Download From Me to You: The Effect of Social Modeling on Treatment Outcomes

XXX10.1177/0963721416657316Faasse, PetrieSocial Modeling and Treatment Outcomes
research-article2016
From Me to You: The Effect of Social
Modeling on Treatment Outcomes
Current Directions in Psychological
Science
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© The Author(s) 2016
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DOI: 10.1177/0963721416657316
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Kate Faasse1 and Keith J. Petrie2[AQ: 1][AQ: 2][AQ: 3]
1
School of Psychology, University of New South Wales, and 2Department of Psychological Medicine,
University of Auckland
Abstract
The social context in which people take medicines can strongly influence the drug response in both positive and
negative ways. We first examine the role of social modeling in influencing treatment outcomes through modifying
placebo and nocebo responses, and then explore possible mechanisms for these effects. Viewing another person show
improvement after taking a drug can increase the placebo component of the medicine and thus the overall potency of
the treatment. Likewise, seeing another person who has taken the same medicine report side effects can substantially
increase adverse effects. Such effects can also occur on a wider scale following changes in medicine formulations
or from vaccinations programs, when the media transmit adverse effects from these treatments to a wider audience.
Females seem to be more susceptible than males to the social modeling of adverse effects of treatments. A greater
awareness of the effects of social modeling has potential to improve the effectiveness of medical treatments, minimize
side-effect burden, and also lead to more effective management of health scares.
Keywords
social modeling, placebo effect, side effects, media, nocebo effect
In 2015, pharmaceutical companies spent an estimated $5.6
billion on drug advertising in the United States (Kantar
Media, 2015). These ads show happy, healthy, socially
engaged patients regaining control of their physical or
emotional health, all thanks to the effectiveness of the
advertised pharmaceutical in treating their illness. With
this positive messaging about treatment benefits, such
advertising presents opportunities for social observational learning of treatment outcomes. Indeed, advocates
have suggested that direct-to-consumer prescription-drug
advertising on television in the United States could
increase the placebo component of the treatment response by enhancing patient expectations of effectiveness
(Almasi, Stafford, Kravitz, & Mansfield, 2006). This may
offer one explanation as to why placebo effects appear to
have increased over time in clinical trials carried out in the
United States but not in Europe or Asia, where such drug
advertisements are not permitted (Tuttle et al., 2015).
In stark contrast to the images of happy and healthy
patients, these advertisements end with an extensive list
of possible treatment side effects, often including symptoms that occur very infrequently. Social observation of
treatment side effects also has the potential to occur in
face-to-face settings between friends, family, and other
patients, as well as through technological mediums
including Internet support groups, social media, and
news media coverage. Television news coverage and
Internet support-group discussions were implicated in
spreading nocebo symptoms in a health scare involving
a medication formulation change in New Zealand (Faasse,
Cundy, & Petrie, 2010). Television coverage contained
interviews with patients who had purportedly been
harmed by the medication. Adverse-event reporting
increased following early news coverage, particularly for
side effects specifically mentioned by patients in the
news segments (Faasse, Gamble, Cundy, & Petrie, 2012).
Increasingly, attention is being paid to the social contexts in which medication use occurs, and for good reason. The social observation of others’ treatment outcomes
has the potential to influence both positive and negative
outcomes in the viewer. Research has focused on two
primary domains: the influence of viewing improvement,
such as pain relief after treatment use, and the influence
Corresponding Author:
Kate Faasse, School of Psychology, University of New South Wales,
Sydney, New South Wales 2052, Australia
E-mail: [email protected]
2
Faasse, Petrie
of viewing side effects. Experimental research using placebo paradigms has highlighted the importance of social
observational learning in enhancing placebo responding,
and has also provided evidence that the modeling of
adverse events or unpleasant outcomes can increase
nocebo responding. In addition, research into the social
observation of symptom reporting has important implications for episodes of mass psychogenic illness and may
offer insights into findings that women are overrepresented as casualties in such episodes. While still in its
infancy, research investigating possible explanations for
such effects has looked at the role of viewer and model
gender, empathy, and anxiety as potential contributors to
the outcomes of social modeling.
