Problem-Solving Skills Training in Adult Cancer Survivors: Bright IDEAS-AC Pilot Study

Abstract

Purpose

Cancer patients experience significant distress and burden of decision-making throughout treatment and beyond. These stressors can interfere with their ability to make reasoned and timely decisions about their care and lead to low physical and social functioning and poor survival. This pilot study examined the impact of offering Problem-Solving Skills Training (PSST) to adult cancer survivors to help them and their caregivers cope more successfully with post-treatment decision-making burden and distress.

Patients and Methods

Fifty patients who completed their definitive treatment for colorectal, breast or prostate cancer within the last 6 months and reported distress (level > 2 on the National Comprehensive Cancer Network distress thermometer) were randomly assigned to either care as usual (CAU) or 8 weekly PSST sessions. Patients were invited to include a supportive other (n=17). Patient and caregiver assessments at baseline (T1), end of intervention or 3 months (T2), and at 6 months (T3) focused on problem-solving skills, anxiety/depression, quality of life and healthcare utilization. We compared outcomes by study arm and interviewed participants about PSST burden and skill maintenance.

Results

Trial participation rate was 60%; 76% of the participants successfully completed PSST training. PSST patients reported reduction in anxiety/depression, improvement in QoL (p<0.05) and lower use of hospital and emergency department services compared to CAU patients (p=0.04).

Conclusions

The evidence from this pilot study indicates that a remotely delivered PSST is a feasible and potentially effective strategy to improve mood and self-management in cancer survivors in community oncology settings.

1. INTRODUCTION

Recent advances in cancer treatment and gains in life expectancy mean that close to 40% of Americans will be diagnosed with cancer at least once in their lifetime.¹ Despite significant breakthroughs in management, cancer patients and survivors experience significant stress throughout the entire continuum of treatment, including the transition to post-treatment survivorship. A large body of literature shows that negative affectivity and poor problem-solving skills are associated with poor treatment adherence and prognosis.^2–4 Recent evidence demonstrates^3,5–9 that cancer survivors are often distressed and overwhelmed by the burden of decision making and prioritizing among family obligations and self-care, employment and disability-related issues, coordination of primary care and specialist services, insurance coverage and other costs.

Prior research has demonstrated that problem-solving skills training (PSST) offered to both cancer patients and their caregivers/supportive others (SO) can significantly improve problem-solving abilities and reduce negative affectivity.^10–12 However, to date, there have been no studies examining whether improvement in problem-solving skills translates into better patient self-management, quicker return to regular activities, and lower utilization of emergency and inpatient services.

We examined the feasibility and preliminary impact of offering the Bright IDEAS system of PSST to adult cancer survivors, Bright IDEAS-AC (BI-AC), to help them and their caregivers improve long-term quality of life and self-management skills. The study tested the following hypotheses: (1) At least 70% of contacted patients will enroll in the study; (2) At least 80% of patients randomized to PSST will complete 80% of PSST sessions; (3) At least 50% of patients will identify a supportive other to join them in learning about problem solving PSST; and (4) At least 50% of patients will identify usefulness of the PSST training as > 3 on a 5-point Likert scale (useful or very useful).

To maximize potential future implementation and dissemination of BI-AC, this pilot study was guided by the Reach, Efficacy/Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework.¹⁵ In addition to Effectiveness, our study assessed the potential of BI-AC for Implementation and Maintenance. Implementation was defined as the extent to which participants in the intervention arm adhered to the intervention protocol. Problem-solving skills maintenance was assessed post-study as the degree to which initial changes in participant behavior were sustained post-intervention.

2. PATIENTS AND METHODS

2.1. Recruitment and Study Population

Adult cancer patients who had completed treatment for stage I-III colorectal, breast or prostate cancer within the previous 6 months were recruited from clinics at Roswell Park Comprehensive Cancer Center (Roswell), Buffalo, NY and Wilmot Cancer Institute (WCI), Rochester, NY. Patients who lived >40 miles from the cancer center were specifically targeted as this population is known to have poorer access to care.¹⁶

Eligibility criteria included: (a) English speaker; (b) a 5-year survival rate of ≥50% deemed by their physician; and (c) a distress level > 2 on the National Comprehensive Cancer Network (NCCN) distress thermometer. The NCCN thermometer is a commonly used tool to assess patient distress during the previous week on a 0 to 10 scale, with any patient reporting distress ≥8 being referred for further psychological evaluation and treatment. For this study we included patients who reported distress greater than 2 and less than 8 to capture patients at risk.^17–19 Exclusion criteria included (a) diagnosis of intellectual disability and/or (b) acute suicidal behavior.

