study design
The various forms of fasting have many, mostly positive health effects. The most obvious is that of losing weight and body fat. The aim of this study was to investigate the feasibility of measuring the effects of a 14-day Periodic Fasting (PF) intervention (<200 cal) on multi-organs of primary interest (liver, visceral/subcutaneous/bone marrow fat, muscle) using non-invasive advanced magnetic resonance spectroscopic (MRS) and imaging (MRI) methods.
One subject participated in a 14-day PF under daily supervision of nurses and specialized physicians, ingesting a highly reduced intake: 200 Kcal/day coupled with active walking and drinking at least 3 L of liquids/day. The fasting was preceded by a 7-day pre-fasting vegetarian period and followed by 14 days of stepwise reintroduction of food. The longitudinal study collected imaging and biological data before the fast, at peak fasting, and 7 days, 1 month, and 4 months after re-feeding. Body fat mass in the trunk, abdomen, and thigh, liver and muscle mass, were respectively computed using advanced MRI and MRS signal modeling. Fat fraction, MRI relativity index T2* and susceptibility (Chi), as well as Fatty acid composition, were calculated at all-time points.
A decrease in body weight (BW: −9.5%), quadriceps muscle volume (−3.2%), Subcutaneous and Visceral Adipose Tissue (SAT −34.4%; VAT −20.8%), liver fat fraction (PDFF = 1.4 vs. 2.6 % at baseline) but increase in Spine Bone Marrow adipose tissue (BMAT) associated with a 10% increase in global adiposity fraction (PDFF: 54.4 vs. 50.9%) was observed. Femoral BMAT showed minimal changes compared to spinal level, with a slight decrease (−3.1%). Interestingly, fatty acid (FA) pattern changes differed depending on the AT locations. In muscle, all lipids increased after fasting, with a greater increase of intramyocellular lipid (IMCL: from 2.7 to 6.3 mmol/kg) after fasting compared to extramyocellular lipid (EMCL: from 6.2 to 9.5 mmol/kg) as well as Carnosine (6.9 to 8.1 mmol/kg). Heterogenous and reverse changes were also observed after re-feeding depending on the organ.
These results suggest that investigating the effects of a 14-day PF intervention using advanced MRI and MRS is feasible. Quantitative MR indexes are a crucial adjunct to further understanding the effective changes in multiple crucial organs especially liver, spin, and muscle, differences between adipose tissue composition and the interplay that occurs during periodic fasting.
This interesting and well-reported study supports the idea that fasting does not just “burn fat” uniformly; it shifts energy stores differently across organs and fat depots. Visceral fat appears more responsive and more durable in its reduction than subcutaneous fat, which is relevant because visceral fat is more strongly linked to cardiometabolic risk. Because this was a case report with one participant, the findings are best viewed as hypothesis-generating rather than definitive.
The long-standing consensus surrounding moderate alcohol consumption has recently been disrupted by a landmark review. Initiated under a US congressional mandate to evaluate the evidence base for the US Dietary Guidelines for Americans, the study—convened by the National Academies of Sciences, Engineering, and Medicine (NASEM) alongside the Department of Health and Human Services (HHS)—concluded that even a single alcoholic beverage per day significantly elevates the risks of serious chronic illness and premature death. After unexplained bureaucratic delays, the release of this taxpayer-funded research delivers a sobering truth: there is no net health benefit derived from alcohol consumption at any level.
For decades, public perception was shaped by data suggesting that a daily glass of wine or beer could act as a cardiovascular shield. This new review systematically dismantles that notion by identifying significant methodological biases in the previous evidence. Chief among these is the “sick quitter” effect, wherein baseline categories of non-drinkers inadvertently included individuals who had abstained precisely because of pre-existing, severe health conditions. By correcting for these distortions, the review demonstrated that health risks accumulate linearly. Alcohol acts as a dose-dependent toxin with no safe lower threshold, and even minimal daily intake accelerates linear risk trajectories for:
- liver cirrhosis,
- severe hypertension,
- various malignancies, including esophageal, colorectal, and breast cancers.
Beyond chronic pathology, low-level consumption also:
- impairs cognitive architecture,
- accelerating brain aging,
- elevates the immediate probability of physical injury.
The friction surrounding the report’s delayed release has exposed systemic vulnerabilities at the intersection of federal policy and corporate lobbying. Historically, US dietary guidelines defined moderate drinking as up to two drinks per day for men and one for women. The new scientific consensus exposes these thresholds as dangerously obsolete, highlighting a stark disconnect between federal health advice and contemporary medical data.
