LAVOIE SMITH, ELLEN M. PhD, APRN-BC, AOCN; SKALLA, KAREN MS, APRN-BC, AOCN; LI, ZHONGZE MS; ONEGA, TRACY PhD; RHODA, JUNE MSN, APRN-BC; GATES, CHARLENE RPT; LITTERINI, AMY PT, DPT; SCOTT, MARY R. MS, APRN-BC, AOCN
The National Cancer Institute (NCI) defines a cancer survivor as anyone who has been diagnosed with cancer, regardless of time since diagnosis, treatment status, or overall prognosis.1 It has been estimated that more than 11.7 million cancer survivors are alive today,2 and this number is expected to increase as a result of ongoing improvements in cancer diagnosis and treatment. However, despite improved survival rates, cancer survivors face numerous challenges, many of which have not been adequately addressed.3–5 For example, survivors may experience a variety of physical and psychological complications resulting from cancer and its treatment, such as pain, cognitive impairment, peripheral neuropathy, fatigue, sleep disturbance, sexual dysfunction, lymphedema, hot flashes, osteoporosis, bladder/bowel dysfunction, anxiety, and depression. Cancer survivors also may experience psychosocial, economic, and spiritual problems including role disruption, social isolation, loss of or change in employment status, and existential struggle for meaning.
The unmet needs of adult cancer survivors are well documented.6–27 Cancer survivors’ unmet needs have been assessed using survey instruments with strong psychometric properties designed to measure physical, psychological, social, resource, and informational needs.9,10,13,18,19,26 However, the generalizability of the findings of most needs assessment research to date is limited because of use of participant samples that are not representative of the broad population of cancer survivors. Most needs assessment studies have been conducted with individuals diagnosed with a specific cancer diagnosis.6,13,17,18,21,23,28,29 Other research has included only participants within a specific phase of survivorship such as early-stage participants, those in remission, or those within months to just a few years beyond diagnosis.10,11,22,24 In addition, several sample populations have included only survivors who were receiving ongoing oncology care,11,18,25,26 omitting those who were no longer followed by an oncology provider. To address some of the limitations of needs assessment research to date, we conducted a pilot study to test a Web-based needs assessment survey aimed at identifying the needs of a more diverse population of cancer survivors with varied cancer diagnoses and those whose experiences span the broad continuum of cancer survivorship from diagnosis to many years beyond treatment. More specifically, the main study aim was to pilot test a Web-based survey mechanism for determining the physical, psychosocial, psychological, spiritual, and economic consequences of cancer care. Since no population-based survivorship survey studies have been published describing an optimal sampling methodology, our second aim was to determine which of three different sampling approaches would be the most effective in reaching a diverse population of cancer survivors. This research was part of a larger needs assessment study that included both participants (patients) and caregivers. We have reported only patient-specific findings.
This cross-sectional, descriptive pilot study was designed to test whether a Web-based survey mechanism could be used to collect information regarding the diverse needs of cancer survivors. The study was approved by Dartmouth Medical School’s Committee for the Protection of Human Subjects, and informed consent was obtained from all participants.
Sample and Setting
The study was conducted at the Norris Cotton Cancer Center (NCCC), an NCI-designated comprehensive cancer center; a component of the Dartmouth-Hitchcock Medical Center in Lebanon, NH, and at nine community-based cancer clinics located in rural and urban areas throughout the state. Data collection occurred between July and November of 2009. Eligible participants were (1) 18 years or older, (2) diagnosed with any cancer type, and (3) able to read and write English or, if unable to read and or write English, had access to a professional interpreter who could work with the participant to complete the survey.
One population-based and two convenience sampling approaches were used to obtain the study sample. We used the NH Mammography Network (NHMN),30 a voluntary state-based registry of over 1 million women receiving mammograms from geographically diverse regions of New Hampshire, to identify a population-based sample of individuals diagnosed with breast cancer. Stratified random sampling based on age and year of diagnosis was used to obtain a population-based sample of individuals from the mammography registry (NHMN) database.
