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1 Introduction

Recent resurgence of traditional medicine (TM) has resulted in a renewed ­ubiquitous curiosity toward their fundamental constructs. Their clearer understanding and subsequent applications based upon evidences are the primary motive of this global curiosity. Ayurveda has responded well to these emerging global demands from TM by making a paradigm shift into its research priorities which now focuses more upon basic research besides the clinical ones [1].

Ayurveda as a major stakeholder among global TM practices proposes its unique pronature biophysical basis toward the understanding of health and disease. It identifies four purusharthas (spiritual, economical, sensual, and renounceable) as the primary objectives of a human life and foresees the enabling health as an essential mean to achieve those. Interestingly, despite of its appearance as a subjective science, Ayurveda stands to be a truly logical, systematic, and comprehensive health science encompassing the wider perspectives of an individual. Charaka Samhita defines Ayurveda as a science dealing with quality of life within philanthropic, misanthropic, pleasurable, and miserable modes of living (Charaka Samhita Su.1/41). Ayurveda deals explicitly with the materials and methods to intervene into the state of disease and health. A disease in Ayurveda is proposed to be an outcome of imbalance among the body constituents, viz., dosha, dhatu, and mala. This imbalance is depicted clinically through altered body functions. Disease management in Ayurveda, therefore, is intended to restore the balance of the inner milieu by regulating diet, lifestyle, and supplementation of naturally occurring compounds. A medical prescription from Ayurveda uniquely considers finer details of the patient and the disease to bring out a typical prescription suiting to individual requirements.

Despite of its textual novelty, for want of objectively applicable tools, the ­fundamental constructs in Ayurveda could not be adequately utilized to raise a dependable and predictable health care. Recent global upsurge of TM, at this juncture, opens up the widening opportunities of critically evaluating Ayurvedic fundamentals for their dependability and reproducibility in health care for meeting the expectations of science [2–4]. Eventual to the global expectations, a few key fundamentals from Ayurveda, viz., prakriti and tridosha have come to a critical reappraisal for their better appreciation and subsequent utilization in health care [5–7].

Prakriti in Ayurveda is defined as an individual quality quantified in terms of dosha and determined by various innate variables expressing that dosha. Dosha, as progenitor to the idea of prakriti, describes physiological system specificity which regulates the physiological and in turn the anatomical expressions specific to human body. Dosha are categorized as vata, pitta, and kapha as per their principal activities and subsequently named together as tridosha. An individual prakriti, in turn, is a realization of predominant dosha activity in a person leading to its physical, physiological, and mental identity [6, 7].

For their omnipresence in principles and practice of Ayurveda, prakriti and tridosha come forward as central dogma in Ayurveda. Conceptually, the duo propose a greater understanding to disease etiology, presentation, and management and eventually offer help in evidence-based decision-making for personalized treatments [5]. Translating this concept into a dependable evidence for decision-making, however, still requires much work. Dahanukar and Thatte [8] have correlated therapeutic outcomes in certain conditions to the prakriti specifications of an individual [8]. Construct of prakriti has recently been correlated HLA alleles [9]. The same is also furthered by biochemical correlates and whole genome expression referring to the various prakriti types [10].

Irrespective to these recent scientific appraisals, a fair utilization of prakriti into the clinical practice still require a dependable, reproducible, and objective method to determine it. We, therefore, need to have a standard tool to determine prakriti unequivocally for its use in clinical practice.