This friction might underscore the impact of the commercial determinants of health, exposing how multi-billion-dollar alcohol conglomerates employ aggressive public relations campaigns and sophisticated scientific interference to preserve market shares. By aggressively marketing alcohol as a benign staple of a healthy lifestyle, the industry had successfully obscured its intrinsic risks. The new evidence shifts the conversation from personal indulgence to an important public health issue.
Update (July 2026): a US government–commissioned analysis of alcohol-related risk was published. Here is its abstract:
The purpose of this study was to estimate the lifetime risk of alcohol-attributable mortality and morbidity in the United States based on a person’s average lifetime weekly alcohol consumption to assess the impact of per-occasion alcohol consumption on health.
Lifetime risks were estimated using a cause-specific modeling approach that combined exposure data from national health surveys, relative risks, population data from the U.S. Census Bureau, mortality data from the Centers for Disease Control and Prevention, and morbidity data from the Institute for Health Metrics and Evaluation. A narrative review assessed the health impact of per-occasion alcohol consumption on health.
At low levels of consumption, no protective net effect of alcohol consumption on health was observed. Elevated mortality and morbidity risks were associated with alcohol consumption starting at relatively low levels. Males consuming >6.5 (95% CI [<1, 13.5]) and females consuming >7.0 (95% CI [<1, 11.5]) drinks per week had life-time alcohol-attributable mortality risks >1:1,000. At >8.5 (95% CI [2.5, 13]) drinks per week for both males and females, these risks increased to >1:100. At 14 drinks per week for males (the upper limit of the former Dietary Guidelines for males), the risk of an alcohol-caused death was 1:25 (4%). Drinking patterns also impacted risk. Above 1 drink per occasion, higher consumption was associated with progressively increased risks of breast cancer, cardiovascular disease, and injury.
Alcohol consumption, including at what may be perceived as “moderate” levels, is associated with increased mortality and morbidity risks. These results support tightening alcohol use guidance in the United States, for both males and females, to no more than 1 drink per day.
Public health significance statement: The Alcohol Intake and Health Study shows that for Americans, even what is socially considered “moderate drinking” increases the risk of dying or developing health problems, helping people better understand the net health impact of alcohol. Furthermore, by identifying the levels of alcohol use that raise the risk of cancer, cardiovascular disease, and injury, these findings can guide individuals, families, and communities in making safer choices about drinking patterns. The results also support changing the U.S. Dietary Guidelines on alcohol to recommend that current adult drinkers consume 1 drink or less in a day.
Authors and independent observers have described the report as having been sidelined during the Trump administration, citing conflicts with industry interests and existing “moderate drinking is safe” messaging.
Hypothyroidism is a prevalent hormonal disorder symptoms often persist despite levothyroxine therapy. Adjunctive individualized homeopathic medicines (IHMs) may improve clinical outcomes, biochemical markers, and quality of life, robust evidence of efficacy remains limited.
The objective of this study was to evaluate the efficacy of add-on IHMs alongside standard levothyroxine therapy in the treatment of hypothyroidism in children and adults.
A 3-month, double-blind, randomized, placebo-controlled trial was conducted in a homeopathic hospital involving 64 trial subjects with hypothyroidism undergoing levothyroxine therapy. The participants received either IHMs plus levothyroxine (verum; n = 32) or placebo plus levothyroxine (control; n = 32) for 3 consecutive months. Patients, study investigators, outcome evaluators, and data entry staff were all kept blinded about the allocation concealment according to a double-blinded approach. The codes were not disclosed to the principal investigator, and unblinding occurred only in cases of clear medication-related risk, substantial benefit, or futility. The primary outcome was the Zulewski’s Clinical Scoring (ZCS); secondary outcomes included thyroid-stimulating hormone (TSH), T3, T4, and ThyroPRO-39 scores.
Both groups showed significant improvement in symptoms and thyroid indices. Between-group difference in ZCS was nonsignificant (mean diff: 0.1, 95% confidence interval [CI] −0.3–0.6, P = 0.567), but significant in T3 (mean diff: −0.2, 95% CI −0.4 to −0.1, P = 0.002), T4 (mean diff: 1.6, 95% CI 1.2–2.0, P < 0.001), and TSH (mean diff: −3.0, 95% CI −5.8 to −0.3, P = 0.033), favoring homeopathy against placebo. Quality-of-life changes were minimal, though some ThyroPRO-39 domains improved significantly with IHMs (e.g., symptoms, P < 0.001; tiredness, P = 0.012; nervousness and tension, P = 0.001; and daily activity, P = 0.001).
