, the survey was adapted based on participants’ feedback before use in this study. Based on the feedback of eight participants, minor language changes were made on two items.

A research assistant distributed self-administered pen‐and‐paper surveys to consenting participants. Each participant completed the survey privately, either while they waited to be seen by the nurse or at the end of their clinic visit. Survey completion took approximately 15 minutes.

Measures

Knowledge regarding cervical cancer screening

Based on literature from the African setting and in the developed world, four knowledge domains (risk factors of cervical cancer, benefits of screening, the meaning of screening results, and recommended screening intervals) were assessed. Knowledge regarding cervical cancer risk factors was evaluated using ten multiple-choice items [29–31]. Six multiple-choice questions were used to assess knowledge about the Eswatini recommended screening intervals [4, 5]. Knowledge regarding the benefits of screening was measured using five items with true/false response options [10, 15, 16]. Three true/false items [15] were used to assess knowledge concerning the meaning of screening results. Each knowledge item was scored one if correct and zero if incorrect.

Sociodemographic variables

Four items were used to collect data on age, marital status, level of education, and availability of electricity in the participant’s household [as an estimate of the participant’s socioeconomic status [6]].

Cervical cancer screening accessibility-related characteristics

Two items (clinic visits in the past six months and travel time to clinic) [32, 33] were used to measure screening accessibility.

Health status

Two items assessed self-reported Human Immunodeficiency Virus (HIV) and Human Papilloma Virus statuses.

Statistical analysis

We assessed selection bias by comparing the age distributions of eligible clinic attendees and study participants using Fisher’s exact test. Cronbach’s alpha coefficient was used to estimate the reliability of the knowledge items, and an alpha equal to or greater than 0.70 was considered satisfactory. Mean scores and ranges for overall knowledge and each knowledge domain were calculated for each participant. Individual item scores were added to calculate each participant’s domain and overall knowledge scores. The minimum and maximum possible overall knowledge scores were 0 and 24, respectively. Participants’ overall knowledge scores were described by their mean, standard deviation (SD) and range. The overall knowledge scores were used to construct an additional dichotomous knowledge variable (0 = scoring below the mean overall score and 1 = scoring equal to or above the mean overall score). Women scoring equal to or above the mean overall score were regarded as having relatively high cervical cancer screening-related knowledge [34]. The frequency and proportion of participants with relatively high cervical cancer screening-related knowledge was calculated.

Descriptive analyses were performed to assess participants’ sociodemographic, cervical cancer screening accessibility-related characteristics, and health status-related characteristics. Mean, standard deviation (SD), and range were used to describe participants’ age. Age was categorised into 25 – 35 years, 36 – 45 years, and 46 – 59 years. Frequencies and proportions were used to assess all other characteristics. The number and proportions of participants who correctly responded to each knowledge item (and 95% confidence intervals) were also calculated.

Linear regression was applied to examine associations between cervical cancer screening-related knowledge and participants’ sociodemographic characteristics (sociodemographic, cervical cancer screening accessibility-related characteristics, and health status-related characteristics). Prior to conducting linear regression analysis, model assumptions were checked, including normality of residuals, homoscedasticity, multicollinearity and model fit. Linearity was not assessed since the model had no continuous independent variable. To check for normality of residuals, homoscedasticity visuals and statistical tests (the Shapiro-Wilk test and White’s test, respectively) were conducted. The Pearson Chi-square tests were used to check the independence between categorical variables. In conjunction with residual analysis and model diagnostics, the R-squared statistic was used to assess the regression model fit.

Previous research and knowledge of clinical importance were used to determine the initial list of covariates to examine in regression analysis. As part of model building, univariate linear regression analysis was used to select variables to include in the first multivariable linear regression model. Covariates with a univariate p-value of <0.25 were considered for inclusion in the multiple regression model. A model with all selected covariates was fitted, after which model reduction was assessed. Covariates that were no longer significant (at p<0.25) in the multivariable model were tested for removal from the model. If the covariate’s removal did not substantively change the remaining coefficients in the model by >∼10%, the covariate was removed from the final model [35]. Likelihood ratio tests were used to decide between competing models. The significance level for multivariate analysis was set at a 0.05 threshold with 95% confidence intervals. Statistics and Data (STATA) software version 16 was used to conduct all statistical analyses.

Sample size

The current study is a sub-study of a larger one reported elsewhere [36], which investigated non-adherence to cervical cancer screening recommendations among women in Eswatini. The aims of this larger study informed the sample size of 377 for the current study.

Results

The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) [37] guided reporting in the current study. All clinics that were approached and invited consented. Out of 459 women approached, 416 met the eligibility criteria. Thirty-nine women declined to participate in the study due to either lack of interest in research or time to complete the survey. Therefore, our final sample of 377 participants gave us a consent rate of 91%. Response rates across clinics were as follows: clinic A – 96%, clinic B – 88%, clinic C – 91%, and clinic D – 89%. No differences between the age distributions of community health workers in Eswatini and study participants were found.

Participants’ characteristics

Participants’ sociodemographic characteristics are shown in Table 1. A majority of the study participants: were 25 – 35 years old (234, 62%), were single (160, 42%), had secondary/ high school level of education (229, 61%), reported being HIV-negative (198, 53%), did not know whether they were HPV-negative or -positive (373, 99%), had electricity in their households (304, 81%), reported travel time to the clinic of 30 minutes or less (192, 51%), and had visited the clinic at least twice in the past six months (237, 63%).

