Ask: what is the question?
Read the title and abstract. What exactly did researchers want to understand? Was it temperature, energy use, comfort, or health?
You don't need a research degree to ask good questions about evidence. Start here.
Most people do not need to read an academic paper line by line. A few careful checks go a long way.
Read the title and abstract. What exactly did researchers want to understand? Was it temperature, energy use, comfort, or health?
Was the study done in a single home, an entire city, a laboratory, or a simulation? Which climate, building type, and season?
Actual energy bills? Indoor sensors? Satellite surface temperatures? Modeling? The method determines what conclusions are possible.
Read the figures and results. Then compare them with the discussion and conclusions. Look for magnitudes, uncertainty, and sample size.
A finding may apply only to specific walls, seasons, equipment, or climates. A correlation does not by itself prove a cause.
Use the DOI link to check the original publication. A publisher page may be paywalled; look for a legal open-access version when available.
A very short outline of the question, approach and main finding. Start here, but do not stop here.
Why the question matters and what earlier studies did or did not show.
Who or what was studied, how data were collected, and what analytical tools were used.
The measured or modeled findings, including charts, tables and uncertainty.
What the researchers think the results mean and how they compare with other work.
What the study cannot establish and where generalization may be inappropriate.
Where the evidence came from and how to find the original publication reliably.
A headline saying “scientists found” does not tell you how evidence was gathered. These common publication types answer different questions.
Researchers collect or analyze data to answer a particular question. This might involve indoor temperature sensors, energy bills, satellite images, laboratory tests or simulations.
Researchers place sensors in ten homes during a heatwave and report what the instruments measured.
Check: How many homes? Were there comparison homes? Was this measured or modeled?
Authors describe and discuss earlier studies on a topic. A general or narrative review can give useful background, but how papers were chosen may be less systematic.
An article explains what past studies say about roof insulation, windows and summer comfort.
Check: Which studies were included? Was the selection method explained?
Researchers follow a documented process to search for, select and assess studies on a defined question. It can help reveal where findings agree and where evidence is weak.
A team searches databases using pre-set criteria to find studies testing urban tree cooling.
Check: Which databases and years? Were weaker studies evaluated?
Researchers statistically combine results from multiple studies when the data are suitable. It may give a more precise overall estimate, but combining very different studies can mislead.
Researchers combine comparable studies to estimate a typical measured response, while checking why results differ.
Check: Were the measurements comparable? How much did results vary?
A manuscript shared publicly before formal journal peer review. It can provide early access to useful ideas, but its methods or conclusions may change.
A researcher shares a new analysis of heat-pump performance while it is being evaluated by a journal.
Check: Has a reviewed version appeared? Is this the latest version?
Reporting can make research accessible, but it is usually not the original study. Headlines may simplify findings or omit important limits.
A website says “Trees reduce city heat by 10 degrees!” without saying which temperature, where or under what conditions.
Check: Can you click through to the original study and verify the claim?
Helpful further reading: NIH guide to research methods ↗ and Cochrane guidance on meta-analysis ↗.
A satellite may show that a black rooftop is 50°C while a lighter rooftop is 38°C. That does not mean the living room became 12°C cooler or that the outdoor air dropped by 12°C. The camera is measuring the surface, not the room or the surrounding air.Ask: What temperature was measured—surface, outdoor air, or indoor air?
Imagine researchers compare a leafy neighborhood at 27°C with a less green area at 30°C. It is tempting to say the trees caused all 3°C of difference. But the areas might also have different building density, traffic, elevation or wind. Without additional tests, we cannot know how much difference comes from trees alone.Ask: Did researchers compare equivalent conditions or rule out other explanations?
A computer model predicts that upgrading a home’s insulation will save $300 a year. That is a prediction based on assumed weather, energy prices, thermostat settings and construction quality. The family’s actual bills might show a different saving.Ask: Is this a predicted saving, or did someone measure it in a real home?
A study finds that exterior shading helped reduce overheating in houses in a hot, sunny climate. That does not tell us the exact savings for an apartment in Toronto, or for a house where winter heating matters more. The same design can have different benefits and drawbacks in different places.Ask: Is the building, climate and situation similar to mine?
Open a paper in our library, read its summary, and compare the explanation with the original study.
Explore reviewed studies ↗