The authors concluded that adjunctive IHMs did not improve symptoms or quality-of-life outcomes over placebo conclusively, but revealed favorable biochemical changes, meriting further long-term studies.
I must admit: I am puzzled by this paper:
- According to the primary endpoint, the result is squarely negative.
- Yet, the article itself is presented as though the findings were positive.
- This is because the some secondary endpoints yielded positive results.
- But how can this be?
- I find the power justification unconvincing; perhaps the study was under-powered?
- The authors report that “Neither group experienced any adverse effects.”
- How can this be?
- Even placebo therapy generates adverse effects!
- And common problems of levothyroxine therapy are palpitations, tremor, nervousness, insomnia, sweating, heat intolerance, headache, diarrhoea, weight loss, and increased appetite.
As I said, I am puzzled. Perhaps the authors’ affiliations might explain?
- Department of Materia Medica, D. N. De Homoeopathic Medical College and Hospital, Affiliated to the West Bengal University of Health Sciences, Kolkata – 700 046, West Bengal, India
- Department of Repertory, D. N. De Homoeopathic Medical College and Hospital, Affiliated to the West Bengal University of Health Sciences, Kolkata – 700 046, West Bengal, India
- Department of Homeopathy, East Bishnupur State Homoeopathic Dispensary, Chandi Daulatabad Block Primary Health Centre, Under Department of Health and Family Welfare, Govt. of West Bengal, India
The Medical Journalists’ Association (MJA) has outlined six practical tips to help scrutinise health claims responsibly and accurately. They are primarily meant for journalists but, I think, they are also usefull for the general public, particularly when dealing with health claims in the realm of so-called alternative medicine (SCAM):
Check the source
Assess whether the claim originates from credible, peer-reviewed research and a reputable institution. Be wary of press releases, anecdotal reports, or media outlets known for sensationalism. Specifically for claims about SCAM, we might also add caution regarding the many third class SCAM journals.
Look for conflicts of interest
Investigate who funded the research and whether any authors or organisations stand to profit from the findings. Industry sponsorship can introduce bias, even in otherwise well-conducted studies. For claims about SCAM, we should remember that financial interest might be secondary to ideological ones.
Examine the study design
Consider whether the research used appropriate methods – such as randomisation, control groups, and adequate sample sizes – to support its conclusions. Observational studies, or case reports, or trials with the often-discussed ‘A+B versus B’ design, for example, cannot prove causation.
Consider the magnitude and relevance of effects
Distinguish between statistical significance and clinical importance. A tiny effect may be statistically significant in a large trial but meaningless in practice. Also ask whether the study population is representative and the outcome can be generalised.
Look for independent replication
Single studies should be treated cautiously until confirmed by other researchers. Consistent findings across multiple studies increase confidence in a claim.
Beware of over-interpretations
Scrutinise whether the authors or media coverage extrapolate beyond what the data support. For instance, generalising from animal studies to humans, or implying benefits without evidence of improved health outcomes.
___________________
If I may, I will add an 7th to the six by the MJA. It is one that I have issued many times previously and that is, I think, essential in SCAM:
If it sounds too good to be true, it probably is!
Exaggerated or false health claims are endemic in SCAM. These 7 tips might be useful in disclosing them and in minimising the harm they can do.
This recent survey caught my attention; here is the abstract:
Homeopathy is one of the most widespread alternative methods of treatment in Bulgaria in the last 25-30 years. The aim of the research is to study and analyze the knowledge and attitudes of Bulgarians over the age of 18 regarding the application of homeopathy as a curative method in general medical practice. A cross-sectional survey among a sample of the general Bulgarian population was conducted during a 4-week period in April-May 2022. The data were collected using the Google Forms platform via an online questionnaire. A total of 508 completed responses were collected (women-450, men-58). The overwhelming number are familiar with homeopathy and have used it before for their own health problems (97% of women and 86% of men). A large number of those who have used homeopathy report an improvement in their health (88% of women and 74% of men). The majority of respondents believe that homeopathy is useful for health care (93% of women and 79% of men). Further representative studies are needed to determine the role of homeopathy as a complementary method in general medical practice.