A convenience sample was drawn from nine community cancer centers and one comprehensive cancer center covering eight New Hampshire counties. Also, surveys were completed by unsolicited individuals who found the survey by chance on one of three Web sites (the second convenience sampling approach), The New Hampshire Cancer Plan Web site (http://www.nhcancerplan.org/nhccc/publications/newsletter.php), and two New Hampshire cancer center Web sites (http://www.cancer.dartmouth.edu/survivorship/survivor-needs-survey.html; www.snhmc.org). Newspaper and radio advertisements also were used to direct survivors to these Web sites.
Invitational letters were sent to 3010 NHMN database registrants with an incident diagnosis of breast cancer occurring between 2000 and 2008. Those receiving letters had previously provided consent to be contacted regarding any potential opportunity to participate in future research. The letters provided information regarding the study purpose and procedures, the survey Web site link, and a unique log-in number that allowed access to the survey.
When checking in for their clinical appointments or while receiving direct care, potential participants from the nine community-based cancer centers were handed an invitational card by a receptionist, nurse, or physician. Approximately 2450 recruitment cards were hand-distributed to cancer survivors. The cards included a brief description of the study, a contact URL for access to the study survey, and a log-in identifier number required for the participant to access the questionnaire (this measure was used to reduce the risk of individuals hacking into the study database). All invitational letters and cards explained that participants without computer access or adequate computer skills would receive help from study staff to complete the survey. For example, participants who did not own a computer could complete the survey during their office visit, using a clinic-owned computer. For individuals needing assistance to navigate the survey, research staff members were available to sit side-by-side with computer-naive participants or to provide coaching over the telephone. To ensure confidentiality and anonymity, staff members offered assistance only with accessing the Web survey and computer navigation techniques. Research staff members remained available in order to answer follow-up questions as participants completed the survey but did not directly witness or influence participant survey question responses.
The third recruitment strategy was to post survey information on three credible Web sites (previously mentioned). The Web survey was available on two collaborating cancer center Web sites deemed credible based on their affiliation with a cancer center. The NH Cancer Plan Web site was prescreened by study investigators and determined to be an appropriate venue for survey access based on Web site information accuracy and comprehensiveness, as well as the Web site’s wide reach to New Hampshire survivors. This sampling strategy facilitated participation by survivors residing in two New Hampshire counties not represented by collaborating cancer clinics. In addition, the Web-based access to the survey provided long-term survivors not currently undergoing active treatment or medical follow-up the opportunity to participate in the study even if they had not received an invitational letter/card with a log-in identifier number.
An iterative process was used to develop, expand, and refine survey questions. This iterative process involved the development and testing of three prior survey prototypes that ultimately lead to the final Cancer Survivor Web-Based Survey (CS-WEBS). The first paper-pencil prototype was developed and piloted at Dartmouth’s NCCC in 2005.31 A second online prototype incorporating computerized branching logic underwent feasibility testing. Next, qualitative feedback obtained from survivors and collaborating community partners was used to modify, clarify, and add survey questions to the third survey prototype. Survey readability was at a fifth-grade reading level.
Test-retest reliability assessment of individual survey items revealed 10% to 90% agreement. CS-WEBS content validity was assessed using established methods.32 Only items with a high content validity index of 1.00 (P < .05) were retained. Evidence of CS-WEBS construct validity was demonstrated based on evidence of high unmet needs in populations where this would be expected. For example, survivors who were currently receiving cancer treatment and younger and more anxious participants had more unmet needs. These findings are consistent with the literature11,21,26,29 and provide evidence of CS-WEBS validity.