Eligible patients were provided further information about the study and those willing to participate were asked to give written informed consent and to agree to audiotaping training sessions. Eligible patients were identified by chart review and mailed an invitation letter followed by a phone call to present study details. Patients expressing a willingness to participate met with the trainer to review the study consent document. Patients who consented were invited to identify a Supportive Other (SO) willing to participate in the study with them. All study procedures and materials were reviewed and approved by Roswell and WCI Institutional Review Boards.

2.2. Study Arms:

2.2.1. Intervention

BI-AC is an evidence-based PSST^10,11 intervention for adult cancer survivors and their caregivers.²⁰ BI-AC is an adaptation of the previously validated Bright IDEAS intervention designed to improve problem-solving skills and negative affectivity of mothers of children newly diagnosed with cancer.^12,21–23 BI-AC is different from Bright IDEAS in two critical ways: (i) BI-AC primarily focuses on adult cancer survivors (instead of mothers of children with cancer) and (ii) in addition to addressing problem-solving skills and mood, BI-AC aims to improve cancer survivors’ ability to make rational decisions and benefit from available medical, social, and supportive services. “Bright” represents the sense of optimism (positive orientation) necessary for successful problem solving. The letters in “IDEAS” signify the five major steps of problem solving: I= identify the problem, D= define your options, E= evaluate your options, A= act, S= see if it worked.^21,22

The intervention consists of eight one-hour individual weekly virtual (phone or video) counseling sessions conducted according to the previously published comprehensive protocol as summarized below.¹² Problem solving is presented as a general coping skill applicable to a range of challenging circumstances commonly encountered by cancer survivors. Patients randomized to the treatment arm are instructed to identify specific problems relevant to them and to their family’s situation to be discussed and then “solved” during PSST sessions and afterwards as “homework”. Session 1 is devoted to rapport building and understanding relevant social and medical information. The trainer introduces PSST and the Bright IDEAS paradigm, presents worksheets to guide PSST homework assignments, and gives an overview of subsequent sessions. In sessions 2–7, the trainer and patient, with a SO if available, review the patient’s identified problems and practice applying problem-solving strategies. Session 8 is focused on a review of PSST and long-term skills use that emphasizes persistence and learned optimism. To assure treatment integrity, every session was audiotaped, de-identified and stored securely; 20% of sessions chosen at random were scored by the treatment integrity monitor (OJS) according to a checklist that was shared with the trainers.

The two trainers employed for this project were psycho-oncology graduate students trained together by one of the study PIs (OJS). The team had weekly debriefings and monthly audits of the recorded sessions to insure fidelity and consistency between the trainers.

2.2.2. Care as Usual Group (CAU)

CAU participants, as well as intervention subjects, used any clinically appropriate medical and behavioral care without restriction as recommended by their healthcare providers. After study completion, CAU participants were offered the PSST training manual and brief counseling about the BI-AC intervention.

2.3. Randomization

After consent was obtained and the baseline assessment (T1) was completed by both the subject and the SO, if any, patients were randomized 1:1 to BI-AC or Care as Usual (CAU) using a permuted block randomization scheme with stratification by sex and study site.

2.4. Measures

In addition to the baseline T1 assessment, study participants completed a self-assessment (T2) immediately following the intervention (PSST arm) or 3 months after enrollment (CAU arm) and at 6 months after enrollment (T3, both arms). All assessment materials were mailed to patients and SOs ahead of their assessment dates. Participants could also complete the assessment over the phone with the research assistant. Participants (both patients and SOs) received stipends after each returned assessment to compensate for their time.

Demographic data were collected at baseline and included age, gender, race/ethnicity, health insurance, place of residence, and living arrangements as well as SO gender and relationship to the patient. Treatment information (diagnosis, treatment history, survivorship care plan, and time since diagnosis and since the end of treatment) was obtained from clinic records.

