key: cord-0695514-pnq51nlc authors: Cheli, Simone; Lam, Wendy W. T.; Estapé, Tania; Winterling, Jeanette; Bahcivan, Ozan; Andritsch, Elisabeth; Weis, Joachim; Centeno, Isabel; Serpentini, Samantha; Farkas, Clemens; Wengström, Yvonne; Fioretto, Luisa; Baider, Lea; Lam, Cherry C. L.; Goldzweig, Gil title: Risk perception, treatment adherence, and personality during COVID‐19 pandemic: An international study on cancer patients date: 2021-08-04 journal: Psychooncology DOI: 10.1002/pon.5775 sha: 496c2f80233cdf2b9d8a7f54ceeaf3c3cbacaf63 doc_id: 695514 cord_uid: pnq51nlc OBJECTIVE: To explore the role of personality traits in moderating the relation between COVID‐19 risk perception and treatment adherence, and between risk perception and psychosocial distress in patients diagnosed with cancer. METHODS: An online survey (n = 1281) was conducted worldwide in seven countries (Austria, Germany, Hong Kong, Italy, Spain, Sweden, and Turkey). Inclusion criteria were to be 18 years of age or older, have received a cancer diagnosis, and be in treatment or follow‐up. A few moderated regression models were performed with both personality traits and Hierarchical Taxonomy of Psychopathology super‐spectra as moderators. RESULTS: Detachment, negative affectivity, psychoticism and all the super‐spectra significantly moderated the relation between coronavirus risk perception and psychosocial distress, after the adjusting effect of confidence in safeguards. Only negative affectivity moderated the association between coronavirus risk perception and treatment adherence. CONCLUSIONS: Personality traits may foster the understanding of how a patient might adjust to cancer treatment and, more generically, to highly stressful events such as the COVID‐19 pandemic. Further research is needed to confirm the results in different cancer stages and types. The novel COVID-19 outbreak has dramatically impacted world healthcare systems. Patients diagnosed with cancer are at risk of being more vulnerable to severe events 1 and suffering more from limited access to healthcare services. 2 Several studies describe a detrimental effect of the pandemic in terms of delay, reduction or cancellation of scheduled treatment, diagnosis, or general health service. 3, 4 This unexpected disruption of cancer care is one of the factors that influence the level of distress of patients, 5 and collective concerns and risk perception that recurs in the general population. 6 Little is known about the psychosocial factors that may moderate or mediate in cancer patients the exposure to and so the adjustment to COVID-19, in terms both of distress and treatment adherence. 7 This limited amount of evidence seems to be explained not only by the novelty of the pandemic, but also by the heterogeneity of psychosocial factors that are recognized as affecting adherence and of which we have no robust evidence in this unexpected context. Indeed, adherence is a multidimensional phenomenon influenced by factors such as patient-related, therapy-related, condition-related, health system, and socio-economic factors. [8] [9] [10] As constructs that are supposed to integrate several bio-psycho-social factors, personality traits may foster the understanding of adjustment to complex diseases such as cancer. 11 This study focuses on the role of personality traits in adherence to cancer treatment and in psychosocial distress during the pandemic. Personality traits can be conceptualized as a set of psychosocial factors considered broad cognitive, emotional and impersonal patterns. 12 Personality traits contribute to various mental, medical, and other important life outcomes, and provide a foundational base to modern approaches to psychopathology. 13 Personality traits might explain phenomena such as treatment adherence better than narrower psychological mechanisms. 11 Moreover, modern approaches to psychopathology, such as the Hierarchical Taxonomy of Psychopathology (HiTOP), 14 15 and the Big Five of personality. 16 Thus, it is important to examine how these models might predict and explain human behavior under stressful events such as the combination of cancer care and the COVID-19 pandemic. Existing systematic reviews suggest that personality is not associated with cancer incidence and mortality, 17 but may be considered a predictor of adjustment to and even adherence to cancer treatment. 11,18 A few recent cross-sectional studies support the hypothesis that specific personality traits are associated with specific psychosocial responses to COVID-19 in the general population. 19, 20 The current multi-national cross-sectional study aimed to test the hypothesis that personality traits, as defined by dimensional models such as AMPD, may moderate the relationship between COVID-19 risk perception and treatment adherence, and between risk perception and psychosocial distress in patients diagnosed with cancer. A dimensional approach was supposed to enable a focus on the level of mal-/adaptiveness rather than psychopathological categories or thresholds. The first and last author reached out to key representatives of seven countries (Austria, Germany, Hong Kong, Italy, Spain, Sweden, and Turkey) who were invited to join this study. The national representatives, in turn, recruited patients through cancer departments who were asked to disseminate the questionnaire. Except for Hong Kong, whose questionnaires were distributed in person due to contextspecific reasons, the survey was disseminated entirely online to overcome the diverse and constantly changing COVID-19 restrictions. One-thousand-two-hundred-eighty-one participants started to fill the questionnaires. Out