Journal of Neuroscience Nursing:
The Stroke Caregiver Unmet Resource Needs Scale: Development and Psychometric Testing
King, Rosemarie B.; Hartke, Robert J.; Lee, Jungwha; Raad, Jason
Questions or comments about this article may be directed to Rosemarie B. King, PhD RN FAHA FAAN, at email@example.com. She is a Research Professor at Northwestern University Feinberg School of Medicine, Chicago, IL.
Robert J. Hartke, PhD MPH, is an Assistant Professor at the Department of Physical Medicine and Rehabilitation and Department of Psychiatry & Behavioral Sciences, Northwestern University Feinberg School of Medicine, and a Psychologist at the Rehabilitation Institute of Chicago, Chicago, IL.
Jungwha Lee, PhD MPH, is an Assistant Professor at the Biostatistics Collaboration Center and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL.
Jason Raad, MS, is a Project Coordinator, Rehabilitation Institute of Chicago, Center for Rehabilitation Outcomes, Chicago, IL.
The authors declare no conflicts of interest.
ABSTRACT: The purposes of this study were to develop and validate a measure of unmet resource needs of the caregivers of survivors of stroke and to describe the caregivers’ unmet needs during 1 year. A longitudinal, descriptive design was used to test the reliability and validity of the Unmet Resource Needs (URN) measure. Item development was based on literature review and preliminary study findings. A stress and coping conceptual model framed the hypotheses. Psychometric testing was based on 6-month postdischarge data (n = 166). Content and structural construct validity, internal consistency reliability through 1 year, and concurrent validity were tested. Change in URN over time was examined. Content validity was supported by floor and ceiling effects less than 5%. Principal axis factoring yielded a 12-item, two-factor solution reflecting general and technology unmet needs. Internal consistency reliability was satisfactory for the total scale and subscales at all times, excepting the baseline three-item technology scale (α = .56). Concurrent validity was supported by significant correlations with model constructs (threat, positive problem solving, depression, preparedness; p < .01) in the expected direction. Functional status and resource use were not associated with the URN. Repeated measures analysis of variance (n = 123) indicated a significant decrease in unmet needs from baseline to 3, 6, and 12 months postdischarge (p < .001). Nevertheless, 42% reported one or more unmet needs at year 1. Assessment and counseling on unmet needs is indicated throughout the caregiving trajectory to reduce negative outcomes.
Stroke is a major cause of serious long-term disability. Approximately 795,000 strokes occur each year in the United States, and over 6 million survivors are living with stroke (Lloyd-Jones et al., 2010). Seventy to eighty percent of survivors are discharged to a community setting, usually in care of a family member (Stineman et al., 2001), whose life may be considerably altered by the sudden demands of caregiving (Covinsky et al., 1994). Evidence of the extent of stroke disability is noted in a report of a 6-month prevalence of 26% and 35%, respectively, for severe disability and depression among older survivors of stroke (Kelly-Hayes et al., 2003). Furthermore, functional levels have been shown to decline annually from 6 months to 5 years after stroke, adding further to the stressors, burden, and needs of caregivers (CGs; Dhamoon et al., 2009).
Family members unexpectedly and quickly assume the caregiving role after a stroke often expressing unmet needs and problems related to inadequate information and resources. Among these needs are training on survivor care skills, information and resources on stroke prevention and recovery, survivor and CG socioemotional needs, and financial and family issues (Bakas, Austin, Okonkwo, Lewis, & Chadwick, 2002; MacIsaac, Harrison, & Godfrey, 2010). The constellation of problems and needs has been implicated in negative outcomes such as increased stress, burden, injury, anxiety, and depression (Hartke & King, 2002; Hinojosa & Rittman, 2009; King, Ainsworth, Ronen, & Hartke, 2010; Mackenzie et al., 2007; Perry & Middleton, 2011; Scholte op Reimer, de Haan, Rijnders, Limburg, & van den Bos, 1998). Identifying and resolving unmet needs can be an important step in promoting positive CG adaptation. Studies focused on assisting CGs with problem solving, and unmet needs have resulted in improvement in one or more adaptive outcomes (Bakas et al., 2009; Grant, Elliott, Weaver, Bartolucci, & Giger, 2002; King, Hartke, & Denby, 2007).