To date, experimental work in this area has focused
exclusively on pain paradigms, primarily using relatively
small student samples. While the studies have been well
designed and have highlighted the potential role of social
modeling in enhancing placebo effects, the literature
would be strengthened by the replication of findings in
more varied research paradigms and participant populations. Study designs would also benefit from the inclusion of a no-treatment (or no-placebo, in this case) control
group. Additionally, current research has used only
placebo treatments. In order to assess how useful social
modeling might be in enhancing treatment effectiveness
in clinical settings, future research could usefully also
investigate outcomes of active treatments.
Social Modeling of Treatment Benefits
and the Placebo Response
Social Modeling of Side Effects and the
Nocebo Response
Social modeling of improvement in a medical context has
the potential to enhance the placebo component of treatment outcomes (Colloca & Miller, 2011). Research into
the impact of social modeling on treatment outcomes is
relatively recent, with the first experimental evidence
published less than a decade ago (Colloca & Benedetti,
2009). Since then, work has mainly been focused on the
social modeling of pain reduction, and further expansion
into non-pain placebo paradigms is needed.
Observing a male model report reduced pain under
specific circumstances (viewing a colored light, in this
case) subsequently generated a substantial analgesic
response in the viewer under those same circumstances
(Colloca & Benedetti, 2009). The degree of placebo
responding was significantly and positively correlated
with reported empathy in the viewer. The effects of social
modeling on placebo responding were seen regardless of
whether the (this time female) model was viewed faceto-face or via video (Hunter, Siess, & Colloca, 2014).
Empathy scores correlated with placebo analgesia, but
only in the face-to-face observation group, suggesting
that empathy alone may not explain placebo responding
following social modeling.
Following on from this work, Koban and Wager (2015)
again demonstrated that the social modeling of pain
reduction resulted in enhanced placebo analgesia and,
more importantly, that it also resulted in lower skin conductance—a physiological indicator of pain. These findings suggest that such positive social-modeling experiences did not just produce a reporting bias by changing
participants’ self-reported levels of pain but enhanced
placebo responding by influencing physiological responses to pain. Further, participant expectations of reduced pain fully mediated the effects of social modeling
of pain reduction on both placebo analgesia and skin
conductance.
Just as seeing a model report improvement can enhance
placebo responding, viewing painful outcomes or
unpleasant side effects can increase the nocebo response.
Seeing a model report increased pain under certain
circumstances (when viewing a red compared to a green
light) also resulted in increased pain reporting (nocebo
hyperalgesia) in viewers, in particular when the model
was male rather than female (Swider & Babel, 2013). In a
study that more closely paralleled a medical treatment
context, observing a model report increased pain in response to a placebo ointment that was described as enhancing skin sensitivity similarly resulted in nocebo
hyperalgesia in the viewer (Vögtle, Barke, & Kröner-Herwig,
2013). In contrast to placebo analgesia, nocebo responding was not found to be related to empathy.
Medical treatments are associated with a variety of
side effects, the experience of which are also susceptible
to social modeling. Using a creative paradigm in which
participants were asked to inhale a “potentially toxic substance” (actually room air), Lorber and colleagues demonstrated that female (but not male) participants who
observed a female model report side effects after the
inhalation reported significantly more side effects themselves compared to those who witnessed no symptom
reporting (Lorber, Mazzoni, & Kirsch, 2007). In a second
study designed to further investigate this gender effect,
participants who witnessed social modeling of side
effects again reported more side effects themselves, and
those who were seated with a model of the same gender
as themselves (regardless of modeling) reported more
side effects of the inhalation than did those who sat with
a model of a different gender (Mazzoni, Foan, Hyland, &
Kirsch, 2010).
In a group setting, participants who viewed both a
male and a female model report feeling unwell after taking a placebo described as a “carrier compound for an
Social Modeling and Treatment Outcomes
antiviral medication” reported significantly more symptoms than did those in the control group (Broderick,
Kaplan-Liss, & Bass, 2011). Recent work has also investigated the role of social observation of side effects in the
context of a beta blocker (actually a placebo) drug study
(Faasse, Grey, Jordan, Garland, & Petrie, 2015). Social
modeling of side effects by a female confederate resulted
in dramatic increases in both symptom reporting and the
number of symptoms attributed to treatment side effects
in female, but not male, participants. Importantly, the
social observation of side effects also had an impact on
placebo responding: Participants (independent of gender)
who saw the model report side effects had a substantially
reduced placebo response in both systolic and diastolic
blood pressure compared to participants in the control
group.