The Social Problem-Solving Inventory-Revised-short form (SPSI-R:S)²⁴ is a 25-item self-report tool linked to a multidimensional model of problem-solving skills. SPSI-R:S has been demonstrated to have strong reliability and validity estimates.²⁵ The scale includes 5 sub-scales grouped into two decision-making styles: constructive (Positive Problem Orientation and Rational Problem Solving) and dysfunctional (Negative Problem Orientation, Impulsivity/ Carelessness, and Avoidance). Each subscale and the total SPSI-R:S scores are expressed on a 0–20 scale; higher scores indicate better skills.

Hospital Anxiety and Depression Scale (HADS) assesses symptoms of depression (7 questions) and anxiety (7 questions) over the previous week, each question on the scale 0 (most of the time) to 3 (not at all); scores >8 are considered abnormal.

The Functional Assessment of Cancer Therapy - General (FACT-G) is a 27-item questionnaire designed to measure four domains of health-related quality of life in cancer patients based on the past 7 days: physical, social, emotional, and functional well-being (score range is 1–108; higher scores indicate better quality of life). The scale’s ability to discriminate patients on the basis of performance status and hospitalization status supports its sensitivity. It has also demonstrated sensitivity to change over time. Differences of 5–7 points are considered clinically significant.

Supportive Other’s Problem Inventory (SOPI) was used to assess the caregiving burden of the SO. We adapted a previously validated tool developed for mothers of children with cancer, Pediatric Parenting Stress Inventory (PPSI).³¹ The tool includes a 45-item listing of potential problems experienced by SOs caring for a cancer survivor during the previous week. SOs were asked to complete the SOPI tool and rank each problem as 0 to 4 (none to overwhelming) at T1, T2, and T3.

Healthcare Utilization was assessed at T2 and T3 by asking the patients about their healthcare utilization since the last study assessment including primary care, specialist and ED visits, use of supportive services and any hospital stays.

2.5. Data Analysis

Data analyses were generated using the SAS System for Windows v.9.3 (2013; SAS Institute, Cary, NC). Data from all participants were analyzed using an intent-to-treat approach. Power calculations show that the proposed sample size n=50 would allow us to detect differences as small as 0.8 standard deviations with at least 80% power for the key parameters (Primary outcome SPSI-R (range 0–20), secondary outcomes HADS (0–21) anxiety and depression). We compared patient demographics and health outcome changes T1-T2 and T1-T3, by study arm, using t-tests and chi-square tests as appropriate. We used multivariate regression analysis, Generalized Estimating Equation (GEE), to identify subgroups of patients with positive and negative responses to problem-solving skills training and to control for multiple observations per patient. Healthcare utilization at 3 and 6 months was compared between the study arms using count data models. Imputation of individual missing values (single or multiple imputation approach, <10% of all assessments) had no effect on the study results.³⁴

2.6. Implementation and Maintenance Assessments

An investigator who was not involved with patient recruitment, intervention or assessment conducted phone semi-structured interviews of a sample of cancer patients and SOs who completed the study. The purpose of the qualitative analysis was two-fold: to learn how the intervention had been implemented and maintained among patients and their SOs and to understand participant experiences and perceptions of the intervention. Participants were mailed invitation letters followed by a phone call inviting them to share their thoughts with the independent investigator confidentially. Fourteen subjects and 5 SOs were contacted; 12 subjects and 3 SOs participated.

3. RESULTS

3.1. Patient characteristics and study feasibility

Our hypothesis one was that at least 70% of contacted patients will enroll in the study. Of 84 eligible patients, 50 (60%) consented to participate. Thus, H1 was not supported. However, we discovered that when recruited at the recommendation of the treating physician, the response rate was 80%; in contrast, 25% responded to recruitment by letter only. Average age of the participants was 63 years (range 45–87); racial and ethnic distributions were representative of the local population (88% white) (Table 1). Two thirds of the participants were women (n=32). and non-participants did not differ in age or cancer type but non-participants were more likely to be men.

Table 1.