With few exceptions, stroke CG unmet needs, other than information, have been assessed in cross-sectional designs, limiting knowledge of needs over time. Conflicting findings were reported for the few studies of needs over time. A qualitative study examined supportive services for 13 CG–survivor dyads 3 weeks and 3 months after discharge (Ski & O’Connell, 2007). The most frequent unmet needs were delays in home rehabilitation and lack of communication from hospital clinicians. No change was found in unmet service needs over time. Studies comparing needs before discharge and 2–6 weeks after discharge reported contrasting findings, with one indicating a nonsignificant decrease (p < .06; Mackenzie et al., 2007) and the other indicating a significant decrease (Mak, Mackenzie, & Lui, 2007). On the basis of CG recall for the first 2 years after discharge, King and Semik found that needs, such as learning care/skills and managing uncertainty, were limited mainly to the first months of caregiving. Other needs extended through 2 years (financial advice, counseling) or arose after discharge (King & Semik, 2006).
Reviews of research on caregiving unmet needs indicated needs required tailoring interventions and consensus that unmet needs occur in multiple life domains (Hafsteinsdottir, Vergunst, Lindeman, & Schuurmans, 2010; MacIsaac et al., 2010). Hafsteinsdottir et al. reported that several studies on information needs found change over time. The reviewers concluded that a reliable, valid measure is needed to assess potential needs over time.
Most findings on unmet needs have been based on semistructured questionnaires or listings of needs (Bakas et al., 2002; Davis & Grant, 1994; King & Semik, 2006) or did not include domains considered essential for stroke CGs (Kristjanson, Atwood, & Degner, 1995). Other measures were lengthy (Serio, Kreutzer, & Witol, 1997), not subjected to psychometric testing (Houts, Doak, Doak, & Loscalzo, 2006; Mackenzie, Holroyd, & Lui, 1998), or were not translated into English (Shyu, 2000).
A psychometrically sound measure has potential for clinical use and in intervention studies to promote CG and survivor adaptation. Therefore, the purposes of the current study were (1) to develop a reliable and valid measure of unmet resource needs and (2) to describe the unmet resource needs of CGs of survivors of stroke over time. The hypothesis was that the Unmet Resource Needs (URN) scale will show evidence of structural construct validity, internal consistency reliability, and content and concurrent validity.
A stress and coping model guided the development and testing of the URN (Moos & Schaefer, 1993). The model proposes that stressful events trigger coping processes to restore balance in the individual’s life. Contextual factors (background, illness, and social environmental factors) influence the coping process (appraisal [threat], coping [problem solving], resource needs and use), which in turn influences physical and socioemotional adaptation outcomes. Moos and Schaefer emphasized the use of internal and external resources in coping with a health crisis, such as the sudden onset of a severe physical disability.
We used a longitudinal, exploratory, descriptive design to test the reliability and validity of the URN measure. The study was approved by the institutional review boards for two free-standing rehabilitation hospitals and rehabilitation units in two hospitals.
Participants were enrolled in a larger intervention study to improve stroke CG adaptation. Subject selection criteria were (1) planned discharge of survivor to home; (2) primary CG living with the survivor; (3) CG not currently in a support group or therapy; (4) access to a telephone and sufficient hearing to use a phone; (5) survivor and CG aged 21 years or older; and (6) CG depression screening score over 9 on the Center for Epidemiologic Studies-Depression (CES-D; Radloff, 1977), which has indicated future depression risk (King, Shade-Zeldow, Carlson, & Roth, 1998). A primary CG was defined as one who supervised, assisted with, or managed care.
Recruiters contacted family members during acute rehabilitation to verify their role as primary CG and to obtain informed consent. Consent of survivors was not necessary for CG participation. Data were collected by research assistants, blind to group assignment, at baseline (acute rehabilitation (time 1), 3–4 months after discharge (time 2), and 6 (time 3) and 12 months (time 4) after discharge. Assessments were read to participants to avoid missing data. Assessments were completed in person at baseline, when possible, and by telephone after discharge. The URN measure was part of a compendium of measures administered at each time.
A background and illness form was developed to collect CG and stroke survivor background and illness-related factors. Internal consistency reliabilities were adequate (.71–.95) for all measures at four times in the study.
