DOI: 10.31038/AWHC.2022522

Abstract

The paper presents a deep reanalysis of the response by consumers to pricing and emotion messages from 30 parallel studies of non-perishable products. The nine pricing and the nine emotion messages were approximate the same across the 30 products. Considering the results from 3656 respondents for pricing, and separately for emotion, revealed the exists about 2-3 new mind-sets, appearing across each of the 30 products. The ability to study judgments of pricing statements separately from judgments of emotion statements provides an increased power of research to more deeply understand the thoughts and feelings of ordinary people in ordinary situations. The implementation demonstrated successfully by the project, ‘Buy It!’ using Mind Genomics suggests the simplicity of creating a database of the mind across products, genders, ages, even cultures, and times, with the data easy to acquire, analyze, and apply.

Introduction

The topic of shopping consumes the attention of researchers, especially market researchers, consumer psychologists, economists, and occasionally occupies clinicians who are called in to deal with dysfunctional behavior involving shopping, especially compulsive shopping [1]. A great deal of the work is from the top down, looking at behavior, tabulating what people like about shopping, about products, and so forth. For the most part, the research focuses on the product, primarily because it is the focus of the marketer of products to sell the product. Whatever can be culled about the shopping situation is of interest to the product marketer, especially when that specific information helps ‘move product.’

Shopping as a behavior attracts a number of disciplines because it represents a fundamental set of behaviors necessary for survival, and an integral part of civilized life. The literature of shopping spans disciplines ranging from focus on the unconscious motives of people [2], to the behavioral economics involved in price [3-6], to the art and science of advertising, and onto the design of the shopping environment, and the observation of people shopping from the point of view of anthropology [2,7-11].

The consumer researcher working in an applied setting is not to be left out of this world. Companies which manufacture products and which offer services are interested in the process of shopping, to understand the way people think, or in today’s parlance the ‘shopper’s journey.’ One need only look at conferences today, many of them sponsored by organizations involved in for-profit consumer researcher, to discover the way companies use different research methods to provide so-called ‘shopper insights [12]. One will come across virtual shopping, a technology going back more than three decades [13], where the store can be set up. One will come across shop-by’s, wherein a researcher will accompany the shopper, asking questions at strategic points. Or one might well encounter eye tracking devices, which measure where on the shelf the shopper’s eyes alight [14,15].

At the most general levels are questionnaires, surveys about the shopping experience. These questionnaires can be of the most general kind, instructing respondents to rate the importance of different aspects of shopping, although such approaches seem to be quite general, and hard to deal with in an abstract situation. If questionnaires and surveys seem too abstract one need only wait, visit a store or a restaurant, to be bombarded later by questionnaire about how was the experience, as stores restaurants, even hospitals and physician’ office attempt to become smarter about the ‘purchaser.’

The Contribution of Experimental Design and Mind Genomics to the Understanding of Shopping

A key issue in research is what is important to the shopper. The question sounds easy, but deceptively so. When one talks about ‘what is important,’ one is requiring the respondent to abstract from a lifetime of experience to provide one number. The typical answers for ‘what is important to you’ are such generalities as price, assortment, product quality, product price, product reliability, convenience of shopping, and so forth.

The reality is that such questions as ‘what is important’ are hard to answer. The difficulties come from different sources. The first source is that it is hard to abstract an experience and rate it. It’s one thing to ask, ‘how much do you like oranges,’ or some other food product. That is pretty easy to answer, although the reality is that the respondent has to call up into memory the orange, and the last time the respondent ate the orange. Once the respondent has eaten an orange and remembers it, the rest is easy. The difficulty occurs when we move from a simple situation, remembering an orange, to the more amorphous situation of shopping for something. Shopping for an item is not like eating the item, in the most direct 1:1 comparison. For example, it may be straightforward to ask, ‘how much do you like eating an orange?’ It is much more difficult, and involves many more subtleties when the question is ‘how much do you like shopping for oranges?’. Furthermore, it’s fairly straightforward to ask a person about the degree to which a person likes or dislikes different aspects of oranges (or a specific orange), such as appearance, aroma, taste/flavor mouthfeel, etc. It’s far harder to answer that question about liking the different parts of the shopping journey for an orange.

The published data, but even more so the private data in the hands of companies, tell us a lot about the shopping experience. Most of the information can be categorized as ‘outside-in.’ That is, we ask the respondent to tell us what is important, or we infer importance by observing behavior. Occasionally, we may ask the respondent to describe the experience in his or her words, exercises which produce so-called ‘verbatims’, or records of the experience of shopping from the mind of the shopper, ask to describe what is happening during the experience. Often this is the richest kind of data because it gives a sense of what the respondent is thinking.

As a prelude to this paper, and the approach discussed in detail, let us begin with the some of the data that the study provides. We do so by putting the study in perspective. The respondent who began did so by selecting a product from a set of 30 products. We thus know that the respondent was interested in the product at some level. The respondent evaluated 60 different vignettes about the shopping experience. Afterwards, the respondent completed a self-profiling vignette. Question #8 presented the respondents with 26 factors, such as appearance, price, et al. The respondent was to check off three of the 26 elements which were deemed most important in the shopping experience.

Table 1 shows the distribution the 12 most aspects of shopping to the respondent. What is important about the numbers in Table 1 is that they allow us a sense of what the respondent feels to be important. What is troubling, however, is the lack of psychological depth, a lack of meaning, other than the most general. There is nothing to connect the term with the shopping experience. It is for that reason that we present an analysis of both shopping and emotional responses to the shopping experience, and determine how these more contextualized, elaborated phases, apply to the shopping experience.

Table 1: Factors that are deemed important to shopper, overall, by gender, and by age. The product data are arranged in descending order by appearance.

A good analogy is the difference between the plot of a novel or play, and the way evocative language brings the plot to life, engaging the reader. It is this ‘bringing the plot to life’ or the letter the mind ‘talk a bit’ in richer language that is the objective of Mind Genomics. The results are both a database and a richer comprehension of the inside of the mind revealed by the pattern of a person’s thought through Mind Genomics cartography, a simple experiment.

Mind Genomics, What it is, Where it Comes from, and How it Evolved to the It! Studies

The original research efforts upon which this reanalysis and paper is based came from pioneering research efforts using Mind Genomics experiments (cartographies) to study how people responded to what makes a shopping experience ideal for them. The project was funded by the University of Indiana. The goal was to create a way to understand the inner mind of a shopper, using experimental design and the (then) newly emerging research approach, first known as RDE (rule developing experimentation) [16], and then known as Idea Map, and finally as Mind Genomics.

The guiding rationale for Mind Genomics is that people respond best to contextualized combinations of ideas, and not to single ideas alone. We are dealing with people, and their evaluation of different representation of ideas that they would encounter in their daily life. Thus, in the world-view of Mind Genomics, the optimum research approach is to combine ideas into vignettes, so that the respondent evaluates a description closer to everyday reality. It seemed quite appropriate to study the mind of shoppers using this method. The key issue was what the stimuli would be to uncover the shopper mind, or more correctly to define what should be measured to uncover the shopper mind.

Mind Genomics creates combinations of messages, combinations of elements, and these elements telling somewhat of a story. The elements are phrases which describe the product or the service. The combinations are called vignettes. Typically, in a Mind Genomics study, the topic is first chosen, and then a set of questions posed. These questions ‘tell a story,’ or at least attempt to give different facets of the topic. Each question becomes the impetus to generate answers, these answers providing specific information about the shopping experience. It is the structured analysis of this type of data which allows Mind Genomics to generate a description of what might be going on in the mind of the shopper.

The next sections below will present the Buy It! project in more detail. Right now, it important to understand the world view of Mind Genomics, its history, and its modification to create the It! studies. These It! studies were developed in a pioneering effort to understand the world of consumer decision making, here for the shopping experience.

The emerging science of Mind Genomics as founded in the 1990’s, combining statistical design of ideas and consumer research, inspired by the pioneering effort of Wharton professors, Paul Green and Yoram (Jerry) Wind. The scientific power and practical applicability of conjoint measurement were to demonstrate themselves in those who used the conjoint methods to study shopping behavior [17].

Looking back a 50-year history, it is abundantly clear that most of the studies ended up being ‘one-off’, half the published paper discussing method, half the study discussing the actual topic results and implications. The studies themselves ranged across many aspects of human behavior, from products to services to even beliefs. The fascination with understanding human decision making through these tools was obvious, but left behind was the untapped potential of creating a database of the mind, using conjoint measurement.

