The influence of pre-visit anxiety on patient-provider communication and breast cancer patient uncertainty

doi:10.21203/rs.3.rs-3417178/v1

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Research Article

The influence of pre-visit anxiety on patient-provider communication and breast cancer patient uncertainty

https://doi.org/10.21203/rs.3.rs-3417178/v1

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Purpose: Effective communication between cancer patients and providers is critical for addressing psychological distress, reducing uncertainty, and promoting patient well-being. This is particularly relevant during medical appointments that may elicit uncertainty, such as surgical consultations for newly diagnosed women with breast cancer. This study aimed to evaluate how pre-appointment anxiety affects patient-provider communication in breast cancer surgical consultations and subsequent post-appointment well-being. Breast cancer patient anxiety has been studied as an outcome of provider communication, though less is known about the extent to which pre-existing anxiety acts as an antecedent to effective patient-provider communication.

Methods: This study analyzed videorecorded breast cancer surgical consultations (N = 51) and corresponding patient surveys to understand how pre-appointment anxiety influences pre-appointment patient uncertainty, patient-provider communication during the appointment, and subsequent post-appointment uncertainty.

Results: Overall, patients with elevated pre-appointment anxiety (n = 12) did not have more pre-appointment uncertainty but were interrupted by their provider at a higher rate than those without anxiety. The proposed model achieved good fit to the data such that more pre-appointment anxiety was associated with more pre-appointment uncertainty, more pre-appointment anxiety was associated with more empathic opportunities per minute, and more empathic opportunities were associated with less post-appointment uncertainty.

Conclusions: Results provide new understanding for how patient anxiety acts as an antecedent to effective patient-provider communication and how this affects patient uncertainty post-appointment. Assessing breast cancer patients’ psychological well-being is crucial for identifying those at higher risk of poor health outcomes and providing holistic cancer care.

Breast Cancer

Oncology

Anxiety

Uncertainty

Communication

Anxiety is highly prevalent among breast cancer patients, with more than one-third of patients in the U.S. experiencing a degree of anxiety throughout their diagnosis and treatment [1–3]. Importantly, breast cancer patients who have symptoms of anxiety have a higher risk for both morbidity and mortality [4, 5]. It is critical that cancer care providers have the tools to understand and address the high prevalence of anxiety in breast cancer patients to meet the needs of this population. Current research favors anxiety and psychological distress as outcomes of medical interactions [6, 7]. However, given the high prevalence of anxiety in this patient population, it is important to investigate the ways in which pre-existing levels of anxiety affect additional aspects of breast cancer patients’ processing and coping with their diagnosis. One potential consequence of anxiety ahead of a medical appointment is patients’ illness uncertainty. Using Uncertainty in Illness Theory [8] and patient-centered communication [9] as frameworks, this study explores how breast cancer patient uncertainty and anxiety pre-appointment influence patient-provider communication and subsequent post-appointment uncertainty.

Breast Cancer and Uncertainty

Illness uncertainty is a cognitive and emotional state in which patients dealing with novel, complex, and/or ambiguous health events are unable to make meaning of these events [8]. Breast cancer patients experience this throughout the illness trajectory, from diagnosis to treatment and beyond [3, 10, 11]. Uncertainty about the diagnosis, cancer-related symptoms, illness prognosis, and treatment decisions all contribute a worse quality of life for breast cancer patients [12–14]. Moreover, illness uncertainty is positively correlated with anxiety during diagnosis [15] and is associated with worse psychological well-being during both the treatment and post-treatment stages [16].

Uncertainty in Illness Theory (UIT) posits that illness uncertainty is influenced by patients’ perceptions of illness-related events (stimuli frame), and appraisal of the stimuli frame is influenced by patients’ cognitive capacity [8, 17]. UIT further suggests that appraisals of illness uncertainty subsequently influence coping with illness. Most investigations of UIT that measure psychological features have considered it in relation to coping and as a final outcome of the model [16–19], but have not explored how cognitive capacity is posited to affect patient outcomes. This study seeks to further understand the cognitive capacity construct, investigating how clinical anxiety acts as an independent variable in the model. We propose the following hypotheses (see Fig. 1A for the hypothesized model):

H1: Clinical anxiety will be positively associated with breast cancer patients’ pre-appointment illness uncertainty.

