The hottest Research Methods Substack posts right now

And their main takeaways
Category
Top Science Topics
UX Psychology β€’ 238 implied HN points β€’ 14 Jun 22
  1. Triangulation in UX research involves using multiple research methods or data sources to study the same phenomenon, enhancing credibility and providing more robust insights.
  2. There are 4 main types of triangulation recognized in research: data triangulation, investigator triangulation, theory triangulation, and methodological triangulation.
  3. Using triangulation in user research can lead to more confidence in data, reveal unexpected findings, and help to understand a problem more clearly, although it may also increase chances of confirmation bias.
The Path Not Taken β€’ 462 implied HN points β€’ 16 Sep 23
  1. Academia may struggle to develop a theory of progressivism if there are few conservatives involved.
  2. There is a lack of academic work on progressivism despite significant changes in left-wing ideology.
  3. The lack of conservatives in academia may hinder the growth of research on progressivism and lead to challenges in developing a comprehensive theory.
Scott's Substack β€’ 39 implied HN points β€’ 05 Feb 24
  1. Triple difference design can be used with continuous treatment by defining the parameters based on dosage levels.
  2. When treatment is continuous, the target parameter shifts from average treatment effect to average causal response function.
  3. Continuous treatments require careful definition of parameters to compare different dosages along a treatment curve.
The Polymerist β€’ 116 implied HN points β€’ 06 Nov 24
  1. Try new things in your career and treat them like experiments. If something doesn't work out, you can always adjust and try again.
  2. It's okay to feel uncertain at the beginning of your career. Each experience helps you learn more about yourself and what you want.
  3. Life will always bring challenges, but keep moving forward and experimenting. Enjoy the process of learning and discovering new possibilities.
UX Psychology β€’ 59 implied HN points β€’ 03 Nov 23
  1. Social loafing in human-computer teams can lead to reduced human effort over time, even if participants report consistent effort and engagement.
  2. Humans may rely excessively on dependable robotic or AI teammates, potentially impairing human attentiveness and performance.
  3. Mitigating the effects of social loafing in human-computer teams can involve strategies such as establishing individual accountability, validating robot or AI performance, and designing robots/AI to provide motivation to human teammates.
Get a weekly roundup of the best Substack posts, by hacker news affinity:
Weight and Healthcare β€’ 299 implied HN points β€’ 15 Dec 21
  1. Correlation does not equal causation. Just because two things happen together doesn't mean one causes the other.
  2. Research on weight and health often overlooks confounding variables like weight stigma, weight cycling, and healthcare inequality.
  3. Assuming higher weight causes health issues has led to harmful practices, like the weight loss industry profiting from perpetuating weight stigma and promoting ineffective solutions.
The Counterfactual β€’ 39 implied HN points β€’ 13 Dec 23
  1. Large Language Models (LLMs) could make scientific research faster and more efficient. They might help researchers come up with better hypotheses and analyze data more easily.
  2. Breaking down the research process into smaller parts might allow automation in areas like designing experiments and preparing stimuli. This could save time and improve the quality of research.
  3. While automating parts of scientific research can be helpful, it's important to ensure that human involvement remains, as fully automating the process could lead to lower-quality science.
The Counterfactual β€’ 59 implied HN points β€’ 27 Jun 23
  1. Measuring abstract concepts like happiness is really tough. Researchers need to find good ways to define and measure these big ideas accurately.
  2. Construct validity is important for any type of research claim. It checks if what you're measuring actually reflects the concept you're interested in.
  3. Making decisions, like hiring or choosing a restaurant, involves relying on imperfect measures. It's essential to understand the limitations of these measures to make better choices.
inexactscience β€’ 39 implied HN points β€’ 09 Aug 23
  1. Relying only on randomized experiments can be limiting. It's important to consider all types of evidence based on their quality.
  2. Not every decision needs a complex A/B test; sometimes simpler data or even gut feelings are enough.
  3. We should weigh the cost of getting reliable data against the value it provides. For some choices, high-quality data is a must, but for others, less rigorous information can do the job.
ASeq Newsletter β€’ 36 implied HN points β€’ 11 Feb 25
  1. Microarrays are often seen as an alternative to sequencing, but some argue sequencing is generally a better option for many applications. It's important to consider these viewpoints when discussing the technologies.
  2. The microarray market is stable, worth around $1 billion, with platforms like Illumina's Beadarray holding a significant share. This indicates that there is still a solid demand for microarray technology.
  3. Reassessing biases about technologies like microarrays can help us understand their current relevance and future potential. It’s always a good idea to keep an open mind when evaluating scientific tools.