During the early years of the 21^st century, author Moskowitz and colleagues at the Understanding and Insight Group, Inc., became interested in creating a large-scale database on topics, using Mind Genomics [18]. It was to address the opportunity of a larger-scale data of the mind which prompted the creation of an approach known as the It! Studies. The approach, developed by the late Hollis Ashman and Jacqueline Beckley of the Understanding and Insight Group, together with author Howard Moskowitz, would put together a group of related studies, studies with similar underlying structure. The major difference among the studies would be the topic. The minor differences would be the specific wording pertaining to the topic.

In the specific studies, each respondent evaluated a unique set of combinations, the vignettes, the messages created by experimental design. Each respondent would rate a unique set of 60 vignettes, rating each vignette on a common scale for the entire set of studies, and all the vignettes. The rating scale would be something: How well does this vignette describe your ideal shopping experience, 1=Not at all … 9=perfectly. In other studies, such as dealing with emotional stressful issues (Deal With It!), the rating scale might be something like ‘How do you feel about this? 1=Can deal with it … 9=Cannot deal with it.’ These are not the actual words, but they give a flavor of the way the rating scale was designed.

The focus of the rating scale was on the degree to which the vignette described something in the mind of the respondent. The assumption was that the respondent may not be able to describe what she or he feels or is thinking, but can recognize it when presented. Psychologists have often reported that recognition memory is easier than reproduction memory [19].

Thus far we are dealing with a new form of test stimulus, a systematically varied set of combinations of answers to questions. Each respondent evaluates a different set of combinations, so that the Mind Genomic experiment covers more of the possible ‘space’ than would any conventional approach. It is with this approach then that the researcher can explore the way people make decisions in the world of the normal, the quotidian, the everyday, such as shopping.

The Buy It! Studies

The It! study reported here deal with the mind of the shopper, for durables, viz., non-perishable items. Figure 1 shows the 30 topics. The goal was to understand how people react both to the product, and to the nature of the store. It is the latter topic, which is of interest here, specifically how people respond to the store based upon what it announces about its pricing, and the shopping experience to be expected.

Figure 1: The 30 products, shown as a wall to the respondents, who would choose the product of interest to them.

Step 1 – Select the 30 Products

Figure 1 shows the 30 different products that were studied, each product the subject of a separate Mind Genomics cartography, in which the respondent would evaluate different vignettes (combinations of statements about the store, for a specific product). Figure 1 is called the ‘wall’. The respondents who agreed to participate were able to choose a product that interested them. When the ‘quota’ for the product was filled the product ‘disappeared’ from the wall. Once again, the purpose was not to present a method, nor to study one topic in depth (viz. one product), but rather to create an integrated database across many respondents and non-perishable products.

Step 2 – Choose the Raw Materials (Elements) that would be Later Incorporated into the Study

The objective of the It! studies was to create a database whose elements could be compared to each other. The strategy to create the raw materials begins with asking questions, here four questions, and providing nine answers to each question. This so-called 4×9 design was the one use for all It! studies, generating36 elements.

The elements had to be particularized for the specific product. For example, many of the elements for ‘candles’ would not be appropriate for ‘sandals’ nor for ‘cars. Yet the form of the element could be maintained. Figure 2 shows the nature of the four questions. Table 2 presents the full set of answers in shortened form, both for Question 2 and for Question 3, respectively. The elements in Question 2 (Service, pricing scheme) and Question 3 (emotional benefits) were most similar across the 30 products, and did not need particularization. It will be the results from Question 2 and Question 3 which will constitute the data from which the analyses in this paper are drawn.

Figure 2: The structure of the four questions, and the nature of the answers to the questions.

Table 2: The topics of the Questions B (Price) and C (Emotion).

Step 3 – Combine the Element (Answers) from the Four Questions into Small, Easy to Read Vignettes

The objective of the Mind Genomics effort is to identify the degree to which each of the 36 elements drives the feeling that the element contributes to the person’s ideal shopping experience. Rather than asking the respondent to check off different words or simple, colorless phrases as being important, Mind Genomics deduces the importance of richer, more evocative phrases, but does it in a more subtle, more ecologically meaningful way. A potentially more productive way combines phrases such as the answers from Questions 1-4, creating vignettes, combinations. The respondent is present with combinations, one combination at a time, rating how well the experience described by the combination of phrases (elements) in the vignette matches the person’s ideal shopping experience. People are accustomed to combinations of features in life, not to single ideas. The task becomes simply to match scale values to compound sets of messages.

The task may seem hard, but once the respondent gets accustomed to the fact that the vignette comprises disconnected phrases, the respondent seems to have no problem rating the combination. Of course, when asked the respondent will say that she or he did not know the ‘right answer,’ was just guessing. Yet the results will show clearly that the respondent was paying attention to the individual features. The story, the vignette, the combination was just there to present something that was realistic in its moderate complexity, preventing the respondent form gaming the system.

The actual combinations of the elements are prescribed by an underlying experimental design, a recipe book of combinations. Although the combinations may be thought of, and even described as random, nothing could be further from the truth. The 60 vignettes prescribed by the design allow each of the 36 elements to appear equally often, and ensure that the 36 elements are statistically independent of each other. The design prescribes combinations comprising 2-4 elements, at most one element or answers from each question, but often no element from either one or from two of the four questions. It is this particular arrangement which allows the researcher to estimate the relation between the presence/absence of each of the 36 elements and the rating (or more correctly the transformed rating). The method for estimation, OLS (ordinary least-squares regression) is perfectly adapted to work with experimental designs.

One more feature of the design is worth noting and emphasizing, the permuted design [20]. The family of permuted designs comprises designs which are mathematically the same, but whose combinations differ. Permuted designs, pioneered by the author and Alex Gofman, in the late 1990’s) ensures that there could be 200 or so different sets of combinations. The researcher using Mind Genomics need not be ‘right’ in the selection of the 60 vignettes, a frequently-encountered problem in conventional research. Rather, the Mind Genomics approach allows exploration of many different combinations. With 100 respondents, the Mind Genomics design ends up testing 100×60 or 6000 different vignettes, 6000 different combinations. Even when there is a great deal of ‘noise’ around each of the 6000 combinations, the pattern underlying the data is generally well-revealed by working with the 6000. Thus, Mind Genomics sacrifices the standard practice of narrowing vision but increased precision within that vision, abandoning that approach to the heretical but ultimate more success approach of broad view, less precision at any point, but ultimately far more precision when the grand pattern is encountered.

Figure 3 shows an example of a vignette the way the respondent would see it. The elements or answers are placed one atop the other, centered, with the rating scale on the bottom. The result is a format easy for the respondent to inspect and visually graze. The respondent may find this strange at first, but eventually the respondent looks at the vignettes, and almost automatically assigns a rating. The respondent generally does not pay much attention to the task, nor is the respondent asked to do so. It suffices that the respondent moves through the evaluation. One can always test for randomness at the level of the individual respondent by computing the goodness of fit of the individual models to the data [18].

Step 4 – Acquire the Ratings, Transform the Ratings to a Binary Scale, and Create the Equations on a Respondent by Respondent Basis

Step 4 constitutes the heart of the data preparation. The Mind Genomics program creates the combinations for each respondent as prescribed by the specific permuted variation of the experimental design, presents the combination on the screen, acquires the rating, and then moves to the next screen. The process is quick, allowing the respondent to rate a vignette almost every 3-4 seconds. The respondent rates each of the 60 vignettes on a 9-point rating scale, shown in at the bottom of Figure 3.

Figure 3: Example of a three element vignette for exercise equipment. This vignette would be presented to one of the respondents choosing the Buy It! study dealing with exercise equipment. It is quite likely in the order of things that this vignette would be presented to only one respondent.

As attractive as the Likert scale of nine (or fewer points) may be, most users of research data do not find it straightforward to interpret the meaning of the scale. The attractiveness of research is greater when the user can see a story. Most users of research prefer answers couched in the ‘yes/no’ mode, viz., that the answer suggests one group (yes) or another group (no), what the topic may be. That binary thinking should be reflected in the data. To do so the Mind Genomics convention for 9-point scales converts ratings of 1-6 to 0 to denote no/low, and ratings of 7-9 to 100, to denote yes/high. To each converted rating is added a vanishingly small random number (< 10^-5), which ensures some minimal variation in the ratings. That minimal variation will prevent statistical issues in the regression analysis, but will not affect the data in any material fashion. The benefit will be results far easier to understand and to interpret.

