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Keywords:

  • psychosocial need;
  • cancer patients;
  • survivors;
  • disease burden

Abstract

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. REFERENCES

BACKGROUND.

The purpose of the current study was to identify unmet psychosocial needs of cancer survivors, understand the distribution of needs across subgroups, and compare unmet needs in 2005 with those identified by Houts et al. in 1986.

METHODS.

Using a sequential mixed methods design, qualitative interviews were conducted with 32 cancer survivors or family members to identify the psychosocial needs of people from the time of cancer diagnosis through survivorship. These data were used to modify a needs assessment that was mailed to a stratified random sample of survivors obtained from the Pennsylvania Cancer Registry.

RESULTS.

A total of 614 survivors returned usable questionnaires. Nearly two‒thirds of respondents reported experiencing at least 1 unmet psychosocial need, particularly emotional, physical, and treatment‒related needs. It is likely that unmet needs in insurance, employment, information, and homecare increased during the 20‒year interval between surveys. Demographics associated with increased unmet need included later stage of disease at the time of diagnosis, younger age, more comorbidities, and lower income.

CONCLUSIONS.

Unmet psychosocial need remains high despite 20 years of effort to address psychosocial issues. This may be due to a mismatch between needs and services. Unmet need may be related to access issues, a lack of awareness of resources, “new” needs that have arisen in a changing healthcare climate, and patient preferences for types of service. Cancer treatment staff should be especially alert for psychosocial problems in younger individuals with an additional illness burden. Cancer 2007. © 2007 American Cancer Society.

Houts et al. published a series of articles in Cancer describing the unmet psychosocial needs of people with cancer and their families in Pennsylvania in the mid‒1980s.1, 2 Utilizing the newly formed Pennsylvania Cancer Registry (PCR), the authors surveyed 629 people with cancer in Pennsylvania to determine the extent to which existing resources and services were meeting patients' psychosocial needs. Results indicated that 59% of people with cancer in Pennsylvania reported at least 1 unmet need in the year after diagnosis. The findings of these studies were used to develop a series of psychosocial and educational programs to address the unmet psychosocial needs of cancer patients.3–8 Subsequent needs assessments have focused on the general unmet needs of cancer patients and their families,9–11 site‒specific unmet needs,12–16 unmet needs related to cancer stage,17–20 relationship‒specific issues,21, 22 ethnicity‒based issues,12, 23, 24 and unmet needs related to socioeconomic status25 and geographic factors.26

Although we currently have a relatively detailed picture regarding the nature of unmet needs, it is unclear how advances in psychosocial oncology have affected the level and type of unmet psychosocial needs experienced by cancer patients. Progress over the past 20 years in the understanding and treatment of cancer may have changed the relative importance of some issues, but has likely led to new psychosocial needs that have been unrecognized until recently. Survivorship issues, including psychosocial adjustment, relationship factors, work issues, reproductive issues, insurance coverage, and secondary cancers, have emerged as important concerns, but the effects of this awareness are not to our knowledge well documented.27–30 Possible negative outcomes of information technologies, such as increased disparities, are beginning to be articulated, although health outcome data concerning the “digital divide” are scant.28, 29, 31–34 Finally, managed care and reimbursement issues have altered the way that cancer care is delivered, and a better understanding of how these changes have affected the needs of patients and families is warranted.

It is not clear whether psychosocial resources for people with cancer are distributed adequately or evenly across racial and age groups, geographic locations, or cancer sites.3544 Furthermore, to our knowledge, little is known regarding the factors that predict who is at higher risk for physical, psychological, or social problems after cancer treatment.27, 45, 46

To begin to address these gaps, this article describes a population‒based study aimed at identifying the unmet psychosocial needs of cancer survivors, understanding the distribution of these needs across subgroups of survivors, developing a model for predicting unmet needs, and comparing unmet psychosocial needs in 2005 with those reported by Houts et al. in 1986.1 We recognize that there are multiple definitions of the term “cancer survivor.” However, in this article, we will use the Institute of Medicine definition of a cancer survivor as a person who is in that phase of care after primary treatment.27

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. REFERENCES

Overview

The study involved 2 phases. In phase 1, semistructured qualitative interviews were conducted with 32 cancer survivors or family members to identify the psychosocial needs of people during the period of cancer diagnosis and treatment. These data were analyzed and identified needs were used to modify the measures employed by Houts et al.1 In the second phase, a sample of cancer survivors was recruited using the PCR and asked to complete the modified measure. Permission for this study was obtained from the Institutional Review Board of the University of Pennsylvania and the Institutional Review Board for the Pennsylvania Department of Health.

