Introduction
Cognitive biases are constructs based on erroneous or deformed perceptions which produce
systematically distorted representations with respect to some aspects of the objective
reality, such as prejudices (Haselton et al., 2005). Biases impact everyday life because
they affect decisions and behaviors. For example, one may persist in an unhealthy
behavior (e.g., smoking) because he selectively overestimates evidence that feeds
up a pre-existing conviction (e.g., “smoking boosts my concentration”) (Masiero et
al., 2019): this is known as confirmation bias (Hernandez and Preston, 2013).
While some biases appear inherent to human cognition, others are situation–specific.
Several studies have shown that there are cognitive biases typical of people who live
with a chronic illness and continually attend to health management (Lichtenthal et
al., 2017). These biases influence information processing about the disease and consequently
decision making (DM), impacting the health and quality of life (Khatibi et al., 2014).
The objectives of the present contribution are to synthetize information on biases
in chronic illness and to highlight the possible effect of biases on health management.
The last sections will explore how biases could influence not only the information
processing, but also the motivation and agency within the patients' healthcare journey.
Cognitive Biases in Chronic Illness
DM in chronic illness is complex because patients find themselves in a state of uncertainty
(Reyna et al., 2015), and have to take life-relevant decisions in an emotionally-charged
situation (Szekely and Miu, 2015; Mazzocco et al., 2019). People are averse to the
unknown and risk (Tversky and Kahneman, 1986), and this may lead them to choose suboptimal
treatments because they are perceived as less risky. For example, a patient may decide
to refuse a treatment as it involves unlikely yet feared risks, this way failing to
consider the benefits (Fraenkel et al., 2012; Pravettoni et al., 2016). The biases
most frequently highlighted in the literature on chronic illness are attentional (Bar-Haim
et al., 2007; Chan et al., 2011), interpretation (Ouimet et al., 2009; Lichtenthal
et al., 2017), and recall biases (Karimi et al., 2016). Attentional bias is defined
by Schoth et al. (2012) as the selective attention to specific information, failing
to consider the alternatives because of the interference of pre-existing sensitivity.
Interpretation bias is the patients' tendency to interpret an ambiguous information
in an illness–related fashion and to catastrophize (Crombez et al., 2013; Khatibi
et al., 2015). Recall bias consists in distortions in the accuracy of the recollections
retrieved (“recalled”) about events or experiences from the past (Last, 2000).
These biases have, in common, the tendency to prioritize information connected to
the disease/illness experience, at any level of information processing and DM. For
example, individuals tend to selectively focus on threat or pain–related words or
pictures (Bar-Haim et al., 2007; Crombez et al., 2013). Attention to threatening stimuli
and illness–related interpretation can lead to biased decisions in terms of treatment
and lifestyle: subjects with chronic pain will tend to focus on pain–related information
and consequent preoccupation (Bar-Haim et al., 2007; Hakamata et al., 2010; Schoth
et al., 2012), this way preferring healthcare options that are less likely to cause
pain, independently of their overall effectiveness or value. Similarly, they would
avoid certain activities they feel potentially pain–inducing, with the consequence
of social isolation and reduced social support (McCracken, 2008; Schoth et al., 2012).
Negative interpretation of information influenced by interpretation bias could promote
a greater pessimism about the potential control of a disease and, therefore, lower
the implementation of control behaviors which are considered ineffective (Miles et
al., 2009; Everaert et al., 2017).
Studies in psycho-oncology have shown that biases play a role in the fear of recurrence
(FOR) (Miles et al., 2009; DiBonaventura et al., 2010). The fear that cancer may return,
an important aspect to monitor in cancer survivors (Marzorati et al., 2017; Tsay et
al., 2020), features a cognitive component related to the survivor's difficulty in
processing disease–related information, thus, reducing the understanding of pathology
and treatment. Patients with FOR tend to focus on the negative aspects within the
doctors' explanation (Wenzel and Lystad, 2005; Davey et al., 2006; Han et al., 2006).
Possible consequences entail detriment to the patient-doctor alliance (Ha and Longnecker,
2010), patient's inability to take into account all aspects of medical information
to take good decisions (Kee et al., 2018), and, in the long run, the tendency to resort
to options alternative to traditional medicine patients feel reassuring (Dobrina et
al., 2020).