The CS-WEBS contained 109 items. Questions assessing demographic variables (cancer diagnosis, years since diagnosis, age, sex, race/ethnicity, education, religion, income, employment, insurance coverage, geographic region) were included within the 109 items. Participants were asked to indicate their survivorship phase defined by treatment status (phase 1 = have not received treatment, phase 2 = currently receiving treatment, phase 3 = completed treatment). Phase 1 respondents answered 103 questions at most, and phases 2 and 3 respondents answered a maximum of 109. Additional questions focused on describing the types of survivor resources currently being utilized and survivor predictions regarding their use of resources in the future. Although study participants answered a large number of questions, which could be burdensome and fatiguing, computer-mediated branching logic ensured that survivors responded only to questions pertaining to their individual circumstances. The response criteria for most survey questions were as follows: (1) I have this problem; (2) I have this problem, but it is not bothering me; (3) I don’t have this problem; (4) I had this problem, but I don’t anymore because I am getting help for it; and (5) I don’t know. Participants were also asked whether they were interested in receiving help for a particular problem using the following response criteria: (1) yes, (2) no, and (3) don’t know.
Instructions for entering the survey Web site were provided in the invitational letters/cards. Unsolicited survivors who had not received an invitational letter/card had access to the survey via a link located on one of the previously mentioned Web sites. Before beginning the Web survey, participants were asked to provide the log-in identifier number from their letter/card. Log-in identifier numbers included a prefix allowing the study team to obtain data regarding the sampling approach used to recruit each participant. The log-in identifier for participants recruited via the mammography network database began with “m.” Those recruited at a cancer clinic/hospital had log-in identifier numbers beginning with “h” for hospital. Unsolicited participants completing the survey via a link from another Web site were automatically e-mailed log-in identifier numbers beginning with “w.” Upon entering the log-in identifier number, participants viewed a cover page describing the survey research and explaining that completing the survey would indicate that they were providing consent to participate. After reading the cover page, survivors choosing to continue with the survey could click on a “Take Survey” button. Implied informed consent was obtained if the participant continued with the survey after reading the cover page instructions. Participants were then presented with a series of questions displayed one question per page. Each page provided options to return to previous questions or instructions, or to ask for e-mail assistance (Figure 1). If participants chose to continue with the survey, an answer to each question was required before the respondent could move on to subsequent questions. Participants could exit the survey at any time.
All statistical analyses were conducted using SAS 9.2 (SAS Institute, Cary, NC). Descriptive statistics were used (frequencies, means, SDs) to describe demographic, clinical, and supportive care needs variables. Fisher exact test was used to test association between two categorical variables. Logistic regression analyses were conducted to determine predictors of unmet needs. Covariates included in the logistic model were age, sex, survivor phase, anxiety, education level, cancer type, and years from diagnosis.
Sampling and Accrual
A total of 547 individuals with cancer completed the survey over 4 months. Most participants (48%) were recruited using the NHMN sampling method (n = 263). This represents 9% of the 3010 women who received an invitational letter. The 10 cancer clinics collectively recruited 170 participants (31%), and 114 (21%) were recruited from selected Web sites listed previously.
The demographic characteristics of the study participants are summarized in Table 1. Less than 1% (n = 5) of participants had received no cancer therapy (phase 1). Thirty-one percent (n = 168) were currently undergoing cancer treatment (phase 2), and 68% (n = 374) had completed cancer treatment. The mean age was 60 years (range, 26–88 years). Older individuals were well represented in the sample, given that 24.5% were between 66 and 75 years, and 8% were 76 years or older. The sample was composed mainly of white (99%), married (71%) women (80%). Most (96%) had obtained at least some level of college education.
Most participants (66%) (n = 362) had been diagnosed with breast cancer. However, a wide variety of other cancer diagnoses were represented in the sample. The pilot sample population was diverse and included participants representing 20 unique cancer diagnoses. With the exception of an overrepresentation of breast cancer survivors in the pilot sample, the diversity and frequency of cancer diagnoses in the pilot sample mirrored New Hampshire incident case data.33
Approximately 45% of participants with a nonbreast solid tumor malignancy were undergoing treatment at the time of the survey (phase 2 survivors), as compared with 44% and 24% of those with hematologic or breast malignancies, respectively. The majority of participants reported being in remission (86.1%) (n = 421) and were many years beyond completion of cancer treatments.