Step 4 Generates a Database of Data, Comprising these Specifics

a. Each row in the database corresponds to one vignette rate by a respondent. Therefore, by design each respondent generates 60 rows of data.

b. The first few set of columns provides the name of the product being studied, the unique identification number of the respondent, and the order of evaluation (from 1 to 60)

c. The second set of columns, totaling 36, corresponds to the 36 elements. Each of the 36 elements is associated with a column. When the element is present in the vignette, the cell is given the value 1. When the element is absent from the vignette, the cell is given the value 0.

d. The third set of two columns corresponds to the rating assigned by the respondent, and the transformed rating. As noted above, ratings of 1-6 are transformed to 0, ratings of 7-9 are transformed to 100, and a vanishingly small random number is added to the transformed number.

e. The remaining columns are given over to a set of self-profiling classification questions, comprising questions about WHO the respondent is, how the respondent FEELS about shopping, and so forth, what are the CRITICAL ASPECTS of the product, etc.

f. The OLS (ordinary regression analysis) is conducted at the level of the individual respondent. At the start, the data base comprised 3967 respondents. The database was reduced to 3656 individual respondents who showed some variation across the 60 vignettes, with at least three vignettes assigned 100 when the rest were assigned 0, or vice versa. The equation for each respondent is: TOP3 = k₀ + k₁(A1) + k₂(A2) … k₃₆(D9). The OLS equation can be done in a straightforward fashion because the set of 36 vignettes were created for each respondent according to the basic experimental design (4×9), which was then permuted to change the specific combinations.

g. The final database for subsequent analyses comprised the set-up information (respondent identification number, product covered by the study, a column for the additive constant and 36 columns for the elements, followed by the columns of classification information, based upon the answers provided by the respondents in the self-profiling classification questionnaire. The respondent completed that questionnaire after finishing the evaluation of the 60 vignettes. The self-profiling classification questionnaire was identical across all 30 products, and all 3656 respondents.

Step 5: Focus on the Two Silos, Question B (price), and Question C (emotion), as well the Self-profiling Classification

The analysis focuses only on the elements which are applicable to the shopping experience recognizing that some of the elements were slightly modified to make ‘sense’ in the context of a vignette. The relevant results appear in Table 2 (nine elements focusing on price), and Table 3 (nine elements focusing on emotions).

Table 3: Performance of the nine elements for Price (Top) and Emotion (Bottom).

A Mind Genomics cartography produces an extraordinary, occasionally overwhelming amount of data. Fortunately, there are no hypotheses to be discussed, nor detailed implications based on the limited set of data. Rather, with 30 studies, we are looking for emergent, easy-to-visualize results, and in the words of the market researcher of today as of this writing (winter 2022), ‘data which tell a story.’

Step 6: Look for Patterns

Our basic data are the coefficients in aforementioned regression analysis, done for each respondent separately. We are not going to focus on the additive constant, but rather focus only the magnitude of the 36 elements. These 36 coefficients tell us the degree to which the individual element drives the response to the similarity of the description to one’s the ideal shopping experience (rating 7-9). Thus, one can assume that each of the 36 regression coefficients shows the degree to which the specific element ‘drives’ the response toward describing the ideal shopping experience, presumably for that product.

The regression analysis is done on a respondent by respondent basis. Our first step in the search for patterns is to replace all coefficients less than+ 10 by a blank in the database. The coefficient +10 corresponds to a statistically significant coefficient in the OLS regression. From other studies, coefficients around +10 or higher suggest that the element is an important element.

Having now eliminated all coefficients lower than +10, we replace the remaining coefficients with the number ‘1’, simply to denote that for the element and for the respondent, the element is statistically significant. Now it is time to prepare the data in a way that will make it easy to discern patterns. We work according to the groups, the groups being defined by the total panel, by self-stated demographics, beliefs, and behaviors, as well as by the study. The strategy is to count the number of individuals who generate a coefficient of +10 or higher for a specific element, and then divide that number of individuals by the total number of individuals in the group.

Table 3 shows two sets of data, for the total panel, the top set corresponding to the percent of times across the total panel of 3656 that the element generated a coefficient of +10 or higher for the pricing elements (Elements B1-B9, in ranked order by total). The bottom set, in contrast shows the percent of times that the element generated a coefficient of +10 or higher for the emotion elements C1-C9, in ranked order by total). To review before the details, the percentages in Table 3 are obtained by dividing the number of coefficients of +10 or higher by 3656, corresponding the number of respondents in the group labelled ‘Total’. To help the pattern emerge more clearly, we have shaded all percentages of 40% or higher. This strategy allows the pattern to jump out at us.

Price: Three key elements drive strong positive reactions

B1 the right place

B4 Extras: Great deal on suggested retail price

B2 Self-serve

Emotion: Only one key element drives strong positive reactions

C3 Come in anxious, leave happy… even though you may have spent a lot of money.

The paucity of strong performing elements may mean either that these elements are not critical, especially ‘emotion’ elements, or that the differences among the groups are more likely to emerge from the individual groups.

Step 7 – The Surprising Similarity of Self-defined Subgroups

One of the continuing findings in Mind Genomics is the similarity of patterns of response across subgroups, these subgroups being defined by the respondent. The subgroups may comprise individuals who are of the same gender, age, education, income. The subgroups may comprise individuals who describe their behaviors in the same way, e.g., the number of people with whom they shop. Or the subgroups may comprise individuals holding different values, such as what is important to them.

In the Buy It! study with the 30 products the respondent completed an extensive self-profiling classification questionnaire, covering geo-demographics, beliefs, and behaviors. Sometimes this is called an A&U study (short for attitude and usage), or a habits and practices study. Do these groups differ in the patterns of elements that they find important? Once again our focus is on the percent of respondents in a group who find the element to be important, viz., the coefficient for the element is +10 or higher for the individual respondent.

Table 4 presents the percent of respondents showing strong coefficients (+10 or higher) for each of the nine price elements, for each defined group, based upon the self-profiling classification. Table 4 is the first of the two tables showing the relation of self-defined groups to responses emerging out of the Mind Genomics experiment Table 4 need not be dissected any further than a quick note to observe that for the most part, three of the nine elements account for a vast majority of the strong performing elements.

Table 4: Percent of respondents in self defined groups who generate strong coefficients for each of the nine PRICE elements (B1-B9). The nine elements are sorted by the percentage shown for the total panel.

B1 The right price

B4 Extras: Great deal on suggested retail price

B2 Self-serve

There are some outliers, such as element B7 Extras: Inexpensive extras, for the couch. refrigerator, and washer, respectively.

Table 5 presents the same analysis, this time for the nine elements (C1-C9) talking about emotions experienced during shopping. Only one element show strength:

C3 Come in anxious, leave happy… even though you may have spent a lot of money

Table 5: Percent of respondents in self defined groups who generate strong coefficients for each of the nine EMOTION elements (C1-C9). The nine elements are sorted by the percentage shown by the total panel.

Step 8 – Uncover Mind-sets for Price and for Emotion, respectively

Previous analyses of Mind Genomics data focused on the entire set of elements tested, rather than focusing on the elements of one silo. The regression analysis would be done on all of the elements, and the reporting would be done on the analysis emerging from all of the coefficients.

The It! studies make such a grand approach difficult. The elements for Questions A and D have been so ‘particularized’ for the product being studied that it makes little sense to work with the coefficients AFTER the regression analysis has been done on all 36 elements. That is, it makes statistical sense to incorporate A1-A9 and D1-D9 into the analyses, estimate their values, as well as estimating the values of B1-B9, and C1-C9, respectively. Afterwards, however, when A1-A9 and D1-D9 have served their purpose in the estimation of values of the 36 coefficients and the additive constant, it makes sense to discard them.

The focus for last new analysis is on two separate sets of data, coefficients B1-B9 on price, and then coefficients C1-C0 on emotion. This last analysis will work with the two data sets separately, for all respondents, and for each data set generate three new mind-sets, using k-means clustering [21-23].