So, the researchers collected 508 responses on Google Forms. This method does not allow calculating a response rate, i.e. a percentage of those who saw the questionnaire and decided to reply. It might well have been 1% or lower. Who can reasonably be assumed to have resopnded? My guess is that those with an interest in homeopathy did and those without it did not respond. Thus, we should not be surprised to see that 97% of women (~90% of the respondents were women) had used homeopathy, 88% reported improvements, 93% belilieve it to be useful for Health care. I have previously compared such SCAM surveys to someone studying our views about hamburgers by placing themselves outside McDonalds and interviewing customers about the subject.
What these figures do not tell us is that presumably ~90% of Bulgarians could not care less about homeopathy! Despite this rather obvious suspicion, the authors ignore the fatal flaw in their survey and state that “the prevailing opinion that homeopathy is beneficial to health care in general is noteworthy. In other studies it is found that patients expected their family physician to refer them to CAM, including homeopathy, to have updated knowledge about CAM, and to offer CAM treatment in the clinic based on appropriate training. It can be assumed that homeopathy could be part of an integrative approach in health care, given the increased number of people wishing to use it, as well as the large number of doctors who have completed a training course in homeopathy in Bulgaria.”
Of course, this would be trivial, if it were not rather typical for a large chunk of “research” getting published in the realm of so-called alternative medicine (SCAM). I did put research in ” “, because it is, in fact, not research as we know it. Too many SCAM “researchers” have settled for conducting pseudo-research, i.e. investigations, like the one above, which can only produce findings that favour SCAM in one way or another. As this sort of thing is happening a thousand times over every month, it gradually erodes science and creates a general (erroneous) feeling (not least on the political level) that SCAM must be good for our health, after all.
And why do SCAM researchers prefer pseudo-research to proper science?
In my view, the answer is clear: they have realised or feel instinctively that proper hypothesis-testing research would not generate the results they so ardently need in order to promote their creed/ideology/business.
As explained in my previous post, plausibility matters. The post was predominantly about biological plausibility – but things can be a little more complex, and it would be foolish to deny the fact that there are two kinds of plausibility; biological and clinical.
Biological plausibility concerns compatibility with established physiology, biochemistry, and pathology. It asks whether a credible pathway exists by which an assumed cause could produce an effect. And it takes into account current knowledge from biology and other natural sciences. Within the Bradford Hill framework, biological plausibility helps distinguish mere statistical associations from actual causes. For more details see my previous post.
Clinical plausibility, by contrast, is based on much softer criteria, such as clinical observation and real-world outcomes. Here, the core question is whether a claimed effect fits observed patient patterns, e.g.:
- temporal relationships,
- dose-response gradients,
- reproducibility across cohorts,
- alignment with known clinical phenotypes.
Supported by case series, observational studies, clinical trials, or epidemiological studies, an intervention can be clinically plausible long before its underlying biology is understood. This has historically been the case for many drugs; an apt example is aspirin which has been used clinically long before a biologically plausible mechanism was discovered..
The two forms of plausibility should be complementary. Ideally, a robust causal claim satisfies both mechanistic logic and clinical observation. Biological plausibility without clinical evidence remains speculative. Clinical plausibility without a known mechanism invites skepticism and further inquiry.
The deficit of biological plausibility is a major indictment of many forms of so-called alternative medicine (SCAM). They often offer no tenable mechanism and fail under rigorous testing. Conversely, demanding full mechanistic clarity before accepting consistent clinical data is likely to hinder progress in healthcare.
In relation to so-called alternative medicine (SCAM), the issue was summarised more than 20 years ago as follows:
In summary, the way to prove the efficacy of most CAM therapies is with well-designed RCTs, and there is no reason to believe that clinical trial designs cannot be developed that allow even complex CAM therapies to be evaluated. The procedures involved can be sophisticated, complex and expensive, however, and this confronts investigators with the challenge of identifying which of the myriad of existing and future CAM therapies merit the effort and expense of definitive RCT evaluation. The challenge should be met as it is in conventional drug discovery, through plausibility-building research. Whenever possible, efforts should be made to establish a credible mechanism of action for a candidate CAM therapy, because this will increase its biological plausibility and reduce the risk of false-negative RCT results. When biological plausibility is lacking, clinical plausibility alone must be the basis for determining whether or not to proceed to the costlier phase of definitive RCTs. The creation of a plausibility-building CAM research strategy will require thought, instruction, funding, and collaboration among conventional clinical investigators and CAM advocates. The advantages are many: fairness, low cost and the creation of rules of engagement for CAM evaluation that foster balanced partnerships between CAM advocates and mainstream clinical scientists.
