According to the United Nations, contraception is a critical issue impacting 1.9 billion women of reproductive age. Worldwide, approximately 922 million women or their partners use contraception. More than half of all contracepting women rely on modern contraceptive products designed to be used by women. These female products comprise long-acting reversible contraceptives (LARCs), such as intrauterine devices (IUDs) and hormonal implants as well as short-acting methods, such as oral contraceptives, known as “the pill,” hormonal patches, vaginal rings, and contraceptive injections. Traditional methods such as withdrawal and calendar rhythm are relied upon by 7% of women, and the single most common contraceptive method worldwide is female sterilization (24%), an irreversible method [1,2].

According to data from the latest National Survey of Family Growth (2017 to 2019), approximately 27.5% of women of reproductive age in the United States use female contraceptive products, comprising oral contraceptive pills (OCPs, 14%), LARCs (10.4%) and other short-acting methods, such as contraceptive injections (2%), vaginal rings (0.8%), and patches (0.3%) [2]. With increasing levels of formal education, the prevalence of LARC and short-acting methods increases while the prevalence of female sterilization decreases [3].

While female contraceptive products are reversible and generally more efficacious than traditional methods, thus offering advantages to women with regards to their family planning and thus self-determination [1,4], they can be associated with unpleasant experiences [5,6], ranging from abdominal pain to mood swings or changes in libido [7,8]. The experience of such unpleasant side effects has a negative impact on a woman’s health, which the World Health Organization defines as “state of complete physical, mental, and social well-being,” and thus on the quality of life [9,10]. Furthermore, negative side effects are a major cause for poor adherence or even discontinuing contraception which may result in unintended pregnancies [11,12].

For women to find the contraceptive method that is most suitable for them and thus make informed contraception choices, it is important to have access to relevant information regarding different available contraception options. The type of information that women require can be assigned to 2 broad categories.

First, information relating to the efficacy of contraceptive methods regarding preventing unintended pregnancies and protection from sexually transmittable diseases is crucial [13]. There is comprehensive clinical as well as real-world data on efficacy and safety of different contraceptive methods [14,15]. These data are generally accessible to women through health care providers (HCPs) or nongovernmental organizations, although there are geographical differences on a global level [16].

Second, women seek information relating to potential unpleasant experiences related to contraceptive methods as these can have a substantial negative impact on women’s well-being, not only impacting women themselves, but also their families [13,17,18]. However, there are 2 major challenges women face when seeking information about potential negative experiences related to contraceptive methods, namely, the availability of data and the accessibility of reliable data [17].

Data on the frequency of negative side effects are generally available, as they are collected in clinical trials and stated on drug labels [19,20]. However, the construct of well-being is more nuanced, comprising a “state of positive feelings and meeting full potential in the world” [21]. Consequently, data on the mere occurrence and frequency of certain side effects provide insufficient information on how certain side effects typically impact well-being. For example, abdominal pain related to a contraceptive product might constitute a neglectable nuisance or a major suffering limiting women’s participation in daily life. Despite the subjective nature of side effect severity [22], for women facing contraception choices, knowing that a certain side effect can be a significant issue for some women constitutes relevant information [17]. However, there is a lack of comprehensive data on women’s subjective and collective unpleasant experiences with different contraceptive methods [23]. Studies have also shown that while women tend to turn to HCPs for contraceptive counseling, HCPs often lack relevant knowledge and provide insufficient information on potential side effects [24,25]. To learn about experiences with different contraceptive methods, women also tend to speak to relatives and friends, but these experiences are subjective and constitute a small sample size.

From this background, social media has started to play an important role as a source of information. Experimental research indicates that social media content may influence women’s intentions to use certain contraceptive products [26] even as social media conversations about contraception have become more polarized in the past 20 years [27].

Thus, there is a growing body of research to evaluate how women use social media to inform contraception choices [28]. To analyze information shared and consumed on social media, natural language processing (NLP) is used due to its capacity to analyze nonstructured, textual data.