of these 968 (76%) completed all the relevant measures. Table 1 present the sociodemographic and medical data. We inspected all study variables (items of the scales of risk perception, confidence in safeguards, non-adherence, Depression, Anxiety, Stress Scale-21, and PID-5-BF) for missing values. The proportion of The research aim was to investigate the role of personality in adjusting to COVID-19, or more specifically to estimate how per- To examine the relationship between the study variables we calculated zero-order Pearson correlations between all the study variables. Then, we performed moderation analysis using the Hayes 30 PROCESS macro. We tested each personality trait as moderating the relations between risk perception and adherence and risk perception and distress (using safeguards perception as a covariate). Finally, we tested the 3 HiTOP superspectra 14 Each of three superspectra was tested as a moderator in a risk perception model as an antecedent of distress and risk perception as antecedent of non-adherence. In all the models confidence in safeguards was included as a covariate. Table 2 and Figure 1 present the psychopathology factors (superspectra) as moderating the relation between risk perception and distress. Each of the three factors was a significant moderator, with higher levels of superspectra related to stronger relation between higher risk perception and higher distress. Table 3 and Figure 1 present the superspectra as moderating the relationship between risk perception and non-adherence. The only factor that was found to be a significant moderator was internalizing. Higher levels of internalizing were related to decreasing relation between risk perception and non-adherence. In the very high levels of internalizing there was even a tendency towards negative (even significant) relationship between risk perception and non-adherence. The present study aimed at exploring the role of personality traits in moderating the relationship between coronavirus risk perception and treatment adherence or distress in patients diagnosed with cancer. Our results suggest that personality, as defined by dimensional rather than categorical models, may be a useful pattern in understanding how persons adjust to stressful events such as the combination of cancer care and the COVID-19 pandemic. While numerous psychosocial factors are associated with distress and adherence, [8] [9] [10] research focused on evaluating measures that can offer a general understanding of recurrent and potentially pathological modes of adjustment. A context such as the pandemic associated with a significant risk 2,3,5,7 of high distress and low adherence can be informative in testing such measures in cancer care. Our results seemingly suggest that the more severe are specific maladaptive traits or HiTOP domains, the greater the relationship between risk perception and psychosocial suffering. Moreover, internalizing superspectrum resulted a negative moderator of the relationship between risk perception and non-adherence: the higher the superspectrum, the lower the association between risk perception and adherence, potentially exposing patients to a distorted decision-making process. To our knowledge, this is the first study using HiTOP in cancer care. Beyond the limitations of a cross-sectional study, the results are consistent with a growing body of evidence about statistical and clinical reliability of hierarchical models of psychopathology that, in turn, are rooted in a dimensional approach to personality. 13, 15 Indeed, personality domains refer to broad and recurrent adaptive or maladaptive strategies the persons use to adjust to their experience. 33 Little is known about applying these approaches in cancer care, 11, 17 but the present study seemingly supports the need for further translational research. Consistent with existing results in the field of mental health, 34 Finally, two results need to be interpreted separately. First, only the internalizing spectrum emerges as a significant moderator concerning adherence. This result seems consistent with the fact that neuroticism is frequently reported as a robust predictor of several mental and physical disorders 35 and a reduced capacity to adjust to chronic conditions. 36, 37 Second, antagonism and disinhibition individually were not moderators but only as superspetrum (i.e., externalizing). We can assume that it is the interaction between these two traits that affect the relationship between risk perception and distress (rather than them individually). The main limit of the study is its cross-sectional design and so the potential hidden effect of several confounding variables related to coronavirus rates of infections and death, or specific public health policies and strategies against COVID-19. Such variables might have affected the reported results and so our conclusions might be unreliable. Similarly, the disease progression or pathology of recruited patients may have biased the study. That said, the research was designed to overcome these limitations. First, the statistical analysis plan included a moderation model that is reputed to be scarcely affected by confounding variables. Second, the choice of personality traits as moderators offered an additional advantage as superordinate and broad domains. Third, preliminary REML analysis confirmed that the confounding variables did not influence the moderation model. Finally, due to the pandemic we could not use physical data to assess adherence, but only a specifically developed questionnaire. This reduces the reliability of our results. 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