Problems of Modern Science Research

When John Snow Father of field Epidemiology contained a cholera outbreak in 1857 London the only collaboration he could afford was from Newcastle surgeon Thomas Michael Greenhow. Equipped with no microscope or prior knowledge of microorganisms, Snow used logical reasoning, a map, and a hypothesis to demonstrate how the 19th-century cholera epidemic was transmitted via a contaminated water supply system. Despite facing rejection for his “germ theory”, he singlehandedly transformed what would now be known as epidemiology (study of epidemics).

Today, epidemiology and other areas of life science have evolved with more reliable mathematical methods and advanced statistical data models to justify findings. Researchers are better equipped to observe causes, evaluate the distribution of illnesses, and recommend preventive measures for chronic and non-chronic diseases including mental health-related illnesses. The analogy of John Snow is almost similar to other leading figures in the life sciences. Worthy mentions among others include Alexander Flemming’s discovery of the antibiotic penicillin and the sanitary medical practices introduced by Joseph Lister. The constant variable here is that pre-modern researchers have mostly delivered groundbreaking research with little or no access to the sophisticated gadgets and knowledge available today.

The process of data collection and analysis in science has greatly improved.?

In this article, we examine the problems that limit modern science and research in its service to humanity, society, and industry.?

Problems and Challenges of Modern Science and Research

The Pressure of Science Research

The science field itself tends to accord respect to scientists based on the quantity of research published and how groundbreaking they are. But how often do revolutionary discoveries occur? Still, this ideal has reportedly determined what and who gets published in prestigious journals today. While this tradition can fan innovation, it also traps researchers in an exhaustive cycle of anxiety and pressure for that groundbreaking discovery. They strive to collect and analyze data at an unhealthy pace which many scientists admit can tempt one into cutting corners and compromising the quality of research.?

A Vox survey with PhD student Jess Kautz at the University of Arizona revealed how the overwhelming stress of data analysis could be detrimental to research findings. There is also an underlying pressure to present the findings as great even if they are mediocre.

Unfortunately, such revelations unravel modern science’s obsession with churning out a novel or groundbreaking research. Again, this can not prevail if researchers still have to work with manual methods of data collection and analysis.

1. Research Process Outdated & Time-consuming

Most modern scientists due to their commitments to the discipline are often subjected to extremely tedious research processes. For people pursuing lifelong careers in research, the task of scanning every scientific literature for relevant information and reviewing research methods does little in minimizing errors in their results. Researchers have no option but to bear the brunt in the name of advancing science. This is because today’s research systems often reward the most significant results and publications more than the process.?

A good instance is the emergence of meta-researchers who now realized that even scientists may be guilty of exaggerating their results. Although this may not be done consciously, a study has shown that p-values [used to validate hypothesis using data] have been misused in biomedical journals.? This method popularly knowns as the p hacking technique demonstrates how researchers showcase only data that validates their hypothesis while simply burying critical results that don't look significant enough.?

This is the 21st century where AI and machine learning are already moving weight in other areas of society. On this side, scientists are barely equipped with research tools that can simplify their research exercises in seconds.

2. Decision-makers at science institutions and firms must remember that a field that does not simplify its processes for research convenience and academic ease only prepares itself for implosion and disaster.

Already, the same meta researchers report an estimated $200billion [approximating to 85percent of global research spending] is sunk into terrible research designs and studies that yield nothing.?

Proving this, Professor of Social Psychology at UC Davis, Simine Vazire who also doubles as a journal editor recommends a system that favors research procedures more over research outcomes. "Grants, publications, jobs, awards, and even media coverage should be based more on how good the study design and methods were, rather than whether the result was significant or surprising."

3. Limited Access to Data

Access to data remains the lifeblood of quality research. A clear instance is during the 2019 COVID pandemic when many scientists were confronted with travel restriction issues. Undoubtedly, such situations would have a huge impact on fieldwork and research collaboration. Scientists who usually have to travel to build networks for their research programs will be compelled to work with what is available. This limits the scope of research by default and even hurts the potential for early-career researchers who want to explore more. Such scenarios could create spaces in long-term data sets and even cause some researchers to lose their entire experiments.

Data access remains challenging as most data repositories are either non-existent or not equipped to be fully online. Access to data fuels both public and private-funded research so why should researchers suffer scarcity of data?

During the Covid19 pandemic, access to online viral genome repositories improved how vaccines were developed and also the viral surveillance.

Unfortunately, the reactive approach to research especially during public health crises discourages the adoption of such repositories. Curiosity and mission-driven research still need to thrive. Life science institutions and firms and their biotech counterparts should be encouraged to invest in, and empower their research teams with platforms that promise unlimited access to research literature and data.

4. Inaccuracies? & Research Deficiency Issues

What is the essence of speed without accuracy? As indicated earlier, modern science’s obsession with the “novel or new” can have its downsides. Such research culture sometimes compels scientists to publish at an alarming rate while reminding them to also chase good and positive results. The graph below presents the usage of the word "novel" in the titles and abstracts of research in Pub Med peaking from the 80s.

And, as we noted earlier, research processes built this way tend to birth many research deficiencies and low-quality studies. To be plain, the researchers simply do not have the capacity or the technical support mechanisms to keep up with such a pace. For instance, when basic search engines are used to gather academic insights instead of dedicated academic search engines then inaccuracies or redundant studies become inevitable.??

Tim Gowers a Mathematician at Cambridge believes more focus should be on thought processes that yield research rather than the research itself. Catchy and front-cover-worthy results are sensational and trigger mass appeal but the dangers of inaccuracies easily overwhelm such research attitudes. It causes a conflict of interest according to Joseph Hilgard, a postdoctoral research fellow at the Annenberg Public Policy Center. "The scientist is in charge of evaluating the hypothesis, but the scientist also desperately wants the hypothesis to be true."

In conclusion, there is indeed pressure on modern scientific research to go where its founding figures have never gone. The quest for the “novel” and ”groundbreaking” is still ongoing. Such a journey will yield true treasures when modern research evolves with more equipped tools for its research, data extraction, and analysis.?

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