<unk> s can improve patient-reported outcomes such as pain and nausea. This effect is unpredictable and hard to measure, even in the best conducted trials. For example, if used to treat insomnia,<unk> s can cause patients to perceive that they are sleeping better, but do not improve objective measurements of sleep onset latency. A 2001 Cochrane Collaboration meta-analysis of the<unk>  effect looked at trials in 40 different medical conditions, and concluded the only one where it had been shown to have a significant effect was for pain. By contrast,<unk> s do not appear to affect the actual diseases, or outcomes that are not dependent on a patient's perception. One exception to the latter is Parkinson's disease, where recent research has linked<unk>  interventions to improved motor functions. Measuring the extent of the<unk>  effect is difficult due to confounding factors. For example, a patient may feel better after taking a<unk>  due to regression to the mean (i.e. a natural recovery or change in symptoms). It is harder still to tell the difference between the<unk>  effect and the effects of response bias, observer bias and other flaws in trial methodology, as a trial comparing<unk>  treatment and no treatment will not be a blinded experiment. In their 2010 meta-analysis of the<unk>  effect, Asbjørn Hróbjartsson and Peter C. Gøtzsche argue that "even if there were no true effect of<unk> , one would expect to record differences between<unk>  and no-treatment groups due to bias associated with lack of blinding." Hróbjartsson and Gøtzsche concluded that their study "did not find that<unk>  interventions have important clinical effects in general". However, in a study in 2010, patients given open-label<unk>  in the context of a supportive patient-practitioner relationship and a persuasive rationale had clinically meaningful symptom improvement that was significantly better than a no-treatment control group with matched patient-provider interaction. Jeremy Howick has argued that combining so many varied studies to produce a single average might obscure that "some<unk> s for some things could be quite effective." To demonstrate this, he participated in a systematic review comparing active treatments and<unk> s using a similar method, which generated a conclusion that there is "no difference between treatment and<unk>  effects". Factors influencing the power of the<unk>  effect A review published in JAMA Psychiatry found that, in trials of antipsychotic medications, the change in response to receiving a<unk>  had increased significantly between 1960 and 2013. The review's authors identified several factors that could be responsible for this change, including inflation of baseline scores and enrollment of fewer severely ill patients. Another analysis published in Pain in 2015 found that<unk>  responses had increased considerably in neuropathic pain clinical trials conducted in the United States from 1990 to 2013. The researchers suggested that this may be because such trials have "increased in study size and length" during this time period. Children seem to have greater response than adults to<unk> s. The administration of the<unk> s can determine the<unk>  effect strength. Studies have found that taking more pills would strengthen the effect. Besides, capsules appear to be more influential than pills, and injections are even stronger than capsules. Some studies have investigated the use of<unk> s where the patient is fully aware that the treatment is inert, known as an open-label<unk> . A 2017 meta-analysis based on 5 studies found some evidence that open-label<unk> s may have positive effects in comparison to no treatment, which may open new avenues for treatments, but noted the trials were done with a small number of participants and hence should be interpreted with "caution" until further better controlled trials are conducted. An updated 2021 systematic review and meta-analysis based on 11 studies also found a significant, albeit slightly smaller overall effect of open-label<unk> s, while noting that "research on OLPs is still in its infancy". If the person dispensing the<unk>  shows their care towards the patient, is friendly and sympathetic, or has a high expectation of a treatment's success, then the<unk>  would be more effectual. Symptoms and conditions A 2010 Cochrane Collaboration review suggests that<unk>  effects are apparent only in subjective, continuous measures, and in the treatment of pain and related conditions. Pain<unk> s are believed to be capable of altering a person's perception of pain. "A person might reinterpret a sharp pain as uncomfortable tingling." One way in which the magnitude of<unk>  analgesia can be measured is by conducting "open/hidden" studies, in which some patients receive an analgesic and are informed that they will be receiving it (open), while others are administered the same drug without their knowledge (hidden). Such studies have found that analgesics are considerably more effective when the patient knows they are receiving them. Depression In 2008, a controversial meta-analysis led by psychologist Irving Kirsch, analyzing data from the FDA, concluded that 82% of the response to antidepressants was accounted for by<unk> s. However, there are serious doubts about the used methods and the interpretation of the results, especially the use of 0.5 as cut-off point for the effect-size. A complete reanalysis and recalculation based on the same FDA data discovered that the Kirsch study suffered from "important flaws in the calculations". The authors concluded that although a large percentage of the<unk>  response was due to expectancy, this was not true for the active drug. Besides confirming drug effectiveness, they found that the drug effect was not related to depression severity. Another meta-analysis found that 79% of depressed patients receiving<unk>  remained well (for 12 weeks after an initial 6–8 weeks of successful therapy) compared to 93% of those receiving antidepressants. In the continuation phase however, patients on<unk>  relapsed significantly more often than patients on antidepressants. Negative effects A phenomenon opposite to the<unk>  effect has also been observed. When an inactive substance or treatment is administered to a recipient who has an expectation of it having a negative impact, this intervention is known as a nocebo (Latin nocebo = "I shall harm"). A nocebo effect occurs when the recipient of an inert substance reports a negative effect or a worsening of symptoms, with the outcome resulting not from the substance itself, but from negative expectations about the treatment. Another negative consequence is that<unk> s can cause side-effects associated with real treatment. Failure to minimise nocebo side-effects in clinical trials and clinical practice raises a number of recently explored ethical issues. Withdrawal symptoms can also occur after<unk>  treatment. This was found, for example, after the discontinuation of the Women's Health Initiative study of hormone replacement therapy for menopause. Women had been on<unk>  for an average of 5.7 years. Moderate or severe withdrawal symptoms were reported by 4.8% of those on<unk>  compared to 21.3% of those on hormone replacement.
Placebo
Nocebo
Drug coupon
Keldur
Artemotil
Creosote
Agamede
Therapy cap