H2: Breast cancer patients’ pre-appointment illness uncertainty will be positively associated with post-appointment illness uncertainty.

Patient-Centered Communication and Uncertainty

One way clinicians can manage patients’ illness uncertainty is through patient-centered communication [16, 20, 21]. Patient-centered communication is conceptualized as communication that (1) elicits patient perspectives, (2) seeks to understand each patients’ unique psychosocial context, (3) creates treatment plans aligned with patients’ beliefs, and (4) creates shared power within the interaction [22]. Patient-centered communication predicts patient outcomes including improved satisfaction, psychological adjustment, stronger therapeutic relationships, and increased patient participation [9, 23–25]. However, it is unclear whether pre-existing anxiety affects how provider communication facilitates this process. In contexts outside of breast cancer, uncertainty is associated with cognitive states that bias information processing and subsequent communication [26]. It is possible that patient anxiety and uncertainty prior to medical encounters may similarly bias information processing and, subsequently, change dynamics of patient-provider communication. However, the connection between illness uncertainty and communication consequences in oncology appointments has not been investigated. Understanding the conditions for effective patient-centered communication is important for optimally supporting breast cancer patient well-being. The following sections will discuss specific patient and provider communication behaviors that significantly impact the level of patient-centered communication in breast cancer appointments.

Patients: Empathic Opportunities

Empathic communication, specifically empathic opportunities, is a robustly operationalized aspect of patient-centered communication in the cancer context [27–29]. Empathic opportunities refer to patient statements that express an emotion such as fear, worry, or relief and explicitly give the medical provider the opportunity to respond empathically [29]. We argue that empathic opportunities align with the first two tenants above (communication that elicits patient perspectives and seeks to understand patients’ unique psychosocial context). Although not patient-centered communication itself, they may indicate a level of comfort with the provider implicit in providing such an opportunity. Moreover, multiple instances of empathic opportunities may indicate a positive reception of previous opportunities and the establishment of a positive patient-provider relationship [30]. Given that illness uncertainty and pre-appointment anxiety may bias patients’ processing of provider communication, this study investigates the following research questions:

RQ1: Is pre-appointment illness uncertainty associated with differing levels of empathic opportunities per minute from breast cancer patients?

RQ2: Are empathic opportunities from breast cancer patients associated with differing levels of post-appointment uncertainty?

Providers: Interruptions & Responses to Empathic Opportunities

One goal of patient-centered care is to facilitate patient participation within medical interactions. Notably, patient participation is also influenced by patients’ psychological processing. Patients with better psychological adjustment are often more participative than those experiencing maladaptive coping styles [31]. Thus, to support all breast cancer patients, providers need to communicate in ways that facilitate both patient involvement within medical appointments and considers patients’ psychological well-being. Encouraging empathic opportunities may help achieve this goal. However, cancer care providers often miss these opportunities [30, 32], which may hinder patient comfort and participation. One way that these opportunities could be missed is through provider conversational dominance, specifically, provider interruptions. When providers interrupt patients, patients may not have the opportunity to fully express their thoughts, feelings, and concerns, which is in direct opposition to the goals of patient-centered communication. Thus, we argue that provider interruptions stand to hinder tenants of patient-centered communication (communication that elicits patient perspectives and creates shared power within the interaction). To investigate the relationships between patient illness uncertainty, oncologist interruptions, and oncologist responses to empathic openings, the following research questions are proposed:

RQ3: Is pre-appointment illness uncertainty associated with differing levels of interruptions by the oncologist?

RQ4: Are interruptions by the oncologist associated with differing levels of post-appointment illness uncertainty?

RQ5: Does the type of provider response to empathic opportunities (missed or not) influence post-appointment illness uncertainty?

Sampling and Procedures

This study involved secondary analysis of videorecorded breast cancer surgical consultations and patient surveys [33]. Primary data were collected between April-December 2009 at a National Cancer Institute-designated comprehensive cancer center in the northeastern United States. Eligible participants were English speaking women newly diagnosed with breast cancer attending a surgical consultation. A single breast surgeon conducted all consultations. Of the 74 participants who consented to be part of the study, 51 completed both pre- and post-appointment surveys. Video recordings of each consultation were reviewed by the first author. Participants were compensated $20. The original study was approved by an Institutional Review Board.