2 Examining Prakriti: Are We Properly Equipped?

Adoption of unambiguous, reproducible, and universally applicable tools to generate evidence is a prerequisite to evidence-based decision-making [11]. Prakriti, for its conceptual and clinical importance to Ayurvedic health care, deserves a detailed yet determinant examination for its possible usage in clinical practice. In Ayurvedic practice, prakriti is examined in connotation to the dosha-related features available to an individual. This feature examination aiming at prakriti diagnosis is usually done through an interaction between patient and physician. To help the interview process and also to bring objectivity to the results obtained through such process, a symptom-based checklist (questionnaire) model is adopted. Most published Ayurvedic researches including many recent ones, requiring a prakriti examination, adopted a similar prakriti examination approach to reach at its diagnosis. Ironically, a validation to any such method aiming at prakriti diagnosis has never been attempted in these studies. It is because of this reason, a prakriti diagnosis made through conventional methods is found to have substantial interrater variability in terms of quantitative estimation of dosha referring to ultimate prakriti diagnosis. Biostatistical quantification of tridosha [12], classification of human population on basis of HLA gene polymorphism and linking it to prakriti [9], and whole genome expression and biochemical correlates of extreme prakriti types [10] are few among recent studies aiming to explore the scientific basis of prakriti. Among these, Joshi [12] adopted a semiobjective questionnaire method utilizing a comprehensive list of 28 features referring to different dosha [12]. The study identified feature classes as important traits with variable expressions as per the dosha influence in an individual. Three possible expressions to every feature class were proposed referring to three major dosha classes: vata, pitta, and kapha. This prakriti analysis model, therefore, was a triple choice questionnaire model where each question represented a feature class and each choice represented a dosha category (Table 6.1). The ultimate prakriti diagnosis in this model is reached through an active–passive interaction between patient and physician to choose the most appropriate expression against selected feature classes. Numbers of expressions favoring individual dosha are then counted, and a proportionate prakriti is inferred by identifying the dosha which is most commonly expressed. Irrespective of its ease of application, this method, however, fails to recognize “the phenomenon of absolute or differential expression of dosha,” a key characteristic of prakriti understanding in Ayurveda. It is important to understand that independent dosha may have an absolute expression of their own in a feature class which is not shared by other dosha or may have a differential expression by sharing the same feature class by other dosha too. Dosha are thereby expressed through a few shared and yet few exclusive features which are phenotypical expressions of their inherent properties or guna (Table 6.2). A compulsive search of expression for some dosha against some trait as is done in triple response model may therefore lead to an erroneous result. The argument of absolute or differential expression of dosha becomes more explicit when we reanalyze Table 6.1 for its application in prakriti diagnosis. In reference to the skin appearance, the first trait, an expression of dry, less oily, and oily skin is considered representative to vata, pitta, and kapha, respectively. Similarly for second trait, an expression of unpleasing, less pleasing, and pleasing appearance is considered representative to vata, pitta, and kapha, respectively. This is important to note that these feature classes are primarily expressed by vata and kapha, respectively, and any moderate expression of features is wrongly attributed to pitta, where these traits are actually not expressed. Ignorance to this important observation of prakriti description in Ayurveda, therefore, is supposed to give false quantitative values to different dosha. Prakriti examination by Patwardhan [9] succumbed to similar methodological pitfall where feature categories were identified and scaled to various dosha orders [9]. Prasher [10] adopted a similar process of prakriti analysis by opting multiple choice questionnaire, with each option referring to a property attributed to either of vata, pitta, or kapha [10]. Unfortunately, this pattern of prakriti evaluation remained prevalent in researches done so far in Ayurveda [13]. A recently developed software by CDAC is also not devoid of the similar pitfall of making a prakriti diagnosis [14].

Table 6.1 Conventionally used triple choice questionnaire model to make a prakriti diagnosis
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Table 6.2 Cross and independent distribution of features among different dosha prakriti
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A predetermination of feature class followed by search for their variable expressions and then the dosha preponderance is the prospective approach of making a prakriti diagnosis. A prospective approach, therefore, makes a prakriti diagnosis through compulsively selecting one among three variables from a feature class to determine either of the dosha prevalence. Incidentally, an unequal distribution of feature classes among dosha groups has given a way to craft artifact expressions to the places where they do not really exist. Meeting with a compulsive choice among a feature class to choose an expression to rate a dosha is supposed to give rise to false results due to mandatory reporting. Additionally, this is also noteworthy that in absence of a clear and convincing expression of features, common trends are to choose the modest options and to avoid the extremes. Therefore, a mandatory reporting does not necessarily infer positive features and instead may be an expression of the exclusion of others. This nonconviction when added with a compulsion to choose either of the available option is supposed to project false positive results in favor of some specific dosha. Pitta, for instance, being moderate in its physical features, has the highest possibility of being represented as false positive. This postulation is also supported through the prakriti distribution pattern observed among the studied population in few of the recent studies [9].