Table 1. Participants’ characteristics (N=377).

Characteristics n (%)
Age
Mean (SD, range) 35 (9.6, 25– 59)
25 – 35 years 234 (62)
36 – 45 years 76 (20)
46 – 59 years 67 (18)
Marital status
Single 160 (42)
Married 151 (40)
Divorced/separated 33 (9)
Widowed 1 (0.3)
Living with a partner 33 (9)
Education
No formal education/primary school 108 (29)
Secondary/high school 229 (61)
Tertiary 40 (11)
Self-reported HIV-positive status 179 (47)
Self-reported HPV status
HPV-positive 4 (1)
HPV-negative -
I don’t know 373 (99)
Have electricity 304 (81)
≤30 minutes travel time to clinic 192 (51)
Clinic visits in the past six months
Never 60 (16)
Once 80 (21)
At least twice 237 (63)
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Cervical cancer screening-related knowledge

Overall knowledge scores

Cronbach’s alpha coefficients for the different knowledge domains were estimated as follows; overall knowledge items (0.74), risk factors of cervical cancer items (0.77), benefits of screening items (0.78), the meaning of screening items (0.72), and recommended screening intervals items (0.65). The overall cervical cancer screening knowledge score ranged between eight and 21 (maximum possible = 24). The mean overall knowledge score was 16 (SD = 2.18). Two hundred and twenty-nine (61%) participants had relatively high knowledge scores (answered 80% or more questions correctly).

Knowledge of risk factors

The mean total knowledge score for cervical cancer risk factors among all participants was 7 (SD = 1.81), out of a possible range of 0 to 10. Birth control pill usage was the only risk factor correctly identified by less than half (143, 38%) of the study participants. Detailed results on knowledge of risk factors are shown in Table 2.

Table 2. Proportions of women correctly responding to items regarding four domains of cervical cancer and screening-related knowledge (N = 377).
Item assessing knowledge Correct response Number (%) giving a correct response 95% CI
Risk factors
Infection with human papillomavirus True 359 (95) 93 – 97
Having more than one sexual partner True 323 (87) 82 – 89
Being bewitched False 310 (82) 78 – 86
Having sex before the age of 16 True 307 (81) 77 – 85
Giving birth before the age of 16 True 305 (81) 77 – 85
Having reduced body immunity True 258 (68) 63 – 73
Living with Human Immunodeficiency Virus True 239 (63) 58 – 68
Smoking True 192 (52) 46 – 56
Giving birth more than once True 187 (50) 44 – 55
Use of birth control pills True 143 (38) 33 – 43
Benefits of screening
The earlier cervical cancer is detected, the better the chance of recovery. True 364 (97) 94 – 98
Cervical screening reduces one’s chance of dying from cervical cancer True 331 (88) 84 – 91
Screening can detect abnormal changes in the cervix before they become cancer. True 313 (83) 79 – 87
Screening can detect abnormal changes that have become cancer, even if the person has no symptoms. True 307 (81) 77 – 85
Cervical screening can detect cancer, but only when the person has cancer symptoms. False 157 (42) 37 – 47
Meaning of screening results
If screening shows abnormal changes in the cervix, a woman may need more tests to determine whether she has cancer. True 357 (95) 92 – 97
If screening shows no abnormal changes in the cervix, a woman won’t need to screen in the future. False 348 (92) 89 – 95
If screening shows abnormal changes in the cervix, this always means a woman has cervical cancer. False 299 (79) 75 – 83
Cervical screening interval
How often should a woman have cervical cancer screening if they are: HIV positive? Annually 341 (90) 87 – 93
After the cervical screening, when does a woman get their results: Immediately 277 (73) 69 – 78
At what age should women have their last cervical screening test? 59 years 115 (31) 26 – 35
At what age should women have their first cervical screening test? 25 years 48 (13) 10 – 17
How often should a woman have cervical cancer screening if they are: HIV negative and HPV-negative? Every 3 years 28 (7) 5 – 11
How often should women have cervical cancer screening if they are: HIV negative and HPV-positive or status is unknown? Every 2 years 20 (5) 3 – 7
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Knowledge of benefits of screening

Most study participants correctly answered most of the benefits of cervical cancer screening items (Table 2). The mean total knowledge score for benefits of screening among all participants was 4 (SD = 0.87), out of a possible range of 0 to 6. Only 157 (42%) participants correctly identified the “cervical cancer screening can detect cancer, but only when the person has symptoms of cancer” item as false.

Meaning of screening results

The mean total knowledge score for benefits of screening among all participants was 3 (SD = 0.58), out of a possible range of 0 to 3. Of the three items, only one - “If screening shows abnormal changes in the cervix, this always means a woman has cervical cancer” - was correctly answered by 79% (n=299) of the participants.

Knowledge of screening intervals

The mean total knowledge score for the screening intervals domain among all participants was 2 (SD = 0.87), out of a possible range of 0 to 7. Few participants correctly identified Eswatini’s recommended age at first (48, 13%) and last (115, 31%) cervical screening tests. Also, only a minority of the participants knew about differences in the frequency of screening for women according to HIV and HPV statuses. For example, only 5% (20) correctly answered items about the Eswatini recommended screening frequency for HIV-negative women and HPV-positive (or with unknown status).