For example, Pleasants et al [28] used NLP to study posts related to birth control on the US platform Reddit and found that “Side Effects!?” is the most common flair, a tag that users can attach to their post to categorize the content. Furthermore, “Experience” and “Side Effects?!” are the most common flairs among the most popular posts, based on the number of comments and “scores,” that is, upvotes minus downvotes [28]. Analyzing contraceptive content shared on X (formerly Twitter) Huang et al [29] discovered that a fifth of all the tweets relate to side effects. Similarly, in a text mining analysis of messages sent on a free sexual and reproductive health information service in Kenya, Green et al [30] found that users wrote most often about family planning and side effects. Balakrishnan et al [31] conducted an NLP-based social listening analysis in a German internet community and observed that side effects are the most common problem associated with most contraceptives. They also found that while the pill is the most frequently mentioned contraceptive method, there appears to be migration from hormonal to nonhormonal methods. In line with this, Felice et al [32] analyzed user reviews of a digital contraceptive supporting women in fertility prediction through a mixed methods approach involving NLP and found that the hormone-free aspect of the contraception experience is highly salient for many users. A content analysis by Pfender and Devlin [33] of YouTube vlogs discussing birth control methods revealed that social media influencers primarily described their discontinuation of hormonal birth control due to experienced side effects. Their study also showed that vlogs may provide inaccurate sexual health information, hereby directly or indirectly discouraging the use of the contraceptive under discussion. In a content analysis of the “sex secrets” Facebook page, Yeo and Chu [34] found that young people predominantly use this social media platform to request information, opinion, or advice, including the topic of birth control. Stoddard et al [35] found that more than half of the most popular contraception videos on TikTok revolved around patient experience. Although videos created by health care professionals received proportionately more views, over half of the total views were still of content generated by laypeople [35].

Overall, these NLP-based social media content studies show that social media is used to share information and consume information on contraception options. Furthermore, they reveal that user-generated content mostly revolves around side effects and that posts discussing women’s experiences with regards to side effects receive the greatest interest. At the same time, the content that is available, especially when shared by influencers, is not always reliable and may misguide contraception choices. In fact, there is increasing concern among researchers and women’s health practitioners that social media influencers spread misconceptions about contraceptive methods, particularly hormonal contraception, which negatively affect the acceptance of efficacious contraceptive methods and thus increase the risk of unintended pregnancies [36].

Furthermore, the previously mentioned studies highlight that unpleasant experiences are an issue that is currently not well-addressed in clinical contraceptive counseling. This further substantiates the observation that users appear to have an unmet need for reliable, trustworthy information. However, existing NLP-based studies do not provide a systematic picture of the association of different side effects with different available contraceptive methods and how severely women experience these side effects.

To fill this gap, the NLP method of sentiment analysis can identify, extract, and quantify the subjective emotions within a text, assigning a continuous sentiment score usually between −1 for highly negative and 1 for highly positive posts [37,38]. Studies using sentiment analysis may thus provide first hints as to how severely women experience certain side effects. Merz et al [27] studied population attitudes toward contraceptive methods over time by performing sentiment analysis on tweets on X regarding contraceptive methods and find that most tweets are negative. In their sample long-acting methods are mentioned more often than short-acting ones and related sentiments are twice as likely to be positive [27]. In contrast, in a study with Indonesian users of X, Sari et al [39] found that users predominantly express negative attitudes toward long-acting contraceptive methods.

However, a major limitation of sentiment analysis is that it can be inaccurate if the model has been trained on biased, limited, or unrepresentative datasets as it may fail to generalize well to diverse and nuanced language usage, such as sarcasm, slang, or cultural context variations present in social media posts. Although the modern state-of-the art approach in sentiment analysis involves using pretrained language models such as Bidirectional Encoder Representations from Transformers or GPT, there is an inherent risk of bias in general and gender bias in particular [40,41], limiting performance in sentiment analysis tasks.

In this context, the information on online drug review forums constitute a great, widely untapped, resource to inform contraception choices. Many online drug review forums contain 2 distinct pieces of information related to a product: a standardized numeric rating score indicating overall product satisfaction and a comment in free text form. A powerful advantage of online product reviews is that the integration of qualitative (text comments) and quantitative (ratings) data facilitates insights into the relationship between issues mentioned in comments and overall product satisfaction, which is presumably closely linked to the impact of the respective product on the well-being of the user.