Clustering in Mind Genomics is a way to divide the respondents into groups based upon the pattern of numbers generated by each respondent, using as a basic a metric of ‘distance’ between pairs of respondents based upon these numbers. For this study, and for each clustering exercise (price, emotion, respectively), the distance between all pairs of the 3656 people was computed based upon the Pearson Correlation. Each respondent generated nine coefficients, say for Price. The ‘distance’ between every pair of respondents was operationally defined as (1-Pearson correlated, based on the 9 pairs of coefficients). The distance measure used a well know statistic, the Pearson correlation or Pearson R. When two patterns are identical, the Pearson R is +1. The distance should be zero, because they show the same pattern. (1-1 = 0). When the patterns are exactly opposite the Pearson correlation, Pearson R, becomes -1, and the distance becomes (1 – – 1), or 2 based on the magnitudes of the nine corresponding coefficients. The measure of distance is defined as D = 1 – Pearson Correlation. The Pearson Correlation, R, takes on the value +1 when two sets of items are perfectly related to each other. When R is 1, the distance is 1-R, 1-1, or 0. The Pearson Correlation r takes on the value blue -1 when wo sets of items are perfectly inversely related. The distance is now 1- -1 or 0.

The story for pricing, Question B, is quite different when we move from the total panel to the three mind-sets. (Note that the number of mind-sets is left to the discretion of the researcher). We choose three mind-sets as a number which often proves to the few numbers of mind-sets to reveal interest and interpretable patterns (Table 6).

Table 6: The performance of elements emerging three mind-sets based upon price (Question B, Silo B).

Mind-Set MSB1 – Fast, easy buying, no price concerns

B2: Self Service; B1: The right price; B4: Extras: Great deal on suggested retail price.

Mind-Set MSB3 – Wants to be pampered, presented with good products, and will pay for it;

B9: Personalized service: Helpful staff; B8: Higher quality brands and services: Designed brands; B1 The right price.

Mind-Set MSB2 – Nothing stands out, almost indifferent to everything.

The story for emotion, Question C (Silo C), is also quite different when we move the total panel to the three mind-sets. We see differences among the three mind-sets based elements C1-C9 (Table 7).

Table 7: The performance of elements emerging from three mind-sets based upon emotion (Question C, Silo C).

Mind-Set MSC1: Simply interested in hassle-free shopping

C2 Lets you get your shopping done quickly

C3 Come in anxious, leave happy… even though you may have spent a lot of money

Mind-Set MSC3: Hassle-free (like MSC1) but also a bit of a seduction for repeat shopping

C2 Lets you get your shopping done quickly

C3 Come in anxious, leave happy… even though you may have spent a lot of money

C5 Such a good experience you will come back for more

Mind-Set MSC3: Shopping is therapy

C7 When you are down, shopping lifts you up

Table 8 presents the performance of these strong performing elements in mind-set by key subgroup. What becomes quite striking in Table 8 is the strength of these emergent mind-sets to perform well across all the smaller subgroups into which respondents fall, based upon their own self-profiling. That is, the emergent mind-sets based upon the pattern of the individual coefficients suggest the reality and strength of these mind-sets. Table 8 suggests that these elements perform well across all the groups. What is not show is the poor performance of these elements in the mind-sets in which the element does not resonate.

Table 8: Strong The performance of key elements in each mind-set (columns) across the different self-defined groups of respondents (rows).

Discussion and Conclusions

The topic of shopping occupies a great deal of attention because of its importance in economies powered by consumer demand. The focus of the effort is on nature of the shopping venue, the way the products are presented, priced, and the nature of the sales effort. This is the world of ‘retail,’ with increasing of the focus which pleases the customer and increases sales. It should come as no surprise that there is a plethora of information on the nature of the sales process for people, this information making interesting reading in the popular press, as well as the to-be-expected abundance of individuals and organizations ready to teach, coach, team-build, all for a fee, of course.

What is lacking, however, is a sense of the inside out, viz., what do shoppers feel to be important, not in the rarified language of science and research, but in the language of feeling. When we talk about the sales situation, what is deemed to be important by respondents? As noted in the introduction, the typical research study focuses on the outside, for example the importance of something general. The description is sterile, the response is considered, the analysis is statistical, and the results are tabulations. The Mind Genomics approach works within these somewhat sterile confines. What is new, however, is the use of evocative phrases, and the effort to get people to match numbers to descriptions in an effort to ‘flesh out’ the inner experience.

The Mind Genomics efforts are labelled cartographies because they ‘map’ a domain, that domain being the mind of the person. In this case, the results of the analysis were remarkable, not so much in the richness of the shopping experience, but just the opposite. For the total panel, the shopping experience appears to be functional, and not emotional, more elements performing well in Question B on price, fewer on Question C on emotion. The results become far richer, however, when we move from the total data across the four questions or silos to each silo, specifically silo B on price, and silo C on emotions. We generate the entire model across 36 elements for each respondent, but then divide the data into the two ‘soft’ sections, statements about price and statements about emotion, respectively. It is then, in this ‘posterior, micro-analysis’ of the silos and the elements where the rich substructure of the mind of the shopper can begin to emerge.

Acknowledgements

The authors wish the acknowledge the support of the University of Indiana which funded the study in 2002, and acknowledge the guidance and friendship of Professor Thomas Hustad.

The creation of the study was directed by Jacquelyn Beckley and by the late Hollis Ashman, then of the Understanding and Insight Group, Inc., of New Jersey

Attila Gere gratefully acknowledges the support of Premium Postdoctoral Research Program of the Hungarian Academy of Sciences.

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DOI: 10.31038/AWHC.2022514

Abstract

Polycystic Ovary Syndrome (PCOS) is a dominant and complex endocrine disorder present in women worldwide. The characteristic features include anovulation, polycystic ovaries, insulin resistance, menstrual irregularities, and hyperandrogenism-related difficulties. Medical treatment of PCOS focus on symptoms, and several drugs, natural products, and herbal plants are applicable to reduce PCOS-associated symptoms. This review discussed the treatment options for PCOS women, including lifestyle changes, bariatric surgery, and therapy for anovulation, insulin resistance, menstrual dysfunction, and hyperandrogenism-related symptoms. Furthermore, it provides the chemical structure of drugs and natural products exhibiting effectiveness in PCOS treatment.

We anticipate that the information provided in this review is beneficial to scientists globally associated with the discovery and development of PCOS treatment in the pharmaceutical industry and academia.

Keywords

Polycystic ovary syndrome (PCOS), Anovulation, Insulin resistance, Menstrual dysfunction, Acne, Alopecia

Introduction

Polycystic Ovary Syndrome (PCOS) is a common endocrine condition of hormonal imbalance in women, and it is affecting at least 5% to 10% of women of reproductive age [1]. Stein and Leventhal first described PCOS in 1953. It is a complicated ovarian disorder characterized by the clinical and biochemical manifestation of hyperandrogenism, ovulatory dysfunction (menstrual disturbances), and polycystic ovaries and one of the most common endocrinopathies in reproductive-age women of the developed world [2]. The main characters of PCOS include excess production of male hormone androgen by the ovaries resulting in anovulatory infertility. Fundamentally, this happens because of the unbalanced release of Luteinizing Hormone (LH) and Follicle-Stimulating Hormone (FSH) from the pituitary gland. The FSH is accountable for follicular development, and increasing the level of the female hormone estrogen and therefore diminution of its level in the bloodstream results in the undeveloped follicles. Several immature follicles dissolve, and the rest of them remain as fluid-filled sac known as cysts, and the name PCOS is derived from these developed cysts in one or both ovaries (Figure 1).

Figure 1: Polycystic Ovary Syndrome (PCOS) in women with cysts in the ovary

Furthermore, not all PCOS patients develop a cyst, and cyst formation might occur in women with no PCOS condition. PCOS patients mainly build insulin resistance resulting in an increased insulin level, and it is one of the significant symptoms and underlying physiopathological causes of PCOS [3]. High insulin and LH levels result in hyperandrogenemia, which involves excess production of the male hormone androgen in females. It is one of the main reasons for PCOS’s clinical complications, including anovulation, abnormal menstrual cycle, and infertility. Furthermore, hyperandrogenism can initiate hirsutism, acne, androgenic alopecia, and metabolic abnormalities such as obesity, insulin resistance, hyperinsulinemia, and dyslipidemia. In many PCOS women, lipid abnormalities, exceptionally high triglyceride, low high-density lipoprotein cholesterol levels, and impaired fibrinolysis have been observed.

