The relationship of negative affect and perceived sensitivity to symptom reporting following vaccination

Petrie, Keith J.; Moss‐Morris, Rona; Grey, Corina; Shaw, Marc

doi:10.1348/135910704322778759

Cited by 71 publications

(58 citation statements)

References 33 publications

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“…Similarly, patients who believe that they are particularly sensitive to the effects of medicines also experience more treatment side effects [38]. Such general negative beliefs, as well as heightened anxiety, may have also contributed to the misattribution of unrelated symptoms to the placebo treatment [39,40]. However, expectations about treatment outcomes were not assessed in the current study, and future research would benefit from investigating both expectations about specific side effects, as well as more general negative beliefs about medicines.…”

Section: Discussionmentioning

confidence: 87%

The Influence of Social Modeling, Gender, and Empathy on Treatment Side Effects

Faasse

Parkes

Kearney

et al. 2018

Annals of Behavioral Medicine

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Background Social modeling has the capacity to shape treatment outcomes, including side effects. Purpose This study investigated the influence of social modeling of treatment side effects, gender, and participant empathy, on side effects of a placebo treatment. Methods Ninety-six participants (48 females) completed a study purportedly investigating the influence of modafinil (actually placebo) on alertness and fatigue. The participants were randomly seated with a male or female confederate and saw this confederate report experiencing side effects or no side effects. Participant empathy was assessed at baseline. Changes in modeled and general symptoms, and misattribution of symptoms, were assessed during the session and at 24-hr follow-up. Results During the experimental session, seeing side effect modeling significantly increased modeled symptoms (p = .023, d = 0.56) but not general or misattributed symptoms. Regardless of modeling condition, female participants seated with a female model reported significantly more general symptoms during the session. However, response to social modeling did not differ significantly by model or participant gender. At follow-up, the effect of social modeling of side effects had generalized to other symptoms, resulting in significantly higher rates of modeled symptoms (p = .023, d = 0.48), general symptoms (p = .013, d = 0.49), and misattributed symptoms (p = .022, d = 0.50). The experience of modeled symptoms in response to social modeling was predicted by participants' levels of baseline empathy. Conclusions Social modeling of symptoms can increase the side effects following treatment, and this effect appears to generalize to a broader range of symptoms and symptom misattribution over time. Higher baseline empathy seems to increase response to social modeling.

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Section: Discussionmentioning

confidence: 87%

The Influence of Social Modeling, Gender, and Empathy on Treatment Side Effects

Faasse

Parkes

Kearney

et al. 2018

Annals of Behavioral Medicine

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“…The fact that participants with more symptoms at baseline were more likely to attribute symptoms to the tablet, and then go on to attribute a higher number of symptoms to the tablet adds support to the theory that many nocebo effects could be due to misattribution of coincidental symptoms (Faasse & Petrie, 2013; Petrie et al ., 2004). This suggestion is supported by the apparently similar nature of the symptoms reported at baseline and post‐exposure.…”

Section: Discussionmentioning

confidence: 99%

“…These can all work to increase peoples’ expectations of side effects (Faasse & Petrie, 2013), one of main mechanisms of nocebo effects (Webster et al ., 2016). Medicine‐related beliefs have previously been shown to be associated with patients’ choice of medicine (e.g., complementary vs. conventional, or generic vs. branded) (Andersson Sundell & Jönsson, 2016; Figueiras et al ., 2010; Petrie et al ., 2001), their adherence to their medication (Horne, Chapman, et al ., 2013; Menckeberg et al ., 2008; Phatak & Thomas, 2006), their information seeking behaviour (Faasse, Grey, Horne, & Petrie, 2015), symptom attribution to a hypothetical medication (Heller, Chapman, & Horne, 2015), and side effect reporting to medications and vaccinations (Nestoriuc, Orav, Liang, Horne, & Barsky, 2010; Petrie et al ., 2004; Rief et al ., 2012). Given how prevalent these beliefs are, and the importance they have for patients’ decisions and experiences in medical settings, it would be useful to evaluate the contribution of these factors in predicting nocebo responses.…”

Section: Introductionmentioning

confidence: 99%

Medicine‐related beliefs predict attribution of symptoms to a sham medicine: A prospective study

Webster

Weinman

Rubin

2018

British J Health Psychol

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ObjectivesTo investigate a range of possible predictors of nocebo responses to medicines.DesignProspective cohort study.MethodsIn total, 203 healthy adult volunteers completed measures concerning demographics, psychological factors, medicine‐related beliefs, baseline symptoms, and symptom expectations before taking a sham pill, described as ‘a well‐known tablet available without prescription’ that was known to be associated with several side effects. Associations between these measures and subsequent attribution of symptoms to the tablet were assessed using a hurdle model consisting of a joint logistic and truncated negative binomial regression.ResultsMen had an increased odds of attributing symptoms to the tablet OR = 1.52, and older participants had decreased odds, OR = 0.97. Medicine‐related beliefs were important, with modern health worries, belief that medicines cause harm and perceived sensitivity to medicines associated with increased odds of symptom attribution, OR = 1.02, 1.10, 1.09, respectively. Trust in medicines and pharmaceutical companies decreased the odds of symptom attribution, OR = 0.91, 0.88, respectively. The number of symptoms at baseline and the expected likelihood of symptoms were associated with an increased odds of attributing symptoms to the tablet, OR = 1.07, 1.06, respectively. Anxiety, previous symptom experience, symptom expectations, and modern health worries were also important in predicting the number of symptoms participants attributed to the tablet.ConclusionIt is hard to predict who is at risk of developing nocebo responses to medicines from demographic or personality characteristics. Context‐specific factors such as beliefs about and trust in medicines, current symptoms and symptom expectations are more useful as predictors. More work is needed to investigate this in a patient sample. Statement of contribution What is already known on this subject? Many patients report non‐specific side effects to their medication which may arise through a nocebo effect.Whether some people are particularly predisposed to experience nocebo effects remains unclear. What does this study add? Demographic and personality characteristics are poor predictors of symptom attribution to a sham medicine.Instead, context‐specific factors that concern people's beliefs surrounding medicines, their current symptoms, and symptom expectations are more useful as predictors of symptom attribution.

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“…One frequently posited explanation for the differential symptom-reporting associated with anxiety is the symptom perception hypothesis. Under this hypothesis, patients with high anxiety over-report unfounded subjective symptoms, owing to increased encoding (noticing or vigilance) and inaccurate recall of symptoms, leading to erroneous attribution of somatic symptoms to medical causes (2,5,24). However, at least with respect to treatment-induced symptoms, elegantly designed prospective studies have begun to provide evidence to refute this theory (4,12,13,25).…”

Section: Discussionmentioning

confidence: 99%

“…Participants were categorized by their total score on negative affectivity (10-50) based on published norms (18) [17][18][19][20][21][22][23][24] and high NA (F: ≥24; M: ≥25). The negative affectivity scores in our sample were similar to those of healthy patients.…”

Section: Methodsmentioning

confidence: 99%