Evaluating data from online review forums to inform decisions is hampered by several limitations, such as potential biases, unrepresentative sample issues, and the potential presence of inauthentic reviews. Nevertheless, consumer behavior in many industries, including health care and retail, indicates that other people’s reviews, particularly when available in large numbers, are important in driving purchase decisions and are thus considered a valuable source of information [42]. Thus, in the context of contraception, reviews data complement information on contraceptive options that women and their partners may receive from other sources, such as HCPs, community workers, scientific studies, or other social media sources.

This research aimed to produce insightful information from a large drug review dataset with regard to which experiences with contraceptive products women described on the web, both qualitatively and quantitatively. The focus is on unfavorable experiences, as previous research has shown that side effects are the topic of greatest interest for women using forums and social media to seek information on contraception.

From this background, in this paper, we investigated the following research questions (RQs):

Our study was performed on a dataset of 19,506 unique online reviews of birth control products in the United States posted on the website Drugs.com [43], a United States–based pharmaceutical information website, between April 2009 and September 2017. The reviews analyzed in this study were extracted from a comprehensive online drug review dataset available for research purposes in the University of California, Irvine (UCI) Machine Learning Repository [44]. The original dataset had been collected via web scraping from the website Drugs.com [43] and comprised 215,063 reviews of drugs treating different conditions, such as high blood pressure, cough, and birth control [45]. While this dataset may be somewhat dated, these reviews are highly relevant for this study. First, the products evaluated have been on the market for many years and are widely used today. Second, analyzing older reviews might even offer the advantage of capturing women’s experiences with contraceptive products in a more authentic, less skewed way. Research has shown that in recent years, social media influencers negatively frame hormonal contraceptives and encourage the uptake of nonhormonal options which may alter women’s attitudes and expectations [26] and thus possibly their online reviews.

The online drug user reviews contained information on the related condition, the name of the drug, a 10-star user rating on overall satisfaction, how many users considered this review helpful, and the date the review was posted. The name of the drug was captured in a structured format as it stemmed from a drop-down menu from which the website users needed to select a drug name when leaving a comment.

The study used publicly available data from the UCI Machine Learning repository. The UCI Machine Learning dataset did not contain any identifying information about the authors of the reviews, such as their username. Furthermore, when posting a review on the website Drugs.com [43], users were required to consent to the publication and use of their reviews. Finally, to the best of our knowledge, the reviews we selected to be in this manuscript do not risk reverse identification as the website Drugs.com [43] does not display full user names alongside the reviews. Therefore, in line with other studies evaluating social media posts on contraception, ethics approval for using these reviews as a basis for analysis was not deemed necessary.

Within the drug review dataset offered by the UCI Machine Learning Directory, 38,436 product reviews were classified as relating to “birth control.” Many reviews were captured twice, once under a product’s brand name and a second time under the name of the respective active pharmaceutical ingredient, that is, the generic name. By removing duplicates, we obtained 19,524 unique birth control reviews. When cleansing the dataset, we retained drug brand names for their greater detail compared to generic names. This granularity is more suitable for analysis, as products with the same active ingredient can vary in dosage and administration schedules across brands. In total, <400 out of 19,524 unique reviews did not contain a brand name, but rather only the generic name. We kept most of those reviews in the dataset, only removing 13 unique reviews of drugs that could not be related to 1 specific contraceptive method, namely, levonorgestrel (10 reviews), which can be a hormonal IUD or emergency contraception commonly sold as Plan B; and Provera (3 reviews), which can either be a birth control shot under the name Depo-Provera or an oral progestin product that is not approved as a contraceptive. The clean birth control dataset contained unique reviews on 169 different products identified by brand name or active pharmaceutical ingredients.

For later analysis and comparison of drug reviews for different contraceptive methods, we categorized all products into 11 contraceptive methods. This categorization focused on the application mode of these products, which is in line with the classification of contraception options typically used for advising women [46]. The methods comprise: hormonal and nonhormonal (ie, copper) IUDs, implants, vaginal rings, birth control shots, hormonal patches, spermicides, and emergency contraception. For OCPs, we distinguished between combined contraceptive oral pills (COCPs), progestin-only pills (POPs), and OCPs that induce a 91-day cycle, as these are expected to have different side effect profiles, and patients are typically counseled differently. Given the small number of reviews on emergency contraception (n=3) and spermicides (n=2), we removed those reviews from the dataset, too, leaving 19,506 reviews on 167 different products across 9 different contraceptive methods.