3 Diagnosing Prakriti: The Retrospective Approach

Against the currently utilized prospective model of prakriti diagnosis based upon feature identification followed by their dosha linking, a retrospective approach promises for more. The later model primarily proposes dosha recognition through identification of their cardinal features and checking for their availability through a binomial questionnaire (Yes/No). Eventually, this approach gives an equal opportunity for every feature either refused or accepted on account of their visibility. A retrospective approach of prakriti diagnosis is advantageous over prospective approach on two important grounds. Firstly, it offers a clear yes–no choice for the specific features making their selection unambiguous. Secondly, it also offers a liberty to refuse a feature by the observer if it is not clearly observable. Both of these factors significantly lower the possibility of misleading inferences arriving due to symptom overlap and compulsive reporting inherent to the prospective approach.

Why dosha represents an unequal distribution of observable features? Ayurveda proposes the theory of dosha property (guna) to answer this. Every dosha is proposed to have some inherent properties called as guna, and explicit phenotypical features of an individual are proposed to be the manifestation of these properties. A retrospective approach of prakriti diagnosis offers to identify the link of dosha guna to their physical manifestation. Eventually, through this way, dosha predominance can also be visualized differentially in reference to the dosha properties responsible for this predominance. Charaka Samhita gives the lead to identify dosha properties through physical expressions leading to manifestation of prakriti (Table 6.3).

Table 6.3 Dosha guna and their manifestations
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4 Objective Identification of the Features for Prakriti Diagnosis

Prakriti identification features as described in Charaka Samhita (Table 6.3), when revisited for their objective verification, have given rise to an interesting observation. This was observed that the enlisted features are easy to be categorized on the basis of their objective verifiability. A prospective feature categorization may be sought as (1) Objectively verifiable features requiring a direct observation by the physician. Examples to this category are the features associated with physical built, height, complexion, etc. (2) Nonverifiable features requiring an interrogation from the patient. This class is primarily represented by the features pertaining to physiological and psychological attributes of a person. (3) There can also be a group of mix features which can either be physically verified and or be interrogated for. Question regarding the physical movements, increased presence of moles, premature graying and fall of hair, and understanding and grasping skills are examples to this category. If we measure the ratio of physically verifiable features against those who require an interrogation, we find that vata and kapha features come mainly from physically verifiable group whereas pitta comes from the interrogation group (Table 6.4).

Table 6.4 Objective classification of features in different dosha groups
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This simple observation may have an important bearing in its relation to prakriti diagnosis. Firstly, it argues for the need of developing measures for a dependable identification of verifiable features (Table 6.5). Secondly, this observation also gives us an opportunity to revisit the conventional thought about prakriti considering their three major classes as independently identifiable set of constitutional components. Being represented by increased amount of physically verifiable features, vata and kapha presumably represent the morphological determinants of the body, whereas being represented by more nonverifiable features, pitta presumably represents the mental and metabolic determinants of the body. An implication of this observation, however, is yet to be ascertained.

Table 6.5 Verifiable features for prakriti diagnosis and possible tests to verify them
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5 Developing a Standard Tool for Prakriti Diagnosis: What are the Primary Requisites?

To consider any diagnostic instrument as a help in clinical decision-making, most important is its validity and reliability. A content and construct validity, hence, requires a proper address in questionnaire-based models leading to prakriti diagnosis [15]. Furthermore, while constructing the questionnaire, ease of understanding, unambiguity, and application is also important. Once constructed, this can be cross-checked for its construct validity through observation of verifiable features by objective methods in parallel to the responses obtained through the questionnaire method. There are many postulated ways to an objective cross-check for verifiable features, and many more such ways can further be identified (Table 6.5).