Comparisons of Patient Characteristics by Arms, Bright IDEAS-AC

	N	Care as Usual n (%)	Bright IDEAS n (%)	p-value
Total
	50	25 (50.0%)	25 (50.0%)
Patient Age
Mean (SD) *	50	63.8 (9.4)	62.3 (8.4)	0.55
40–49	4	2 (8.0%)	2 (8.0%)	0.904
50–59	12	6 (24.0%)	6 (24.0%)
60–69	25	13 (52.0%)	12 (48.0%)
70–79	6	2 (8.0%)	4 (16.0%)
80+	3	2 (8.0%)	1 (4.0%)
Gender:
Male	18	9 (36.0%)	9 (36.0%)	1.000
Female	32	16 (64.0%)	16 (64.0%)
Ethnicity:
Hispanic	1	0 (0.0%)	1 (4.0%)	0.368
Non-Hispanic	48	24 (96.0%)	24 (96.0%)
Unknown	1	1 (4.0%)	0 (0.0%)
Race:
African American	4	2 (8.0%)	2 (8.0%)	0.572
Asian/Pacific Islander	1	0 (0.0%)	1 (4.0%)
Caucasian	44	22 (88.0%)	22 (88.0%)
Mixed	1	1 (4.0%)	0 (0.0%)
Marital Status
Single	2	0 (0.0%)	2 (8.0%)	0.503
Married	33	18 (72.0%)	15 (60.0%)
Divorced	13	6 (24.0%)	7 (28.0%)
Other	2	1 (4.0%)	1 (4.0%)
Cancer Diagnosis
Colorectal	20	10 (40.0%)	10 (40.0%)	0.924
Breast	21	11 (44.0%)	10 (40.0%)
Prostate	9	4 (16.0%)	5 (20.0%)
Study Site
Western New York	21	10 (40.0%)	11 (44.0%)	0.774
Finger Lakes Region	29	15 (60.0%)	14 (56.0%)
Caregiver participating
No	33	13 (52.0%)	20 (80.0%)	0.037
Yes	17	12 (48.0%)	5 (20.0%)

^*Numbers presented were mean (SD).

Half of the participants preferred receiving study materials via regular mail, with only 18% opting for electronic communication. One third of the patients were recruited and received training fully remotely due to COVID-19 pandemic restrictions. Participants and non-participants did not differ in age or cancer type but non-participants were more likely to be men.

3.2. Intervention adherence

Our second hypothesis was that at least 80% of patients randomized to PSST will complete 80% of PSST sessions. Seventy-six percent (n=19) of the PSST patients completed the PSST (defined as sufficient mastery of problem-solving skills as verified by the therapist after at least 6 sessions). The primary reason for not completing eight sessions was inability to schedule sessions within the 16-week window allowed. None of the CAU participants requested PSST training at the end of the 6-month follow-up.

3.3. Assessment of problem-solving skills, negative affectivity and QoL

Five PSST patients (20%) and one CAU patient (4%) did not complete at least one of the three study assessments and 3 PSST patients missed two assessments. The reasons for missing assessments were active or passive refusal (4 of 6), cancer recurrence (1 of 6) and family emergency (1 of 6). Five of the six patients with missed assessments were women.

Patients in the treatment arm reported a trend towards reduced dysfunctional problem-solving style (Impulsivity/Carelessness Style, p=0.06) and improved constructive style (Rational Problem Solving, p=0.09) while problem-solving skills of CAU patients remained unchanged (Figure 1). Lower problem-solving skills at baseline was associated with greater improvement in skills at 6 months (p=0.03).

Figure 1. Outcome measures at T1 (pre-randomization), T2 (immediately postintervention) and T3 (6 months post-randomization).

Mean + SE. Individual components of SPSI-R:S: Rational Problem Solving (RPS), Impulsivity/Carelessness Style (ICS); Hospital Anxiety and Depression Scale (HADS), and Functional Assessment of Cancer Therapy- General (FACT-G). Bars represent 95% confidence intervals.

Patients in the PSST arm reported significant reductions in anxiety and depression (Δ=−1.5 at T2 and −2.6 at T3 for anxiety, and −1.0 (T2) and −1.4 (T3) for depression, p<0.05) and improvement in cancer-specific quality of life (Δ=3.2 at T2 and 8.0 at T3, p<0.05) that were sustained at 6 months (Figure 1, Table 2). Anxiety and QoL in CAU patients remained unchanged (p>0.05) and depression worsened (p<0.05).

Table 2.

