Historically and currently, many health educators misunderstand the definition and meaning of inductive and deductive reasoning, and these inaccurate interpretations are often used to incorrectly distinguish quantitative and qualitative methods. Deduction is typically defined as reasoning from the general to the specific, and induction is typically defined as reasoning from the specific to the general. Contemporary definitions of deductive and inductive reasoning differ from the more typical but antiquated definitions of these terms. Deductive reasoning is defined by contemporary philosophers as an argument in which a person intends to position premises that guarantee a conclusion. In inductive reasoning, on the other hand, a person intends to conditionally or probabilistically accept the conclusion based on the strength of the premises (The Internet Encyclopedia of Philosophy, 2007). The distinction between historical and contemporary definitions of deduction and induction has a meaningful impact on health education and the quantitative and qualitative methods divide.
Health educators often align quantitative research with deductive reasoning and qualitative research with inductive reasoning. Based purely on contemporary definitions of deduction and induction, however, qualitative research does not necessarily use inductive reasoning, and quantitative research does not necessarily use deductive reasoning. The type of reasoning depends on the intent of the researcher, not on the type of research methods. Furthermore, the type of reasoning is set a priori and should not be changed later. Well supported inductive reasoning does not shift in reasoning type from induction to deduction, and a poorly constructed deductive argument does not change to an inductive argument post hoc.
Health educators should also recognize that the history and definition of induction and deduction largely falls under the philosophy of science and that science has preferred the hypothetic-deductive method for approaching 100 years. However , people develop and maintain their values through scientific methods as well as several other modes of valuing and that: 1) the majority of people in the United States and the world are not scientifically literate, and 2) most people do not use science or reason as their primary mode to understand the natural world.
In contemporary literature, a quadrant of types of or models to research that included exploratory-qualitative, exploratory-quantitative, confirmatory-qualitative, and confirmatory-quantitative research has been positioned. In further bridging the quantitative and qualitative divide, an additional level can and should be added to the quadrant scheme. In the revised categorization of research, types of or approaches to research include: inductive-exploratory-qualitative, inductive-exploratory-quantitative, inductive-confirmatory-qualitative, inductive-confirmatory-quantitative, deductive-exploratory-qualitative, deductive-exploratory-quantitative, deductive-confirmatory-qualitative, and deductive-confirmatory-quantitative research (see Table 1 for description).
In health education, researchers often use statistics or qualitative analyses to describe data, summarize data, or draw inferences from collected data. Due to the probability, biases, fallibility, and/or errors in these research methods and the researchers using these methods, it is very likely that the conclusions of deductive arguments within health education are unfounded or at least overstated. Health educators should base their arguments on inductive reasoning in which conclusions are conditionally or stochastically accepted or declined based on the strength of argument, not on the guaranteed conclusions of deductive reasoning. The use of inductive reasoning in both quantitative and qualitative research adds to the trustworthiness, utility, and soundness of health educators’ arguments. By positioning deductive arguments, health educators often extend beyond the truth of their premises and/or the validity of the argument, and as a result, conclusions and recommendations are sometimes overstated and arguments unsound.
The phenomenon of positioning invalid, untrue, or unsound deductive arguments is common among people. Moreover, Albert Ellis positioned that exaggerated conclusions were the foundation of mental health problems. People often argue, especially regarding emotion-laden or ego-focused topics, as if their under-supported premises and invalid argument structures must support exaggerated conclusions. More often than not, regardless of emotional state, however, the support for deductive arguments is less than adequate in the complexity of the naturalistic social environment. Due to either-or thinking and confirmation bias, people often attempt to understand and control the complexity of the natural world through unsupported or under-supported arguments in which the premises, conclusions, and their interconnections are over simplified. The human tendency to use heurisitics is well documented in the economic and psychological literature (e.g., Kahneman & Tversky). Health educators should recognize this tendency in people in general and health educators in particular. Given that the true distinction between deduction and induction is based on the intention of the person arguing and not necessarily the qualities of the argument itself, unjustified deductive arguments in which premises actually do not guarantee the conclusions in the natural world have contributed to much human suffering or to borrow Daniel Leviton’s term– horrendous death. Deduction is based on guarantees that are typically undersupported in naturalistic research designs. Inductive reasoning leaves more room for discussion of premises and conclusions as well as plurality. Through induction one increases the discussion evidentiary truths and avoids oversimplifying the complexity of many public health programs. Whereas deductive works within a dichotomous perspective of black and white, yes or no, or right or wrong, induction works within a continuum thereby leaving room for discussion for a greater breadth and depth of discussion of complexity and variability.
Table 1. Describing eight distinct categories of research approaches.
1) inductive-exploratory-qualitative Using qualitative methods in data collection and analysis, a researcher engages in a process of discovery without an a priori argument structure and believes that the emerging conclusion is not guaranteed to be true but interprets truth or trustworthiness based on evidentiary support of probabilistic premises.
2) inductive-exploratory-quantitative Using quantitative methods in data collection and analysis, a researcher engages in a process of discovery without an a priori argument structure and believes that the emerging conclusion is not guaranteed to be true but interprets truth or trustworthiness based on evidentiary support of probabilistic premises.
3) inductive-confirmatory-qualitative Using qualitative methods in data collection and analysis, a researcher engages in a process of discovery with an a priori argument structure and believes that the pre-determined conclusion is not guaranteed to be true but interprets truth or trustworthiness based on evidentiary support of probabilistic premises.
4) inductive-confirmatory-quantitative Using quantitative methods in data collection and analysis, a researcher engages in a process of discovery with an a priori argument structure and believes that the pre-determined conclusion is not guaranteed to be true but interprets truth or trustworthiness based on evidentiary support of probabilistic premises.
5) deductive-exploratory-qualitative Using qualitative methods in data collection and analysis, a researcher engages in a process of discovery without an a priori argument structure and believes that the emerging conclusion is guaranteed to be true based on deterministic premises.
6) deductive-exploratory-quantitative Using quantitative methods in data collection and analysis, a researcher engages in a process of discovery without an a priori argument structure and believes that the emerging conclusion is guaranteed to be true based on deterministic premises.
7) deductive-confirmatory-qualitative Using qualitative methods in data collection and analysis, a researcher engages in a process of discovery with an a priori argument structure and believes that the pre-determined conclusion is guaranteed to be true based on deterministic premises.
8 ) deductive-confirmatory-quantitative Using quantitative methods in data collection and analysis, a researcher engages in a process of discovery with an a priori argument structure and believes that the pre-determined conclusion is guaranteed to be true based on deterministic premises.