Sample

Potential participants were stratified by age, ethnicity, geographic setting, and cancer site and randomly sampled from the PCR. All participants had received a diagnosis of cancer between 3 and 4.5 years earlier. Because of PCR procedures and hospital reporting delays, it was not possible to obtain registry data any closer to the date of diagnosis. We stratified based on cancer sites with >5% prevalence and oversampled African Americans, individuals aged <44 years, and individuals residing within rural areas within these strata. Cancer sites with a prevalence of <5% were combined into an “other” category and the same oversampling scheme was applied.

Recruitment

A total of 2585 potential participants were identified in the stratified sample and were sent a letter informing them of the project and its voluntary nature, and alerting them to the arrival of the survey. Survey booklets with instructions and consent forms were sent 2 weeks later. Participants returned the survey and consent forms in an enclosed, self‒addressed business‒reply envelope.

Measures

Our revised survey included 14 categories of psychosocial need and was comprised of 92 items. Needs were assessed for Activities of Daily Living, Transportation, Financial Issues, Employment Issues, Insurance, Emotional Concerns, Relationship with Medical Staff, Cancer Information, Home Care, Nutrition, Treatment‒Specific Issues (surgery, chemotherapy, and radiation), Social Relationships, and Spiritual Issues. Individuals completed a 4‒point Likert scale indicating their experience of each need (How muchof a problem has this been for you since your diagnosis?) and, if experienced, whether they received enough, some but not enough, or no assistance in dealing with it. Participants completed demographic information and a 22‒item physical comorbidity checklist adapted from the Multi-level Assessment Instrument (MAI) developed by Lawton et al.47

Analyses

The first step was to assess the representativeness of the sample by examining their demographic characteristics relative to the PCR. Next, weights were applied to the data to better approximate the population found in the PCR. All variables were checked for skew and kurtosis and appropriate transformations were applied. A significant positive skew was present in the number of unmet needs. Data analyses were performed with and without log10 transformations to reduce skewness. No differences were found between transformed and nontransformed analyses. For ease of interpretation, nontransformed analyses are presented.

Bivariate associations among demographic characteristics and unmet needs were analyzed to determine correlations between unmet need and participant characteristics. Multivariate hierarchical linear regression was used to determine the relative importance of significant univariate participant characteristics to need status. Finally, data from our sample were compared with data from the study by Houts et al.1 to assess changes in the proportion of individuals reporting unmet needs.

RESULTS

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. REFERENCES

Response Rate and Demographic Characteristics

A total of 614 survivors (23.8%) returned informed consent forms and completed questionnaire packets. Table 1 presents a comparison of responders with nonresponders and with the overall cancer registry population for 2001, the year from which data were sampled. Compared with nonresponders, individuals who returned the completed questionnaire packets were younger, more likely to be married and white, and less likely to live in an urban setting and have an initial diagnosis of lung or colorectal cancer (all P <.005). Responders and nonresponders did not differ significantly with respect to stage of disease at the time of diagnosis or sex. Our sample differed little from the overall registry population, noting that the primary discrepancies were with regard to cancer site and patient age (ie, our sample was younger, and more likely to have a diagnosis of lung cancer and less likely to have a diagnosis of prostate or colorectal cancer). These differences most likely reflect our oversampling of younger cancer survivors and were dealt with by the weighting of data in our analyses.

Table 1. Comparison of Sample, Nonresponders, and Statewide Registry Population
VariableSample (n = 614)Registry (n = 44,990)Nonresponders (n = 1971)
  • *

    Data were unavailable from the registry.