Associations between participants’ characteristics and cervical cancer screening-related knowledge

None of the linear regression assumptions was violated. An R-squared value of 0.34 suggested that only 34% of the variance in the dependent variable is explained by the independent variables in our model. Age, marital status, HIV status, and travel time to the clinic met the criteria (p ≤ 0.25) for inclusion in the adjusted linear regression model. HIV status and travel time to the clinic were the only variables significantly associated with cervical cancer screening-related knowledge. Compared to HIV-positive participants, HIV-negative participants had 0.61 times lower cervical cancer screening knowledge scores (β = -0.39, 95% CI: -0.56, -0.19, p = 0.03), assuming all other variables in the model were held constant. Participants who travelled more than 30 minutes to the clinic had 0.3 times lower cervical cancer screening knowledge scores (β = -0.70, 95% CI: -1.15, -0.25, p < 0.01) compared to participants who travelled less than 30 minutes to the clinic (Table 3).

Table 3. Associations between cervical cancer screening-related knowledge and participants’ sociodemographic characteristics (N=377).

Woman characteristic Overall knowledge score
Unadjusted β coefficient (95% CI) p-value Adjusted β coefficient (95% CI) p-value
Age
25 – 35 years R R
36 – 45 years 0.65 (0.09,1.22) 0.02* 0.55 (-0.06,1.16) 0.08
46 – 59 years 0.10 (-0.49,0.69) 0.73 0.13 (-0.56,0.81) 0.72
Marital status
Single R R
Married 0.39 (-0.09,0.88) 0.11* 0.37 (-0.15,0.90) 0.16
Divorced/separated/widowed -0.10 (-0.92,0.72) 0.81 -0.38 (-1.32,0.55) 0.42
Living with a partner -0.34 (-1.16,0.48) 0.41 -0.44 (-1.25,0.36) 0.28
Education
No formal education/primary school R
Secondary/high school -0.17 (-0.67,0.33) 0.50 - -
Tertiary -0.23 (-1.02,0.57) 0.57 - -
HIV status
HIV-positive R R
HIV-negative -0.39 (-0.83,-0.22) 0.03* -0.39 (-0.56,-0.19) 0.03**
Have electricity
Yes R
No -0.22 (-0.78,0.33) 0.43 - -
Travel time to the clinic
≤30 minutes R R
>30 minutes -0.53 (-0.97,-0.09) 0.02* -0.70 (-1.15,-0.25) <0.01**
Clinic visits in the past six months
Never R
Once 0.25 (-0.48,0.98) 0.50 - -
At least twice 0.39 (-0.35,0.89) 0.39 - -
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* - statistically significant p-value at α = 0.25

** - statistically significant p-value α = 0.05

Discussion

The current study presents information on cervical cancer screening knowledge and associated factors among a sample of women 25 – 59 years old in Eswatini. This study examined other pertinent knowledge domains besides previously reported knowledge about cervical cancer risk factors. These included recommended screening intervals and the benefits and meaning of cervical cancer screening results. Results indicate that most women had higher screening knowledge levels. Cervical cancer screening knowledge scores of HIV-negative participants were significantly lower than those of HIV-positive participants. Also, the knowledge levels of women who travelled more than 30 minutes to the clinic were lower than those who travelled less than 30 minutes.

Cervical cancer screening-related knowledge

Almost two-thirds (61%) of the participants in the current study had relatively high overall knowledge scores. However, several studies in sub-Saharan Africa suggest that women generally lack information about cervical cancer screening [38–40]. Accordingly, a systematic review of sub-Saharan studies reported low knowledge and awareness about cervical cancer and screening as a critical barrier to participation in cervical cancer screening [41].

The relatively high overall knowledge in the current study may be related to the sample’s somewhat higher education levels; 71% had at least secondary or high school level education. Studies in the Democratic Republic of Congo [42] and Ethiopia [43, 44] concluded that educational attainment was positively associated with women’s knowledge about cervical cancer screening. In addition, the relatively high cervical cancer screening knowledge could also be attributed to sampling women attending primary healthcare clinics. These women may be expected to have more opportunities to access cervical cancer information than those in the community [32].

While the overall knowledge of cervical cancer risk factors was relatively high, knowledge about specific risk factors was limited. For example, only 38% of the study participants correctly associated using the birth control pill and the risk of developing cervical cancer. While women may need to be educated about this risk factor, health education messages addressing this risk should be carefully crafted to avoid undermining the use of this birth control method which has helped reduce other problems such as unplanned pregnancies, abortions and maternal morbidity and mortality [45]. More importantly, health education messages should address the importance of consistent and correct use of condoms in preventing pregnancy and male-to-female genital HPV transmission [46].

Most participants (58%) believed screening could detect cancer only when a woman had cancer symptoms. Previous African studies have reported similar findings [47, 48]. This misconception may mean that screening is perceived as a diagnostic test rather than a screening test and could result in delays in screening [49]. Therefore, it may be beneficial to incorporate differences between screening and diagnostic tests in future health education messages.

One of the positive findings of this study was that most participants had higher scores of knowledge regarding the meaning of screening results. This may mean that participants are exposed to high-quality information from health providers regarding the meaning of cervical cancer screening [50]. Personal experience with screening may also increase women’s knowledge about screening [51].