Measures

A series of analyses were conducted to check reliability, dimensionality, and factor structure for survey measures. Confirmatory factor analyses (CFA) were assessed using a combination of fit statistics including c², root mean square error of approximation (RMSEA), confirmatory fit index (CFI), and standardized root mean square residual (SRMR). Good fit was considered at RMSEA < 0.06, CFI > 0.95, and SRMR < 0.08 [34].

Clinical Anxiety

Anxiety (H1) was measured using the 7-item anxiety scale from the Hospital Anxiety and Depression Scale (HADS) [35]. The HADS asked participants to rate how often they experienced symptoms of anxiety on 4-point scales specific to each item. An example item is, “I feel tense or ‘wound up’” (not at all to most of the time). Confirmatory factor analysis supported a unidimensional structure and good model fit (c² = 15.66 (14), p = 0.33; RMSEA = 0.05; CFI = 0.99; SRMR = 0.06). The scale achieved good reliability (α = 0.89). Items were totaled for a score that could range from 0–21. Scores from 0–7 are considered no anxiety, 8–10 are borderline anxiety, and scores ≥ 11 represent clinical cases of anxiety [35]. Scores were dichotomized as clinical anxiety (HADS ≥ 11, n = 12) and low anxiety (HADS < 11, n = 35) for group comparisons and left as a continuous ordinal score for modeling.

Pre- and Post-Appointment Uncertainty

Illness uncertainty (H2, RQ1-4) was assessed using an adapted 7-item version of the Uncertainty in Illness Scales [36]. Participants responded to the scale pre- and post-appointment. Items were adapted for this population and treated based factor analyses described previously [37]. Participants rated the degree to which they agreed with statements about their uncertainty on a 5-point scale (strongly disagree to strongly agree). An example item is, “Because of the unpredictability of my illness, I cannot plan for the future.” Pre- and post-appointment uncertainty achieved good reliability (α = 0.86 and 0.80, respectively). Confirmatory factor analysis supported unidimensional factor structures for pre- and post-appointment uncertainty. Pre- appointment uncertainty did not achieve acceptable model fit (c² = 30.42 (14), p = 0.01; RMSEA = 0.16; CFI = 0.88; SRMR = 0.07). Post-appointment uncertainty did achieve good model fit (c² = 12.61 (14), p = 0.56; RMSEA < 0.01; CFI = 1.00; SRMR = 0.05). Thus, no additional modifications to the scale were made. Items were summed for a final composite score that could range from 7–35. Higher scores indicate more illness uncertainty.

Empathic Opportunities

Empathic opportunities (RQ1, RQ2) were assessed using an adapted form of an established empathic communication coding framework [29]. Empathic opportunities were defined as statements that directly expressed an emotion such as fear, worry, or relief. In a limited number of cases (n = 3) the provider initiated an opportunity by inviting the patient to share their feelings without verbal prompting by the patient. Most consultations (68.63%) had between one and three empathic opportunities. Two appointments had no empathic opportunities and one appointment had nine opportunities. To account for varying lengths of appointments, number of empathic opportunities was divided by length of the consultations for a rate of empathic opportunities.

Aligned with the above framework [29], provider response to each empathic opening was also coded. Responses were coded as missed, positive, or negative (see Table 1). Missed opportunities were those where the provider did not explicitly acknowledge the emotion behind the statement and continued with the discussion. Responses that acknowledged the empathic opening were further categorized as either positive or negative. Provider initiated empathic openings were coded as positive empathic openings. To account for varying lengths of appointments, the total number of each response type was divided by consultation length for response type rates.

Provider Interruptions

Provider interruptions (RQ3, RQ4) were considered when the oncologist’s speaking turn cut patients off mid-sentence or spoke over to the extent that patients could not be understood. Most consultations (76.5%) had ≥ 3 instances of the provider interruptions. Two appointments had no instances of provider interruptions; one appointment had 15. To account for varying appointment lengths, the number of interruptions was divided by the consultation length for a rate of provider interruptions. To account for varying patient participation, patient word count was divided by interruption rate to create a rate of provider interruptions as a function of participation.