For what regards recall bias, people with past experience of pain or suffering create
memory traces that distort the memory of a stimuli associated with those sensations
(Karimi et al., 2016). Some studies on patients with chronic pain have shown propensity
to recall pain–related information (Pincus and Morley, 2001; Rusu et al., 2012). Studies
have demonstrated a recall bias for somatic symptoms showing a retrospective overestimation
of symptom severity (Broderick et al., 2008; Walentynowicz et al., 2015). Lindberg
et al. (2017) showed that breast cancer survivors' perception of past quality of life
is significantly worse than it actually was (physical and cognitive functioning, fatigue,
and pain). Patients with depression and pain recalled negative health–related information
to a greater extent than the non-depressed controls and patients with depression or
pain only, showing that the recall bias is exacerbated both bythe psychopathological
and physical condition (Rusu et al., 2012). While there is less information on the
direct influence of recall bias on health management, the propensity to recall negative
information may affect the patients' self-efficacy or their belief to be able to manage
their own health, in that memory of successful management (“mastery”) is crucial to
the maintenance of motivation (Hiltunen et al., 2005). In other words, it would hinder
the perception of an effective self-agency which is necessary to implement healthy
behaviors and treatment adherence, especially when it requests effort on the patient's
side.
Biases in Self-Perception
The tendency to focus on a threatening stimuli may affect a chronic patient's cognition
on a deep level. According to literature, this tendency may be rooted in self-perception.
Self-perception is defined as the “cognitive generalizations about the self, derived
from past experience, which organize and guide the processing of self-relevant information
contained in the individual's social experience” (Markus, 1977, p. 64). Self-perception
may be distorted (Alloy et al., 1988; Walfish et al., 2012). Chronic patients may
develop self-perception focused on illness–related memories, such as viewing themselves
as “sick” or “injured.” Indeed, chronic disease implicates years of experience, adaptation
to a disease of varying severity, making this information highly accessible. On one
hand, self–related biases influence distorted tendencies in information processing
such as those outlined above (attentional, interpretation, and recall biases) (Derry
and Kuiper, 1981; Clemmey and Nicassio, 1997; Guzman and Nicassio, 2003). On the other
hand, illness–related self-representation could be directly associated with mental
health outcomes, such as anxiety and depression (Triberti et al., 2019), especially
when the current (“actual”) self is perceived inconsistent with other coexisting self-representations
(e.g., the “ideal self” or the person one would like to be), a phenomenon known as
“self-discrepancy” (Higgins, 1987, 1989). This result emerged for example in a research
where oncological patients were asked to create digital avatars representing their
multiple facets of the self (Triberti et al., 2019), as well as in qualitative and
quantitative research focused on the chronic patients' self-perception (Clemmey and
Nicassio, 1997; Bailly et al., 2015; Michaelis et al., 2019). Recent reviews highlight
that self-discrepancy represents a contributory factor in psychiatric disorders (Mason
et al., 2019) and negatively affects the patients' quality of life (Kwok et al., 2016).
Social Biases
Full consideration of biases within the chronic illness context requires taking into
consideration those related to social cognition. DM rarely occurs in isolation. Indeed,
the decisions in a chronic illness are often influenced by others (Ellickson et al.,
2005; Germar et al., 2014). Others' influence on decisions can often lead to a wrong
evaluation of the choices with a tendency to take a greater risk (Gardner and Steinberg,
2005; Muchnik et al., 2013). Social biases can occur within the social context. Several
studies have dealt with the study of group psychology (Bar-Tal, 2012; Hogg, 2012;
Thibaut, 2017); for example, the classic experiment by Asch (1951) showed that a subject
will tend to conform his opinion, even when clearly untrue, to that of the other members
of the group he feels part of because of social pressure. Groups may exert an influence
on the cognitive processes and decisions just by a conformity effect. Certainly, such
classic experiments may be criticized today, for example, because they rely on abstract
tasks and artificial settings and have a low ecological validity (Arjoon, 2008). Yet,
it is well-known that groups belonging could promote biases in reasoning. Chronic
patients are influenced by caregivers, family, and close friends, who often have different
preferences regarding the treatment (Laryionava et al., 2018). Furthermore, health
and medicine have now become an increasingly shared context online; patients have
access to information that is not always reliable and evidence–based, and they may
join groups more easily, often with the aim to share experiences, receive advice,
and empathic support. The well-known example of anti-vaccine groups and related studies
(Jolley and Douglas, 2014) show that the exposure to conspiracy theories within groups
may sensitively affect the patients' health decisions. Even in the case of chronic
patients, a social bias can, therefore, lead the patients to change their attitudes
and opinions in favor of those shared by relevant groups.