To analyze which negative experiences or side effects related to birth control options women described, we created a new attribute marking all reviews with a rating of ≤5 (on a scale from 1 to 10) as unfavorable reviews. Rather than limiting our analysis to reviews associated with strictly negative ratings (usually defined as ≤3), we deliberately used a wider window to also include negative to neutral ratings (scores of 4 and 5) as these might also contain relevant descriptions of unpleasant experiences. Overall, 8330 reviews fell into our definition of unfavorable (ie, nonpositive with a rating of 5 and lower).

Table 4 presents the 8 themes extracted from the 8330 unfavorable birth control product reviews in our dataset. Overall, each extracted theme corresponded to a description of side effects. There was no topic that explicitly alluded to nonhealth aspects such as cost, ethical or societal concerns, or accessibility. A total of 4 topics extracted were highly specific and related to “weight gain,” skin problems,” “loss of libido,” and “mental health problems.” Another 3 topics related to the impact of the contraceptive product on women’s menstrual cycle but alluded to distinct aspects, which we named “menstrual irregularities,” “cramps and pain,” and “continuous bleeding.” The final topic, “multiple cause dissatisfaction,” was a mixed, broad topic. It was the least distinct topic, comprising a mixture of diffused complaints ranging from headache, tiredness, general life, and relationship issues to a mere product warning. A sample review that scored high on the topic “multiple cause dissatisfaction” read as follows:

Table 5 provides sample reviews for each topic. More examples can be found in Multimedia Appendices 1 and 2.

For each topic, Table 4 also presents the share of online user reviews where this topic was dominant having the highest topic value in the topic matrix W. Thus, the dominant topic is the issue voiced most firmly in an unfavorable review. Table 4 shows that with this dominant topic modeling scheme, the reviews were relatively evenly distributed among the 8 identified topics. The rarest dominant topic was “weight gain” with 9.69% (807/8330) of the unfavorable reviews predominantly describing this side effect. “Multiple cause dissatisfaction” dominated in 17.92% (1493/8330) of the unfavorable reviews.

For each contraceptive method, Figure 3 shows the relative frequencies of the dominant topics in descending order according to average rating. For both copper and hormonal IUDs, the most frequent complaint by far was “cramps and pain,” which was the dominant theme in 38% (n=90) and 42% (n=355) of the reviews, respectively. For COCP, the most common complaints were “multiple cause dissatisfaction” (n=831, 21%) and “skin problems” (742, 19%). For POP and OCP that induce a 91-day cycle, “menstrual irregularities” were the most common issue (n=49, 21%, and n=49, 24% of reviews, respectively). For implants, as well as for hormonal shots, “continuous bleeding” (n=436, 21%, and n=61, 19%, respectively) was the most frequent problem described in the reviews. For hormonal patches and vaginal rings, the most frequent dominant topic was “multiple cause dissatisfaction” (n=57, 36% and 106, 36%). For hormonal patches, the second most frequently described dominant side effect prominently voiced in unfavorable online reviews was “skin problems” (n=28, 18%).

When reviewing the relative frequencies of dominant topics identified in Figure 3, it is important to remember that each contraceptive method was associated with a different proportion of unfavorable reviews. This was analyzed in the context of RQ 1 and is depicted in Table 3 which displays substantial variation in the proportion of unfavorable reviews across contraceptive product categories; with POP having the highest share of unfavorable reviews (n=232, 53.1%) and copper IUDs having the lowest share of unfavorable reviews (n=234, 29.3%). Scaling the relative frequencies of the dominant topics shown in Figure 3 with the overall share of unfavorable reviews of contraceptive methods displayed in Table 3, we find that for certain contraceptive methods, specific issues were very commonly discussed in online reviews in general, as in the following examples:

The final RQ relates to how severely such side effects might impact the well-being and overall quality of life of women. This approach is important for providing a balanced picture of the frequency numbers described earlier. Not every side effect, even if common, necessarily impacts overall well-being to the same extent. For example, individual reviews illustrate that “cramps and pain” might have a much more negative impact on overall well-being than menstrual irregularities. For illustration, a sample review with “cramps and pain” as the dominant topic read as follows:

While a sample review where menstrual irregularities were voiced read as follows:

Figure 4 displays boxplots of unfavorable ratings by dominant topic. The boxplots show that the frequency distributions for all dominant topic-based groups are left skewed. Consistently, the first quartile of ratings is a 1, that is, at least a quarter of all reviewers (2986 across all groups, ie, 35.8% on average) writing a nonpositive review submitted the lowest possible rating. The medians displayed in the boxplots as orange vertical lines range from 2 to 3. Only 3 dominant topics were associated with a median rating of 3, namely “menstrual irregularities,” “weight gain,” and “loss of libido.” For all other dominant topics, half of all unfavorable reviews have a rating of ≤2.

The mean ratings per dominant topic are represented as green star. On average, reviews predominantly describing menstrual irregularities have the highest average rating (mean 2.92, SD 1.53; 1223/8330, 14.68%). The next highest average ratings were in reviews describing weight change (mean 2.87, SD 1.52; 807/8330, 9.69%) and loss of libido (mean 2.84, SD 1.49; 963/8330, 11.56%). Conversely, reviews with the lowest ratings, on average, predominantly described multiple cause dissatisfaction (mean 2.34, SD 1.45; 1493/8330, 17.92%), cramps and pain (mean 2.39, SD 1.55; 926/8330, 11.12%), and continuous bleeding (mean 2.45, SD 1.47; 965/8330, 11.58%). Skin problems (mean 2.53, SD 1.49; 1051/8330, 12.62%) and mental health problems (mean 2.57, SD 1.48; 902/8330, 10.83%) had slightly greater ratings than the bottom 3 groups.

Our findings are in line with the literature evaluating how users, mostly women, use social media to discuss and evaluate different contraception options. Side effects were the most important area that was discussed online. Our NLP algorithm extracted 8 topics, of which 7 clearly describe a specific unpleasant side effect and only 1 less concise topic also encompasses other issues such as general life challenges, relationship issues, or product warnings. The algorithm did not extract any frequent words indicative of nonhealth related challenges such as cost and accessibility.

Our research extends the existing body of knowledge in several aspects. First, we found that in the online drug review forum, niche products tend to be overrepresented compared to their prevalence among the respective populations in the United States. For example, Table 3 shows that 22.52% (4392/19,506) of the reviews discussed hormonal implants. However, their prevalence among women using reversible contraceptive products (either LARCs or short-acting methods) is 7.3% [2]. Similarly, vaginal rings (827/19,506, 4.24% of reviews vs 2.9% in the respective population [2]) and hormonal patches (800/19,506, 4.1% vs 1.1% [2]) appear to be overrepresented. Even more interestingly, IUDs are substantially underrepresented. While 18.82% (3671/19,506) of contraceptive product reviews discuss IUDs, they are used by almost a third of women [2] using female contraceptive products.

The underrepresentation of IUDs might be attributable to the fact that on average, women tend to be more satisfied with IUDs than with other contraceptive products (Figure 2; Table 3). In general, people are more likely to write an online review when they have a complaint than when they are satisfied [52]. Nevertheless, in Figure 2 and Table 3, we observe that a substantial share of women report positive experiences with contraceptive products, ranging from slightly >70% (2589/3671, 70.52%) of favorable reviews for IUDs to 46.9% (205/437) for reviews of POP. Overall satisfaction with reviewed birth control products may be even greater if the probable negative bias inherent in online reviews is accounted for.

Our NLP-based evaluation of product reviews also offered valuable insights into how women experience different product-based contraceptive methods and how negative experiences relate to the overall satisfaction with the method.