Reliability of the prakriti diagnosis tool can be tested by subjecting the tool to reliability testing. A test–retest reliability is the one which is done by subjecting the same instrument to the same subject with a difference of few days. This test–retest reliability can further be strengthened by making an intrarater (when the repeat test is done by the same rater) and interrater (when the repeat test is done by some other rater) observations. The observations obtained can further be subjected to statistical methods like Pearson’s correlation coefficient and Cohen’s kappa coefficient of agreement to test them more critically.

6 Diagnosing Prakriti: What Could Be the Prototype Standard Model?

By visualizing the limitations of the existing methods of prakriti diagnosis, and also by identifying the basic requisites of making a standard tool to generate evidences, we can propose a prototype tool addressing the concerned issues. Considering the prakriti description based upon the properties of individual dosha type, a prakriti analysis questionnaire (PAQ) model can be prepared which essentially looks for the clear presence or absence of features. An arbitrary numerical value can be provided to each response obtained in order to get cumulative ratio of each dosha featured in an individual subset (Table 6.6). A liberty to accept or reject any feature in this proposed model eliminates the crux of compulsive reporting and consequent false-positive or false-negative inference in favoring or declining some particular dosha. The tool can further be verified through cross-testing the verifiable features and also through reliability testing, as discussed above.

Table 6.6 Prototype prakriti analysis questionnaire (PAQ)
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7 Conclusions: Way Ahead for Prakriti Diagnosis in the Twenty-First Century?

Why do we need an evidence base to Ayurvedic practice? Do we still require an evidence base for a health-care practice which has proven its effects through historical evidence of its practice? These commonly raised arguments referring to the research needs in Ayurveda are required to be analyzed in relation to extended benefits of putting contemporary evidence base to the practice of Ayurveda, primarily for a prospective better health care and secondarily for enrichment and eventual growth of Ayurveda as a true science. Advantages of bringing evidence base to a medical practice are obvious, tangible, and numerous. This ultimately aims to deliver the advantages of rigorous researches in the field of medicine for the best possible patient care. A decision-making in medical practice shall therefore take the account of every possible and relevant information available which can make a change in the intervention aiming at ultimate betterment in proposed outcomes. An evidence base is therefore required to be adopted at every level of health-care practice from diagnostics to the therapeutic decision-making. Ayurveda too require a similar and thorough work to bring out an evidence base to its diagnostics primarily to support its fundamentals upon which a decision of therapeutic intervention can dependably be made.

Prakriti examination for its conceptual importance to Ayurvedic clinical practice requires effective and reliable tools of diagnosis, without which, it remains unable to offer any help in therapeutic decision-making in Ayurvedic practice. A prototype PAQ for prakriti diagnosis, hence, is proposed after a prudent analysis of limitation of existing models in use and methods required to fill the gap. This proposed prototype model, however, still requires to be tested on various parameters to test its validity and reliability. Once pilot tested, and suggested for possible limitations, it can go for further revisions till it is finally approved or rejected. If arrived at approval in course of its study, it can serve the purpose of being a handy tool for physician to retrieve dependable information regarding the patient’s prakriti and its possible utilization in consequent Ayurvedic health care.

Moreover, and in concert with the properties of Ayurveda related to the genomic characteristic of the patient, we also submit that future research in complementary and alternative medicine will elucidate molecular genomic, proteomic, and ­epigenetic biomarkers of the Ayurvedic states and traits described above, in a ­manner similar to what is noted in the case of pathologies such as HIV/AIDS [16] and cancer [17]. A panel of biomarkers carefully articulated in the same manner could come together “to vote” [17] for prakriti parameters and come to form the fundamental of evidence-based Ayurveda-driven clinical intervention. Notably, few recent works on prakriti have already started building the evidences to test this hypothesis [18, 19].