Here is where you'll find out exactly how we frame our policies for researching, writing, reviewing, and revising content.
At Perfect Hair Health, we are committed to providing accurate, original, and comprehensive articles about hair loss science. We distill complex research into lay terms to empower hair loss sufferers with unbiased, evidence-based information. Our research methodologies and peer-review policies allow us to create content that we believe far surpasses other consumer resources.
This editorial guide explains our writing style, how we create content, and how we conduct research.
Our writing style takes a conversational approach (i.e., "we", "our") – with an emphasis on academic and historical perspective changes across any hair loss topic. We believe that conveying the story of how a belief, treatment, or research avenue came to be is a far more compelling story than solely presenting readers with bulleted facts.
Our content is written with transparency in mind. Instead of making outright statements about our research, we take the reader through a journey to logical conclusions. We want our audience to feel a part of every single step of our methodology. We don’t want our readers to take everything we say at face value; we are committed to maintaining their trust with every piece of content.
To create content for Perfect Hair Health, we start by fielding our membership community. Members of the community often request specific topics of which we continuously compile in an internal list.
Once a topic is selected, we begin to compile information related to that content piece. We leverage a list of questions that are standardized across different article types (treatments, study overviews, ultimate guides, etc.). This guides our writers through a research framework that underpins the content creation process for our in-house writers and researchers.
It is critical that our researchers are not only involved in the scientific or medical field, but also specialize in hair loss research. This is why, for every article, we staff at least one person who is the first author of at least one peer-reviewed publication regarding hair loss.
When working on a new article, we disperse the responsibilities of research collection and synthesis across multiple people in the medical and/or scientific field. This reduces the risk of research "blind spots" and helps us create a more robust, comprehensive content piece.
Strategies for research vary by article type, but, in general, look like the following:
- Identify the latest literature review from a top-ranked dermatology journal. Read the article in full, as well as its references.
- Find previous literature reviews from top-ranked dermatology journals dating 5, 10, and 20+ years prior to understand the historical evolution of the field, the current consensus, where research is heading, and which questions remain to be answered.
- Use PubMed, Google Scholar, and other research databases to conduct search terms related to the article to identify publications that these literature reviews may not have identified.
- Comb through all studies to unearth the objectivity, data collection practices, and conflicts of interests of the individual studies.
- Use this information to begin answering the research questions identified at the outset of research, revising with new questions as necessary, until all research has been collected.
Our researchers are then instructed to organize these findings in an easy-to-understand, logical, thorough, and compelling order to ensure any ambiguities on a given topic are uncovered for readers. We emphasize the importance of highlighting the highest quality of studies while letting our readers in on any caveats and nuances within the available research.
Response and Regrowth Rates
In our content on specific hair loss treatments, we like to provide objective calculations of response rates and regrowth rates. This gives our readers a clear idea of what they should expect from any given treatment.
Response rates and regrowth rates are catalogued as percentages of a test population. Response rates are defined by the average number of subjects who experience a slowing or stopping of hair loss, as well as any degree of hair regrowth. If studies report a change in absolute hair count, this data is used to calculate the average percentage of hair regrowth that subjects experience.
The calculations process our research team employs is as follows:
- Researchers comb through individual studies to identify data such as hair counts, investigator assessment, and patient satisfaction.
- Subjective data like investigator assessment and patient satisfaction can be used to calculate a response rate. Objective data like hair counts can be used to calculate both response rates and regrowth rates. However, regrowth rates can only be determined using objective hair counts.
- For response rates, the number of patients who report a positive outcome are averaged per study. Then, all averages are added together and divided by the number of studied to calculate a more comprehensive response rate.
- For regrowth rates, studies that do not report hair counts are excluded. From the remaining studies, the difference between the average baseline hair count and final assessment hair count are calculated. Then, this difference is divided by the average baseline hair count to produce a percentage-based regrowth rate for each individual study. Finally, the data from all applicable studies are added together and divided by the number of data sets retrieved to produce an estimated regrowth rate.
General regrowth and response rates are reported at the beginning of each article, with some study-specific calculations dispersed throughout the body of an article.
In some cases, clinical response and regrowth rates are not always reflected in real-world experience. There are many variables that can influence the clinical-to-real-world translation that can’t always be accounted for in research. In spite of these variations, we strive to provide a general ball-park estimate for our readers.
Upon delivery of an article draft, the article is shared with other members of the team, where questions, clarifications, and revision requests are proposed.
Upon addressing these comments, articles are delivered to the lead researcher and writer for final revisions and copy editing. During final revisions and copy editing, the lead researcher and writer will often inject personal experiences as well as anecdotes from readers into the article that are relevant to the questions answered.
Starting in 2019, after final copy editing is complete, articles undergo an informal peer-review process prior to publication. This is where a medical professional with peer-reviewed publications and/or experience in dermatology and/or hair loss research is sent the article for fact-checking, updates, and final revisions. Upon receiving these revisions, the lead editor and writer incorporates them into the article, and the article is then published and sometimes shared across subscribers.
We strive to provide information that is 100% unbiased, accurate, and evidence-based. While our editorial policies create a framework for minimizing errors, mistakes do happen. In cases where errors occur – or where information evolves and requires an article to be updated – immediate action is taken to edit and correct the article. In minor cases – i.e., typos – these edits aren't noted to readers. In significant cases – i.e., shifts in understandings of hair loss pathology that make a past article less relevant – these edits are noted toward the top of the article.
We don't endorse or recommend any products for hair loss, as doing so would undermine our editorial policies and potentially subjectively bias our writing. Rather, we strive to create content that allows hair loss sufferers to make informed decisions about their treatment options. This does not require product endorsements; it requires comprehensive, unbiased education.
We don't accept advertisement placements on Perfect Hair Health, from any company, ever. Like paid product endorsements, this could create bias. Our credibility and the trust of our readers is our utmost priority -- beyond the income that advertisements could potentially provide.