Within-Group Changes in Outcome Measures, by Intervention Arms

OUTCOME	DIRECTION	STUDY ARM	T2-T1	P-VALUE	T3-T1	P-VALUE
SPSI-R:S	positive	BI-AC	0.6 (2.0)	N/S	0.3 (2.3)	N/S
		CAU	0.3 (0.15)		0.6 (1.7)
ANXIETY	negative	BI-AC	−1.5 (3.4)	0.03	−2.6 (3.9)	<0.05
		CAU	0.6 (3.0)		0.6 (3.2)
DEPRESSION	negative	BI-AC	−1.0 (3.9)	0.02	−1.4 (4.2)	0.04
		CAU	1.4 (3.2)		1.2 (3.8)
FACT-G	positive	BI-AC	3.2 (12.2)	N/S	8.0 (8.9)	0.01
		CAU	−0.4 (10.1)		−0.6 (10.1)

3.4. Impact of PSST on care utilization

The overall use of hospital and ED services was very low among the survivors in both groups although no subjects in the intervention group were admitted to the hospital or visited the ED: hospital (0.0 vs 0.4 visits, p=0.04); ED services (0.0 vs 0.3 visits, p=0.09). The use of ambulatory services (e.g., outpatient PCP and specialist visits, therapy, yoga, acupuncture and others) was not statistically different between the treatment arms (6.5 vs 5.7 visits, p=0.55).

3.6. Participation of supportive others

Our third hypothesis was that at least 50% of patients will identify a supportive other to join them in learning about problem solving. This hypothesis was not supported. Seventeen patients (34%) were accompanied by a SO who agreed to participate prior to randomization. By chance, SO participation was significantly higher among patients in the control arm (48% vs 20%, p=0.04). Despite low participation, recruitment of SOs revealed that male participants were significantly more likely to be accompanied by a SO compared to female participants (56% vs 22%, p<0.05). For men, all SOs were spouses or intimate partners. For women, SOs consisted of intimate partners (84%) and adult female children (14%). Participation of a SO did not have a significant effect on patient outcomes or intervention adherence. Self-reported SO burden as measured by the SO PI was not significantly different between the treatment groups and did not change over time (p>0.5).

3.7. Bright IDEAS-AC Acceptance and Sustainability

Overall, all BI-AC patients were willing to recommend the intervention to other cancer survivors; 90% of PSST patients viewed the intervention as useful or very useful – much higher than 50% we hypothesized (H4). Eighty five percent of participants were still using BI-AC at least once a week 3 months after completing the training.

During interviews, SOs commented positively on the benefits of using BI-AC (Supplemental Table 1A). Several patients pointed out that the skills they learned through BI-AC would also be very helpful to cancer patients who are still undergoing treatment, well before they reach the survivorship stage.

4. DISCUSSION

Our pilot study demonstrated that remote PSST delivery was acceptable and sustainable for a diverse range of cancer survivors. Patients who received PSST reported meaningful improvements in problem-solving skills, anxiety/depression and QoL after six to eight weekly remote training sessions. PSST patients also reported lower use of emergency services compared to CAU patients. Lastly, study participants indicated that PSST would be very helpful to patients undergoing active treatment.

According to the literature,^36,37 patient issues such as distress, depression, anxiety, body image, sexual dysfunction and intimacy concerns may vary depending on patient sex, as well as financial issues resulting from workforce displacement and/or costs of treatment but are similar across all cancer types. Indeed, in all Bright IDEAS studies including the one reported here, the problems were broadly logistical (how can I possibly get to appointments for treatment?) or emotion focused (how can I handle my anxiety about recurrence/hair loss/social isolation?) The specific issue or challenge provides the content for learning the steps of Bright IDEAS; successful resolution or, at least, a path to resolution, becomes the motivator for continued use.

Other evidence-based approaches to enable cancer patients to manage their care and control stress and symptoms of anxiety/depression include self-management (SM)³⁸ and cancer patient navigators (CPN)³⁹. While these interventions have been shown to be effective in RCTs, implementation of self-management training and cancer care navigation programs has been slow and challenging. Expectations for patients and families to manage themselves have outpaced the development of effective SM interventions that impart the knowledge and skills and facilitate the social networking patients and families require for managing themselves. Patients and families also need to be assessed to determine their willingness to manage their health care themselves, including managing doctor appointments, long-term side-effects, emotional turmoil, and family dynamics. A CPN is an individual trained to help identify and resolve real and perceived barriers to care, enabling patients to adhere to care recommendations and thus improve their cancer outcomes CPN programs have generally been provided to patients actively undergoing treatments at a facility, thus limiting their usefulness for survivors who are receiving survivorship treatments in the community. The main challenge to broader dissemination of the CPN model is lack of funding for CPN training and reimbursement for CPN services by health insurance. Compared to SM and CPN, BI-AC provides an effective and potentially sustainable approach to delivery of supportive care to cancer patients and their supportive others.