Item development for the URN measure was guided by the conceptual model, findings from our earlier study on unmet needs of stroke CGs (King & Semik, 2006) and from a focus group evaluation of a pilot study of a CG intervention (King, Hartke, Iris, Herring, & Alexander, 2003). Unmet needs were defined as the CG’s desire for more assistance, support, or information to manage physical or emotional concerns (Mistiaen, Duijnhouwer, Wijkel, de Bont, & Veeger, 1997). A search of the literature added further information. To decrease participant burden, we used need categories rather than specific needs. The 13-item URN scale addressed access to CG and survivor resources for managing emotional, physical, and behavioral consequences of stroke. Responses (1 = strongly disagree to 5 = strongly agree) are summed. One item was reversely scored. Higher scores indicated greater unmet needs; the potential range of scores was 13–65.
Coping Process Measures
The Appraisal of Caregiving Scale (Revised) is a 27-item, 5-point response scale that assessed benefit, benign, and threat appraisals (Carey, Oberst, McCubbin, & Hughes, 1991; Oberst, 1991). The 12-item threat appraisal subscale was used in the current study. Higher mean scale scores reflect higher levels of the scale construct. The possible range of scores was 1–5. Validity was supported by significant correlations in the expected directions between the scales and caregiving antecedents and outcomes. Alpha coefficient was .92 (Oberst, 1991).
The Social Problem-Solving Short Form-Revised was used to assess problem-solving coping (D’Zurilla, 1996; D’Zurilla & Sheedy, 1991). The 25-item scale measures problem orientation (positive and negative) and problem-solving styles (impulsive/careless, avoidance, rational). Only the positive problem-orientation scale (PPO) was used in the current study. The responses range from (0 = not true to 4 = extremely true). Possible scale scores range from 0 to 20. Higher scores are desired for the PPO. Validity has been supported by correlations with depression and anxiety in the expected directions (D’Zurilla, 1996).). Internal consistency reliability was adequate, ranging from .72 to .85.
Resource use was assessed using the investigator-generated Intervening Events Questionnaire. CGs were asked to check the resources used since the prior assessment on listings of 15 resources and to add items not listed. Items used were summed.
Adaptation Outcome Measures
The Preparedness for Caregiving Scale was used to assess perception of preparedness to manage the tasks and stresses of caregiving (Archbold, Stewart, Greenlick, & Harvath, 1990). CG reliability and validity evidence are strong for this 8-item, 5-response option scale (0 = not at all prepared to 4 = very well prepared). The potential range of scores is 0–4.
Depression was assessed using the CES-D (Radloff, 1977; Shinar et al., 1986), which has extensive evidence of reliability, validity, and sensitivity to change. The 20-item CES-D measures depressive symptom severity during the past week. The possible range of scores is 0–60; higher scores reflect greater symptom severity, with 16 indicative of depression. Baseline scores were used to identify eligibility for enrollment.
Survivor functional status was measured using the Functional Independence Measure (FIM), which assessed disability severity using an 18 item, 7-point scale; higher scores represent greater independence (Granger, Hamilton, & Sherwin, 1986). The FIM is reliable and valid, sensitive to change, and used widely to show functional change. Data were retrieved from the survivors’ medical records at baseline and from CGs after discharge.
We assessed the structure of the instrument using principal axis factoring (PAF) and promax rotation on time 3 data (Tabachnick & Fidell, 2001). We selected time 3 because that is the point when survivors’ progress usually stabilizes, therapy has usually been discontinued, and effective CG coping decreases (Van Puymbroeck & Rittman, 2005). Criteria for extraction included (a) loadings of at least .40 and at least .15 difference in cross-loadings, (b) use of the scree plot to identify the number of factors, and (c) eigenvalues greater than 1.0 (Tabachnick & Fidell, 2001). When low factor loadings (<.40) occurred, one item was deleted and the PAF repeated until all items loaded according to entry criteria. Kaiser–Meyer–Olkin test values were examined for sampling adequacy. Cronbach alphas were estimated on the final factors; items with item–total correlations below .30 were deleted, and alpha with item deleted was examined.
Concurrent construct validity was assessed by examining the relationship between time 3 URN and time 3 PPO, threat appraisal, depression, preparedness, survivor functional status, and number of resources used. Spearman correlation coefficients were computed because functional status was not normally distributed. Repeated measures analysis of variance was computed to assess change in the URN from baseline through 1 year.
The sample for the psychometric analysis was 166 participants with complete time 3 data. Table 1 shows baseline CG and survivor demographic and illness data. CGs were well educated; the majority was White and women. The majority of survivors was White, men, and hospitalized for a first stroke. The time 3 mean FIM score of 96 reflected the need for supervision or cueing for daily living activities. Descriptive statistics for the URN and outcome and coping process variables are in Table 2. Readability of the URN scale items was 8.0 grade using the SMOG method, which involves calculating the number of polysyllabic words (McLaughlin, 1969).