Weight and Healthcare β€’ 159 implied HN points β€’ 27 Oct 21
  1. The Weight and Healthcare Newsletter explores weight science, weight stigma, and healthcare, offering valuable information to support individuals dealing with medical weight stigma.
  2. Weight stigma in healthcare causes significant harm, especially to individuals with higher weights and multiple marginalized identities. There is a more helpful and less harmful paradigm available through examining evidence and lived experiences.
  3. Positive changes are possible in healthcare regarding weight-inclusive care and best practices. Education and dialogue can lead to improved understanding and practices among healthcare professionals.
A Biologist's Guide to Life β€’ 42 implied HN points β€’ 14 Dec 24
  1. Using 'anti' labels in discussions can over-simplify and misrepresent people's true beliefs. It makes conversations harder and ignores important details.
  2. Questioning vaccines or other technologies doesn't mean being against them; it can be a way to improve them. Critics should be heard instead of labeled negatively.
  3. Curiosity and open-mindedness in science can lead to better understanding and advancements. Engaging with skepticism might help scientists and the public work together more effectively.
Living Fossils β€’ 31 implied HN points β€’ 12 Feb 25
  1. Ego depletion, the idea that willpower decreases after making tough choices, has been largely debunked. Many studies found that there is no strong evidence to support this theory.
  2. The ego depletion debate shows how important solid theories are in science. Without a strong theory, even widely accepted ideas can lead researchers astray.
  3. Psychology needs to be more disciplined in building ideas that align with what we know about the human mind and evolution. This helps avoid wasting time on false concepts.
UX Psychology β€’ 79 implied HN points β€’ 11 Apr 22
  1. Participants in research studies often change their natural behavior to match what they think the researcher expects.
  2. Demand characteristics, the Hawthorne effect, and social desirability bias are related but have subtle differences in how they impact participant behavior.
  3. To mitigate the impact of demand characteristics in UX research, strategies like using a double-blind approach, being mindful of participant cues, recruiting diverse participants, and employing methodological triangulation can be effective.
inexactscience β€’ 39 implied HN points β€’ 27 Mar 23
  1. Running Coibion-Gorodnichenko regressions with individual data can lead to misleading results. It's important to use appropriate data types to avoid confusion in the findings.
  2. Individual forecasts tend to produce negative results compared to positive results in average forecasts. This means that the insights from these regressions can differ significantly based on the data used.
  3. The methodology is sensitive to noise and measurement errors, which can skew results. Researchers need to be cautious and robust in their approach to ensure accurate interpretations.
Never Met a Science β€’ 33 implied HN points β€’ 16 Dec 24
  1. Survey experiments help researchers understand how political choices are influenced by different factors. They combine theories from political science and public opinion to analyze voter behavior.
  2. The history of survey experiments shows a shift between theory and empirical data. Political science focused on testing theories with limited data, while public opinion research prioritized random sampling to gather accurate data about citizen views.
  3. Different academic traditions use survey experiments for different reasons. Understanding these differences can help avoid confusion and improve collaboration across fields.
What's Important? β€’ 26 implied HN points β€’ 11 Jan 25
  1. The Telepathy Tapes suggests that some non-speaking autistic children may have psychic abilities like telepathy. This idea challenges traditional views of science and consciousness.
  2. While the podcast may present intriguing cases, it is not a formal scientific study, and the findings need more thorough investigation to be validated.
  3. Many people find the messages from the children in The Telepathy Tapes align with spiritual beliefs, sparking a broader discussion about the nature of consciousness and human connection.
Jakob Nielsen on UX β€’ 27 implied HN points β€’ 07 Nov 24
  1. AI can now operate computers just like humans, which means it can click, type, and understand what’s on the screen. This makes using computers easier for everyone, especially for those who struggle with traditional interfaces.
  2. AI agents are expected to take over simple tasks for users, like booking hotels or managing reservations, making life more convenient. However, understanding personal preferences may take some time for AI to improve.
  3. AI's capability to watch and analyze user interactions can help conduct usability studies more effectively. This could lead to better products, as AI can help gather insights about how real users behave.
ASeq Newsletter β€’ 14 implied HN points β€’ 13 Feb 25
  1. Acorn Genetics is working on a new type of DNA sequencing technology. This technology promises to be fast, giving results in just minutes.
  2. The platform aims to be affordable, costing less than $10,000, which could make it accessible to more users.
  3. One of the cool features is that it won’t require any training to use, meaning anyone could operate it easily.
ASeq Newsletter β€’ 14 implied HN points β€’ 30 Oct 24
  1. Vendors sometimes quote theoretical maximums for data output, which can be misleading. It's important to understand that these numbers might not reflect actual performance.