In our exploratory study, we observe that, on average, women are highly satisfied with their IUDs. In fact, among all contraceptive methods, IUDs are given the highest average ratings on the drug review website (Table 3). This finding is corroborated by existing research indicating high satisfaction levels with this contraceptive method [56]. IUDs offer substantial advantages. The hormonal IUD is known for its ability to significantly reduce menstrual bleeding, with the 52 mg version being approved by the Food and Drug Administration in the United States for both contraception and heavy menstrual bleeding treatment. On the other hand, the copper IUD stands out as the sole nonhormonal choice that offers the convenience of not requiring action during each sexual encounter. Although both types of IUDs can cause undesirable bleeding-related side effects—typically breakthrough bleeding with the hormonal IUD and heavy periods with the copper IUD—these decrease over time [54,61]. We can reasonably assume that women opting for an IUD, which necessitates a medical procedure for insertion, would be well-informed and prepared for this.

However, our research indicates that for a limited group of women, IUDs appear to create major problems. Between 11.3% (90/800) and 12.37% (355/2871) of all written online reviews emphatically describe cramps and pain related to the insertion procedure or persisting pain. In fact, cramps and pain are the dominant topic in 41.9% (355/848) and 38.5% (90/234) of unfavorable reviews of copper and hormonal IUDs, respectively (Figure 3). We also see that, on average, the ratings of reviews where cramps and pain are the dominant topic are the second lowest, occurring only slightly above multiple cause dissatisfaction (Figure 4). This observation has substantial implications for IUD counseling practices. Although physicians typically inform women about the potential side effects of IUDs, our findings underscore the necessity for health care professionals to provide even more comprehensive counseling regarding the risk of temporary as well as lasting cramps and pain, which heavily hampers women’s well-being, and to offer pain control options for the insertion procedure.

Our study is subject to several limitations. First, the reviews and ratings in online forums may exhibit bias, often skewing toward negative experiences, and there may even be a risk of fake reviews. Consequently, our dataset may not accurately represent the broader population of women using birth control products. Nonetheless, this limitation does not detract from our study’s objective, which is to illuminate the experiences with different contraceptive methods women share on a drug review website. This study was intended to supplement traditional qualitative but informal information sources used by women and their partners. Consequently, our extensive analysis of nearly 20,000 online reviews arguably offers a more representative and robust overview than anecdotal evidence gathered from conversations with friends and family regarding birth control options. All the same, we note that the reliance on data from a single source (ie, the website Drugs.com) may introduce a bias. This could affect the findings. Although the drug review dataset dates from 2009 to 2017, reviewers might have already been influenced by social media influencers, who are increasingly expressing concerns about hormonal contraceptives, sometimes inflating the severity of side effects [36], and advocating for nonhormonal methods. Furthermore, the dataset only contains reviews of products. As such, natural contraceptive methods, such as calendar rhythm and withdrawal are not covered. Performing the NLP and sentiment analysis on other contraceptive product review websites could enhance the breadth and robustness of our findings but is outside the scope of this analysis.

Second, our categorization did not stratify by dose or regimen timing (eg, 21 vs 24 active pills) due to insufficient review information (eg, Loestrin could refer to multiple different products with the same active ingredients in different doses and durations), nor by progestin type to avoid small group sizes.

Third, there are important limitations inherent in the topic modeling of birth control product online reviews. While topic modeling offers valuable insights, it is crucial to acknowledge its constraints so that they can be addressed effectively in future research. One of the primary limitations is the subjectivity involved in choosing the right number of topics. In addition, topic modeling may not adequately capture rare or nuanced topics. In our study, which identified 8 topics, we observed 1 particularly ambiguous topic, “Multiple cause dissatisfaction.” This topic is frequently associated with vaginal rings and hormonal patches and occasionally encompasses other topics, potentially obscuring the clarity and precision of our overall results. Conversely, our algorithm effectively differentiates between “menstrual irregularities” and “continuous bleeding,” despite their similarities. Notably, women experience “continuous bleeding” as more problematic than “menstrual irregularities.” However, due to the overlap in these side effects and the associated words, some reviews scored highly for both topics.

Another limitation in topic modeling is the potential ambiguity in allocating reviews to specific topics, which stems from the inherent challenge of accurately capturing the thematic essence of the text. For example, a word such as “skin” in an unfavorable review does not necessarily imply a discussion about skin-related problems. Furthermore, one review may describe several topics or side effects (Multimedia Appendix 2). Thus, analyses that are based on reviews grouped by dominant topic may not fully reflect other potentially confounding aspects.