Structural Construct Validity
The factor analysis loadings yielded a two-factor solution that meets the analytic criteria. PAF was computed on the time 3 (6-month) 13-item URN scales with no missing data. The initial PAF indicated that all items, except item 9, which was reversely scored, met the loading criteria of .40. After deletion of item 9, “I usually tried to get a resource or service that I thought we needed,” two factors explaining 56% of variance emerged. Factors one and two explain 43% and 12%, respectively, of the total variance. Loadings ranged from .46 to .77 for factor 1 and .66 to .89 for factor 2. No item was cross-loaded at the .40 level. The scree test confirmed a two-factor solution. The Kaiser–Meyer–Olkin was .849, supporting sampling adequacy. The Bartlett’s test of sphericity was significant (p = .000), indicating that the correlation matrix was appropriate for the analysis. Table 3 shows factor loadings, item means and standard deviation, and item–total correlations for the URN items. Factor 1 reflected general resource needs, and Factor 2 reflected technology needs.
There is no agreed-upon method to test for floor and ceiling effects. Therefore, we examined the proportion of scores with floor and ceiling effects using total scale scores under 24 (strongly disagree) and ≥48 (strongly agree), respectively. Ceiling and floor effects were below the acceptable cutoff of 15% (Terwee et al., 2007). Floor effects ranged from 1.2% at baseline to 4.4% at time 4. Ceiling effects were absent at each time (0%).
Spearman correlations between the time 3 URN and time 3 coping and adaptation outcome variables ranged from −.11 for resource use to −.46 for preparedness for caregiving (Table 4).Whereas significant positive correlations were found for threat appraisal and depression (p < .01), significant negative associations were observed between the URN and preparedness for caregiving and positive problem solving. Relationships were such that greater threat and depression were associated with higher unmet needs. Lower preparedness and positive problem solving were associated with greater unmet needs. Resource use and functional independence were not significant.
Internal Consistency Reliability
Cronbach alphas were over .70 for the total scale and general needs subscale at all times in the sample of 166 CGs. The total scale coefficients ranged from .84 to .88 across four times. The general needs and technology scale alpha coefficients, respectively, ranged from .84 to .87 and .56 to .85. The alpha coefficients for the three-item technology needs subscale was inadequate at time 1, α = .56, and was .69 at Time 2.
Description of URN
Item statistics are in Table 3. Item means ranged from 2.04 (“I wished I could use the internet, but did not have computer access”) to 2.61 (“I did not know what kind of resources or services would help with a problem”). Standard deviations ranged from .91 to 1.10, indicating good variability. Item–total correlations ranged from .42 to .72. The mean scale scores for time 3 technology (2.29) and general resource needs (2.39) reflected neutral agreement (neither disagreeing nor agreeing) with the resource need item. Each item was endorsed as an unmet need by a minimum of 12% of CGs. Items endorsed as a need by 20% or more were “needed a service to help with caregiving but did not have it,” “needed services for my emotional needs but was reluctant to use them,” “I did not know what kind of resources would help,” “I did not know where to get help finding resources,” and “I wanted to use the LIFE center but did not know how.” The LIFE center is a patient–family resource center available to all CGs in the research study, either in person or through the Internet or telephone. It is similar to services in many rehabilitation hospitals that provide resources and personnel to convey information on resources and other information to aid adaptation to disability. Unmet needs remained common at 1 year when 42% of 123 CGs reported one or more unmet resource needs. One CG strongly agreed with needing all 12 resources.
Repeated measures analysis of variance indicated that unmet needs decreased significantly (F(3, 369) = 38.34, p < .0001). This finding was significant with Bonferroni correction. Results were as follows: (a) time 2, t(123) = −5.00, p = .000; (b) time 3, t(123) = −4.53, p = .000; and (c) time 4, t(123) = −6.94, p = .000. Post hoc paired t tests, based on cases with data at four times, indicated a significant reduction between baseline URN and each follow-up score. Table 5 shows the URN scale scores and alpha coefficients at all times for 123 CGs with data at four times. Alpha coefficients for this sample were similar to the larger sample of 166, ranging from .58 (time 1 technology scale) to .87 (time 3 total scale).
We developed the URN to meet the need for a psychometrically sound measure of unmet needs of CGs of survivors of stroke. The URN shows construct validity, including structural, content, and concurrent validity, and internal consistency reliability during the first year of caregiving.