Women’s knowledge of Eswatini’s recommended screening intervals, particularly the age for starting and frequency of screening according to HIV and HPV statuses, was poor. Two previous studies reporting similar results suggested that this knowledge gap was likely related to poor dissemination and communication of screening interval information by primary healthcare clinic nurses [52, 53]. In line with this, some previous African studies have reported that healthcare workers generally have insufficient knowledge about cervical cancer screening age and interval among healthcare workers [10, 54]. Therefore, it would be necessary for educational programs (to increase knowledge about recommended screening intervals) to target both health providers and women.

Associations between participants’ characteristics and cervical cancer screening-related knowledge

The current study found statistically significant associations between HIV status, travel time to the healthcare clinic and knowledge about cervical cancer screening. HIV-negative participants had significantly lower knowledge levels than HIV-positive participants. Similar results were reported in studies conducted in Zambia [55], the Lao People’s Democratic Republic [56], and the USA [57]. One reason for this finding could be that, compared to HIV-negative women, HIV-positive women may have better access to information about cervical cancer and screening [55]. Since 2018, the US Government, through PEPFAR, has supported the Government of Eswatini in cervical cancer screening and treating precancerous lesions for HIV-positive women. HIV-positive women are prioritised through this program with health education and cervical cancer screening [58]. Also, HIV-positive women are more likely to visit health facilities (where most health education occurs) as they seek life-long HIV treatment and care [55]. In the process, their chances of being informed about cervical cancer and screening may increase.

Participants who travelled more than 30 minutes to the clinic had lower cervical cancer screening knowledge scores than those who travelled less than 30 minutes to the clinic. This likely reflects reduced access to health care (including health education) for individuals who travel for extended periods to reach the nearest healthcare clinic [59]. While no previous study has reported similar findings, this finding should nonetheless be considered by health programs in Eswatini when tailoring education interventions to increase community cervical cancer screening-related knowledge. Community-based health education implemented by community health workers is an example of an intervention that may increase cervical cancer screening-related knowledge in the community [60].

Strengths and limitations

The study had a high response rate (estimated at 91%), increasing the chances of the results being representative of our target sample. Also, the current study examined crucial cervical cancer screening knowledge domains (benefits of screening, meaning of screening results, and screening intervals) that previous Eswatini studies have overlooked. Several limitations of the present study should be acknowledged. Firstly, our results may not be generalisable to the general population of Eswatini women, as the participants were only recruited from primary healthcare clinics. Therefore, results need to be interpreted with caution. Second, women’s HIV statuses were self-reported. Women may have underreported being HIV positive to present themselves in a socially desirable way. Third, due to participant burden concerns, it was impossible to assess all possible correlates of knowledge. Fourth, the current study focused on cervical cancer screening knowledge. While knowledge has been shown to be correlated with screening uptake in past research (7, 8, 62), interventions focussing on knowledge alone are ineffective in improving screening [61]. This suggests that knowledge may be a necessary but not sufficient condition for cervical cancer screening participation [62, 63]. The need for future well-controlled intervention studies to examine the impact of interventions focussed on knowledge and addressing other barriers to screening participation is indicated. Finally, while our model identified statistically significant relationships, only 34% of the variance in the dependent variable was explained. This remaining 66% may be due to random error or other factors not captured by our model. Despite meeting model assumptions, these limitations suggest avenues for future research. Increasing the sample size and exploring potential independent variables could strengthen the reliability and generalizability of our findings. Additionally, incorporating qualitative methods could further clarify the complex dynamics at play.

Conclusion

While overall knowledge about cervical cancer screening was relatively high among the study participants, there were gaps in knowledge regarding specific risk factors of cervical cancer and when to begin and how often to screen. These findings may inform future educational programs to create and sustain an accurate understanding of cervical cancer screening in Eswatini communities. Educational programs must advocate for and target HIV-negative women and women who travel for extended periods to reach the nearest healthcare clinic. Future studies involving larger samples from the community may help confirm and explain why travel time matters in cervical cancer screening knowledge levels.

Acknowledgments

The authors would like to thank Ms Siphosethu Mamba for her assistance with collecting the study data. The authors are also grateful to Dr Christopher Oldmeadow for the statistical advice.

Data Availability

In accordance with the ethical and legal requirements outlined in the Eswatini Health and Human Research Ethics Guidelines – 3rd Edition, the data supporting the study findings cannot be shared publicly. Data are available from the Eswatini Health and Human Research Review Board (prm2@ehhrrb.org.sz) for researchers who meet the criteria for access to confidential data.

Funding Statement

Open Access funding was supported by a project grant from the National Health and Medical Research Council/Global Alliance for Chronic Diseases ([PGK], [MC], [LM], [RSF]; APP2010271).

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Decision Letter 0

Gulzhanat Aimagambetova

16 Nov 2022

PONE-D-22-25805A Cross-sectional Study Reporting the Level of Knowledge Regarding Cervical Screening among Women in EswatiniPLOS ONE

Dear Dr. Khumalo,

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Reviewer #1: The study aimed to assess the knowledge of cervical screening in Eswatini women. The study results suggest overall respondents had a high knowledge level, and some factors were independently associated with the knowledge. I have several comments and concerns that need clarification or additional considerations. Please see them below:

Check the sentence in the lines 85-87

The authors could be more explicit in discussing how this study differs from previous research.