  2. Comparing different technologies can be complicated because they have different specifications and capabilities. Each technology, like PacBio, Oxford Nanopore, and Illumina, has its unique strengths and limitations.
  3. In the real world, the difference between what is theoretically possible and what is actually achieved can be significant. This means we should be cautious and not rely solely on theoretical figures.
Data Science Weekly Newsletter β€’ 19 implied HN points β€’ 13 Oct 22
  1. Building a community around R in the pharmaceutical industry can help users connect and share knowledge more effectively. It's important to identify who the users are and create a space for collaboration.
  2. Creating research ideas can start with understanding gaps in existing literature. By reading a single paper, you can learn frameworks to generate new ideas and improve your research quality.
  3. Data cleaning for machine learning models is crucial, starting from the ETL pipeline. It’s important to commit to high-quality data from the beginning to avoid common pitfalls that impact model accuracy.
Axial β€’ 7 implied HN points β€’ 31 Jan 25
  1. Researchers used a special microscope to watch how nucleosomes and chromatosomes come apart in real-time. This lets us see important details about how these DNA structures change.
  2. The study found that the disassembly process is not symmetrical; some parts come off before others. This shows a new way that DNA is accessed for various functions.
  3. Linker histone H1 plays a big role in how these structures disassemble. When H1 is present, it makes the process slower and changes the way the nucleosomes fall apart.
Creating Inequality β€’ 4 HN points β€’ 14 Jun 23
  1. Pecking orders in animals might not be based on individual abilities but on dynamic interactions within a group.
  2. Linear pecking orders can arise from intricate behavioral dynamics rather than differences in individual qualities.
  3. Pecking orders are not stable and enduring, but rather constantly changing structures formed by ongoing aggressive interactions within a group.
Weight and Healthcare β€’ 2 HN points β€’ 15 Oct 22
  1. The National Weight Control Registry's definition of weight loss success may not accurately represent the reality of weight loss maintenance.
  2. The NWCR's findings do not conclusively disprove the idea that weight loss attempts fail about 95% of the time.
  3. The NWCR's suggested behaviors for weight loss maintenance lack specificity and may not be effective for the general population.
Niko McCarty β€’ 0 implied HN points β€’ 25 May 24
  1. Biotechnology needs a common foundation, much like how hydrogen is essential to physics. This foundation would help scientists work together more effectively and share their findings.
  2. If scientists could collaborate and understand life better, they could design solutions for diseases and other challenges. This could lead to a future where we have more control over creating living organisms for our needs.
  3. Focusing on studying a simple organism like Mycoplasma genitalium could be key to building this foundation. By deeply understanding it, we could create models that help us predict how other cells function.
ASeq Newsletter β€’ 0 implied HN points β€’ 27 Feb 25
  1. Roche is working on new nanopore sequencing technology, focusing on how much the instruments will cost to produce. Understanding these costs is important for the technology's success.
  2. The nanopore sequencing process involves collecting a large amount of data quickly, which means the data rates are extremely high. This could lead to challenges in storing and processing such vast amounts of information.
  3. Since the raw data volume is so large, it's unlikely that most users will store it all. Instead, they will probably need to focus on analyzing only the most crucial information collected.
School Shooting Data Analysis and Reports β€’ 0 implied HN points β€’ 30 Sep 18
  1. There is a lack of accurate and consolidated statistical data on school shootings in the USA.
  2. The K-12 School Shooting Database was created to address this data gap by including detailed incident information and sources for further research.
  3. The database collects data from various sources, filters incidents, and provides interactive analysis tools for users to generate more accurate reports and make informed decisions.
Hypertext β€’ 0 implied HN points β€’ 27 Mar 24
  1. Experimentation and evaluation are crucial in discovering effective social solutions; funding should consider reinvestment in programs with null results for improvements.
  2. Interpreting null findings from programs is important; reasons for ineffectiveness could range from program inefficacy to delivery issues or changing environments.
  3. Being cautious in prioritizing 'evidence-based' programs is necessary; it may hinder innovation and obstruct the quest for better solutions.
Nano Thoughts β€’ 0 implied HN points β€’ 20 Jan 25
  1. Not all zeros in data mean the same thing. Sometimes, they can indicate something was never there, or other times, they mean something was just missed.
  2. Zero inflation happens when there's lots of data and many readings come back as zero. This can make it hard to understand what's really going on behind those zeros.
  3. There are different methods to deal with zeros in data, like checking if they are real or just unnoticed signals. Choosing the right method is important to get accurate insights.