Our study of PSST is unique in several important ways. Our inclusion criteria were less restrictive than previous trials of PSST, thus, allowing a wider range of oncology patients to participate (i.e., no requirement for a SO, broader range of distress and functional status at baseline). Similarly, virtual phone-based recruitment and the intervention itself allowed for greater patient accessibility and potential for BI-AC maintenance (e.g., centralized BI-AC administration, low patient and clinic burden). This remote, centralized delivery approach could help reduce disparities in access to cancer survivorship supportive services between academic and community oncology practices, as tele-counseling is quickly becoming a new norm and is reimbursed by most health insurance plans. Bright IDEAS provides an opportunity for experienced psycho-oncology providers at large cancer centers or private psychology clinics to provide BI-AC, a billable therapy service (CPT 90791,90832, 90834, 90837), to any cancer patient within the provider’s licensure.⁴⁰ Finally, by collecting data on different types of health services used by study subjects, we tested whether PSST could improve quality of care for cancer survivors by shifting their utilization away from emergency department visits. We were not powered to detect significant differences between groups, especially since the use of these services is low overall even among patients undergoing treatment.⁴¹ However, this would be an excellent area of future investigation.

Despite its strengths and innovation, this study had several limitations. First, only 17 SOs were named by patients and of these, only 20% of PSST patients were accompanied by a SO, a rate significantly lower than among control patients. Since the choice of SO was made before randomization, the most likely explanation is chance alone. Second, identifying and recruiting patients from institutional electronic databases (e.g., tumor registry, scheduling system, EMR) is an attractive strategy to minimize the burden on treating physicians for their recommendation but resulted in a poor participation rate. We hypothesize that the main reason for this problem was outdated contact information for cancer survivors and missing data on cancer recurrence, survivorship status and distress that can misidentify many ineligible candidates. However, we should never underestimate the power of provider recommendation, which clearly was a major factor in our recruitment efforts.^42,43 Third, this pilot study was not powered to detect differences in our exploratory hypothesis that either hospital-based or ambulatory health services utilization would be different between groups. We also relied on patient recall over the past three months, which is known to result in underestimates of actual utilization and miscategorizations.⁴⁴ Fourth and finally, limited sample size did not allow us to control for differences in prior treatment or tumor site and stage which are independent predictors of health services utilization.⁴⁵ We would like to emphasize that this study was designed as effectiveness-implementation study and that the several hypotheses were formulated to explore HOW to best implement the intervention. Hence, rejecting these hypotheses does not de-value the effectiveness of BI-AC but rather provides empirical evidence to adjust recruitment process and eligibility requirements for the future studies as well as clinical practice.

6. CONCLUSIONS

Our findings suggest that remotely delivered PSST is a feasible and potentially effective strategy to improve mood and self-management in cancer survivors. Given that many oncology patients have limited access to guideline-recommended care, our findings support the implementation of BI-AC as one potential solution to reduce disparities in cancer survivor outcomes. Paired with growing evidence of the feasibility, cost-effectiveness and acceptability of remote services for cancer patients across the continuum of the disease, the evidence from this pilot study could help guide development and implementation of a sustainable BI-AC intervention even for oncology patients receiving definitive care in community settings that lack the resources typically available at large centers.

Supplementary Material

1

Supplemental Table 1A. Results of the BI-AC Implementation and Maintenance Assessments

Highlights:

• Remote problem-solving skills training is acceptable for cancer survivors.

• A third of patients in the study were accompanied by a supportive other.

• Three quarters of the survivors were able to complete the training.

• Patients who received PSST reported meaningful improvements in outcomes.

• The majority of PSST patients viewed the intervention as useful or very useful.

Vitae

Katia Noyes, PhD, MPH is professor of Public Health and Surgery at the University at Buffalo School of Public Health and Health Professions. She is also Director of Surgical Outcomes and Research (UB SOAR), for the UB Department of Surgery, and Adjunct Professor of Cancer Control at Roswell Park Comprehensive Cancer Center. She is a health services researcher with interest in cancer services delivery, dissemination and implementation research, cost-effectiveness evaluations and outcomes disparities.