The nocebo literature benefits from having used a
broader range of experimental research paradigms to
investigate the role of social modeling in the experience
of side effects. Again, the studies have been well designed
and have highlighted the potential importance of social
modeling in the experience of nocebo effects, but future
research would benefit from the addition of a no-treatment
control group. The literature would be strengthened by
replication of the current findings across a broader range of
participants, and consideration of the role of social modeling of side effects in active treatments going forward.
Social Modeling in the Media
These direct and crossover effects from side-effect modeling to nocebo and placebo responding are of particular
importance in treatment-related health scares—where
news or social-media coverage of others’ side effects may
not only increase side effects across a large number of
viewers but also reduce the placebo component of the
treatment, thereby diminishing its overall effectiveness.
Misleading media reporting can result in increased anxiety, driving patients to seek care and reassurance unnecessarily, overwhelming healthcare systems (Yuji, Narimatsu,
Tanimoto, Komatsu, & Kami, 2011). Increased levels of
anxiety in the public following health scares can be seen
in language use in blog posts and appears to drive
people to seek additional health information (Tausczik,
Faasse, Pennebaker, & Petrie, 2012). Television news coverage has been linked to increased adverse-event reporting following a highly publicized medication formulation
change (Faasse et al., 2012). Media reporting has also
been linked to the spread of symptoms following influenza vaccination, with the additional consequence of
suboptimal levels of vaccination being reached (Huang,
Hsu, Lee, & Chuang, 2010). Thus far, research in this area
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has been observational, and future work would benefit
from an experimental approach.
Mass Psychogenic Illness
The social transmission of nocebo symptoms also occurs
in group settings—with symptoms spreading via line of
sight, sound, or communication (Bartholomew & Wessely,
2002). These mass psychogenic illness episodes involve
an illness outbreak that follows a perceived toxic exposure (which can include medications or vaccinations),
but for which no feasible organic explanation can be
found (Page et al., 2010). Women are often overrepresented as casualties of mass psychogenic illness episodes
(Bartholomew & Wessely, 2002). Seeing a model report
unpleasant symptoms is likely to both increase viewers’
expectations that they will also become unwell and cause
extreme anxiety about the possibility of toxic exposure
(Balaratnasingam & Janca, 2006). In these episodes, not
just one but multiple potential models provide information to others as psychogenic illness symptoms spread
through the group. Such social modeling may also happen through technological channels, including Internetbased social media (Bartholomew, Wessely, & Rubin,
2012). The spread of psychogenic symptoms through
viewing YouTube videos is suspected in at least one
incident involving U.S. schoolgirls (Bartholomew et al.,
2012).
Some symptoms appear to be particularly prone
to social transmission, including contagious yawning,
itching, and coughing (Norscia, Demuru, & Palagi, 2016;
Papoiu, Wang, Coghill, Chan, & Yosipovitch, 2011;
Pennebaker, 1980). Contagious yawning occurs significantly more often in female than male viewers and tends to
occur more readily between people who have closer social
bonds (Norscia et al., 2016). This may explain why mass
psychogenic illness episodes tend to occur within cohesive or isolated groups (Bartholomew & Wessely, 2002).
Episodes of mass psychogenic illness tend to change
with society, reflecting dominant social beliefs and
concerns of the time (Balaratnasingam & Janca, 2006;
Bartholomew & Wessely, 2002). The relatively recent rise
in episodes following medical treatments, in particular
vaccination, may reflect heightened public concern
around such interventions (Clements, 2003). A number of
vaccines have been implicated in mass psychogenic illness episodes, including those for human papillomavirus
(Clements, 2007) and H1N1 influenza (Huang et al.,
2010). Given the importance of medical treatments and
mass vaccination campaigns, these events have the
potential to severely compromise health behaviors and
health outcomes. The rise of social media and the ease
Faasse, Petrie
4
with which information can be transmitted may mean that
such media-driven incidents will increase in the future.