There two aims but there are not reflected in the manuscript title and abstract.

How do ineligible healthcare clinics differ from the included clinics?

What were exclusion criteria?

Were all women recruited to take part in the study? What were response rates across healthcare clinics? What type of sampling technique was utilized?

The survey development section needs more clarification. How many items initially were selected? (the authors may provide the list of identified items in the supplementary materials section) How did experts agree on the final 29-item survey (please describe the process)? Were the survey in English or siSwati? If yes, who and how the survey was translated? Could the authors provide more information on how the survey was modified after the pretesting (they may include before and after survey versions)? What type of pretesting technique was utilized? What was the rationale for selecting only 25 participants? Have the authors checked internal reliability and validity of the survey when pretested it?

What theoretical framework was applied to answer the research question? The theoretical framework may help with explaining the rationale for selecting some covariates for the analysis.

It is not clear how the overall knowledge score was calculated. What was the rationale for dichotomizing the overall knowledge score (why this cut-off were selected)?

The authors mentioned that the Cronbach’s alpha was calculated to assess the internal reliability. I wonder whether inter-item correlation and potentially explanatory factor analysis was performed?

In the analysis part, the authors stated that “The potential for introducing confounding bias was also considered in addition to significance. No confounding effects were found.” Could they elaborate more what do mean by this statement and how it was performed?

Also, it is not clear what was the rationale for using 0.25 threshold for selection of variables for the multivariable analysis? If a variable passed the threshold in the univariate analysis, what happened next? All variables were included in the model? What about clinically or epidemiologically important variables?

Have the authors checked the linear regression assumptions? Multicollinearity? Model fit?

Prior conducting the study, have the authors calculated the required sample size for this study? If not, maybe it would be interesting to determine the statistical power of the analysis?

In Table 3, have p-value estimates for multi-level categorical variables were corrected for multiple pair-wise comparison tests?

I am concerned about the robustness of the study results given some of the important independent factors for the knowledge are missing or not included in the survey (e.g., socio-economic status, previous history of gynecological diseases, history of cervical cancer screening). I am also concerned about the novelty of the research, because the knowledge may not actually correlated with the uptake. If data permits, I would be interested to see if the hypothesis can be tested and results presented to make a stronger conclusion.

I believe the limitations section also needs some improvements based on the comments raised in this review.

Reviewer #2: Dear Authors,

Thank you for this opportunity to read and review your manuscript. In covers an important topic as Cervical cancer remains a huge medical and public health issue, especially in low- and middle-income countries. Cervical cancer prevention programs are well developed now, however, in some parts of the world it is still not properly implemented. The manuscript is clearly written in professional, unambiguous language. The reference list is up-to-date. However, some corrections should be made before acceptance and publishing.

1. The manuscript title should be rephrased: current version “A Cross-sectional Study Reporting the Level of Knowledge Regarding Cervical Screening among Women in Eswatini”. Suggested - The Level of Knowledge Regarding Cervical Cancer Screening among Women in Eswatini: A Cross-sectional Study. Or any other that will sound more clear.

2. The abstract represents the study very well. However, it should be revised. The academic writing style of the abstract and the manuscript in general should be improved. It is better if the text is rewritten to be from a third parity. Example: current version ‘We conducted a cross-sectional study involving three hundred and seventy-seven women aged 25 to 59 selected from four primary healthcare clinics in Eswatini.” Suggested - A cross-sectional study involving three hundred and seventy seven women aged 25 to 59 selected from four primary healthcare clinics in Eswatini was conducted.

3. The introduction part gives a clear understanding of the study rationale. However, please rethink whether you need subheadings in the introduction part.

4. A short notes about the country, Eswatini, would be very useful for a potential reader to understand specifics o the country. One paragraph noting the country location, population, income (World Bank) – low- or middle income, specifics of the healthcare system pointing on the cervical cancer screening and vaccination (if it is covered by the government or not, which is partially already mentioned). This information will definitely help potential readers to get into the problem discussed in the manuscript.

I would recommend removing the subheadings form the introduction, it will improve the text comprehension.

5. Aims should not be separated from the introduction part, but presented as a last paragraph in the introduction. It will sound better without numbering (1 and 2), but as a plane text. Please always refer to the PLOS ONE Guide for authors.

6. The methods part includes all required data. However, as in the introduction part, there are too many subsections, some of them could be merged. Example: subsection “Sample” (line 120) should be merged with subsection “Sampling and recruitment” (line 124). Please revise the methods section accordingly.