Ultimately, in my view, not a dogmatic stance but a balanced integration of both biological and clinical plausibility should underpin rational decisions about which medical hypotheses to pursue, adopt, or discard.
Evidence‑based medicine (EBM) was developed to make clinical decisions more reliable by grounding them more solidly in good research. Thus, randomised clinical trials, systematic reviews, and meta-analysis became crucial for healthcare. That development brought undeniable progress, but it also created a problem: if we focus exclusively on such evidence, we might neglect an important question:
IS THE TREATMENT IN QUESTION BIOLOGICALLY PLAUSIBLE?
Put simply, EBM asks “Does it work in this study?” without first asking “Could it reasonably work at all?”
The neglect of biological plausibility can lead to wasted resources, misleading conclusions and, in some cases, the promotion of nonsense. The issue is, of course, particularly relevant in so-called alternative medicine (SCAM) known for its frequent lack of plausibility. A simple example might explain this more clearly: in homeopathy, we see an abundance of poor-quality studies with a positive result. This could easily lead to the overall impression that homeopathy works, while in fact it cannot reasonably work at all.
So, how can we reasonably take account of this complication? It turns out there are several options:
Option 1 Gatekeeping
One way to account for plausibility within EBM is to use it to decide what we test in the first place. Before launching an expensive clinical trial, we can ask for a clear explanation of how the proposed intervention might reasonably work. If no such rationale can be articulated without contradicting science, it is reasonable to conclude that the intervention lacks sufficient plausibility to justify the time, money and ethical burden involved in testing it on patients. In practice, this kind of gatekeeping often happens informally, but making it explicit and mandatory could help keep overtly implausible interventions from consuming scarce resources.
Option 2 Prior probability
Plausibility can also be integrated into how we interpret trial results. Some trialists treat a statistically significant result as an infallible signal that the therapy was effective. When a trial result is “statistically significant”, it means the data we observed would be unlikely if the treatment had no effect. Prior probability is another way of expressing plausibility. If a hypothesis is highly plausible given existing scientific knowledge, a positive trial fits into a broader, coherent picture. If a hypothesis is highly implausible, a positive trial is more likely to be a false positive, an artefact of bias, chance, methodological flaws, or fraud. In other words, for low‑plausibility claims, we need stronger and more consistent evidence before accepting them as true. The less plausible a claim is, the more extraordinary the evidence must be.
Option 3 Guidelines
Guideline development offers another opportunity to embed plausibility into EBM. When expert panels prepare recommendations, they typically grade the strength of evidence according to study design, risk of bias, and consistency of results. They might also add a distinct step in which they rate the plausibility of the intervention. This rating could be justified explaining how well the intervention fits with established knowledge. Guideline writers could then let this plausibility rating influence the strength of their recommendations.
Health technology assessments have been moving in this direction for some time. It makes guideline documents more transparent: clinicians could see not only what the trials showed, but also how the intervention was judged to fit into or contradict broader scientific understanding.
Option 4 Causation
Finally, causation frameworks are being used to bring plausibility into EBM. When we decide whether an association is causal, we often rely on criteria such as consistency, temporality and strength of association. Biological plausibility is another of these criteria. Using it systematically means asking whether there is a logical pathway from intervention to outcome that passes through known mechanisms and observed effects. If such a pathway can be sketched in a way that accords with science, plausibility is high. If not, plausibility is low, and we should be more cautious about drawing causal conclusions from statistical associations alone.
EBM has revolutionized healthcare, but evaluating evidence in a vacuum can carry the risk of validating the absurd. To minimise this risk, we might consider integrating biological plausibility into EBM, a possibility that has long been discussed by many experts in the field. This approach is not a rejection of EBM, but a vital safeguard for it which ensures that the evidence aligns with and strengthened by fundamental science and existing knowledge. By demanding extraordinary evidence for extraordinary claims, medicine can better protect its resources, maintain intellectual integrity, and ensure that clinical practice rests on a foundation that is both statistically sound and scientifically reasonable.
The IGeL-Monitor is a German information portal that reviews self-pay medical services offered in doctors’ offices. It summarizes the likely benefit and harm of these services in plain language so patients can make more informed decisions. It is run by the “Medizinischer Dienst Bund” and uses evidence-based assessments rather than advertising or provider opinion.