Analyses

Initial analyses included one-tailed bivariate correlations with Bonferroni-adjusted significance levels across model variables. Hypothesized relationships among study variables were tested using one-tailed t-tests. Differences between patients with high versus low anxiety were compared on all study variables using c² and two-tailed t-tests. Path analysis assessed overall fit of the proposed model. Model fit was assessed using the same fit criteria described above. Linear regression modeling was conducted using response types (missed, positive, or negative) as predictors and post-appointment uncertainty as the dependent variable. Data were analyzed using STATA MP (version 17.0).

Participants, Demographics, and Descriptive Statistics

Basic demographic information (age, education, race, marital status, and income) was collected (see Table 2). Consultations lengths ranged from 9.3 to 60.7-minutes (M = 27.4-minutes). Patients with clinical anxiety did not have more pre-appointment uncertainty (p = 0.94) but were interrupted at a higher rate (p = 0.04) than those without clinical anxiety. Pairwise correlation of model variables with Bonferroni corrections revealed only one statistically significant correlation; pre-appointment uncertainty was correlated with post-session uncertainty (p < 0.01). Although moderate correlations were present (i.e., > 0.25), no other relationships were significant (see Table 3).

Path Modeling (H1, H2, RQ1-4)

Path modeling was performed to test whether the theoretical model in Fig. 1A was supported. The proposed model achieved excellent data fit (χ² (4) = 4.29, p = 0.37; RMSEA = 0.04; CFI = 0.99; SRMR = 0.07) (see Fig. 1B). The path from clinical anxiety was positively associated with pre-appointment uncertainty (p = 0.03); H1 supported. Pre-appointment uncertainty was positively associated with post-appointment uncertainty (p < 0.01) such that more uncertainty pre-appointment was associated with more uncertainty post-appointment (H2 supported). The path from pre-appointment uncertainty was positively associated with the rate of empathic openings (p = 0.02) such that more uncertainty was related to more empathic opportunities (RQ1). The path from empathic openings was negatively associated with post-appointment uncertainty and approached statistical significance (p = 0.06) such that a higher rate of empathic openings was related to less post-appointment uncertainty (RQ2). The paths from pre-appointment uncertainty to provider interruptions (RQ3) and from provider interruptions to post-appointment uncertainty (RQ4) were not statistically significant (p = 0.58 and 0.83, respectively).

To improve model fit, the path from provider interruptions to post-appointment uncertainty (RQ4) was removed and the path analysis was re-run. This path had the smallest coefficient and a non-significant p-value. Overall, the adjusted model also achieved excellent fit to the data (χ² (5) = 4.34, p = 0.50; RMSEA < 0.01; CFI = 1.00; SRMR = 0.07) (see Fig. 1C). All paths were statistically significant except for the path from pre-appointment uncertainty to provider interruptions (RQ3). This adjusted model was not a significantly better fit to the data than the original hypothesized model (Δχ² = 0.05, Δdf = 1, p = 0.82).

Linear Regression Modeling (RQ5)

Linear regression modeling of post-appointment uncertainty explored the possible influence of provider responses to empathic openings on post-appointment uncertainty (RQ3). Results revealed no significant predictors, though positive responses were trending significant (β = -32.21, p = 0.06) such that a higher rate of positive responses to empathic openings was associated with lower levels of post-session uncertainty. Missed opportunities (β = 4.21, p = 0.70) and negative responses (β = -19.96, p = 0.19) were not significant predictors. Overall, the regression model provided minimal explanatory power (F (3, 46) = 1.85, p = 0.15), predicting 10.76% of the variance in the response variable (R-squared = 0.11).

This study evaluated how pre-appointment anxiety affects patient-provider communication in breast cancer surgical consultations. Pre-appointment anxiety was associated with higher levels of pre-appointment uncertainty and, subsequently, more empathic openings per minute. In other words, more anxious breast cancer patients arrived at their surgical consultation with more uncertainty about their illness and offered more statements about their emotions. This adds to extant literature that describes differences in patient participation in care based on their psychological well-being [31]. Additionally, patients who provided more emotion statements generally had less post-appointment uncertainty, despite differences in how the provider responded to those statements. Previous research has demonstrated an association between illness uncertainty and psychological adaptation to illness [16]. Knowing that patients who arrived to their appointment with more anxiety had more uncertainty, these findings support emotion statements as a patient communication behavior that may have a positive effect on well-being independent of provider communication.

