Unethical informed consent caused by overlooking poorly measured nocebo effects

Unlike its friendly cousin the placebo effect, the nocebo effect (the effect of expecting a negative outcome) has been almost ignored. Epistemic and ethical confusions related to its existence have gone all but unnoticed. Contrary to what is often asserted, adverse events following from taking placebo interventions are not necessarily nocebo effects; they could have arisen due to natural history. Meanwhile, ethical informed consent (in clinical trials and clinical practice) has centred almost exclusively on the need to inform patients about intervention risks with patients to preserve their autonomy. Researchers have failed to consider the harm caused by the way in which the information is conveyed. In this paper, I argue that the magnitude of nocebo effects must be measured using control groups consisting of untreated patients. And, because the nocebo effect can produce harm, the principle of non-maleficence must be taken into account alongside autonomy when obtaining (ethical) informed consent and communicating intervention risks with patients

Positive messages may reduce patient pain: A meta-analysis

Introduction Current treatments for pain have limited benefits and worrying side effects. Some studies suggest that pain is reduced when clinicians deliver positive messages. However, the effects of positive messages are heterogeneous and have not been subject to meta-analysis. We aimed to estimate the efficacy of positive messages for pain reduction. Methods We included randomized trials of the effects of positive messages in a subset of the studies included in a recent systematic review of context factors for treating pain. Several electronic databases were searched. Reference lists of relevant studies were also searched. Two authors independently undertook study selection, data extraction, risk of bias assessment, and analyses. Our primary outcome measures were differences in patient- or observer-reported pain between groups who were given positive messages and those who were not. Results Of the 16 randomized trials (1703 patients) that met the inclusion criteria, 12 trials had sufficient data for meta-analysis. The pooled standardized effect size was −0.31 (95% confidence interval [CI] −0.61 to −0.01, p = 0.04, I2 = 82%). The effect size remained positive but not statistically significant after we excluded studies considered to have a high risk of bias (standard effect size −0.17, 95% CI −0.54 to 0.19, P = 0.36, I2 = 84%). Conclusion Care of patients with chronic or acute pain may be enhanced when clinicians deliver positive messages about possible clinical outcomes. However, we have identified several limitations of the present study that suggest caution when interpreting the results. We recommend further high-quality studies to confirm (or falsify) our result. FUNDING Alexander Mebius research has been funded through the ERC grant "Philosophy of Pharmacology: Safety, Statistical Standards, and Evidence Amalgamation" (GA: 639276

Me ei tea, kas enamik ravimeetodeid toimib, ja veel vähem teame, kas need põhjustavad kahju, on väidetud uues uuringus*

Eesti Arst 2022; 101(9):521–52

Why include humanities in medical studies: comment

Five reasons why teaching medical humanities in medical schools improves student performance, enhances wellbeing, and ameliorates patient outcomes

Philosophical essentials in evidence-based medicine: Evaluating the epistemological role of double blinding and placebo controls.

The Evidence-Based Medicine (EBM) movement endorses a hierarchy of evidence that places randomized controlled trials at the top. More specifically, double-blind, placebo- controlled trials are often considered to be the 'best of the best'. This view leads to the paradox that treatments that seem to be most strongly supported by evidence, ranging from tracheotomies to rabies vaccines, have never been tested in randomized trials of any description and are hence supported by (allegedly) sub-optimal evidence. Moreover many of these treatments do not seem supportable by best evidence - how, for example do we keep the surgeons who perform tracheotomies 'blind'. After a brief introduction (chapter 1), and review of the literature (chapter 2), I argue that criticisms of the EBM hierarchy can be launched from the simple basis that best evidence rules out the most plausible rival hypothesis (chapter 3). To examine the relative evidential weight of placebo controlled trials compared to 'active' controlled trials (in which the control treatment is an existing established treatment) requires a good deal of conceptual work. I defend a modified version of Grunbaum's (1981/1986) definition of placebos (chapter 4), then provide constraints on what can count as a 'legitimate' placebo control (chapter 5). Next, I explain why double-blinding does not always rule out additional rival hypotheses. I then argue that the arguments for the superiority of placebo controls are flawed. The 'assay sensitivity' argument is limited in scope and based on a misconception about the nature of placebo controls (chapter 7), while the claim that only placebo controlled trials measure the absolute effect size relies on the questionable assumption that placebo and non-placebo effects add rather than interact (chapter 8). I conclude that the evidence hierarchy endorsed by EBM does not stand on solid foundations

Exploring the Asymmetrical Relationship Between the Power of Finance Bias and Evidence

