Information support,illness perceptions,and distress in survivors of differentiated thyroid cancer

Abstract

Survivors of differentiated thyroid cancer report significant distress. This study examines illness perceptions as mediating the relationship between information support and distress among survivors of differentiated thyroid cancer. Data were obtained from the Patient Reported Outcomes Following Initial Treatment and Long-term Evaluation of Survivorship registry. Model results revealed that greater information support was associated with better illness perceptions, and that better illness perceptions were associated with less distress. Information support and distress were indirectly related via illness perceptions. Results highlight the importance of addressing illness perceptions in this population and suggest that informational interventions may help serve this function.

Keywords

illness perception information psychological distress survivorship thyroid cancer

Introduction

Survivors of differentiated thyroid cancer (DTC) report notable distress despite excellent disease prognosis (5-year survival rate: 98.1%; National Cancer Institute, 2016). Patients and survivors of DTC indicate greater levels of anxious and depressive symptoms and lower levels of emotional functioning than non-patient populations, and evidence suggests that distress persists throughout long-term survivorship (Crevenna et al., 2003; Hoftijzer et al., 2008; Husson et al., 2013a; Tagay et al., 2006). Predictors of distress in this population, however, remain largely unexplored. Thyroid cancer patients cite a lack of informational support to be one of the most difficult aspects of managing the illness and specifically report that receiving more information about the disease would improve care (Banach et al., 2013). Indeed, evidence suggests that cancer patients who report receiving limited information and those who report a need for additional information are at greater risk of compromised emotional functioning (Beckjord et al., 2008; Vogel et al., 2009). Collectively, these results support the need to examine patient experiences with and satisfaction with information quantity (hereby referred to as information support) in relation to distress among survivors of DTC. A second underexplored area with regard to distress among survivors of DTC is patient illness perceptions. Illness perceptions are associated with the “common-sense model” of self-regulation and refer to the cognitive and emotional representations that patients generate about their illnesses (Leventhal et al., 1997, 2003). Examining illness perceptions as a predictor of distress among survivors of DTC is warranted, because more threatening or worse views of illness are associated with worse emotional functioning in other chronic illness populations (Hagger and Orbell, 2003). With regard to oncology populations, relationships between threatening illness perceptions and worse emotional functioning have been demonstrated in individuals with head and neck cancer, breast cancer, brain tumors, and prostate cancer (Keeling et al., 2013; Rozema et al., 2009; Scharloo et al., 2005; Traeger et al., 2009). Surprisingly, the association between illness perceptions and distress among survivors of thyroid cancer has yet to be examined. For patients with a history of DTC in particular, it has been found that threatening cognitive representations of illness are associated with greater perceived emotional impact of illness (Hirsch et al., 2009). Such results encourage further exploration of the relationship between illness perceptions and general distress in survivors of DTC.

In considering how information support, illness perceptions, and distress may be related among survivors of DTC, it seems prudent to examine illness perceptions as a mechanism of action by which information support influences distress. Recently, Husson and colleagues found that among cancer survivors, perceptions of having received more disease-specific information were associated with better (less threatening) illness perceptions (Husson et al., 2013b). These findings corroborate the possibility that illness perceptions may be a mechanism by which information support can influence distress. Furthermore, results from a recent study on diabetes-related distress found that Personal Control illness perceptions mediated the relationship between the quality of the doctor-patient relationship and diabetes-related distress, suggesting that illness perceptions may play a key role in provider–patient interactions (Bridges and Smith, 2016). This study examines the influence of information support as a particular aspect of provider–patient interactions, to address the self-reported needs of thyroid cancer patients for increased information support and because of the evidence that information support is related to illness perceptions in other oncology populations. Examining such relationships may clarify points of intervention to reduce distress in this population.

Thus, the primary goals of this study are as follows: (1) to examine how information support and illness perceptions relate to distress in survivors of DTC and (2) to investigate illness perceptions as a mechanism by which information support and distress are related. Specifically, it is hypothesized that (1) greater information support will be associated with less distress, (2) less threatening illness perceptions will be associated with less distress, and (3) illness perceptions will mediate the relationship between information support and distress.