The IGeL‑Monitor has recently focussed on osteopathy for non‑specific low back pain and judged the evidence as “unclear” stating that the current evidence does not reliably show a benefit, nor does it demonstrate meaningful harm. The reassessment pooled evidence from ten randomised clinical trials including about 1,160 participants. While some trials suggested small improvements in pain or function, the overall certainty of these findings was low due to methodological weaknesses in the primary studies. The reviewers therefore concluded that there is no convincing, high‑quality proof that osteopathic manual therapy provides a clinically relevant advantage over sham or usual care.
A further concern highlighted in the assessment is publication bias: positive trials may be preferentially published. This phenomenon that exaggerates apparent benefits.
No clear pattern of harm from osteopathic treatment was identified. Adverse events were inconsistently and inadequately recorded in the trials. This fact not only limits the confidence about safety, but is also a clear breach of medical ethics.
The IGeL‑Monitor reiterates its previous (2018) position: with current data one cannot reliably endorse osteopathy as an effective out‑of‑pocket intervention for non‑specific low back pain, nor can one identify significant risk. Hence the label “unclear.” For patients considering osteopathy as a self‑paid service, the IGeL‑Monitor recommends being informed about the uncertain benefit and the weak evidence base when weighing potential costs against likely outcomes.
The new assessment is in agreement with much that I have been saying on this blog. I nevertheless would like to add one important point: back pain is the one condition for which the evidence is relatively sound. There are many other conditions for which osteopathy is being relentlessly promoted as an effective therapy with even less or no reliable evidence at all.
An article entitled “Beyond the Appearance of Rigor: Trustworthiness, Integration, and Standardization in Traditional, Complementary, and Integrative Medicine” caught my eye. The name “Traditional, Complementary, and Integrative Medicine” is, I think, impressive as it demonstrates the seemingly infinite ability of SCAM-promoters to come up endlessly with new and ridiculous terms! Please allow me nonetheless to continue calling it so-called alternative medicine (SCAM).
The paper itself might be summarised as follows:
SCAMs struggles to fit into mainstream science. Trustworthiness isn’t just about flashy, individual study results; it requires a reliable system of transparent data and independent replication. However, forcing SCAM into mainstream healthcare via scientific scrutiny, standardisation and integration is a double-edged sword. It strips away the personalized, holistic essence of these therapies. Instead of abandoning science or changing the therapies, researchers need to use creative, flexible scientific methods that document the real-world complexity of SCAM without trying to force it into an artificial mold.
I have heard this argument often, particularly early on when I started applying science to SCAM. SCAM proponents were initially taken by the idea; later, when the results were often not what they expected, they were less impressed and argued that, because science failed to produce positive results, something must be wrong with it and in need of improvement. Specifically, the arguments were:
- SCAM is individualised,
- SCAM is holistic,
- SCAM is complex,
- SCAM is subtle,
- SCAM depends on the skill of the practitioner.
And therefore, SCAM cannot be fitted into the straitjacket of science, particularly not in the one imposed by the randomised clinical trial.
It took many years to convince some SCAM proponents that these notions were erroneous, that science is not always perfect but that no better method for testing exists, that many mainstream interventions (e.g. physiotherapy, psychotherapy) are just as complex, holistic, etc. as is SCAM. Eventually the argument that SCAM defies scientific evaluation disappeared – not totally, but almost.
Now, 30 years later, it is back!
One cannot even blame the SCAM enthusiasts for reviving it. Thirty years of research and very little of SCAM has been proven to work – unless one gives SCAM a huge ‘benefit of the doubt’ and pretends poor science constitutes proof. Even the treatments that SCAM proponents celebrate as evidence-based fall apart once we scratch the surface and discover how poor and irreproducible the evidence mostly is.
Yes, I do sympathise with the frustration of SCAM proponents as they gradually realise all this. Many of them know only too well that their most solid evidence can be taken apart by any first-year medical student with rudimentary skills of critical evaluation. Many of them therefore have long moved away from hypothesis testing research and prefer the type of investigation that never generates a negative finding (e.g. surveys, qualitative studies, sociological approaches). Others, including the two authors of the above-mentioned paper, prefer to go full circle and revive the notions we dealt with decades ago claiming we need different standards for SCAM than for the rest of medicine.
Perhaps someone should tell them that double standards are never a good idea?