Fifty-two percent (n = 285) of participants had commercial insurance, and very few, approximately 2.4% (n = 13), were completely uninsured. We were successful at recruiting survivor participants from all 10 counties in New Hampshire. Participants reported receiving cancer care at numerous rural and urban-based community cancer centers/hospitals located throughout the state, as well as at New Hampshire’s tertiary medical center/comprehensive cancer center. As would be expected, the highest number of participants was from the more heavily populated counties (Hillsborough, Rockingham, and Merrimack counties) or from Grafton county, the location of the state’s only comprehensive cancer center.
There were no significant differences in age, marital status, religion, or years since diagnosis based on recruitment strategies. There were significant differences in the frequency of cancer diagnoses and remission rates across recruitment strategies. Participants recruited via the mammography registry were more likely to have breast cancer (P < .0001) and to be in remission (P < .0001) than participants recruited using the other methods.
Physical and Psychological Needs
Physical and psychological needs are summarized in Tables 2 and 3. These data illustrate that symptoms may be present but not necessarily bothersome. Fatigue, the most commonly reported problem, was reported by 47% of the sample. A high incidence of fatigue among cancer survivors has been reported elsewhere.24–26 Other common symptoms/problems reported by survivors include forgetfulness (39%), joint pain (34%), anxiety (31%), trouble sleeping (28%), numbness and tingling in the hands and feet (27%), inflexibility (23%), weight gain (23%), osteoporosis (19%), and pain in other places (19%). The number/percentage of survivors wanting help for the most common bothersome symptoms by survivorship stage is summarized in Table 3. The most frequently requested assistance needs were for losing weight (74.2%), lessening tiredness (50%), and improving flexibility (69.3%), sleep (68.5%), and forgetfulness (60.2%). In addition, these data reveal that many survivors still struggled with physical and psychological problems well beyond cancer treatment, as demonstrated in the large percentage of phase 3 survivors wanting help for a variety of symptoms.
Economic, Social, and Spiritual Needs
A small percentage of survey participants reported having financial problems (12%), for which most wanted help (67%). Common types of financial problems included increased debt (66%), loss of assets (42%), and increased insurance costs (30%). Ten percent of those with financial problems indicated that lack of money limited their access to support services. Only a few survivors reported having problems communicating with caregivers (9%). Tobacco use and alcohol abuse were infrequent among respondents (5%, 3%). Fifty-two percent of tobacco users expressed interest in receiving help to quit or with staying tobacco-free, and 80% of those reporting too much alcohol intake wanted help. Most respondents (89%) reported having no spiritual concerns (finding meaning in life). However, 70% (n = 19) of those having difficulty finding meaning in life reported wanting help for this problem.
Survivor Needs by Cancer Type
There were statistically significant associations between cancer diagnoses and the proportion of survivors experiencing specific problems. Several problems were experienced more commonly in participants diagnosed with nonbreast solid tumor malignancies (Table 4). For example, intimacy/sexual difficulties were reported by approximately 48% of those with nonbreast solid tumors versus 32% and 19% of survivors with hematologic and breast malignancies, respectively (<0.0001).
Survivor Needs by Survivorship Phase
As expected, there were statistically significant associations between survivor stage and the proportion of survivors experiencing problems. Those undergoing treatment (phase 2) had the highest reported incidence of 25 problems of the total 33 possible problems (P range = .054 to < .0001) when compared with participants in the other two groups. Phase 1 survivors had the highest incidence of anxiety (P = .006), constipation (P < .001), depression (P = .054), and spiritual concerns (P = .007) compared with other survivors. However, it should be noted that the sample size for phase 1 was low (n = 5).
Survivor Needs by Years Since Treatment
For phase 3 participants, there was a statistically significant association between the number of years since treatment for cancer and three problems: financial issues (P = .021), life enjoyment (P = .005), and osteoporosis (P = .005). Difficulties with enjoying life were reported most often in the first year following treatment completion. Financial issues were reported most often by survivors in their second year beyond treatment completion. Osteoporosis was reported more often in those at 6 to 20 years posttreatment.