Method

Participants

All data for this study were obtained from the Patient Reported Outcomes Following Initial Treatment and Long-term Evaluation of Survivorship (PROFILES) registry (Van de Poll-Franse et al., 2011). The PROFILES registry facilitates research in psychooncology by collecting psychosocial data from patients and survivors of cancer, and linking this data to clinical information collected by the Netherlands Cancer registry (Janssen-Heijnen et al., 2005; Van de Poll-Franse et al., 2011). Data are then de-identified and made available to outside researchers, as was the case for this study. This study was reviewed by the Institutional Review Board and was deemed non-human subjects research.

In 2010, PROFILES researchers mailed a population-based survey to individuals who were diagnosed with thyroid cancer between 1990 and 2008 in the southern region of the Netherlands. Exclusion criteria for collection of thyroid cancer patient data are presented in detail elsewhere (Husson et al., 2013a), but chiefly included cognitive impairment or severe illness that precluded participation, unverifiable address, death prior to study commencement, and hospital declination of participation. For this study, data from survivors with a history of DTC in particular (i.e. papillary or follicular thyroid cancer; Mazzaferri and Kloos, 2001) were included in analysis.

Measures

Information support

Indicators for an information support latent variable were derived from a Dutch translation of the EORTC QLQ-INFO25 (INFO25; Arraras et al., 2010). The INFO25 is a self-report measure regarding information patients received throughout the course of disease and treatment. The measure consists of four subscales and eight single items. The four scales represent perceptions regarding quantity of information received in four domains: disease, medical tests, treatment, and other services. This study utilized scores from the four scale scores and from the single item “Were you satisfied with the amount of information you received?” Higher scores on these questions represent greater information support (i.e. perceptions of having received a greater quantity of information in the four measured domains, and greater satisfaction with the quantity of information received). Internal consistency and test–retest reliability for all scale scores are established (Arraras et al., 2010).

Illness perceptions

Illness perceptions were measured using the summary score of a Dutch translation of the Brief Illness Perceptions Questionnaire (B-IPQ; Broadbent et al., 2006). The B-IPQ is a self-report questionnaire that measures patients’ illness perceptions in the following domains: “consequences,” “timeline,” “personal control,” “treatment control,” “identity,” “concern,” “understanding,” and “emotional response.” “Consequences” refers to perceptions regarding the overall impact of illness, “timeline” refers to perceptions regarding the duration of illness, “personal control” refers to perceptions regarding patient ability to manage illness, “treatment control” refers to perceptions regarding the efficacy of treatment in managing illness, “identity” refers to perceived symptom experience (i.e. to what extent does one experience symptoms from illness), “concern” refers to the perceived level of concern about illness, “understanding” refers to perceived comprehension of illness, and “emotional response” refers to the perceived emotional impact of illness. Higher summary scores indicate overall more threatening or worse illness perceptions. Psychometric properties of B-IPQ summary score are established (Hallegraeff et al., 2013).

Distress

Distress was measured using the summary score of a Dutch translation of the Hospital Anxiety and Depression Scale (HADS; Zigmond and Snaith, 1983). The HADS is a 14-item measure, consisting of questions regarding patient anxiety and depression. Previous research supports use of the overall summary score as a measure of distress (López et al., 2012; Pallant and Tennant, 2007). Higher scores indicate greater symptomatology.

Statistical analysis

Data preparation and descriptive analysis took place in SPSS Version 23. Structural equation analyses were conducted in Mplus Version 7.2, using a robust maximum likelihood estimator (MLR; Muthén and Muthén 1998–2012). A mediation model was planned to evaluate study hypotheses. The following pathways were included in the model: a direct pathway from information support to distress (evaluating Hypothesis 1), a direct pathway from illness perceptions to distress (evaluating Hypothesis 2), a direct pathway from information support to illness perceptions, and an indirect pathway from information support to distress via illness perceptions (evaluating Hypothesis 3).