Patients with high anxiety experienced more provider interruptions per minute despite having no difference in the amount of patient participation. This may indicate a subtle difference in patient assertiveness when anxiety levels are high before medical appointments, aligning with limited research available on this topic. In family medicine higher levels of pre-appointment anxiety predict higher levels of provider information-giving [38] and individual differences in breast cancer patient characteristics have been associated with different communication patterns during appointments [39].

The current study has several strengths. It combines patient survey data and videorecorded medical interactions, allowing for the association of patient perceptions and physician behaviors in the same study. Although existing interpersonal communication literature emphasizes the use of theory to guide study design, the theories employed are often tested using self-report surveys, rather than actual communication behaviors. This study situates the logic of UIT as antecedent to actual patient-provider communication behaviors – a unique contribution to the body of work supporting UIT. Additionally, the pre- and post-appointment survey design supports the proposed directionality of provider behaviors on patient outcomes.

Study Limitations

Along with the strengths above, there are important study limitations to consider. This study utilized data from only one provider. We cannot conclude whether patterns seen in this study generalize to surgical oncology, early breast cancer appointments, oncology care more broadly, or if it is unique to this provider. Other oncologists may have different patterns of communication that could influence how these findings generalize across providers. Next, given the limited sample size of this study, detailed comparisons of model constructs across demographic variables were not sufficiently powered. Future studies should expand the current efforts by including multiple clinicians and replicating the methods within a population of patients of diverse sociodemographic identities. Despite these limitations, this study is expected to contribute to the broader literature on anxiety, illness uncertainty, and patient-provider communication in a breast cancer context.

Clinical Implications

Results indicate breast cancer patients with anxiety pre-appointment are at-risk for more illness uncertainty and are more likely to explicitly provide empathic opportunities. This supports the need for added attention to empathic opportunities to not only address patients emotionally, but to also assess whether a patient may be at higher risk to have pre-existing anxiety. Additionally, results provide evidence for the effects of positive provider responses to empathic openings. Although not significant in our data, positive responses to empathic openings trended towards significantly predicting a reduction of post-appointment uncertainty. Because reduction of breast cancer patient uncertainty is associated with better psychological outcomes [16], this finding may have implications for patients beyond the initial interaction. Future research should clarify the effects of providers positively responding to empathic openings to address patient uncertainty versus the effects of providing an empathic opening on its own (i.e., indicating feeling comfortable with the provider).

The content of breast cancer surgical consultations (i.e., providing surgical treatment options and education) has been shown previously to help reduce patient anxiety [40]. However, patient anxiety pre-appointment has had limited investigation as an antecedent to patient-provider communication. Recognizing patients’ psychological well-being remains critical for all oncology care providers. Awareness of patient pre-appointment anxiety can guide providers to invite more empathic opportunities and be cautious of their own communication behaviors. Results provide new understanding for how patients’ pre-appointment anxiety influences effective patient-provider communication and post-appointment uncertainty. Assessing the psychological well-being of breast cancer patients is crucial for identifying those at high risk of negative health outcomes and providing holistic care.

Acknowledgements

The authors would like to thank the participants who spent their time and energy to provide these data. We would like to acknowledge the efforts of Drs. Jeffrey Robinson and Robert Kearney in the conceptualization and primary data collection.

Declaration of Interest Statement

The authors declare no competing interests.

Ethics Approval

This study was approved by the Rutgers University Institutional Review Board on May 22, 2008 (approval #08-426M).

Funding Statement

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Consent to Participate

Informed consent was obtained from all individual participants included in the study.