Mean age at diagnosis, y57.063.659.7
Female sex56.4%53.4%54.6%
White89.9%90.4%81.4%
Married or in marriage‒likerelationship67.7%*59.8%
Income ≥$40,000/y52.2%**
Urban residence71%66.8%79%
Employed fulltime31.2%**
Stage of disease at diagnosis
 In situ9.8%11.2%9.2%
 Localized56.0%55.5%55.5%
 Regional21.3%19.7%19.8%
 Distant8.0%7.8%9.6%
 Unknown4.9%5.8%6.1%
Diagnostic category
 Breast24.3%23.3%17.2%
 Prostate15.2%20.0%14.1%
 Lung10.1%4.5%12.2%
 Colorectal8.8%13.8%11.8%
 Skin8.6%5.7%6.7%
 Other33%32.7%38.0%

Comorbidity

On average, participants reported a moderate number of comorbid conditions (M = 2.72; standard deviation [SD], 2.12). The most common comorbid conditions included hypertension (40%), arthritis (36%), and sleep problems (31%). Other prominent comorbid conditions included cataracts (15%), skin problems (14%), heart problems (14%), bladder problems (13%), diabetes (13%), and emphysema (11%). The range of comorbid conditions was large (R = 0–13), with 10% of the sample reporting ≥5 comorbid conditions and 18% reporting no comorbid conditions. The total number of comorbidities was found to be positively correlated with age (r = 0.35; P < .001) and ethnicity (F1,612 = 7.10; P < .005) such that nonwhite individuals (M = 3.7) reported more comorbidities than white individuals (M = 2.44). The number of comorbidities was found to be unrelated to stage of disease at the time of diagnosis, marital status, sex, or whether one lived in an urban versus a nonurban setting (all P > .05).

Level of Unmet Need

After the study by Houts et al.1 a need was classified as “unmet” if an individual reported experiencing it as at least “a small problem” and received anything other than “enough” assistance in dealing with it. Unmet needs were summed within categories. Table 2 describes the level of unmet need by category. To allow for comparison with the statewide cancer patient population, data were weighted to reflect the sex, age, cancer site, and ethnicity of the registry population from which they were sampled.

Table 2. Reporting of Unmet Need by Category
Need category≥1 Unmet need≥3 Unmet needs
  • SD indicates standard deviation.

  • *

    Maximum is 2 unmet needs.

Activities of Daily Living (eg, feeding, dressing, or doing light housework)17.9%4.2%
Transportation (eg, getting transportation for medical treatments)5.2%1.2%
Financial (eg, paying for prescription medications)23.7%7.8%
Employment issues (eg, doing work or keeping your job)14.5%4.9%
Insurance (eg, completing insurance forms)22.6%9.0%
Emotional (eg, feeling very nervous, afraid, tense, down, or depressed)38.7%24.7%
Relationship with medical staff (eg, feeling medical staff was insensitive or untruthful)12.4%2.4%
Obtaining cancer information (eg, getting information about your illness or treatment)20.7%9.9%
Homecare (eg, preparing to move from hospital to home)11.7%3.5%
Nutrition (eg, appetite changes, knowing what foods to eat)21.4%7.4%
Issues related to support for physical symptoms (eg, fatigue, nausea or vomiting, pain)37.5%18.7%
Treatment effects (radiation, chemotherapy, surgery) (eg, taking care of yourself on a daily basis)29.4%11.4%
Family relationships (eg, increased difficulties at home )14.6%6.0%
Spiritual issues (>2)* (eg, feeling a need for spiritual help)6.0%1.4%
Total Unmet NeedM = 7.72 [SD, 12.09]; R = 0–81 

Nearly two‒thirds (64.9%) of weighted respondents reported at least 1 unmet need, whereas 48.3% reported ≥3 and 23.4% reported ≥11 unmet needs. The level of unmet need varied by category, with the highest need noted in the Emotional (38.7%) and Physical (37.5%) domains and quite low levels observed in the areas of Spirituality (6.0%) and Transportation (5.2%). We also examined the level of specific unmet needs within categories. The most commonly reported needs included difficulties due to “tiring easily” (24.6%), “feeling very nervous or afraid” (22.1%), “feeling down or depressed” (23.1%), “difficulty with memory or concentration” (19.6%), and “difficulty sleeping” (18.3%).