Despite these challenges, our analysis suggests that using TF-IDF and NMF for topic modeling with 8 topics is the most effective approach. In this setup, most topics, apart from “multiple cause dissatisfaction” and the occasionally intersecting “menstrual irregularities” and “continuous bleeding,” are well-defined by distinct symptom sets, differentiating them from others. The process involved careful consideration of both the interpretability and the distinctiveness of each topic.

Finally, given the exploratory nature of our study, we did not engage in statistical significance testing; consequently, we could not definitively determine whether the observed differences in contraceptive method ratings are systematic. This study was primarily descriptive and does not involve inferential statistical analysis or controlling for confounding variables. We also did not investigate potential interactions between different side effects, such as whether reports of mental health issues could lead to more negative evaluations of other symptoms. The suitability of the dataset for inferential statistics is questionable, as it does not meet several crucial assumptions for significance tests, such as normality, homoscedasticity within groups, or independence of observations.

In summary, our findings provide semiqualitative insights, highlighting the occurrence of certain side effects in the real world and how they are associated with online contraceptive product ratings. A deeper understanding of effect sizes, relationships, and causality requires further research.

This study contributes to the understanding of how contraceptive methods impact women’s overall well-being, as interpreted from a large corpus of online user narratives. Our findings provide a complementary perspective to those derived from clinical trials or the adverse effects documented in pharmaceutical labels and package inserts. By leveraging NLP to analyze user reviews, we aimed to support women in choosing contraceptive options that are not only safe and effective but also reduce the likelihood of specific symptom clusters that could negatively affect their quality of life.

For instance, women seeking contraception may have specific concerns, such as potential effects on libido, skin health, or menstrual regularity. While no contraceptive option is completely free of side effects, it is crucial that women have access to information that enables them to make informed decisions about which side effects they are prepared to accept, guided by the experiences of others. Accordingly, our analysis empowers women to benefit from the collective insights and experiences of a large user base, supporting more informed decision-making. In addition, this information aids HCPs in offering personalized advice to women and their partners.

A key observation from our study is that all female contraceptive methods reviewed online are associated with a substantial percentage of negative ratings. Notably, no contraceptive method to be administered by women received <29% unfavorable evaluations. This finding underscores a significant opportunity for enhancement in the realm of female contraception. The objective for manufacturers would be to innovate and develop contraceptive methods that exert minimal or no negative impact on the well-being and quality of life. In light of this, there is a recent trend toward natural or calendar-based methods sometimes supported by digital cycle tracking tools. Depending on individual life circumstances and personal beliefs, these methods may constitute a viable alternative for some women despite the inherent risks resulting from use failure (the website Drugs.com [43] provides a comparison of efficacy and typical use failure rates). Greater awareness of the side effects of contraceptive products for women could guide couples in making joint decisions about contraception and a more equitable sharing of responsibilities by considering more options. A secondary insight from our study is that dissatisfaction was particularly common for contraceptive products that may result in irregular or continuous bleeding, especially when users may have expected reduced or absent menstrual bleeding. IUDs are generally rated more positively than other methods, although about 1 in 10 users report severe cramps and pain which are linked to very poor ratings.

In conclusion, a pivotal element of efficacious reproductive management is the provision of comprehensive information to women regarding the potential side effects of contraceptives and their likely impact on overall well-being and quality of life. Advancements in artificial intelligence in general and NLP in particular can help in extracting, aggregating, interpreting, and sharing this information. In a broader context, the empowerment of women to manage their reproductive health is acknowledged as a fundamental catalyst for economic advancement and the achievement of personal and professional aspirations, as emphasized by organizations, such as the United Nations, the World Health Organization, and the Organisation for Economic Cooperation and Development. Moreover, female sexuality transcends the dimensions of reproduction and birth control, encompassing aspects of pleasure and human connection, thereby enhancing overall well-being [62]. Access to suitable contraceptive methods and thorough information about these options are vital in facilitating this empowerment.