PCOS and associated complications physically affect the female body, and the complicated connection between genetics, environment, and hormones instigates mental health problems [4]. Reports suggest that PCOS patients are three times presumably suffer from depression, stress, anxiety, and Obsessive-Compulsive Disorder (OCD), bipolar illness, and eating problems. In PCOS women, the depression could be biological or because of distress associated with infertility, abnormal menstrual cycles, acne, body shape, and appearance or external pressure, including demands related to marriage, children, societal attitudes, standards, and culture. In certain cultures, irregular menstrual cycles link to a reduced sense of feminine identity, and therefore women develop feelings of being incomplete. PCOS-related ovulatory dysfunction is responsible for 75 percent of all female infertility cases and severely impacts psychological well-being, including depression in infertile women. Nevertheless, depression scores were still higher in PCOS patients in trials that included only infertile women or omitted all infertile women.

Polycystic ovary syndrome is a metabolic, hormonal, and psychosocial disorder with distinct biopsychosocial aspects and causing severe impacts on the life of PCOS patients. Women must take PCOS symptoms seriously and consult a medical professional or a counselor about any distress they are experiencing, as well as any misconceptions they may have regarding PCOS. The medical practitioner and gynecologist can facilitate the diagnosis and offer proper treatment and advice to manage PCOS. It is advisable to take good care of one’s physiological and physical health during PCOS treatment. In this respect, the advice from mental health professionals and psychologists and the lifestyle change are beneficial. Comprehensive treatment of PCOS patients in the early stages will help them overcome emotional stress; a significant complication mostly overlooked in PCOS patients. Early diagnosis and long-term management of PCOS will reduce its associated long-term complications, including metabolic syndrome and cardiovascular diseases, and allow PCOS women to live healthy and happy, active lives [5]. This review article is within the context of our ongoing drug design and discovery research work [6-14]. Here we have compiled the inclusive information related to PCOS, including its symptoms, management, and treatment, focusing on approved drugs. This article is valuable to PCOS patients and doctors, scientists involved in PCOS-related treatment and research, and anyone interested in acquiring more information on PCOS.

Common Symptoms of PCOS

PCOS symptoms are present in different ways in women with variations in severity and can change at various stages of women’s life. Some women can have only a few symptoms, mild symptoms, or many symptoms with seriousness. In PCOS women, menstrual cycles mostly last more than 35 days, as opposed to the usual 25- to 35-day menstrual cycle duration, and many women have fewer than six periods per year [15]. The women’s irregular menstrual cycle leads to the disruption of the ovulation schedule because of the hormonal imbalance. The eggs located in the follicles do not mature and ovulate, resulting in cysts in the ovaries and periods or irregular periods.

Furthermore, because of the inconsistent ovulation or inability to ovulate, the female may have trouble getting pregnant. The bodily mechanisms of normal females are different from PCOS females [16]. The hormone insulin, mainly responsible for converting sugars and starches into energy, is not utilized adequately, resulting in high insulin concentration and insulin resistance in PCOS women. Higher insulin level causes more release of male hormone androgen (hyperandrogenism) that induces weight gain. Hyperandrogenism can result in hirsutism, androgenic alopecia, or female pattern hair loss, specifically from the top of the scalp and forehead. Androgen hormones also induce the sebaceous glands to expand and produce more sebum resulting in acne on the face and body. In addition, acanthosis nigricans is witness as one of the symptoms of PCOS. It is an unsightly harmless skin condition that involves the development of patches of dark or dense skin on particular parts of your body, particularly on the pelvic area, beneath the breasts, armpits, and nape (i.e., back of the neck) is witnesses as one of the symptoms of PCOS. Skin tags are one of the less frequent signs of PCOS, although they do happen. Tiny, flexible lumps or flaps of skin are known as skin tags. PCOS-related skin tags usually develop in the same places as dark skin patches. The long-term effects of PCOS in later life include type 2 diabetes, cardiovascular diseases, and sleep apnoea, a sleeping disorder where breathing is interrupted. For several years, if a woman didn’t have periods or had highly irregular periods of less than four periods in a year, they have a greater than usual chance of getting womb lining cancer (endometrial cancer). However, the risk of developing endometrial cancer is still low and reduced by taking period-controlling medications such as the contraceptive pill or an intrauterine system (IUS). The PCOS symptoms also impair women’s confidence and self-esteem, and they might experience sadness and mood fluctuation [17].

Treatment Options for PCOS Women

As such, there is no specific treatment for PCOS. However, its therapy involves symptoms suppression. PCOS treatment is symptom-based (Figure 2) and focused on the primary leading illness. Therefore, treatment plan varies from person to person based on the symptoms. Here in this section, we will discuss in detail the various approaches utilized in PCOS treatment.

Figure 2: Most common PCOS-associated clinical symptoms

Lifestyle Changes

The primary treatment approaches for women with polycystic ovary syndrome include diet, weight loss, and exercise. Obesity is one of the major issues not only in women but in our society as well. It is responsible for abnormalities in the reproductive system and metabolism, particularly in PCOS women [18]. Around 40-80% of PCOS patients suffer from obesity-associated anovulation, miscarriage, and late pregnancy complications. Some reports suggest that hyperandrogenism in PCOS women can cause obesity with a high waist/hip ratio independent of the Body Mass Index (BMI) [19]. Weight loss is a first-line treatment in obese PCOS patients with infertility issues. However, it is only recommended in overweight PCOS patients with a BMI of 25-27 kg/m². In obese PCOS women, it is observed that weight loss can improves the endocrine profile and circulating androgen and glucose level and increases the ovulation and pregnancy rates.

Additionally, in obese PCOS patients, it is recommended to follow a hypocaloric diet with low carbohydrate intake that can be easily tolerated and maintained [20]. A low-fat diet reduces hyperinsulinemia and improves metabolism. Integration of low glycemic index food in the diet has exhibited improved insulin sensitivity and ovarian function. PCOS women mainly have a higher level of inflammation; therefore, an anti-inflammatory diet is recommended for PCOS women. Regular exercise and a nutritious diet can help maintain the bodyweight of PCOS patients and, therefore, can decrease the risk of severe health conditions, particularly high blood pressure, stroke, sleep apnea, etc. [21]. In addition, exercise mainly improves glucose metabolism and regulates insulin level, lowering testosterone level and helping to battle testosterone-related symptoms such as acne, hair loss, and unusual hair growth on the face. Undoubtedly, exercise is essential for PCOS patients. Still, the exercise program must be designed with the best activity of adequate duration and frequency, based on the patient’s degree of obesity and baseline fitness.

Bariatric Surgery

Recently, bariatric surgery emerged as an alternative approach for weight loss in obese PCOS patients who cannot reduce weight with diet and exercise [22]. However, the perfect bariatric procedure for PCOS is unidentified; the most common approaches include restrictive and combined restrictive, malabsorptive practices, adjustable gastric banding, and the Roux-en-Y gastric bypass. Reports suggest that bariatric surgery in some PCOS women effectively improves ovulation, insulin resistance, hyperandrogenism, and hirsutism. In several obese PCOS patients, a regular menstrual cycle is restored after bariatric surgery [23]. Undoubtedly, bariatric surgery leads to weight loss and therefore results in resumed ovulation and pregnancy. However, they are at higher risk of nutritional deficiency affecting the fetus’s nutrition and pregnancy. Reports suggest that women who conceive after bariatric surgery are at more risk for mall-for-gestational-age babies and shorter pregnancies. Although bariatric surgery has its own short and long-term risks, considering its potential benefits, it can be included as part of the treatment in PCOS women.

Therapy for Anovulation (Infertility) in PCOS Women

Ovulation is a vigorous process that involves highly coordinated endocrine changes with the hypothalamus, pituitary, and ovaries. Anovulation is the lack of ovulation and the most common cause of infertility that affects around 30% of infertile women. PCOS condition is one of the most commonly encountered reasons for anovulation [24]. In PCOS women, anovulation is described by the better response of some follicles to FSH and LH, multiple follicle development, and the arrest of antral follicles related to the suppression of serum FSH. High levels of LH, androgens, and insulin play a significant part in the anovulation process, enhancing steroidogenesis and stopping follicular growth. Several fertility drugs and medications can normalize ovulation, and we have discussed them in this section.