Burgess C, Cornelius V, Love S, Graham J, Richards M, Ramirez A (2005) Depression and anxiety in women with early breast cancer: Five year observational cohort study. BMJ 330:1–4. https://doi.org/10.1136/bmj.38343.670868.D3
Hashemi S-M, Rafiemanesh H, Aghamohammadi T, Badakhsh M, Amirshahi M, Sari M, Niaz B, Kamran R (2020) Prevalence of anxiety among breast cancer patients: A systematic review and meta-analysis. Breast Cancer 27:166–178. https://doi.org/10.1007/s12282-019-01031-9
Sutton TL, Koprowski MA, Grossblatt-Wait A, Brown S, McCarthy G, Liu B, Gross A, Macuiba C, Hedlund S, Brody JR, Sheppard BC (2022) Psychosocial distress is dynamic across the spectrum of cancer care and requires longitudinal screening for patient-centered care. Support Care Cancer 30:4255–4264. https://doi.org/10.1007/s00520-022-06814-z
Kisely S, Alotiby MKN, Protani MM, Soole R, Arnautovska U, Siskind D (2023) Breast cancer treatment disparities in patients with severe mental illness: A systematic review and meta-analysis. Psychooncology 32:651–662. https://doi.org/10.1002/pon.6120
Wang X, Wang N, Zhong L, Wang S, Zheng Y, Yang B, Zhang J, Lin Y, Wang Z (2020) Prognostic value of depression and anxiety on breast cancer recurrence and mortality: A systematic review and meta-analysis of 282,203 patients. Mol Psychiatry 25:3186–3197. https://doi.org/10.1038/s41380-020-00865-6
Street RL, Makoul G, Arora NK, Epstein RM (2009) How does communication heal? Pathways linking clinician-patient communication to health outcomes. Patient Edu Couns 74:295–301. https://doi.org/10.1016/j.pec.2008.11.015
Brandão T, Schulz MS, Matos PM (2017) Psychological adjustment after breast cancer: A systematic review of longitudinal studies. Psychooncology 26:917–926. https://doi.org/10.1002/pon.4230
Mishel MH (1988) Uncertainty in illness. Image J Nurs Sch 20:225–232. https://doi.org/10.1111/j.1547-5069.1988.tb00082.x
Epstein RM, Street RL (2007) Patient-centered communication in cancer care: Promoting healing and reducing suffering. National Institutes of Health, Bethesda, MD
Mehnert A, Hartung TJ, Friedrich M, Vehling S, Brähler E, Härter M, Hubshman M, Schulz H, Wegscheider K, Weis J, Koch U, Faller Hermann (2018) One in two cancer patients is significantly distressed: Prevalence and indicators of distress. Psychooncology 27:75–82. https://doi.org/10.1002/pon.4464
Rogers CC, Pope S, Whitfield F, Cohn WF, Valdez RS (2022) The lived experience during the peri-diagnostic period of breast cancer: A scoping review. Patient Edu Couns 105:547–585. https://doi.org/10.1016/J.PEC.2021.06.017
Engelhardt EG, Pieterse AH, Han PKJ, van Duijn-Bakker N, Cluitmans F, Maartense E, Bos M, Weijl NI, Punt CJA, Quarles PVUM, Sleebook H, Portielje JEA, van der Hoeven KJM, Woei-A-Jin FJS, Kroep JR, de Haes HCJM, Smets EMA, Stiggelbout AM (2017) Disclosing the uncertainty associated with prognostic estimates in breast cancer: Current practices and patients’ perceptions of uncertainty. Med Decis Making 37:179–192. https://doi.org/10.1177/0272989X16670639
Liu L-N, Li C-Y, Tzuh S, Huang CS, Chiou AF (2006) Role of continuing supportive cares in increasing social support and reducing perceived uncertainty among women with newly diagnosed breast cancer in Taiwan. Cancer Nurs 29:273–282. https://doi.org/10.1097/00002820-200607000-00004
Parker PA, Alba F, Fellman B, Urbauer DL, Li Y, Karam JA, Tannir N, Jonasch E, Wood CG, Matin SF, Parker PA (2013) Illness uncertainty and quality of life of patients with small renal tumors undergoing watchful waiting: A 2-year prospective study. Eur Urol 63:1122–1127. https://doi.org/10.1016/j.eururo.2013.01.034
Liao M-N, Chen M-F, Chen S-C, Chen P-L (2008) Uncertainty and anxiety during the diagnostic period for women with suspected breast cancer. Cancer Nurs 31:274–283. https://doi.org/10.1097/01.NCC.0000305744.64452.fe
Broadbridge E, Greene K, Venetis MK, Lee LE, Banerjee SC, Saraiya B, Devine KA (2023) Facilitating psychological adjustment for breast cancer patients through empathic communication and uncertainty reduction. Patient Edu Couns 114:107791. https://doi.org/10.1016/j.pec.2023.107791
Clayton MF, Mishel MH, Belyea M (2006) Testing a model of symptoms, communication, uncertainty, and well-being, in older breast cancer survivors. Res Nurs Health 29:18–39. https://doi.org/10.1002/nur.20108
Guan T, Santacroce SJ, Chen D-G, Song L (2020) Illness uncertainty, coping, and quality of life among patients with prostate cancer. Psychooncology 29:1019–1025. https://doi.org/10.1002/pon.5372
