1.5 Cautions and Challenges from Science

There is no doubt that the scientific method illuminates and illustrates human development as nothing else does. Facts, hypotheses, and possibilities have all emerged that would not be known without science—and people of all ages are healthier, happier, and more capable than people of previous generations as a result.

For example, infectious diseases in children, illiteracy in adults, depression in late adulthood, and racism and sexism at every age are much less prevalent today than a century ago. Science deserves credit for all these advances. Even violent death is less likely, with scientific discoveries and education likely reasons (Pinker, 2011).

Developmental scientists have also discovered unexpected sources of harm. Video games, cigarettes, television, shift work, and asbestos are all less benign than people first thought.

Although the benefits of science are many, so are the pitfalls. We now discuss three potential hazards: misinterpreting correlation, depending too heavily on numbers, and ignoring ethics.

Correlation and Causation

Probably the most common mistake in interpreting research is the confusion of correlation with causation. A correlation exists between two variables if one variable is more (or less) likely to occur when the other does. Thus, there is a relationship or link between one variable and the other. A correlation is positive if both variables tend to increase together or decrease together, negative if one variable tends to increase while the other decreases, and zero if no connection is evident.

To illustrate: From birth to age 9, there is a positive correlation between age and height (children grow taller as they grow older), a negative correlation between age and amount of sleep (children sleep less as they grow older), and zero correlation between age and number of toes (children do not have more or fewer toes as they grow older). (Now try taking the quiz on correlation in TABLE 1.7.)

Expressed in numerical terms, correlations vary from +1.0 (the most positive) to –1.0 (the most negative). Correlations are almost never that extreme; a correlation of +0.3 or –0.3 is noteworthy; a correlation of +0.8 or –0.8 is astonishing.

Many correlations are unexpected. For instance, first-born children are more likely to develop asthma than are later-born children, teenage girls have higher rates of mental health problems than do teenage boys, and newborns born to immigrants weigh more than do newborns of non-immigrants. (All these correlations are discussed later.) At this point, the important caution to remember is correlation is not causation. Just because two variables are correlated, that does not mean that one causes the other; it only proves that they are connected somehow. Many mistaken and even dangerous conclusions are drawn because people misunderstand correlation.

Quantity and Quality

A second caution concerns how heavily scientists should rely on data produced by quantitative research (from the word quantity). Quantitative research data can be categorized, ranked, or numbered and thus can be easily translated across cultures and for diverse populations. One example of quantitative research is the use of children’s school achievement scores to measure the effectiveness of education.

Since quantities can be easily summarized, compared, charted, and replicated, many scientists prefer quantitative research. Statistics require numbers. Quantitative data are easier to replicate and less open to bias, although researchers who choose this method have some implicit beliefs about evidence and verification (Creswell, 2009).

When data are presented in categories and numbers, some nuances and individual distinctions are lost. Many developmental researchers thus turn to qualitative research (from quality)—asking open-ended questions, reporting answers in narrative (not numerical) form. Qualitative researchers are “interested in understanding how people interpret their experiences, how they construct their world” (Merriam, 2009). Qualitative research reflects cultural and contextual diversity, but it is also more vulnerable to bias and harder to replicate.

Developmentalists use both quantitative and qualitative methods (Creswell, 2009). Sometimes they translate qualitative research into quantifiable data; sometimes they use qualitative studies to suggest hypotheses for quantitative research.

One caution applies especially to qualitative research: Scientists must not leap to conclusions on the basis of one small study. In the same way, personal experiences may suggest topics and hypotheses, but the particulars of our lives are no substitute for empirical research on hundreds of other people. Another caution applies to quantitative research: The accuracy of the conclusions depends on exactly how the numbers were defined and collected—a truth that is obvious when you realize that a score of A (80–100 percent) in one class is easier to get than a B (70–79 percent) in another.

A Bite Worse Than Its Bark A crucial question for all scientists is whether their research is ethical and will help solve human problems.

MARK PARISI/ATLANTIC FEATURE SYNDICATE/OFFTHEMARK.COM

Ethics

The most important caution for all scientists, especially for those studying humans, is to uphold ethical standards in their research. Each academic discipline and professional society involved in the study of human development has a code of ethics (a set of moral principles) and specific practices within a scientific culture to protect the integrity of research and research participants.