7. Please mention in the methods part if the STROBE guideline for cross-sectional studies was used. If not, then why?

8. What criteria were used to select clinics for inclusion in the study?

9. When choosing a clinic to be included in the study, was the location of the clinic considered?

10. Has the WHO questionnaire been adapted considering local peculiarities?

11. The results section presents a very interesting and valuable data, supported by clear tables and description.

12. In general, the discussion part is interesting, however, requires improvement to meet the style appropriate for research manuscripts. The first paragraph of the discussion should provide to a potential reader the study rationale in brief. Please find below the suggestions how the discussion part should be restructured:

Discussion

1.1 Rationale of the study (why it was done)

1.1.1 Main findings of the study

1.1.2 What makes our study unique

1.1.3 What it adds to what we already know

1.2 Subject of the discussion

Comparison of our results with neighboring countries, with countries of the same

development levels (income), with developed high-income countries). Agreement and

disagreement with the studies compared. Suggested similar articles to compare with (from countries of the similar income) - doi: 10.1200/GO.20.00619; doi: 10.1177/17455065211004135; doi: 10.1371/journal.pone.0261203

1.4 Sum up of the study, study strengths and limitations

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PLoS One. 2024 Apr 18;19(4):e0300763. doi: 10.1371/journal.pone.0300763.r002

Author response to Decision Letter 0

4 Aug 2023

Dear Editorial Office,

Re: “PONE-D-22-25805: A Cross-sectional Study Reporting the Level of Knowledge Regarding Cervical Screening among Women in Eswatini”

Thank you for allowing us to submit a revised draft of our manuscript. We are grateful for the insightful comments on our manuscript, which have improved it. We have incorporated most of the suggestions made by the reviewers. Those changes are highlighted in yellow in the text. Please see below for a point-by-point response to the reviewers’ comments and concerns.

REVIEWER COMMENTS

Reviewer #1:

Check the sentence in lines 85-87. The authors could be more explicit in discussing how this study differs from previous research.

In lines 79 – 87, we have modified the description of previous research and highlighted how this research provides important methodological improvements.

There are two aims, but they are not reflected in the manuscript title and abstract.

Changes have been made to the title to reflect the second aim. Please see page 1.

How do ineligible healthcare clinics differ from the included clinics? What were the exclusion criteria?

Clinics providing care to fewer than 50 women aged 25-59 per week and those attending only to HIV-positive women were ineligible to participate. This information has been added on page 5, lines 121 to 122.

Were all women recruited to take part in the study?

A consecutive sample of women who met the inclusion criteria was asked to participate in the study. This information has been on page 6, lines 129 – 130.

What were response rates across healthcare clinics?

Response rates across clinics were as follows; clinic A – 96%, clinic B – 88%, clinic C – 91%, and clinic D – 89%. This information has been on page 10, lines 242 – 244.

What type of sampling technique was utilized?

Consecutive sampling was used to select women until the target sample size was reached. Please see page 6, lines 129 – 130.

The survey development section needs more clarification. How many items initially were selected? (the authors may provide the list of identified items in the supplementary materials section)

The survey development section has been modified on pages 6 to 7, lines 137 to 166. An English version of the survey is also attached to this response letter.

How did experts agree on the final 29-item survey (please describe the process)?

The process is described on page 6, lines 137 to 143.

Were the survey in English or siSwati? If yes, who and how the survey was translated?

The process is described on pages 6 to 7, lines 144 to 152.

Could the authors provide more information on how the survey was modified after the pretesting (they may include before and after survey versions)?

Information is provided on page 7, lines 161 to 166.

What type of pretesting technique was utilized?

The technique is described on page 7, lines 154 to 170.

What was the rationale for selecting only 25 participants?

Bonett's formula was used to calculate the minimum sample size required to test for Cronbach's Alpha- coefficient (please see page 7, lines 153 – 154). In addition, previous research recommends sample sizes between 24 and 50 (Sim and Lewis, 2012; Julious, 2005).

Sim J, Lewis M. The size of a pilot study for a clinical trial should be calculated in relation to considerations of precision and efficiency. J Clin Epidemiol 2012; 65:301-308.

Julious SA. Sample size of 12 per group rule of thumb for a pilot study. Pharm Stat 2005; 4:287-291.

Have the authors checked internal reliability and validity of the survey when they pretested it?

As stipulated on page 7, lines 153 to 160, Cronbach’s alpha coefficient was used to estimate the reliability of the knowledge items. Content validity was assessed by six health behaviour experts during survey development. Given that the survey was mainly derived from WHO and Eswatini screening guidelines, construct validity was not assessed.

What theoretical framework was applied to answer the research question? The theoretical framework may help with explaining the rationale for selecting some covariates for the analysis.

Based on previous research, we expected age, marriage, education, HPV-positive status, socioeconomic status (based on electricity availability), and the number of clinic visits in the past six months to correlate positively with knowledge, while the distance to the nearest clinic would be negatively correlated. This information has been included in the revised manuscript on pages 4 to 5, lines 99 to 103.

It is not clear how the overall knowledge score was calculated.

The description of how we calculated the overall score has been modified on page 8, lines 194 to 197.

What was the rationale for dichotomizing the overall knowledge score (why this cut-off were selected)?

Dichotomising the knowledge score allowed labelling/describing participants as having or not having an outcome (higher level of knowledge in this case) to facilitate a better understanding of our sample. This was only done for descriptive analysis purposes. In regression analysis, we used the knowledge score as a continuous variable to avoid losing information, decreasing statistical power and increasing the probability of type I error.

The authors mentioned that the Cronbach’s alpha was calculated to assess the internal reliability. I wonder whether inter-item correlation and potentially explanatory factor analysis was performed?

The survey items were taken from the WHO guidelines, which are deemed credible. Also, a panel of experts deemed the survey items relevant. For these two reasons, we did not perform inter-item correlation. Performing explanatory factor analysis was not part of the study’s aims. Also, given our sample size, this analysis may have been insufficiently powered.