Prior to evaluating the mediation model, a confirmatory factor analysis (CFA) was conducted to confirm the statistical viability of the planned information support latent variable. Indicators for the variable included the four INFO25 scale scores and the INFO25 satisfaction question score. Fit indices for the model indicated poor fit to the data (Hu and Bentler, 1999): root mean square error of approximation (RMSEA) = 0.106, comparative fit index (CFI) = 0.972, and χ² (5) = 20.325, p = 0.001. There was a notable discrepancy between the amount of variance accounted for in the “other services” indicator (23.6%) versus the amount of variance accounted for in the other indicators (51.2%–75.0%). In contrast to the other scale scores, “other services” assessed information received beyond the course of primary medical care (e.g. self-care). Thus, the CFA was revised to exclude “other services.” The revised model fit the data well (RMSEA = 0.055; CFI = 0.996; χ² (2) = 3.618, p > 0.05), and all factor loadings were significant. The resulting information support latent variable was included in the mediation model used to test primary study analyses.

Results from primary analyses prompted an unplanned exploratory analysis regarding the relationship between specific illness perception domains and distress. Thus, after evaluating the mediation model, Pearson’s correlations were computed between individual illness perception domains (as measured by single item indicators on the B-IPQ) and distress (as measured by the HADS total score).

Results

Participant characteristics

Of the 334 DTC patients invited to participate, 285 mailed back the survey (“respondents”). One participant was excluded due to risk of traceability, and thus 284 were included in the structural analyses. Respondents were 76.4 percent female and diagnosed on average 9.67 years (SD = 5.36 years) prior to data collection. There were no significant differences between respondents and non-respondents on demographic or clinical variables (see Table 1).

Table 1.

Participant demographic and clinical information.

	Respondents(n = 284)	Non-respondents(n = 49)
Gender
Male	67 (23.6%)	14 (28.6%)
Female	217 (76.4%)	35 (71.4%)
Age at time of questionnaire (M, SD)	55.98 (14.12)	54.31 (16.62)
Age at diagnosis (M, SD)	46.31 (14.51)	44.55 (16.77)
Years since diagnosis (M, SD)	9.67 (5.36)	9.76 (5.25)
Tumor type
Papillary	216 (76.1%)	37 (75.5%)
Follicular	68 (23.9%)	12 (24.5%)
Stage at diagnosis
I	168 (59.2%)	29 (59.2%)
II	51 (18.0%)	11 (22.4%)
III	43 (15.1%)	6 (12.2%)
IV	17 (6.0%)	3 (6.1%)
Unknown	5 (1.8%)	0 (0%)
Primary treatment
Surgery alone	67 (23.6%)	10 (20.4%)
Surgery + ablation	207 (72.9%)	39 (79.6%)
Surgery + radiotherapy	8 (2.8%)	0 (0%)
Other	2 (.7%)	0 (0%)
Partnership^a
Partner	224 (78.9%)	–
No partner	60 (21.1%)	–
Education level^a
High	76 (26.8%)	–
Middle	177 (62.3%)	–
Low	30 (10.6%)	–
Unknown	1 (0.4%)
Employment^a
Employed	147 (51.8%)	–
Not employed	132 (46.5%)	–
Unknown	5 (1.8%)

Partnership, education level, and employment information was not available for non-respondents.

Consistent with previous studies (e.g. Roerink et al., 2013), clinical variables were not significantly related to reported distress. Specifically, there were no significant differences in distress levels between patients with a history of papillary thyroid cancer versus follicular thyroid cancer (U = 6069.500, p = 0.620), and stage was not predictive of distress levels (χ²(3) = 5.580, p = 0.134). Furthermore, age at time of questionnaire (r = 0.091, p = 0.140), time since diagnosis (r = −0.056, p = 0.362), and age at time of diagnosis (r = 0.110, p = 0.074) were not significantly correlated with distress at the 0.05 level.