Selective Estrogen Receptor Modulators

Selective Estrogen Receptor Modulators (SERMs) are antiestrogens having selectivity to stimulate or inhibit the estrogen receptor of different target tissues and show variation in the ratio of the estrogenic and antiestrogenic at other tissues [25]. Clomiphene (Figure 3) (brand name Clomid and Serophene) is a triphenylethylene-derived non-steroidal selective estrogen receptor modulator used as an ovulation-inducing drug for the last 40 years. It is the first-line treatment in an ovulating woman, including PCOS patients. Clomiphene functions by affecting the hypothalamus and pituitary gland and subsequently increasing GnRH, FSH, and LH secretion that leads to follicle (egg) development and ovulation [26]. The pregnancy rate with clomiphene is 30-40% despite a reasonable ovulation rate of 70-80%, credited to the anti-estrogenic effect of clomiphene on endometrium and cervix. The multiple pregnancy rates after conception with clomiphene is 7.8%, with most twins and triplet or less than 0.9%. With Clomiphene treatment, mainly pregnancy is observed within the first six ovulatory cycles, and the live birth rate ranges from 20 to 40%.

Figure 3: Chemical structure of drugs for the treatment of anovulation in PCOS women

Starting dose for clomiphene is 50mg/day for five days and then increased to 50mg/day and a maximum of 150mg/day in subsequent cycles if the patient remains anovulatory. However, clomiphene usage is associated with side effects including bloating, stomach or pelvic pain, ovarian enlargement, dizziness or headaches, hot flashes, abnormal uterine bleeding, yellow eyes or skin, nervousness, and change in vision or loss in vision possibly because of anti-estrogenic effect in the hypothalamus [27].

Tamoxifen (Figure 3) is another non-steroidal selective estrogen receptor modulator with a triarylethylene skeleton, which is used as an oral ovulatory agent because of its antiestrogenic activity clomiphene. Tamoxifen pregnancy rate (30-50%) and ovulation rate (50-90%) is better than tamoxifen [28]. Tamoxifen without the involvement of hypothalamic-releasing factors stimulates the ovary and promotes folliculogenesis. Tamoxifen exhibits a minimal anti-estrogenic effect on the cervix and endometrium and enhanced functioning of the corpus luteum; therefore considered an appropriate alternative to Clomiphene in PCOS patients who fail to ovulate with clomiphene or show clomiphene resistance [29]. The side effects of tamoxifen treatment include bone pain, hot flashes, nausea, fatigue, mood swings, depression, headache, and hair thinning.

Aromatase Inhibitors

Aromatase inhibitors are competitive inhibitors of enzyme aromatase that play a crucial role in the final step of the estrogen biosynthetic pathway. Anastrozole and letrozole (Figure 3) are non-steroidal aromatase inhibitors with encouraging ovulation-inducing properties [30]. Anastrozole and letrozole are selective, reversible, and highly potent aromatase inhibitors with a half-life of around 45 hours, much better than clomiphene (half-life 5-7 days). Compared to anastrozole, letrozole is studied comprehensively and considered first-line therapy in PCOS women for ovulation induction. Letrozole functions by inhibiting estrogen production in the hypothalamus-pituitary axis leading to an upsurge in Gonadotropin-Releasing Hormone (GnRH) and FSH level and subsequently results in enhancing the mature follicle quantity, optimizing ovulation, and increasing the pregnancy rate in PCOS women. The letrozole offers several advantages as an ovulation-inducing agent, including oral administration, shorter half-life, minimal peripheral antiestrogenic effect on the endometrium, higher implantation rate, and stimulating mono follicular growth ovulation, therefore, reducing the rate of multiple pregnancies [31]. Compared to clomiphene, letrozole has exhibited a 50-60% live birth rate, lower multiple pregnancy rate, higher per cycle and cumulative ovulation rate, and better quality ovulation. Letrozole can effectively induce ovulation in women with the estrogen-sensitive disease, particularly breast cancer, and long-term letrozole treatment is safe and effective in postmenopausal women with early breast cancer. Letrozole in long-term use produces more mature follicles and successful pregnancies than its short-term usage [32]. The most common side effects of letrozole include hot flashes, headaches, dizziness, weakness, bone pain, muscle or joint pain, swelling, and weight gain.

Gonadotropins

Gonadotropins are hormones secreted from the anterior pituitary gland and act on the gonads to increase the production of sex hormones and stimulate ova production in females. The main gonadotropin hormones are Follicle-Stimulating Hormones (FSH) and Luteinizing Hormones (LH). Exogenous gonadotropins are used as a second-line treatment to induce ovulation in PCOS women who developed resistance to clomiphene [33]. Gonadotropins work by inducing ovulation, maintaining follicle growth, and attaining healthy follicles for fertilization with no peripheral anti- estrogenic effect. Gonadotropins in low doses offer a high ovulation rate, mono follicular development, and lower the risk of Ovarian Hyperstimulation Syndrome (OHSS) and multiple pregnancies [34]. Patients who are unsuccessful in ovulating after clomiphene treatment suffers from severe ovarian abnormality, requiring a higher threshold dose of exogenous FSH. Whereas the patients who are successful in ovulation but unable to conceive after clomiphene intake need a lower FSH threshold. Therefore, a lower dose of exogenous FSH can attain sufficient ovarian stimulation. The two most commonly used approaches for ovulation induction with gonadotropins in clinical practice are the low-dose step-up and the low-dose step-down protocols. The chronic low dose protocols will reduce the risk of multiple follicular developments and their associated perils, including multiple pregnancies and OHSS. Additionally, the gonadotropin treatment is quite expensive, time-consuming and requires continuous monitoring by expert [35].

Glucocorticoids

Glucocorticoids are a class of corticosteroids having steroidal skeleton and secreted from the adrenal glands in stress response and effective at reducing inflammation and suppressing the immune system [36]. Glucocorticoids such as prednisone and dexamethasone (Figure 3) have been utilized in the anovulation treatment. In PCOS patients resistant to clomiphene treatment and having normal androgen levels, the addition of dexamethasone in high dose and short duration to clomiphene displayed a favorable response for induction of ovulation with minimal anti-estrogenic effect on the endometrium and higher ovulation and pregnancy rates. In PCOS patients with elevated androgen levels, only the low dexamethasone dose was efficient in increasing ovulation and pregnancy rate. Additionally, in PCOS patients, the addition of glucocorticoids during induction of ovulation by letrozole showed substantial improvement in folliculogenesis, ovulation, and pregnancy. However, glucocorticoids usage is associated with potentially adverse effects on insulin sensitivity; hence, its prolonged use must be avoided [37].

Laparoscopic Ovarian Diathermy

Laparoscopic ovarian drilling with laser or diathermy is a surgical treatment used to destroy part of the ovary in PCOS patients with anovulation [38]. It is recommended as a second-line treatment in clomiphene-resistant PCOS women who cannot undergo gonadotropin treatment because of high cost and continuous monitoring. In clomiphene-resistant PCOS women undergoing LOD versus gonadotropin treatment, the pregnancy rate was lower, whereas no difference in ovulation or pregnancy, live birth, and miscarriage rate was observed. In addition, ovarian drilling was ineffective in improving metabolic abnormalities, and in some PCOS patients, it exhibited temporary fertility advantages and required adjuvant therapy after drilling with clomiphene. LOD was more effective in patients with high LH levels, and after surgery, a substantial decrease in LH and androgen levels was observed. Furthermore, in some women (63%-85%), LOD retained the menstrual cycle and caused a prolonged positive effect on the reproductive system [39].

In vitro Fertilization

In Vitro Fertilization (IVF) is an assistive reproductive technology that involves fertilizing an egg with sperm “in vitro.” After the fertilized egg experiences embryo culture, it is stored or implanted in the uterus for creating a successful pregnancy. The in vitro fertilization technique is primarily used in patients where other treatments, including clomiphene citrate, letrozole, gonadotropins, etc., were unsuccessful. It is one of the last options to attain pregnancy in PCOS women [40]. However, in some patients with concomitant diseases, IVF is the first option. IVF in PCOS women have displayed decent pregnancy and live birth rates with reduced risk of multiple pregnancies. Therefore it is one of the rational options to accomplish pregnancy in PCOS women. However, the IVF procedure is expensive with no guarantee of success and can take patients’ emotional/psychological toll. Additionally, other drawbacks of in vitro fertilization include higher chances of ovarian hyper-stimulation syndrome (OHSS), multiple pregnancies (around 20-30%), ectopic pregnancy, and risk of prematurity and low birth weight in babies [41].