Broadbridge E, Greene K, Venetis MK, Lee LE, Banerjee SC, Buckley de Meritens A, Catona D, Devine KA (2023) The influence of perceived provider empathic communication on disclosure decision making. Health Commun 1–18. https://doi.org/10.1080/10410236.2023.2243409
Clayton MF, Dudley WN, Musters A (2008) Communication with breast cancer survivors. Health Commun 23:207–221. https://doi.org/10.1080/10410230701808376
Lake PW, Conley CC, Pal T, Sutton SK, Vadaparampil ST (2022) Anxiety and depression among Black breast cancer survivors: Examining the role of patient-provider communication and cultural values. Patient Edu Couns 105:2391–2396. https://doi.org/10.1016/j.pec.2021.12.020
Epstein RM, Franks P, Fiscella K, Shields CG, Meldrum SC, Kravitz RL, Duberstein PR (2005) Measuring patient-centered communication in patient-physician consultations: Theoretical and practical issues. Soc Sci Med 61:1516–1528. https://doi.org/10.1016/j.socscimed.2005.02.001
Mead N, Bower P (2000) Patient-centredness: A conceptual framework and review of the empirical literature. Soc Sci Med 51:1087–1110. https://doi.org/10.1016/S0277-9536(00)00098-8
Pinto RZ, Ferreira ML, Oliveira VC, Franco MR, Adams R, Maher CG, Ferreira PH (2012) Patient-centred communication is associated with positive therapeutic alliance: A systematic review. J Physiother 58:77–87. https://doi.org/10.1016/S1836-9553(12)70087-5
Zwingmann J, Baile WF, Schmier JW, Bernhard J, Keller M (2017) Effects of patient-centered communication on anxiety, negative affect, and trust in the physician in delivering a cancer diagnosis: A randomized, experimental study. Cancer 123:3167–3175. https://doi.org/10.1002/cncr.30694
Knobloch LK, Satterlee KL (2009) Relational uncertainty: Theory and application. In: Afifi TD, Afifi WA (eds) Uncertainty, information management, and disclosure decisions: theories and applications. Routledge, New York, pp 106–127
Bylund CL, Makoul G (2002) Empathic communication and gender in the physician–patient encounter. Patient Edu Couns 48:207–216. https://doi.org/10.1016/S0738-3991(02)00173-8
Mercer SW, Maxwell M, Heaney D, Watt GCM (2004) The consultation and relational empathy (CARE) measure: Development and preliminary validation and reliability of an empathy-based consultation process measure. Fam Pract 21:699–705. https://doi.org/10.1093/FAMPRA/CMH621
Suchman AL, Markakis K, Beckman HB, Frankel R (1997) A model of empathic communication in the medical interview. JAMA 277:678–682. https://doi.org/10.1001/JAMA.1997.03540320082047
Morse DS, Edwardsen EA, Gordon HS (2008) Missed opportunities for interval empathy in lung cancer communication. AMA Arch Intern Med 168:1853–1858. https://doi.org/10.1001/archinte.168.17.1853
Venetis MK, Greene K, Checton MG, Magsamen-Conrad K (2015) Decision making in cancer-related topic avoidance. J Health Commun 20:306–313. https://doi.org/10.1080/10810730.2014.965364
Hsu I, Saha S, Korthuis PT, Sharp V, Cohn J, Moore RD, Beach MC (2012) Providing support to patients in emotional encounters: A new perspective on missed empathic opportunities. Patient Edu Couns 88:436–442. https://doi.org/10.1016/j.pec.2012.06.015
Venetis MK, Robinson JD, Kearney T (2013) Consulting with a surgeon before breast cancer surgery: Patient question asking and satisfaction. J Health Commun 18:943–959. https://doi.org/10.1080/10810730.2012.757391
Hu L, Bentler PM (1999) Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal 6:1–55. https://doi.org/10.1080/10705519909540118
Zigmond AS, Snaith RP (1983) The Hospital Anxiety and Depression Scale. Acta Psychiatr Scand 67:361–370. https://doi.org/10.1111/J.1600-0447.1983.TB09716.X
Mishel MH (1996) Uncertainty in illness scales manual
Venetis MK (2010) Communication-participation behavior during the delivery of breast-cancer care. Doctoral dissertation, Rutgers University
Street RL (1991) Information-giving in medical consultations: The influence of patients’ communicative styles and personal characteristics. Soc Sci Med 32:541–548. https://doi.org/10.1016/0277-9536(91)90288-N
Siminoff LA, Graham GC, Gordon NH (2006) Cancer communication patterns and the influence of patient characteristics: Disparities in information-giving and affective behaviors. Patient Edu Couns 62:355–360. https://doi.org/10.1016/J.PEC.2006.06.011
Morris J, Royle GT (1988) Offering patients a choice of surgery for early breast cancer: A reduction in anxiety and depression in patients and their husbands. Soc Sci Med 26:583–585. https://doi.org/10.1016/0277-9536(88)90021-4