In the analysis part, the authors stated that “The potential for introducing confounding bias was also considered in addition to significance. No confounding effects were found.” Could they elaborate more what do mean by this statement and how it was performed?

We have modified our statement on adjusting confounding in the analysis phase on page 10, lines 228 to 233.

Also, it is not clear what was the rationale for using 0.25 threshold for selection of variables for the multivariable analysis?

As a rule of thumb, a liberal threshold is used in univariate analysis when selecting variables for the multivariable analysis. According to Hosmer and Lemeshow, and Sperandei, using traditional levels of significance, such as 0.05, can fail to identify variables associated with the independent variable.

Hosmer DW, Lemeshow SJAlr. Interpretation of the fitted logistic regression model. 2000;2:47-90.

Sperandei S. Understanding logistic regression analysis. Biochem Med (Zagreb). 2014;24(1):12-8.

If a variable passed the threshold in the univariate analysis, what happened next?

Please see page 10, lines 224 to 230, for details on model building.

All variables were included in the model?

Please see a description of variables included in the multivariable regression model on page 15, lines 286 to 287.

What about clinically or epidemiologically important variables?

As described on page 9, lines 221 to 222 an initial list of covariates to be examined in regression analysis was determined using previous research and knowledge of clinical importance. Likelihood ratio tests were used to decide between competing models.

Have the authors checked the linear regression assumptions? Multicollinearity? Model fit?

A statement summarising the statistical analyses conducted to check the linear regression assumptions can be found on page 9, lines 214 to 220. A summary of results from these analyses is presented on page 15, lines 285 to 286.

Prior conducting the study, have the authors calculated the required sample size for this study? If not, maybe it would be interesting to determine the statistical power of the analysis?

Sample size determination is described on page 10, lines 238 to 240.

In Table 3, have p-value estimates for multi-level categorical variables were corrected for multiple pair-wise comparison tests?

Given our sample size (377), we believe there was no indication for correcting for multiple pair-wise comparisons. A rule of thumb by Green (1991) in Tabachnick and Fidell (2014) suggests that to avoid the problem of multiple testing, the sample size should be greater or equal to 104 + m, where m is the number of predictors. Given 20 predictors in the current study, 104 + m equals 124.

Tabachnick, B. G., Fidell, L. S., & Ullman, J. B. (2007). Using multivariate statistics (Vol. 5, pp. 481-498). Boston, MA: pearson.

I am concerned about the robustness of the study results given some of the important independent factors for the knowledge are missing or not included in the survey (e.g., socio-economic status, previous history of gynecological diseases , history of cervical cancer screening)

We selected correlates that had strong backing from previous research to avoid the risk of multiple testing associated with including many correlates. We may have mixed studies suggesting other variables. As a result, we have included the potential to omit potential confounder/important covariates as one of the study’s limitations on page 20, lines 384 to 392.

I am also concerned about the novelty of the research, because the knowledge may not actually correlated with the uptake. If data permits, I would be interested to see if the hypothesis can be tested and results presented to make a stronger conclusion.

In the limitations section (page 20, lines 386 to 392), it is now made clear that knowledge is a necessary but not a sufficient condition for screening participation. The need for future well-controlled intervention studies to determine what might help increase screening participation is indicated.

I believe the limitations section also needs some improvements based on the comments raised in this review.

The limitations section has been revised.

Reviewer #2:

The manuscript title should be rephrased: current version “A Cross-sectional Study Reporting the Level of Knowledge Regarding Cervical Screening among Women in Eswatini”. Suggested - The Level of Knowledge Regarding Cervical Cancer Screening among Women in Eswatini: A Cross-sectional Study. Or any other that will sound more clear.

The manuscript title has been modified. Please see page 1.

The abstract represents the study very well. However, it should be revised. The academic writing style of the abstract and the manuscript in general, should be improved. It is better if the text is rewritten to be from a third party. Example: current version ‘We conducted a cross-sectional study involving three hundred and seventy-seven women aged 25 to 59 selected from four primary healthcare clinics in Eswatini.” Suggested - A cross-sectional study involving three hundred and seventy seven women aged 25 to 59 selected from four primary healthcare clinics in Eswatini was conducted.

The abstract and manuscript have been rewritten in the third person.

The introduction part gives a clear understanding of the study rationale. However, please rethink whether you need subheadings in the introduction part. I would recommend removing the subheadings from the introduction, it will improve the text comprehension.

Subheadings have been removed.

A short notes about the country, Eswatini, would be very useful for a potential reader to understand specifics of the country. One paragraph noting the country location, population, income (World Bank) – low- or middle income, specifics of the healthcare system pointing on the cervical cancer screening and vaccination (if it is covered by the government or not, which is partially already mentioned). This information will definitely help potential readers to get into the problem discussed in the manuscript.

Information about Eswatini has been added on page 5, lines 107 to 120.

Aims should not be separated from the introduction part, but presented as a last paragraph in the introduction. It will sound better without numbering (1 and 2), but as a plane text. Please always refer to the PLOS ONE Guide for authors.

As suggested, aims are now presented in the last paragraph of the introduction section. Please see pages 4 to 5, lines 93 to 103.

The methods part includes all required data. However, as in the introduction part, there are too many subsections, some of them could be merged. Example: subsection “Sample” (line 120) should be merged with subsection “Sampling and recruitment” (line 124). Please revise the methods section accordingly.