Alaina L. Zapf, MA is a PsyD candidate in counseling and research assistant in the Department of Pediatrics and the James P. Wilmot Cancer Institute at the University of Rochester Medical Center.

Rachel M. Depner, PhD is a clinical psychologist and researcher at the Department of Psychiatry and Human Behavior at Alpert Medical School, Brown University. Her clinical and research interests focus on coping with difficult/traumatic life events and embodied self-regulation throughout the lifespan.

Tessa Flores, MD is Assistant Professor of Oncology at Roswell Park Comprehensive Cancer Center. She is Medical Director of Cancer Screening and Survivorship Program. She is a board certified internist and pediatrician. She is passionate about preventative care, wellness, cancer screening, and cancer survivorship.

Alissa Huston, MD is Assistant Professor of Medicine at the James P. Wilmot Cancer Institute at the University of Rochester, where her clinical efforts are focused on breast cancer. She is also the Director for Medical Student and Resident Education for the Hematology/Oncology Division. Her research efforts focus on understanding the effects of treatment for breast cancer upon bone health, the role of vitamin D in breast cancer and how improvements in education affect residents and medical students rotating on our inpatient oncology unit.

Hani H. Rashid, MD is a Professor of Urology. He joined the University of Rochester Medical Center in 2006 and has also served as Director of Robotics at Highland Hospital since 2011. Since 2019, he has been Program Directory for the Urology Resident Program. His areas of expertise include robotic and laparoscopic surgeries for prostate, kidney, bladder, adrenal and ureteral cancers.

Demetria McNeal, PhD, MBA is Assistant Professor of Medicine at the University of Colorado- Anschutz. Her focus is helping health care professionals and leadership teams develop and implement adaptive, sustainable strategies that produce results that address inequities in care delivery. These strategies oftentimes require creative, disruptive, innovative and unconventional approaches.

Louis S. Constine, MD, FASTRO, FACR is Professor of Radiation Oncology and Pediatrics and Vice Chair of the Department of Radiation Oncology. He is also the Director of the James P. Wilmot Cancer Institute Judy DiMarzo Survivorship Program. After graduating from Stanford University, and the Johns Hopkins University School of Medicine, he trained in pediatrics, pediatric oncology, and radiation oncology, and has board certification in these areas.

Fergal J. Fleming, MD is Associate Professor of Surgery and Oncology. He has been a Fellow in the URMC Division of Colorectal Surgery since 2009. Dr. Fleming was awarded his medical degree from the University College of Dublin, Ireland in 1998. He is also a Fellow of the Royal College of Surgeons in Ireland. Dr. Fleming’s surgical residency included extensive training in general, vascular and hepatobiliary surgery, as well as dedicated training in colorectal surgery. He was successfully awarded the Intercollegiate Specialist Examination (UK and Ireland) in general surgery with a sub-specialty interest in colorectal surgery in 2009. In addition to being licensed to practice medicine in the state of New York, Dr. Fleming is on the Specialist Register of the Irish Medical Council in recognition of his specialist training in the field of surgery.

Gregory E. Wilding, PhD is a Professor and Chair in the Department of Biostatistics at the University at Buffalo. He joined the Department of Biostatistics and Bioinformatics at Roswell Park Comprehensive Cancer Center as an Associate Biostatistics Consultant in 2004. He became an Assistant Professor of Biostatistics and Oncology in 2007 at Roswell Park. Then in 2009 he became an Associate Professor of Biostatistics and Oncology at Roswell Park and Professor in 2015.

Olle Jane Z. Sahler, MD is Professor of Pediatrics, Psychiatry, Health Humanities & Bioethics, and Oncology at the University of Rochester. She is a Behavioral Pediatrician and has specialized in the care of children and adolescents for 40 years. For the past 25 years, she has also been the Director of Pediatric Psychosocial Oncology Services and Research and for the past 15 years, she has served as Medical Director of the Long-Term Childhood Cancer Survivors Program at the Golisano Children’s Hospital in Rochester. She has published and presented widely on adaptation to chronic and terminal illness, in particular, to cancer. She has been the Principal Investigator on all foundation and NIH-funded projects to develop, evaluate, and disseminate Bright IDEAS awarded to the Psychosocial Adaptation to Childhood Cancer Research Consortium.