Future Directions
The role of social modeling in health and treatment outcomes has been paid relatively little attention, particularly given that such processes have the capacity to either
enhance medication effectiveness or dramatically increase
side effects, depending on the modeled outcome. To
date, questions remain around why women appear to be
more likely to experience symptoms in response to social
modeling and, more broadly, why women are overrepresented in cases of mass psychogenic illness. This may, in
part, be explained by findings that indicate that women
tend to report higher numbers of physical symptoms in
daily life and are more likely to experience nocebo effects
(Barsky, Saintfort, Rogers, & Borus, 2002; Liccardi et al.,
2004; Petrie, Faasse, Crichton, & Grey, 2014). Women
tend to experience more symptoms and more side effects,
meaning that they may also be more likely to model symptoms to others. Because observers learn more from models
they can readily identify with (Braaksma, Rijlaarsdam,
& van den Bergh, 2002), such social modeling may have
particular influence on female observers. However, little
research has been done in this area, and it remains unclear
whether seeing a model of the same gender as the viewer
is particularly effective (as suggested by Mazzoni and colleagues, 2010) or whether there might be different mechanisms at work in male and female viewers; additional
research is needed to answers these questions.
The role of empathy—both dispositional and situational—warrants further investigation. In the social modeling of pain relief, viewer empathy also appears to play
a role in placebo responding (Colloca & Benedetti, 2009;
Hunter et al., 2014). Women tend to report higher levels
of empathy than men, and these psychological differences are associated with both neuroanatomical differences in the mirror-neuron system and greater neuronal
activity when processing emotion-related stimuli (Cheng
et al., 2009; Christov-Moore et al., 2014; Schulte-Rüther,
Markowitsch, Shah, Fink, & Piefke, 2008). Empathy and
the mirror-neuron system may facilitate the social contagion of symptoms in cases of mass psychogenic illness
(Lee & Tsai, 2010), offering another possible piece of the
puzzle in explaining why women may be more responsive to the social modeling of symptoms than men.
High levels of anxiety are often present in mass psychogenic illness episodes. However, the role of emotional
distress in the social transmission of placebo and nocebo
effects has received little attention to date. Heightened
emotional distress is associated with increased rates of
symptom reporting (Salovey & Birnbaum, 1989), as well
as the tendency to attribute more symptoms to a medical
treatment or intervention (Petrie, Moss-Morris, Grey, &
Shaw, 2004). As might be expected in cases of mass psychogenic illness, evidence also suggests that distress can be
“caught” from other people (Laird et al., 1994). This social
spread of anxiety appears to be facilitated when participants face the same threatening situation (Gump & Kulik,
1997). Emotional contagion has also been found in online
social networks (Kramer, Guillory, & Hancock, 2014), which
may help to explain apparent episodes of technological
transmission of mass psychogenic illness symptoms.
Finally, the role of social modeling in both placebo
and nocebo responding may have particular utility and
importance in medical care. Future research would benefit from the examination of the role of social modeling
(of either treatment effectiveness or side effects) in
patient outcomes from active medical treatments, bridging the gap between theory and real-world applications.
While the influence of social modeling of placebo
responding has been demonstrated in pain paradigms,
evidence for responses outside of pain is currently lacking. Social modeling has the potential to act as a powerful intervention to increase overall treatment effectiveness.
Increased symptoms following face-to-face or online
social modeling during medical treatment could lead to
increased demand for medical care, as well as treatment
discontinuation or non-adherence (Barsky et al., 2002;
Petrie et al., 2014). Similarly, the experience of psychogenic symptoms in response to a presumed toxic exposure has the potential to overwhelm medical services in
real health emergency situations (Engel et al., 2007; Page,
Petrie, & Wessely, 2006). Social modeling processes could
also have important implications for the way randomized
controlled trials are carried out. Generating a deeper
understanding of these processes, and how to use them
to facilitate the best outcomes for patients, has the potential to enhance treatment effectiveness and minimize
unpleasant symptoms and side effects.
Recommended Reading
Bartholomew, R., Wessely, S., & Rubin, G. J. (2012). (See
References). Provides an example of social modeling and
transmission of symptoms through social media.
Colloca, L., & Benedetti, F. (2009). (See References). An early
study showing the influence of social modeling on placebo
effects in pain.
Faasse, K., Gamble, G., Cundy, T., & Petrie, K. (2012). (See
References). doi:10.1136/bmjopen-2012-001607. Provides
an example of social modeling of side effects through television coverage.
Faasse, K., & Petrie, K. J. (2013). The nocebo effect: Patient expectations and medication side effects. Postgraduate Medical
Journal, 89, 540–546. doi:10.1136/postgradmedj-2012-131730.
Provides an overview of the nocebo effect.
Social Modeling and Treatment Outcomes
Declaration of Conflicting Interests
The authors declared that they had no conflicts of interest with
respect to their authorship or the publication of this article.
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