The weighted sample was used to estimate the number of individuals in the state of Pennsylvania diagnosed with cancer within the current year who are likely to experience unmet needs over the next 4.5 years. The estimated 76,355 new cases of cancer diagnosed in the state of Pennsylvania in 200548 were used as the basis for these projections. We estimated that 49,554 people in Pennsylvania will experience at least 1 unmet need and 36,879 people will experience ≥3 unmet needs over the 4.5 years from the time of diagnosis. This represents only those needs related to incident diagnoses during 1 year, and would increase yearly as new incident cases are diagnosed.

Relative Change in Unmet Need from 1986 to 2005

Because our questionnaire was based on the data from Houts et al.1 a number of scales could be reconstructed to identify change in need over the 20‒year period. A few caveats need to be kept in mind when examining these correlations. The sample in the study by Houts et al. was comprised of individuals who were diagnosed with cancer within the previous 2 years, whereas the current study covered 3.0 to 4.5 years. In addition, the study by Houts et al. used a telephone survey rather than a self‒report questionnaire, and self‒report tends to generate higher rates of problem reporting than interviews.49–52 Figure 1 presents a graphic comparison of the current study findings compared with those obtained in 1986. Although the pattern of unmet needs remained substantially unchanged from 1986, 4 categories increased to >100%: insurance, employment, information, and home care.

thumbnail image

Figure 1. Proportion of respondents having at least 1 unmet need in 2005 compared to those in 1986.

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Predictors of Unmet Need

We first examined demographic and medical predictors of the single composite measure of unmet needs and then assessed significant correlations within category subscales. In addition, Holm53 step‒down adjustments were made for comparisons of composite scales to keep family‒wise error rates at 0.05. Unweighted data were used in the analyses because our objective was not to model correlations in the registry population but to understand correlations within our sample. The unweighted composite measure of unmet need was slightly higher than the weighted value (M = 9.33; SD, 13.77) and internal consistency as assessed by Cronbach α was adequate (α = 0.88). Table 3 presents the results of the initial analyses.

Table 3. Univariate Predictors of Composite Unmet Need
Categoric predictorVariable (n)M (SD)F-ratioP
  • SD indicates standard deviation.

  • *

    P < .05 for family‒wise comparisons using the Holm step‒down procedure.

  • FSThe number differs due to some missing data.

Gender
 Male (268)7.68 (12.33)  
 Female (346)10.61 (14.68)6.87.009*
Race
 White (546)9.42 (13.92)  
 Nonwhite (67)8.63 (12.67)0.195.659
Marital status
 Unmarried (195)11.06 (15.63)  
 Married/similar (409)8.59 (12.83)4.22.04*
Geographic locale
 Urban (436)9.29 (13.54)  
 Suburban (68)10.53 (16.15)  
 Large town (48)5.92 (9.05)  
 Small town/rural (62)10.93 (15.30)1.44.23
Staging at diagnosis
 In situ (60)7.67 (12.52)  
 Localized (344)7.62 (11.96)  
 Regional (131)12.62 (16.06)  
 Distant (59)13.65 (16.22)6.48<.0001*
Income per year
 <$20,000 (122)14.70 (18.05)  
 $20,000–$40,000 (145)9.17 (13.53)  
 $40,000–$60,000 (101)8.49 (13.45)  
 >$60,000 (190)7.37 (10.75)7.45<.0001*
Continuous predictorrP  
Age−0.250<.0001*  
No. of comorbidities0.254<.0001*  
Time since diagnosis−0.060.18  

Gender was found to be significantly associated with unmet need, with women reporting greater unmet need than men. At the individual category level, women reported greater unmet needs in Emotional‒, Physical‒, Family‒, and Treatment‒specific domains (all F(1612) ≥ 4.07; all P < .05). Unmarried individuals reported a greater total unmet need, as well in the individual areas of Emotional, Activities of Daily Living, and Transportation (all F(1602) ≥ 4.23; all P < .05). Stage of disease at the time of diagnosis was found to be correlated with total unmet need, and individuals with regional or distant disease reported higher levels in all categories (all F(3580) ≥ 2.72; all P <.05), except for those concerning Insurance, Medical Staff, Information, and Nutrition. Income level was found to be correlated with total unmet need; individuals with lower incomes reported greater unmet need in all domains (all F(3554) > 3.60; all P <.05) except Emotional, Medical Staff, Information, and Spiritual. Younger individuals reported greater unmet need in all domains except the Activities of Daily Living, Transportation, and Financial domains (all r – 0.14 to – 0.27; all P < .001). Finally, the total number of comorbidities predicted unmet needs in all categories (all r 0.08 to 0.27; all P < .05). Neither race nor geographic locale was found to be correlated with unmet need in a univariate fashion.