Mediation model

Fit indices suggested that the hypothesized model fit the data well (RMSEA = 0.044; CFI = 0.992; χ² (8) = 12.291, p > 0.05). The paths from information support to illness perceptions (β = −0.132, SE = 0.063, p = 0.037), and from illness perceptions to distress (β = 0.470, SE = 0.047, p < 0.001) were significant, indicating that greater information support was associated with less threatening illness perceptions, and that less threatening illness perceptions were associated with less distress. The direct pathway from information support to distress was not significant (β = −0.022, SE = 0.074, p = 0.767); however, the indirect pathway from information support to distress through illness perceptions was significant (β = −0.062, SE = 0.031, p = 0.043). This indirect relationship suggested that the relationship between information support and distress was dependent on the relationship of both of these variables to illness perceptions. This model accounted for 22.4 percent of the variance in the distress variable. Model results are displayed in Figure 1.

Figure 1.

Mediation model: standardized pathway coefficients are shown.*p < 0.05; **p < 0.001.

Given the observed importance of illness perceptions with regard to distress among survivors of DTC, an unplanned exploratory analysis was conducted to determine whether certain illness perception domains in particular were related to distress. Such information could be used to further inform specific interventions to address distress in this population. Pearson’s correlations (displayed in Table 2) revealed statistically significant correlations between distress and all illness perception domains except “timeline.” Based on Cohen’s (1988) criteria, large or medium effect sizes were observed for “emotional response” (r = 0.502), “consequences” (r = 0.427), “identity” (r = 0.387), and “concern” (r = 0.360).

Table 2.

Pearson’s correlations between illness perception domains and distress.

Illness perception domain	r
Consequences(“How much does your illness affect your life?”)	0.427**
Timeline(“How long do you think your illness will continue?”)	0.093
Personal Control(“How much control do you feel you have over your illness?”)	−0.127*
Treatment Control(How much do you think treatment can help your illness?”)	−0.139*
Identity(“How much do you experience symptoms from your illness?”)	0.387**
Concern(“How concerned are you about your illness?”)	0.360**
Understanding(“How well do you feel you understand your illness?”)	−0.282**
Emotional Response(“How much does your illness affect you emotionally? E.g., does it make you angry, scared, upset, or depressed?”)	0.502**

B-IPQ: Brief Illness Perceptions Questionnaire; HADS: Hospital Anxiety and Depression Scale.

Each illness perception domain is measured by a single item on the B-IPQ, presented parenthetically. Distress is measured by the HADS total score. Perceptions of greater illness threat are represented by higher scores on Consequences, Timeline, Identity, Concern, and Emotional Response, and by lower scores on Personal Control, Treatment Control, and Understanding.

p < 0.05; **p < 0.001.

Discussion

Primary study hypotheses were largely supported from the structural equation analysis: greater information support was associated with less threatening illness perceptions, less threatening illness perceptions were associated with less distress, and greater information support was indirectly associated with less distress via illness perceptions. This study is the first to establish these relationships among survivors of DTC. The direct relationship between information support and distress was not significant. Collectively these results suggest that the effect of information on distress is dependent on impacting illness perceptions. These results also suggest that interventions targeting illness perceptions are needed to impact distress in survivors of DTC, and that information provision is one avenue through which patient illness perceptions may be influenced.

Results from the secondary, exploratory, analysis revealed that nearly all illness perception domains were associated with distress among survivors of DTC. Patient perceptions regarding emotional impact of illness, consequences of illness, symptom experience, and concern regarding illness may be particularly important to target, given that these illness perception domains (“emotional response,” “consequences,” “identity,” and “concern”) demonstrated the strongest relationships with distress. Future research may use a measure with an established factor structure (e.g. Illness Perceptions Questionnaire- Revised; Moss-Morris et al., 2002) to further evaluate relationships between particular illness perceptions domains and distress. Thus, this study provides an important starting point for determining points of intervention to address distress among survivors of DTC and implicates several illness perception domains as particularly worthy of future investigation.