Therapy for Insulin Resistance in PCOS Women

The occurrence of insulin resistance measured by compromised glucose tolerance and its incidence rate is much higher in PCOS women than women with no PCOS and the same age and weight. Insulin resistance is associated with diabetes, metabolic syndrome, and in later stages with cardiovascular issues [42]. The treatment of PCOS with diabetes needs proper lifestyle changes including, diet and exercise and proper medications. The most common medicine to improve insulin resistance in PCOS patients is metformin (Figure 4) [43]. Metformin is an oral antidiabetic drug that belongs to the biguanide class, sold under the brand name Glucophage to treat type 2 diabetes mellitus. It is used as a first-line drug for treating type 2 diabetes, particularly in obese patients; however, it works more effectively in non-obese PCOS women than obese PCOS patients. It is used as a second-line agent to treat infertility in patients suffering from polycystic ovary syndrome. It is related to an increase in the menstrual cycle, improvement in ovulation, and reduction in circulating androgen level. In addition, metformin can support weight loss by enhancing metabolic functions [44]. Metformin’s clinical role is to obstruct glucose production, reduce glucose uptake by the intestine and increase insulin sensitivity in peripheral tissues. In PCOS women, metformin improves ovulation induction by lowering insulin levels and varying the insulin effect on ovarian androgen biosynthesis, theca cell proliferation, and endometrial growth [45]. Moreover, it can inhibit ovarian gluconeogenesis and therefore lowering ovarian androgen production. Metformin’s safe profile makes it the most commonly used drug in treating glucose intolerance and elevated diabetes risk in PCOS women. Metformin is given in numerous routines with focus and monitoring on patient tolerance. The target dose for metformin is 1500-2550 mg/day, which is achieved slowly by beginning with 500mg/day metformin for one week followed by 1000mg/day for another week and then 1500mg/day. Primarily the metformin exhibits response at the dose of 1000mg/day only in some patients the dose reaches 1500 or 2000 mg/day. Metformin also works efficiently in combination with clomiphene and gonadotropins. Clomiphene can improve ovulation and pregnancy rate, whereas gonadotropins encourage mono ovulation and decrease the dosage and duration of gonadotropins and the risk of canceled cycles. The most common complications associated with metformin use are nausea, diarrhea, weakness, flatulence, myalgia, hypoglycemia, and abdominal pain. Thiazolidinediones (Figure 4), also known as glitazones, are another class of insulin-sensitizing drug that has displayed good ovulation and pregnancy rates [46]. These drugs improve insulin sensitivity by increasing the ovulation rate and glucose tolerance and reducing circulating androgen. Troglitazone, rosiglitazone, and pioglitazone molecules of the thiazolidinediones class have been studied extensively, however in animal studies; these molecules possess hepatotoxicity, cardiovascular risk, weight gain, and reproductive toxicity and therefore resulted in restricted use in PCOS women [47].

Figure 4: Chemical structure of drugs for the treatment of insulin resistance in PCOS women

Therapy for Menstrual Dysfunction in PCOS Women

PCOS patients mainly suffer from abnormal menstrual patterns because of prolonged anovulation, and these menstrual irregularities usually have a history dating back to menarche [48]. Some PCOS women have oligomenorrhea, menstrual bleeding <9 menstrual periods per year, or secondary amenorrhea, which is the absence of menstruation for six months. In addition, other consequences of anovulatory menstrual cycles include dysfunctional uterine bleeding and infertility. Ongoing anovulation can increase the risk of endometrial hyperplasia and carcinoma. Therefore, it must be treated on time. The most common approach to treat menstrual abnormalities in PCOS women is oral contraceptives [49]. In PCOS women who do not wish for pregnancy, hormonal contraceptives are the first-line treatment for menstrual irregularities. PCOS women are administered using progestin such as medroxyprogesterone (Figure 4) or oral contraceptive with a combination of estrogen and progestin to reduce circulating androgens, maintain regular menstrual cycles, and reduce the risk of endometrial hyperplasia and cancer. Additionally, metformin is used to improve insulin resistance and menstrual irregularities in PCOS women who cannot take or tolerate hormonal contraceptives or lifestyle changes that have no positive effect on them. Metformin can reduce free testosterone levels, cure metabolic and glycemic abnormalities and maintain regular menstrual cycles.

Therapy for Hyperandrogenism Related Symptoms in PCOS Women

Hyperandrogenism is one of the principal features of PCOS and is clinically displayed as hirsutism, acne, and alopecia, etc. [50]. The hyperandrogenism symptoms vary from patient to patient, and subsequently, its treatment.

Hirsutism

Hirsutism is a condition in women that results in excessive terminal hair in androgen-dependent areas of the body. This disorder mainly occurs because of increased androgen action on hair follicles or upsurge circulating level of androgens or amplified sensitivity of hair follicles to normal levels of circulating androgens. Treatment options for hirsutism in women with PCOS or without PCOS are the same. They include therapies that aim to local expressions of hirsutism or target underlying causes using proper medications [51]. The effective therapies that target the local expressions of hirsutism include hair removal using physical means such as shaving, laser therapy, electrolysis, topical treatment, etc. Pharmacological treatment is focused on blocking the androgen action at hair follicles or restricting androgen production [52].

Medications under pharmacological treatment generally take around six months to show a significant effect on hair growth. Patients intolerant to medical therapy are treated with a combination of local measures and drug treatment. Several medicines have been studied for the treatment of hirsutism in PCOS patients, and the most effective drug options are oral contraceptives, antiandrogens, and topical cream. Low-dose Oral Contraceptive Pills (OCPs) are mainly used in women who do not wish to conceive. Birth control pills or oral contraceptives comprising estrogen and progestin are used to treat hirsutism caused by androgen production; however, the selection of oral contraceptives is substantial because some of the progestins also have an androgenic effect. The low-dose OCPs available in the market include ethinyl estradiol (Figure 5) in doses ranging from 15-35g. OCPs with less androgenic progestin such as norgestimate, gestodene, and desogestrel (Figure 5) are good options for hirsutism treatment [53]. Anti-androgens, a drug that blocks androgens from binding to the receptor, are prescribed after six months of ineffective oral contraceptive treatment. Response to antiandrogen in hirsutism treatment is prolonged and sometimes takes around 18 months, and the most commonly used antiandrogens are spironolactone (Aldactone) and flutamide (Eulexin) (Figure 5). Spironolactone is safe and low- cost drug that possesses moderate antiandrogenic effects when monitored in high doses (100-200 mg daily). It works as dose-dependent competitive inhibitors of the androgen receptor and demonstrates effectiveness on hirsutism treatment. Flutamide is non-steroidal, selective antiandrogen with no progestogenic effect and equally effective as spironolactone, but its application required hepatic function monitoring. In addition, estrogen-progestin combination therapy, including a combination of OCPs, effectively reduces terminal hair growth and acne formation in PCOS patients.

Figure 5: Chemical structure of drugs for the treatment of hyperandrogenism-related symptoms in PCOS women

Moreover, topical cream naming Eflornithine (Vaniqa) (Figure 5) is a prescription cream that displayed effectiveness in slowing down the growth rate of excessive facial hair in women [54]. Eflornithine is ineffectual in completely removing the existing hair. Therefore, it is used in combination with laser therapy to enhance its response. Gonadotropin-releasing hormone agonist (Gn-RHa) including, leuprolide (Lupron), is effective in women with severe insulin resistance who are unresponsive to combination hormonal therapy or not able to tolerate oral contraceptive pills [55]. It works by suppressing pituitary hormones, reducing androgen and estradiol secretion, and subsequently reducing the severity of hirsutism; however, the Gn-RHa treatment is expensive, and its use is associated with long-term consequences as hot flushes, bone demineralization, atrophic vaginitis. In some PCOS women with elevated adrenal androgen levels, glucocorticoids suppress adrenal androgen secretion [56]. Glucocorticoids such as prednisone and dexamethasone have shown efficiency against hirsutism in patients with classic congenital adrenal hyperplasia and retained normal ovulatory cycles. In addition, insulin-lowering agents are beneficial in patients struggling with terminal hair growth. Metformin and thiazolidinediones have shown effectiveness in lowering ovarian androgen secretion by improving insulin sensitivity. Metformin therapy has shown improvement in clinical manifestations of hyperandrogenism [57].