Ethical standards and codes are increasingly stringent. In Canada, most educational and medical institutions have a Research Ethics Board (REB), a group that permits only research that follows certain guidelines. Although REBs often slow down scientific study, some research conducted before they were established was clearly unethical, especially when the participants were children, members of minority groups, prisoners, or animals (Blum, 2002; Washington, 2006).

Protection of Research ParticipantsResearchers must ensure that participation is voluntary, confidential, and harmless. In Western nations, this entails the informed consent of the participants—that is, the participants must understand and agree to the research procedures and know any risks involved.

If children are involved, consent must be obtained from the parents as well as the children, and the children must be allowed to end their participation at any time. In some other nations, ethical standards require consent of the village elders and heads of families, in addition to that of the research participants themselves (Doumbo, 2005).

Historically, shocking examples of unethical practices—from not treating syphilis to neglecting babies—include some “studies carried out by respected psychologists and published in the finest journals of the day. We’ve come a long way since then, baby. And babies are grateful.” (Stephen L. Black, personal communication, 2005).

Protection of participants may conflict with the goals of science. The Canadian Psychological Association suggests ways to resolve this conflict. Its four guiding principles are

1. respect for the dignity of persons, which includes such factors as non-discrimination, informed consent, and confidentiality
2. responsible caring, which involves competence and the intention to maximize benefits while minimizing harm
3. integrity in relationships, which emphasizes an objective approach to research and the complete avoidance of any conflict of interest
4. responsibility to society, which involves the general development of knowledge that will benefit society as a whole.

Note that all four of these principles should be followed, if possible, but they are ranked in order of importance: Respect for individuals is most important (Canadian Psychological Association, 2010).

Implications of Research ResultsOnce a study has been completed, additional issues arise. Scientists are obligated to promote “accuracy, honesty, and the obvious prohibitions of fraud or misrepresentation” (Canadian Psychological Association, 2000).

Deliberate falsification is rare. When it does occur, it leads to ostracism from the scientific community, dismissal from a teaching or research position, and, sometimes, criminal prosecution. Another obvious breach of ethics is to “cook” the data, or distort one’s findings, in order to make a particular conclusion seem to be the only reasonable one. This is not as rare as it should be. Tenure, promotion, and funding all encourage scientists to publish, and publishers to seek, remarkable findings. Researchers recognize the “file-drawer” problem—studies that do not demonstrate significant findings are relegated to personal files rather than publication, creating a bias in the scientific literature in favour of those studies that do demonstrate statistically significant results. This is problematic since it may be important to know that findings were not significant. Awareness of this danger is leading to increased calls for replication (Carpenter, 2012).

Insidious dangers include unintentionally slanting the conclusions and withholding publication of a result, especially when there is “ferocious…pressure from commercial funders to ignore good scientific practice” (Bateson, 2005). Similarly, non-profit research groups and academic institutions pressure scientists to produce publishable results.

Ethical standards cannot be taken for granted. As stressed at the beginning of this chapter, researchers, like all other humans, have strong opinions, which they expect research to confirm. Therefore, they might try (sometimes without even realizing it) to achieve the results they want. One team explains:

Obviously, collaboration, replication, and transparency are essential ethical safeguards for all scientists.

What Should We Study?

Finally, the most important ethical concern for developmentalists is to study issues that will help “all kinds of people, everywhere, of every age” live satisfying and productive lives. Consider these questions, for instance:

• Do we know enough about prenatal drug abuse to protect every fetus?
• Do we know enough about poverty to enable everyone to be healthy?
• Do we know enough about same-sex relationships, or polygamy, or single parenthood, or divorce, to make sure all people develop well no matter what their family structure?
• Do we know enough about dying to enable everyone to die with dignity?

The answer to all these questions is a resounding NO. The reasons are many, but a major one is that these topics are controversial. Some researchers avoid them, fearing unwelcome and uninformed publicity (Kempner et al., 2005). Few funders are eager to support scientific studies of drug abuse, poverty, non-standard families, or death, partly because people have strong opinions on these issues that may conflict with scientific findings and conclusions. Religion, politics, and ethics shape scientific research, sometimes stopping investigation before it begins. Yet developmentalists must study whatever benefits the human family.

The next cohort of developmental scientists will build on what is known, mindful of what needs to be explored. Remember that the goal is to help all 7 billion people on Earth fulfill their potential. Much more needs to be learned. This book is only a beginning.