Multivariate Model for Predicting Unmet Needs

Significant univariate predictors were entered into a hierarchical linear regression model predicting composite unmet need, and significant multivariate predictors were retained. The final model can be seen in Table 4. Age, Number of Comorbidities, Income, and Staging remained independent predictors. Gender and Marital Status were not found to be significant predictors. Only Age and Number of Comorbidities produced a significant interaction in the prediction of total unmet needs. The interaction is represented in Figure 2, using the methods suggested by Aiken and West.54 As can be observed, the predicted level of unmet need among younger individuals with a higher comorbid illness burden was >2.75 times that of younger individuals with few comorbid conditions, and was >4.25 times the level of unmet need among older individuals with a similar comorbidity burden.

thumbnail image

Figure 2. Age by comorbidity interaction predicting unmet needs. Because we were concerned that the comorbid condition related to sleep disturbance might serve as a proxy for depression/anxiety and therefore drive the correlation between comorbidity and unmet need, we performed analyses with and without the sleep comorbidity. The results were similar with regard to direction and significance in both sets of analyses.

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Table 4. Multivariate Predictors of Unmet Need
 VariableBetaTP
Step One
 Age−0.43−10.20<.001
 Comorbidity0.348.10<.001
 Staging0.102.69.007
 Income−0.209−5.09<.001
   R2 = 0.245<.001
Step TwoAge × comorbidity−1.016−5.173<.001
   ΔR2 = 0.037<.001

DISCUSSION

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. REFERENCES

Nearly two‒thirds of cancer survivors in Pennsylvania reported experiencing at least 1 unmet psychosocial need 3.0 to 4.5 years from the time of diagnosis, particularly emotional, physical, and treatment‒related needs. Nearly half of the current study sample experienced >3 unmet needs. Greater unmet need was associated with younger age, female sex, the presence of comorbidities, lower income, and being single. Respondents who were younger and reported multiple comorbidities reported the most unmet needs. Somewhat unexpectedly, race, geographic location, and type of cancer were found to be unrelated to need. Results suggest that the overall level of unmet needs is at least as great as that experienced in the mid-1980s, and that insurance, employment, information, and homecare are especially likely to have increased. This is despite significant public health efforts to address the needs of cancer survivors.

A number of limitations must be considered. Our response rate was modest, and respondents were more likely to be younger, married, and a nonminority, and less likely to live in an urban setting and have an initial diagnosis of lung or colorectal cancer compared with nonresponders. Of these, age and marriage were correlated with unmet needs, although our weighting strategy should have decreased differences between our study sample and the PCR. Reporting biases also should be considered, although it appears equally likely that socially desirable responses could bias our results toward the null if needs are viewed as a sign of failure to cope adequately. In addition, many of our effects, although significant, are of moderate magnitude, suggesting that unmeasured variables account for the majority of variance in unmet needs.

That unmet needs have remained high since the survey by Houts et al.1 20 years ago may be due to a variety of factors. Expectations regarding the cancer experience, changes in the specific types of needs, and greater role disruptions resulting from the increased reliance on home‒based care may account for some need. In addition, changes in the ease with which survivors can access information without concomitant changes in how this information can be evaluated, weighed, and digested may result in greater levels of informational need now than in the recent past, and data from the current study are consistent with this theory. Similarly, much has been accomplished in the past 20 years to improve the number and variety of resources available to cancer patients and survivors, but this increase in access may not be reflected in decreased need. Working with the American Cancer Society, we identified numerous cancer‒related resources in areas of high need.55 Nevertheless, cancer care services that are rendered primarily to outpatients frequently are not covered by third‒party payors. Even when “quality‒of‒life” services are reimbursed, accessing services may be difficult given the competing demands of role functions.