Table 1

Example empathic opportunities and responses.
	Example
Patient-initiated opening n = 147 (98%)	P:So that is going to be a separate issue altogether? O: Yes. I doubt that it is going to be an issue for you, and I am just basing that on experience. P:I’m just trying to prepare myself, you know, asking the worst questions so this way I am not worrying with it.
Possible responses	Example
Missed opportunity n = 96 (64%)	O: So let’s assume that it’s okay and so we don’t really have to do anything over there, just deal with the left side. P: We can be hopeful. I could use something good. O: So at that point we’ve done the mastectomy and we’ve done the reconstruction so the treatment of the breast is done. Now, we’re going to totally switch gears now.
Positive response n = 25 (17%)	P: …I think the thing that stresses me and gets me worried and panicked is surgery. I never had surgery. I had my wisdom teeth removed, you know, but that’s as far as it went. So that scares me, you know? O: Yeah, and that’s very understandable.
Negative response n = 29 (19%)	P: This is a little more complicated than I thought. O: Oh, this is very complicated. This is a complicated – P: I thought that since it’s such an early stage, that basically I would have a lumpectomy, and I would not need radiation. O: Right, so whatever your source of information was, it’s not correct.

Note. P = Patient, O = Oncologist.

Table 2

Demographic information and descriptive statistics.
	Total N = 47	Low anxiety n = 35	High anxiety n = 12	p-value
Age – Mean (SE)	53.89 (1.58)	54.37 (1.73)	52.81 (3.40)	0.42 †
Education – frequency				0.10 ‡
High school or less	12	9	3
2 years of college	8	7	1
4 years of college	19	11	8
Advanced degree	8	8	0
Race/ethnicity – frequency				0.16 ‡
White/Caucasian	39	31	8
Black/African American	2	1	1
Hispanic	2	0	2
Asian	4	3	1
Income – frequency				0.93 ‡
$0-$75,000	20	15	5
$76,000-$200,000+	23	17	6
Marital status				0.32 ‡
Single and never married	4	2	2
Single and divorced/widowed	14	12	2
Legally married or domestic partnership	29	21	8

Note. SE = Standard error.

† One-way analysis of variance with Bonferroni-adjusted significance levels.

‡ Chi-square test.

Table 3

Descriptive statistics and correlations between model variables
				Correlations
Variable	M	SD	⍺	(1)	(2)	(3)	(4)	(5)
(1) Pre-appointment anxiety	8.06	4.17	0.89	--
(2) Pre-appointment uncertainty	17.98	6.28	0.86	0.30	--
(3) Post-appointment uncertainty	14.38	4.37	0.80	0.28	0.59*	--
(4) Rate of empathic openings	0.11	0.08	--	0.12	0.27	-0.14	--
(5) Rate of interruptions	0.18	0.10	--	0.25	-0.04	-0.09	0.30	--

Note. M = mean, SD = standard deviation; ⍺ = Cronbach’s alpha. One-tailed Bonferroni-corrected correlations (* p < .01).

No competing interests reported.

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Reviewers agreed at journal
28 Nov, 2023
Reviewers invited by journal
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Editor assigned by journal
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Submission checks completed at journal
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First submitted to journal
06 Oct, 2023

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The influence of pre-visit anxiety on patient-provider communication and breast cancer patient uncertainty

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