Other areas of future research include investigation of the relationships among information support, illness perceptions, and distress in other populations. For example, evaluation of these relationships among recently diagnosed patients of DTC may reveal why a direct relationship between information support and distress was not evidenced in this study of long-term survivors. Indeed, direct relationships between information experience and distress variables have largely been established in oncology populations more recently diagnosed (see Husson et al., 2011), and all participants in this study were diagnosed more than years prior to data collection. Future research may also investigate whether illness perceptions mediate established relationships between information experiences and distress in other cancer populations. The extent to which information support explains variance in established associations between the doctor–patient relationship and both illness perceptions and distress (e.g. as demonstrated in Bridges and Smith, 2016) is likewise unknown. This is an important area of future investigation, given that survivors of DTC are required to have regular physician visits throughout survivorship to receive necessary thyroid hormone replacement therapy. Regular contact with physicians and continued discussions regarding their cancer histories may contribute to patients’ persistent negative illness perceptions and related distress. Future research may reveal whether addressing pertinent doctor–patient variables (including information support) may counteract such effects by directly addressing illness perceptions and distress.

This study was limited in access to clinical parameters, but as in previous research, the available clinical parameters (stage, tumor type, age at diagnosis, age at time of questionnaire, and years since diagnosis) were not significantly related to distress. Other work has also found thyroid hormone levels to be unrelated to distress among survivors of DTC (e.g. Roerink et al., 2013). However, it is important to note that survivors of DTC often require supraphysiological dosages of thyroid hormone replacement for many years. Given that thyroid hormones affect mood, analyses regarding illness perceptions and emotional functioning among survivors of DTC specifically receiving supraphysiological dosages of hormone replacement is warranted (Ritchie and Yeap, 2015). Furthermore, though clinical variables may not be directly related to distress in this population, it may be that they impact distress indirectly through other channels. For example, it could be that information support is particularly crucial with regard to impacting illness perceptions among those with later stage cancers, or that illness perceptions are more strongly predictive of distress among those more recently diagnosed. Further investigation regarding effects of clinical indicators on relationships demonstrated in this study may further illuminate how present results are informed by clinical parameters.

There is current debate regarding the classification of many thyroid conditions as cancer. Specifically, there has been a strong proposal to reclassify what has traditionally been termed encapsulated follicular variant of papillary thyroid carcinoma (EFVPTC) to “noninvasive follicular thyroid neoplasm with papillary-like nuclear features” (NIFTP) to reflect the indolent nature of this clinical presentation (Nikiforov et al., 2016). Such a change presents a natural opportunity for identifying the degree to which illness perceptions and patient distress levels are dependent on whether thyroid disease is labeled as “cancer.” Furthermore, future research may investigate whether information support and illness perceptions differentially impact distress depending on whether the patient has a diagnosis of thyroid carcinoma versus NIFTP. Relatedly, investigation of how relationships among information support, illness perceptions, and distress may differ between patients having received surgery for thyroid cancer versus patients having received surgery for other non-cancerous thyroid conditions (e.g. benign multinodular goiter) may further clarify the impact of a diagnosis of cancer on the aforementioned parameters.

Clinical implications for the study include strong support for continued evaluation of patient illness perceptions by medical professionals. Illness perceptions may play a key role in distress years after the diagnostic period, as results from this study were found for a survivorship population diagnosed, on average, 9.76 years prior to data collection. Continued communication between medical professionals and patients will be vital to achieve this goal. Furthermore, information support will be necessary for patients who experience changes in the classification of their disorder (i.e. from EFVPTC to NIFTP). Overall, this study suggests that ongoing efforts to satisfy patient information needs and address illness perceptions may influence distress in survivors of DTC and improve overall quality of care.

Footnotes

Acknowledgements

The authors would like to dedicate this work to Nicholas J. Cassisi, D.D.S., M.D., Chairman Emeritus at the Department of Otolaryngology, University of Florida College of Medicine. He successfully treated many thyroid cancer patients throughout his career and his insights about patient care were an inspiration for this article.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

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