Although resources such as support groups, information services, patient education tools, and homecare programs exist, many gaps persist. It remains unclear whether identified gaps between services and need is due to a mismatch between available services and perceived need, services that cannot keep apace with “new” needs, access issues related to resources, or a lack of information regarding resources. Patient expectancies also may play a role in psychosocial adjustment.46 Clinical guidelines mandating that no cancer patient should experience distress that goes unrecognized and untreated (National Comprehensive Cancer Network [NCCN] Clinical Guidelines, available at: http://www.nccn.org/professionals/physician_gls/PDF/distress.pdf [Accessed June 4, 2007]) may alter survivors' expectations concerning the adequacy with which their needs can be met within the current healthcare system.

Our finding that younger cancer survivors with comorbid conditions experience the highest levels of unmet need deserves comment. Houts et al.46 reported similar associations. Younger age is consistently associated with increased psychosocial distress among cancer patients,56 perhaps because a life‒threatening illness is more likely to disrupt family and occupation roles and is generally unexpected. Physical comorbidity also has been associated with decrements in quality of life among cancer patients, although the majority of studies have focused on its influence on well‒being among older adults.57, 58 Increased needs in the presence of a comorbid condition may be due in part to combining needs due to cancer with those due to other illnesses. However, this combination is not simply additive. Resources needed to support people with preexisting illnesses may be stretched thin before the cancer diagnosis, and adding another serious illness may stretch them to the breaking point. Physical limitations, fatigue, or pain may be exacerbated by the cancer diagnosis as well. While receiving active cancer treatment, the person with cancer may have access to cancer support services; however, after the initial treatment, patients return to their primary care physicians, where specialized services may be absent. Lack of attention to the specialized needs of younger cancer survivors in these settings may, in part, explain the correlation at 3.0 to 4.5 years after diagnosis.

Although women report more unmet needs than men on univariate analyses, this correlation was found to be nonsignificant once variances attributable to age, income, staging, and comorbidity are taken into account. This suggests that need is correlated with deficits in resources and disruptions in role function, for which gender is only a crude marker. Regardless of gender, decreased resources, increased demands, and more psychosocial stressors result in greater unmet need.

Although we did not directly assess differences in the absolute level of need between our sample and that of Houts et al.1 it does not appear that unmet need has decreased, and in fact needs may have increased in some domains. Differences may be attributed in part to the fact that our survey took place between the third and fifth year after diagnosis and the study by Houts et al.1 took place in the year after diagnosis. However, this difference most likely underestimates the increased amount of unmet need because one might expect distress to be more acute during the period of active treatment. In addition, we found no correlation between the level of unmet need and time since diagnosis.

The study by Houts et al.1 found no association between race and unmet needs, but did report that lower‒income patients reported more economic unmet needs. We also did not find differences related to race; however, lower income was found to be associated with 10 categories of unmet need. This difference suggests that income may have become more important in coping with cancer over the 20‒year period between the study by Houts et al.1 and the current report. We need to better understand what the pathways are through which income affects unmet need. Access is an obvious explanation, but more covert (and less easily captured) factors such as literacy and stigma also must be considered.

Conclusions

Rates of perceived unmet needs among persons with cancer have remained high over the 20‒year span between the study by Houts et al.1 and the current survey. There is evidence suggesting that unmet needs for insurance, employment, information, and homecare have increased during this period. These high rates exist despite increased attention to controlling the side effects of treatment and managing pain, and an awareness of the psychosocial effects of cancer and cancer treatments on patients and their families. The reasons for the continuing high rates of reported unmet needs are complex and should be the subject of future study. Future research should include objective as well as subjective measures of the need to clarify the meaning and causes of patient reports.

Correlates of unmet needs also were found to be similar in the 2 surveys, although there is some suggestion that income may be playing an increasingly important role in coping with cancer. The prominence of comorbid conditions as a predictor of unmet needs in the years after cancer treatment suggests that the primary care setting may be 1 place in which service referral can occur, because the majority of cancer survivors return to their primary care providers after acute treatment. Future research also needs to consider the longitudinal implications of unmet needs on psychosocial outcome, physical problems, and survival, especially for younger patients.

Acknowledgements

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. REFERENCES

Supported in part by a grant from the Pennsylvania Department of Health, Division of Cancer Control.

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  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. REFERENCES
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