Acne and Alopecia

For acne treatment, both oral contraceptive pills and antiandrogens have been used successfully, whereas for alopecia, there are no extensive trials, but oral contraceptive pills and antiandrogens are administered [58,59]. Oral contraceptive pills treatment has shown a reduction in inflammatory acne count around 30-60% and is very useful in patients with deep-seated nodules or relapsing on isotretinoin. For alopecia treatment, spironolactone has shown some effect in few studies similar to finasteride.

PCOS Treatment with Natural Products

Natural products have been in immense use throughout human evolution. Several natural products from plants are used to cure various types of diseases in humans. Correspondingly, the natural molecules affecting the various pathological aspects of PCOS play a significant role in overcoming PCOS-related symptoms [60].

Inositol

Inositol is a vitamin-like substance with a basic chemical formula similar to glucose (C6H12O6) and is present in many plants and animals. Inositol exists in different stereoisomers with Myo-inositol (Myo-Ins) and D-chiro-inositol (D-Chiro-Ins) (Figure 6) the most common [61]. Both the isomers are the second messenger of insulin. The Myo-Ins (expression of glucose transporters and cellular glucose uptake) and D-Chiro-Ins (glycogen synthesis and storage) are involved in different functions. Furthermore, physiologically the Myo-Ins is converted into D-Chiro-Ins through the activation of the insulin-dependent epimerase enzyme. PCOS women mostly exhibit compromised inositol metabolism and insulin resistance, causing a reduction in the intracellular conversion of Myo-Ins to D-Chiro-Ins inositol [62]. Several studies suggested that the dietary supplementation of Myo- Ins, alone in combination with D-Chiro-Ins, effectively improves metabolic and hormonal profile, reduces hyperandrogenism, refining oocyte quality, and maintains a regular menstrual cycle. Mainly, in obese patients, the 40:1 ratio of Myo-Ins and D-Chiro-Ins was most effective in restoring ovulation and normalizing the progesterone, LH, SHBG, estradiol, and testosterone level [63]. Inositol can efficiently regulate glucose metabolism, and therefore in PCOS treatment, it can utilize competently.

Figure 6: The chemical structure of natural products is effective in the treatment of PCOS

Flavonoids

Naringenin (Figure 6) is a tasteless and colorless flavanone present primarily in grapefruit and in various fruits and herbs [64]. Studies with naringenin in PCOS women suggest that it can decrease the level of testosterone and estradiol and increase the concentration of enzymes involved in scavenging reactive oxygen specie. Additionally, naringenin exhibited positive cytoprotective and anti-inflammatory results in the animal model, inhibited PCOS-associated weight gain, and reduced serum glucose levels [64]. Another flavonoid that positively affects PCOS treatment is rutin (Figure 6), a plant pigment found in certain fruits and vegetables. In obese mice, rutin can control obesity and insulin resistance, and rutin treatment is significantly effective against hyperandrogenism and infertility.

Vitamins

Vitamin C (Figure 6), also called ascorbic acid, is a micronutrient essential for cells and tissues’ physiological and healthy growth. It is a water-soluble vitamin with antioxidant properties and can restore fat-soluble vitamin E (Figure 6) antioxidant nature. In PCOS rats, it was observed that vitamin C level was controlled throughout the menstrual cycle. It plays a significant role in regulating the menstrual cycle and ovarian functions [65]. Vitamin E, also known as tocopherol, is a fat-soluble vitamin with antioxidant properties, and it neutralizes free radicals and promotes cell renewal. Because of its anticoagulant and antioxidant properties, Vitamin E displays the ability to improve endometrial thickness in women with idiopathic infertility. It effectively reduced oxidative stress and subsequently reduced the exogenous human menopausal gonadotropin; however, its intake does not affect the pregnancy rate [66]. Vitamin D (Figure 6) a fat-soluble secosteroid essential for calcium homeostasis and bone mineralization. In humans, vitamin D3, known as cholecalciferol and vitamin D2, also called ergocalciferol, are the most common forms of Vitamin D. Recent reports suggest that vitamin D deficiency plays a part in insulin resistance and inflammation, dyslipidemia, and infertility in PCOS women. Therefore, Vitamin D as a supplement may reduce insulin resistance and hyperandrogenism in patients with PCOS [67]. In addition, it was observed that the average vitamin D level in women helps attain more endometrium thickness and, therefore, increases the chances of pregnancy. It is evident that vitamins affect the various pathological features of PCOS; therefore, further study is required to establish the positive impact of vitamins in PCOS treatment.

Omega-3 Fatty Acids

Omega-3 fatty acids are polyunsaturated fatty acids, and their three primary forms are Alpha- Linolenic Acid (ALA), Eicosapentaenoic Acid (EPA), and Docosahexaenoic Acid (DHA). The ALA is found in plant oil such as flaxseed, soya bean, and canola oil. The biologically active Eicosapentaenoic Acid (EPA) and Docosahexaenoic Acid (DHA) are common in fish and other seafood. Omega-3 fatty acids are notable for their antioxidant, anti-inflammatory, anti-obesity, and insulin-sensitizing activity. Reports suggest that omega 3- fatty acids control insulin resistance and maintain total cholesterol, triglyceride, and low-density lipoprotein. Though no confirmation data is available suggesting the direct effect of omega-3 fatty acids on BMI, fasting insulin and glucose, and HDL< FSH, LH, SHGB, and total testosterone. In PCOS women, Omega-3 fatty acid supplements may decrease inflammation because of a reduction in high-sensitivity C-reactive protein and an increase in adiponectin level [68]. It’s recommended to administer omega-3-fatty acids in PCOS women with inflammatory and cardiovascular-related symptoms [69]. The most common side effects of omega-3-fatty acids include mild gastrointestinal discomfort, intestinal gas, nausea, diarrhea, headache, and synergistic effects. It is not recommended during antiplatelet and anticoagulant treatment, and its use requires continuous monitoring in obese PCOS patients.

Herbal Plants in PCOS Treatment

At present, no perfect treatment is available for the PCOS symptoms. Therefore, herbal plants bearing active compounds are practical alternatives to available drugs and have attracted much attention in recent years [70]. The treatment of PCOS women with M. spicata (spearmint) tea twice a day exhibited a positive effect and decreased the level of free and total testosterone, increased the FSH and LH level, and subsequently decreased the hirsutism. The oral treatment with cinnamon (C. Zeylancam) can improve insulin sensitivity, and PCOS women can experience a significant decrease in insulin resistance. The Maitake mushroom (Hen-of-the-wood) extract co- treatment with clomiphene citrate significantly improved insulin sensitivity and supported ovulation in PCOS patients [71]. The O. Majorana (Sweet Marjoram) tea treatment can improve insulin sensitivity and act as an antiandrogen, subsequently decreasing fasting insulin levels and DHEA-S [72]. In combination with metformin, the fenugreek (T. foenum graceum) seeds also show insulin sensitivity, reduce polycystic ovaries, and improve menstrual cycles [73]. Additionally, the plant has a large amount of phytoestrogen, including raspberry, licorice, soya been, etc. are having antiandrogenic properties and are therefore effective in decreasing androgen levels in PCOS patients [74]. The plants having an antioxidant property such as C. Sinensis (Green tea), B. Vulgaria (bamboo), P. granatum I. (Pomegranate juice), etc. significantly improve serum level of sex hormone and reduce oxidative stress [75].

Conclusion

PCOS is a severe heterogeneous disorder found in women with no complete understanding of its pathophysiology. No permanent therapy is available for PCOS. However, its treatment is symptom-based. PCOS-associated symptoms include anovulation, insulin resistance, menstrual dysfunction, hirsutism, hyperandrogenism, acne, and alopecia. PCOS women are susceptible to obesity, diabetes, and adverse cardiotoxicity. The review article provides comprehensive information regarding the most common therapies advantageous in treating PCOS symptoms. Several approved drugs applicable in the treatment of various PCOS symptoms have been discussed in detail. In addition, the natural products and herbal plants exhibiting beneficial effects in the preliminary examination on PCOS women have been included in the article. Substantial work is required to understand the pathophysiology and genetics of PCOS syndrome to develop specific treatment and to delay the long-term effects of PCOS in women. Furthermore, extensive research is needed to investigate more drugs like chemical compounds and natural products to discover a suitable cure for improving PCOS symptoms. The information presented here is beneficial to researchers, clinicians, and the pharmaceutical industry and promotes finding and developing PCOS treatment.

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