The Influence of Biases on the Patients' Decision Making
Biases can influence the DM process in chronic illness (Gorini and Pravettoni, 2011;
Lucchiari and Pravettoni, 2013). Some cognitive biases in chronic illness could enhance
attention to and the salience of symptoms which tend to be perceived as uncontrollable
and incurable (Moss-Morris and Petrie, 2003), so that they negatively influence the
patients' decisions regarding treatment and health management. Furthermore, patients
affected by biases in self-perception may find themselves in a situation of perceived
helplessness and self-derogation, which affects their ability to manage their own
health and possibly augments the risk of mental health issues, such as anxiety. Psychologically
vulnerable chronic patients could also refer to others and groups to make health decisions,
which is a risky strategy especially when unprofessional opinions are involved.
It is possible that biases in chronic illness could influence DM and the formation
of effective motivation to engage in healthy behaviors. Many psychological interventions
are conducted to help patients manage their own health, as well as to recover a sense
of authority and control over their life, this way addressing the biases' effects
(Kondylakis et al., 2017). However, the patients' decision to take part in such interventions
could be influenced by biases as well. Among the multiple possible mechanisms, we
hypothesize that this happens because of three main processes (Figure 1). The first
involves fatigue as psychological process directly related to biases. Recent studies
have underlined that a reason to decline participating in a psychological intervention
or resorting to psychological support is feeling tired or weak (Bernard-Davila et
al., 2015; Aycinena et al., 2017). Indeed, it exists as a reciprocal interaction between
the systematic biases and perception of fatigue: on the one hand, fatigue (physical
and cognitive) leads to a careless information processing which augments the likelihood
of biased reasoning (Boksem and Tops, 2008; Howard et al., 2015); on the other hand,
symptom focusing and the way chronic patients interpret disease–related information
are demonstrated to augment their perception of fatigue (Wiborg et al., 2011; Hughes
et al., 2016).
Figure 1
Three main processes that influence patients' health management.
Another relevant process regards the perception of helplessness as a self-perception
component. Helplessness leads subjects to perceive symptoms like chronic pain as uncontrollable,
unpredictable, and immutable, and to generalize these to daily functioning (Abramson
et al., 1978; Evers et al., 2001). Along with passive coping (activity avoidance and
persistent worrying), this contributes to perceiving the disease as uncontrollable
and invincible, reducing self-efficacy, and the motivation to react to it (Samwel
et al., 2006; Verhoof et al., 2014).
Finally, it is possible that the influence of systematic biases is pervasive to the
point that it influences motivation formation. While motivation is often conceptualized
as a dynamic force or pull (e.g., drive, instinct, intention), it could be structured
as the declarative, explicit course of actions and outcomes to achieve, namely objectives
or goals (Ryan, 2012; Triberti and Riva, 2016). Goal setting is a fundamental component
of any care plan (Vaughn et al., 2016). Goal setting allows patients to identify the
short- and long-term objectives to achieve, taking into account the patient's needs
and lifestyle (Wade, 2009; Levack et al., 2015; Smit et al., 2019). Biases and, in
particular, the tendency to focus on the negative factors may lead the patients to
formulate goals to avoid the negative symptoms (e.g., pain), instead of pursuing the
long-term personal growth objectives (e.g., “I will not participate in the intervention
because it's tiring: I just need to rest”).
On this basis, it is possible that systematic cognitive biases in chronic illness
do not only influence the treatment decisions but also the motivation to resort to
interventions that could help in reduce their detrimental effects. In other words,
the repeated influence of the cognitive biases may be associated with a “vicious circle”
that reduces the patients' motivation to recognize and address the same mental health
issues that influence their DM.
Conclusion
The present contribution explored the ways biases could influence the motivation and
agency within the patients' healthcare journey. By considering of chronic illness
biases, we hypothesized that DM and motivation are directly altered, leading to a
reduced patient engagement in their own healthcare. The strength of this hypothesis
lies in the possibility to test it by quantitative research focused on the prevalence
of specific biases in patient populations characterized by a low engagement and/or
by the tendency to decline participation in health interventions. On the other hand,
its weakness lies in the possibly reciprocal interaction between the biases and engagement:
patients may incur in frequent biased cognition exactly because they are not adequately
supported in their care process. Furthermore, the three mechanisms hypothesized here
do not exhaust all the possible influences of biases so that future research should
provide evidence to build a more complete model of their effects on the patients'
decision making. This would allow the practitioners to understand how to address dysfunctional
cognition to improve the accessibility and effectiveness of health engagement interventions.
Author Contributions
LS conceived the ideas presented in the article and wrote the first draft. ST contributed
with the discussion on the ideas presented and supervised the writing. Both authors
contributed equally to the revision.
Conflict of Interest
The authors declare that the research was conducted in the absence of any commercial
or financial relationships that could be construed as a potential conflict of interest.