Survivor Needs by Education
There were statistically significant associations between educational background and the proportion of survivors experiencing certain problems. More respondents with less than a high school education, as compared with other educational levels, reported problems with diarrhea (P < .0001), edema (P = .01), fatigue (P < .001), financial problems (P < .001), nausea/vomiting (P = .024), and life enjoyment (P = .004).
Total Unmet Needs
A total score for unmet needs was calculated based on the number of “wants help” responses. A higher unmet needs score equated to more unmet need. Based on logistic regression results (converted to a dichotomous variable: “needs help” vs “no help needed”), there was a significant association between receiving ongoing treatment and having unmet needs (phase 2) (odds ratio [OR], 1.70; 95% confidence interval [CI], 1.14–2.53) (P = .009). Survivors who reported having problems with anxiety also tended to have more unmet needs (OR, 2.55, 95% CI, 1.73, 3.76) (P < .0001). In contrast, older individuals had less unmet need (OR, 0.98; 95% CI, 0.97–1.00) (P = .05). Sex, education, cancer type, and years from diagnosis did not predict unmet need.
There were several findings regarding survivor program resource utilization that can help guide cancer clinicians and administrators make decisions regarding what programs to offer to cancer survivors. Mental health counseling and yoga were used most often by those between 46 and 60 years of age (P = <0.0001, 0.005). Younger cancer survivors, 20 to 29 years, were more likely to use Internet support groups (P = 0.012). Reiki was most appealing to survivors aged 20 to 45 years of age (P = 0.002). Older individuals (>75 years) were the least likely to use supportive resources when compared with other age groups (P <0.0001). In addition, years since treatment completion did not seem to influence resource utilization except that in-person support groups were used most by those at 11 to 20 years posttreatment (P = .05).
There were statistically significant associations between cancer type and the proportion of survivors using the various resources. More individuals with breast cancer reported using resources, specifically one-on-one support from another survivor (P = .009), exercise (P = .007), and yoga (P < .0001).
Mental health counseling, support groups, exercise, yoga, Reiki, and nutritional counseling were used most often by those with college/graduate degrees (P range = .017 to <.0001). Conversely, the percentage of survivors who did not use any supportive resource was higher in those with less education (P = .001). Participation in an exercise program was the only type of supportive resource that was associated with income: more survivors in the high-income categories reported using exercise when compared with the lower-income groups. Finally, 99.6% said that they might utilize support services if available. The 10 most popular resources are listed in Table 5. An in-person support group was the most desired resource.
The time needed to complete the survey ranged from 12 to 18 minutes. Anecdotal feedback from survivors suggested that the survey was easy to complete, and computer-naive users reported not being threatened by the technology. Although most respondents completed the survey independently, 15 respondents required assistance from study staff because of lack of computer access/skills. As an outcome of our collaborating relationships with nine community cancer centers, site-specific results were easily disseminated to participating community partners within 1 month of study completion.
The main aim of this cross-sectional pilot study was to test a Web-based survey for assessing the needs of a broad population of cancer survivors living in urban, rural, and remote areas of New Hampshire. The second aim was to develop a survey methodology facilitating population-based sampling. The Web-based format facilitated rapid and comprehensive data collection from a statewide population, and results were quickly available to participating cancer clinics. Another advantage of the Web-based system was that respondents were required to answer each question before moving on to the next. The data were then directly imported into a database for immediate analysis. Direct data entry minimizes the risk of data entry errors and missing data.
The NHMN served as an effective avenue for access to a population-based sample of participants with breast cancer. Use of this sampling approach resulted in an expected overrepresentation of breast cancer survivors in our sample. However, other sampling approaches were effective in locating individuals with other cancer types, including rare malignancies. The individuals accrued represented a geographically diverse sample of survivors from rural and urban areas of New Hampshire. In addition, a broad age range was represented in the sample population. Although our survivor sample lacked adequate representation of those who were less educated and non–English speaking and of diverse ethnic and racial backgrounds, inclusion of 98% whites in our sample is comparable to New Hampshire demographic estimates (96% white).34 We did not find the perfect solution to the problem of underrepresentative samples in needs assessment research to date. However, the varied sampling approaches used in this research and the Web-based survey technology were successful in finding survivors statewide with diverse diagnoses and those with unique survivor perspectives spanning from diagnosis to years beyond cancer treatment.