As suggested methods section has been modified.

Please mention in the methods part if the STROBE guideline for cross-sectional studies was used. If not, then why?

A statement on the STROBE guideline has now been included on page 10, lines 238 to 239. The STROBE checklist is also attached to this response.

What criteria were used to select clinics for inclusion in the study?

Information on inclusion criteria is presented on page 5, lines 121 to 122.

When choosing a clinic to be included in the study, was the location of the clinic considered?

As indicated on page 5, lines 121 to 123, the location (region) of the clinic was considered when we selected clinics. Since all primary healthcare clinics are in rural areas, rurality was not considered.

Has the WHO questionnaire been adapted considering local peculiarities?

No WHO questionnaire was used. Instead, WHO guideline recommendations were expressed in question form and used to assess knowledge among women. WHO guideline recommendations account for local peculiarities, especially socioeconomic status, such that there are specific recommendations for poor resource countries and developed countries. Countries adopt (from the WHO recommendations) guidelines that would work for their local situations.

In general, the discussion part is interesting, however, requires improvement to meet the style appropriate for research manuscripts. The first paragraph of the discussion should provide to a potential reader the study rationale in brief. Please find below the suggestions how the discussion part should be restructured:

As suggested, the discussion section has been modified. Please see pages 17 to 20.

We look forward to hearing from you regarding our submission and responding to any further questions and comments you may have.

Kind regards,

Phinda Goodwill Khumalo

Attachment

Submitted filename: Response to reviewers.docx

pone.0300763.s001.docx (138.9KB, docx)

Decision Letter 1

Gulzhanat Aimagambetova

13 Dec 2023

PONE-D-22-25805R1Cervical Cancer Screening Knowledge and Associated Factors among Eswatini Women: A Cross-sectional StudyPLOS ONE

Dear Dr. Khumalo,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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We look forward to receiving your revised manuscript.

Kind regards,

Gulzhanat Aimagambetova

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: All my previous comments were addressed. I have some minor comments that authors may consider addressing to strengthen their manuscript:

In the lines 286-287, it says that the “…The goodness of fit of the regression 287 model was estimated at 34%...”. I wonder what type of test was used? How to interpret this result?

In the sample size calculation section, it seems the formula for prevalence sample size calculation was used. I wonder what parameters were used to calculate the required sample size? What were the assumptions?

**********

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If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

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PLoS One. 2024 Apr 18;19(4):e0300763. doi: 10.1371/journal.pone.0300763.r004

Author response to Decision Letter 1

19 Feb 2024

JOURNAL REQUIREMENTS

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

- To the best of our knowledge, none of the cited papers in our manuscript have been retracted. However, due to difficulty in identifying the publication journal of "Knowledge of cervical cancer and patronage of cervical cancer screening services among female health workers in Kumasi, Ghana 2011" by Adageba et al. (reference 54), we opted to remove this reference in line 347. The information it provided is adequately covered by the remaining references within the same topic area.

- Three references in the reference list have been reformatted to comply with the journal's specific formatting requirements. These changes are highlighted on page 24.

- An additional reference has been added to the reference list and cited on line 234.

REVIEWER COMMENTS

Reviewer #1:

In the lines 286-287, it says that the “…The goodness of fit of the regression model was estimated at 34%...”. I wonder what type of test was used? How to interpret this result?

- In lines 285-287, we have modified this statement and mentioned that “An R-squared value of 0.34 suggested that only 34% of the variance in the dependent variable is explained by the independent variables in our model.”

- We acknowledge that given our results, about 66% of the variance is unexplained by the model and could be due to random error or other factors not included in the analysis. We have since included this as one of the limitations of our study in lines 393-399.

In the sample size calculation section, it seems the formula for prevalence sample size calculation was used. I wonder what parameters were used to calculate the required sample size? What were the assumptions?

- The current study is a sub-study of a larger one (Reference 37) investigating non-adherence to cervical cancer screening recommendations among women in Eswatini. To estimate the proportion of non-adherent women in the target population, the larger study aimed for a sample size of 385 using a 95% confidence interval and a 5% margin of error for an expected proportion of 50% (formula: n = [p̂ × (1 - p̂) × z2)]/MOE2. While the current study aimed to recruit 385 women, only 377 consented to participate.

Decision Letter 2

Gulzhanat Aimagambetova

5 Mar 2024

Cervical Cancer Screening Knowledge and Associated Factors among Eswatini Women: A Cross-sectional Study

PONE-D-22-25805R2

Dear Dr. Phinda Khumalo,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Gulzhanat Aimagambetova

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

**********

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Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: (No Response)

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Reviewer #1: No

**********

Acceptance letter

Gulzhanat Aimagambetova

27 Mar 2024

PONE-D-22-25805R2

PLOS ONE

Dear Dr. Khumalo,

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PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    Attachment

    Submitted filename: Response to reviewers.docx

    pone.0300763.s001.docx (138.9KB, docx)

    Data Availability Statement

    In accordance with the ethical and legal requirements outlined in the Eswatini Health and Human Research Ethics Guidelines – 3rd Edition, the data supporting the study findings cannot be shared publicly. Data are available from the Eswatini Health and Human Research Review Board (prm2@ehhrrb.org.sz) for researchers who meet the criteria for access to confidential data.

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