Financial conflicts of interest can influence the design, conduct, and dissemination of medical trials. In attempting to resist “finance bias,” critics and proponents of evidence-based medicine (EBM) and its precursors have largely focused on trying to improve evidence. These efforts have led to successes ranging from the 1962 Kefauver-Harris amendments to the US Federal Drug and Cosmetic Act of 1938 to recent recommendations that all trials be published. However, there are two problems with the strategy of trying to improve evidence as a buffer against finance bias. First, without political teeth, rules of evidence can be ignored with relative impunity. This is because, as sociologist Bent Flyvbjerg has pointed out, there is an asymmetry between power (of finance bias) and rationality (evidence), tending towards victory of power in an open confrontation. Second, by improving the way evidence is produced, the process has become more expensive, and thus more susceptible to influence by finance bias. Unless they address the powers behind finance bias directly, critics and proponents may be doomed to lose the war against finance bias, even if they win some battles. For EBM to be effective, the power of finance bias influencing the production and dissemination of evidence needs to be addressed as a priority. This is starting to happen, with initiatives such as the AllTrials campaign, which identifies and exposes unpublished trials. On the other hand, there are reasons to be less optimistic, as Cochrane, the most trusted source of evidence, has become more susceptible to stronger influences from industry

Beyond empathy training for practitioners: Cultivating empathic healthcare systems and leadership

Empathic care benefits patients and practitioners, and empathy training for practitioners can enhance empathy. However, practitioners do not operate in a vacuum. For empathy to thrive, healthcare consultations must be situated in a nurturing milieu, guided by empathic, compassionate leaders. Empathy will be suppressed, or even reversed if practitioners are burned out and working in an unpleasant, under‐resourced environment with increasingly poorly served and dissatisfied patients. Efforts to enhance empathy must therefore go beyond training practitioners to address system‐level factors that foster empathy. These include patient education, cultivating empathic leadership, customer service training for reception staff, valuing cleaning and all ancillary staff, creating healing spaces, and using appropriate, efficiency saving technology to reduce the administrative burden on healthcare practitioners. We divide these elements into environmental factors, organisational factors, job factors, and individual characteristics

The importance of values in evidence-based medicine

Abstract Background Evidence-based medicine (EBM) has always required integration of patient values with ‘best’ clinical evidence. It is widely recognized that scientific practices and discoveries, including those of EBM, are value-laden. But to date, the science of EBM has focused primarily on methods for reducing bias in the evidence, while the role of values in the different aspects of the EBM process has been almost completely ignored. Discussion In this paper, we address this gap by demonstrating how a consideration of values can enhance every aspect of EBM, including: prioritizing which tests and treatments to investigate, selecting research designs and methods, assessing effectiveness and efficiency, supporting patient choice and taking account of the limited time and resources available to busy clinicians. Since values are integral to the practice of EBM, it follows that the highest standards of EBM require values to be made explicit, systematically explored, and integrated into decision making. Summary Through ‘values based’ approaches, EBM’s connection to the humanitarian principles upon which it was founded will be strengthened

How evidence‐based medicine is failing due to biased trials and selective publication

Evidence-based medicine (EBM) was announced in the early 1990s as a 'new paradigm' for improving patient care. Yet there is currently little evidence that EBM has achieved its aim. Since its introduction, health care costs have increased while there remains a lack of high-quality evidence suggesting EBM has resulted in substantial population-level health gains. In this paper we suggest that EBM's potential for improving patients' health care has been thwarted by bias in the choice of hypotheses tested, manipulation of study design and selective publication. Evidence for these flaws is clearest in industry-funded studies. We argue EBM's indiscriminate acceptance of industry-generated 'evidence' is akin to letting politicians count their own votes. Given that most intervention studies are industry funded, this is a serious problem for the overall evidence base. Clinical decisions based on such evidence are likely to be misinformed, with patients given less effective, harmful or more expensive treatments. More investment in independent research is urgently required. Independent bodies, informed democratically, need to set research priorities. We also propose that evidence rating schemes are formally modified so research with conflict of interest bias is explicitly downgraded in value

How evidence‐based medicine is failing due to biased trials and selective publication

Evidence-based medicine (EBM) was announced in the early 1990s as a 'new paradigm' for improving patient care. Yet there is currently little evidence that EBM has achieved its aim. Since its introduction, health care costs have increased while there remains a lack of high-quality evidence suggesting EBM has resulted in substantial population-level health gains. In this paper we suggest that EBM's potential for improving patients' health care has been thwarted by bias in the choice of hypotheses tested, manipulation of study design and selective publication. Evidence for these flaws is clearest in industry-funded studies. We argue EBM's indiscriminate acceptance of industry-generated 'evidence' is akin to letting politicians count their own votes. Given that most intervention studies are industry funded, this is a serious problem for the overall evidence base. Clinical decisions based on such evidence are likely to be misinformed, with patients given less effective, harmful or more expensive treatments. More investment in independent research is urgently required. Independent bodies, informed democratically, need to set research priorities. We also propose that evidence rating schemes are formally modified so research with conflict of interest bias is explicitly downgraded in value