Cancer survivors experience numerous challenges resulting from the disease and/or its treatment. Our findings are consistent with other needs assessment survey results reported in the literature with respect to the types of problems experienced by cancer survivors such as fatigue, anxiety, depression, pain sleep disturbance, financial concerns, and so on.3,4 Our study also supports the findings of Hodgkinson and colleagues,11 suggesting that survivor needs do not necessarily decrease over time.
The results of this study provide additional insight into high-risk populations such as younger individuals. For example, study results suggest that younger age is associated with more unmet needs. Other researchers have reported similar findings.11,28 Contrary to our results, sex25,26 and cancer diagnosis9 were found to predict unmet needs in several other studies. Incongruent needs assessment findings may be partially due to variations in instrument format and focus. For example, the CS-WEBS is more heavily focused on measuring a comprehensive list of late effects of cancer treatment than some surveys.12,15,17,19 Other surveys include more questions assessing information, communication, resource, and psychosocial needs.15,16,20,23 Also, most published needs assessment research to date has focused on recruiting survivors at the time of their routine visit to a cancer provider, limiting representation of those too ill or too far out from treatment to still be receiving follow-up cancer care.11,18,25,26 The CS-WEBS’s Web-based format enabled participation of individuals who might not have been otherwise accessible. Therefore, it is possible that our results vary from other published results because of subtle differences in the sample populations based on cancer-specific characteristics.
The CS-WEBS results can also be used to determine which cancer survivor programs/resources are most desirable to various populations such as to younger versus older survivors or to those with specific cancer types. Based on the results of this study, emerging cancer survivor programs in New Hampshire might choose to focus less on developing educational programs and more on expanding in-person support group resources that are accessible in both conventional and nonconventional ways.
There are several study limitations. Use of the NHMN resulted in a sample population with a disproportionate number of individuals with breast cancer. It is possible that the needs of New Hampshire survivors may vary from survivors in other areas of the country. Also, the overall survey response rate was low, possibly resulting in response bias. However, our limited use of methods to enhance the response rate was dictated by the pilot design of project and subsequent limited funding. Another study limitation is that although mechanisms were used to encourage those with limited computer and Internet experience to participate, these individuals were underrepresented. Providing survey access via a variety of mechanisms, such as via Web or telephone mechanisms, may facilitate broader survivor participation in the future. Also, with the exception of data collected from NHMN participants, cancer diagnosis, stage, treatment information, and other demographic data were obtained via self-report mechanisms and may lack accuracy. Finally, the survey’s scoring mechanism could be revised in the future to provide data describing not only the incidence of specific needs, but also the degree/severity of need.
Use of the CS-WEBS could lead to advances in cancer survivor care in a variety of ways. First, the CS-WEBS can be used to identify gaps in care, as well as which resources survivors are likely to utilize. Second, the CS-WEBS database might be modified into a cancer survivor registry for use in New Hampshire, and possibly other states, to collect data regarding unmet needs. Further testing to assess the survey’s ability to detect change over time could lead to use in longitudinal studies or quality improvement efforts focused on assessing whether survivor services have been effective in decreasing unmet needs over time.
The CS-WEBS was developed to assess the continuing needs of cancer survivors. Survey results supported that cancer survivors struggle with many enduring problems. The Web-based methodology facilitated rapid accrual of a large sample, and results were quickly disseminated to those interested in using the data to suggest survivor resources.
The authors thank Kristen Anton and Susan Gallagher for their administrative and technical expertise. The authors would like to acknowledge the efforts of all collaborating partners who facilitated the conduct of this research: Cindy Arcieri, Susan Brighton, Jerry Diener, Connie Jones, Nancy Kane, D. J. Lee, Maryanne Mercier, Patricia Thayer, Barbara Weismantel, and Nancy Wood. They also thank the NH Comprehensive Cancer Collaboration for supporting the project.
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