This weekend’s “long read” is a study by Massachusetts General Hospital and 10 academic partners trying to determine if there is a link between social media use and depression. Spoiler: The researchers found some specific correlations, but they raise many more questions than they answer.
The researchers recruited 8,000 people on the internet to participate in the study. They surveyed the study participants on which of eight social media sites and apps they used and also asked participants to complete a commonly used assessment of whether someone is showing signs of depression, called the Patient Health Questionnaire 9 (or PHQ-9). The assessment asks nine questions about specific symptoms and assigns 0–3 points per question, depending on how often the patient exhibits each symptom. The higher the PHQ-9 score, the more severe the signs of depression.
This weekend’s long read is a research paper from the leading medical research journal in the U.K., The Lancet. The paper, however, has local roots: It was authored by researchers at the University of Washington’s Institute for Health Metrics and Evaluation. The paper attempts to ascertain the accuracy of statistics on U.S. deaths caused by police in the National Vital Statistics System (NVSS), the Centers for Disease Control and Prevention’s (CDC) official repository on births and deaths.
The NVSS collects data from death certificates, including the cause of death. Usually a physician fills out the death certificate, but it could be completed by a coroner or medical examiner instead if there is suspicion of crime, foul play, or police violence. However, that creates a conflict of interest, as the paper describes, if the same government responsible for police violence is also responsible for reporting it.
This weekend’s “long read” is a column from Dr. Arnold S. Monto, an epidemiologist at the University of Michigan School of Public Health. Our hopes that COVID-19 could be eradicated, he says, were based on faulty assumptions, and we now need to shift to planning for how we will deal with the virus for the foreseeable future — much the same way that we manage influenza.
This weekend’s “long read” comes from investigative journalism organization InvestigateWest, and it dives into why childcare services are so expensive in Washington — and across the nation.
Childcare in our state can be ruinously expensive for families, costing anywhere from $11,000 per year for a 4-year-old in a program designed to meet the state’s minimum standards, to over $30,000 for an infant in a “high quality” childcare center. But if you think providers are raking in the money, you’d be wrong; most of them are operating on thin margins.
Each year nearly $4 trillion is spent on health care in the United States; of that, about one-quarter, or $950 million, is spent on administrative expenses. This week’s “long read” is a report by the business consultant McKinsey & Company on how money could be saved through administrative simplification and other business process improvements.
American health care is a multi-payer (over 900 of them), largely for-profit system. The benefit of such a system is that it can drive innovation in technology and treatments, as we have seen during the COVID-19 pandemic with vaccines to reduce infections and new drugs to treat the disease. But as we all know only too well, it is a broken system in many aspects: It’s expensive, often inefficient, and far less than comprehensive. Many of the policy decisions that brought us to this point are beyond the scope of McKinsey’s study, but it doesn’t take much work to identify the inefficiency and expense derived from the overhead of having multiple payers, providers, and patients. The health care industry is also heavily regulated, which protects patients but creates additional overhead for compliance.
This week’s “long read” is light on words and heavy on charts and graphs. It’s a comparison of the cost to generate electricity from a number of different sources, both clean and dirty.
The business and finance consultant company Lazard has compiled an analysis of the “levelized cost of energy” every year since 2007. By “levelized,” they mean that they factor in all of the costs: capital costs to build out electricity generation facilities, including the materials, manufacturing, construction, installation, permitting, and property; ongoing operational and maintenance costs; fuel costs for the types of generation that require fuel; and regulatory costs. They calculate the expected operational lifetime of a power generation facility and then divide the sum of the costs by the total expected power generation over a facility’s lifetime to arrive at a cost per megawatt-hour.
Over the past 18 months, I’ve read well over a hundred research papers on COVID-19, treatments, and vaccines. This week’s “long read” is hands down the most informative of all of them.
One of the essential tenets of science is that it must be repeatable: Every time an event happens, we should expect the same result. In practice we often don’t see precisely the same result, even in laboratory conditions, because of experimental error, contamination, sampling error, unknown confounding factors, and bias (intentional or otherwise). That’s why in the world of science a single research study alone isn’t enough to establish new knowledge; the scientific community waits until other researchers have replicated the study and independently confirmed the results.
In our mad rush to save lives by developing treatments and vaccines for COVID-19, we have often substituted a single carefully crafted and skeptically reviewed clinical trial for the greater assurance that we would get with multiple complete studies — at least for the purposes of “emergency use authorization” by the U.S. Food and Drug Administration (FDA). But with the passage of time, and the need to recertify the vaccines in multiple countries, there is now a substantial number of vaccine studies that have been published. Together they give us much higher confidence in our estimates of the effectiveness of the vaccines.
This weekend’s “long read” is an article published by Noah Smith, looking at the productivity of construction workers and how it’s measured.
The conventional wisdom is that for decades construction productivity has been in a slow decline, in sharp contrast to other intensive industries such as agriculture and manufacturing. This graph from the Economist sums up the picture well:
This week’s long read is a survey — but mercifully one that doesn’t ask a single question about candidates on the November ballot. The local organization sea.citi, which bills itself as “a tech industry nonprofit strengthening our region by promoting civic engagement and building relationships between community, government, and innovation workers,” recently polled Puget Sound-area tech workers to test their views on a range of civic issues, their employers’ actions, and where they want to live and work post-pandemic.
The report buries the demographic data in the back, but it’s worth addressing it first to provide some context because tech workers are not representative of the general population in the Seattle area. Not surprisingly, the survey group skewed male, white, and middle-aged. They also are predominantly transplants to the area: 72% of them moved here as an adult.
This week’s “long read” is an article in the journal Nature, looking at the long and complicated path leading to the mRNA vaccine technology and techniques used to create the Moderna and Pfizer vaccines against COVID-19.
“Messenger RNA,” or mRNA, is essentially a recipe for building proteins. Living cells use it as a way of passing notes around: Parts of our DNA are transcribed into mRNA, which is then read by the tiny factories in our cells that produce proteins.
Technically, a virus isn’t alive: It’s just a string of genetic material surrounded by a coating of fat (what biologists call “lipids”) with some proteins on the surface that help it to gain access into our cells (such as the COVID-19 “spike protein”). Once a virus invades our cells, its DNA is also transcribed into mRNA that contains the blueprint for the virus, and then our own cells do all the hard work to churn out thousands of virus copies.