Although the CG literature reports that unmet needs are related to CG depression, we found no study that provides evidence for this association. However, the difficulty of caregiving problems and problem stress are related to depression (Hartke & King, 2002; King et al., 2010). Conceptually, problems are similar to unmet needs but are not the same. Identifying the relationship between depression and unmet needs is an important contribution to clinical practice.
The study hypotheses are supported. Structural construct validity is supported by the PAF findings of two unmet need dimensions (general and technical) that meet all the criteria for retention in the 12-item scale. Evidence for content validity is provided by low floor and ceiling effects and development of the URN using data provided by CGs. Concurrent validity is supported by significant and moderate time 3 correlations between the URN and the PPO, threat appraisal, depression, and preparedness for caregiving. The relationships are such that fewer unmet needs are related to healthy coping and outcomes, for example, PPO, greater preparedness, and lower depression and threat appraisal. Our findings did not confirm prior reports that burden or survivor function was related to unmet needs (Hinojosa & Rittman, 2009; Scholte op Reimer et al., 1998). Functional status, which reflects burden, was marginally significantly related to unmet needs (p < .06), and resource use was not significant (p < .05). The cross-sectional analyses prohibit determining causality. Future longitudinal or intervention research is needed to clarify the direction of these relationships.
The hypothesis on internal consistency reliability is supported by alpha coefficients equal to or exceeding .70 for all except the time 1 three-item technology subscale. The technology needs scale is not recommended for use as a separate scale during the predischarge phase because of questionable reliability before discharge. At that time, it is likely that CGs are less aware of postdischarge resource needs and the usefulness of technology, such as Internet Web sites targeted to CGs. Nevertheless, both the 12-item and nine-item general scales showed high internal consistency reliability for the predischarge assessment time.
The scale covers a wide range of needs as a clinical tool and could serve as a precursor to discussion with CGs to either meet needs directly or point the way to resources. Our finding that unmet resource needs decrease quickly is similar to one report (Mak et al., 2007) but differs from others (Mackenzie et al., 2007; Ski & O’Connell, 2007). However, Mackenzie’s finding is marginally significant (p < .06). We found that the reduction in unmet needs between before discharge and 3 months after discharge is sustained during the year. However, 42% of CGs continued to report an unmet need at 1 year. Hinojosa and Rittman reported that 22%–29% of chronic CGs reported unmet needs, related to managing behavior, safety issues, protecting the survivor, and managing the survivor’s emotions (Hinojosa & Rittman, 2007). Similarly, finding services for the survivor’s emotional response is a common need in our study. At time 3, 19% and 13% of CGs reported unmet needs for patient emotional and behavioral concerns, respectively. Resources for managing the CG’s own emotions, reluctance to use resources for self, and not knowing which resources would help were common needs in our study.
Several limitations exist in our study, including a modest sample size with a ratio of 12:1 (participants to items). Recommendations for sample size for factor analysis vary considerably. Recommendations for ratios of participants to items range from 5:1 to 20:1 or, alternatively, recruit a sample of 300 or more participants (Henson & Roberts, 2006; Tabachnick & Fidell, 2001). Although our findings are promising, this is the first step in the development of the URN scale. The next steps should be confirmatory factor analysis to confirm the factor structure and reliability in a larger sample and to examine predictive validity. Also, temporal stability should be assessed with no more than 2 weeks between assessments to add support for scale reliability. Further refinement of the scale could include the addition of an item on information needs related to stroke symptoms and prevention (Bakas et al., 2002). In addition, the current scale does not allow CGs to add unmet needs, which could provide important information. The high drop-out rate is a limitation because we cannot determine how CGs who dropped out would have responded about resource needs over time.
Implications For Practice
Identifying the resource needs of family CGs can help to define interventions to reduce negative outcomes after stroke. Despite the limitations noted, the URN holds promise to help clinicians quickly assess if an intervention for unmet needs is indicated. This brief, structured measure can be used in clinical settings and in research studies. The brevity of the scale and its eighth-grade readability level support its use as a self-report measure. Strengths of the study include guidance by a conceptual model and findings of preliminary studies as well as using a prospective design that allowed assessment of change over 1 year.
This work was supported by the National Institute of Nursing Research #5RO1NR009077 (Rosemarie B. King, PI). We thank the caregivers who graciously gave their time and energy to participate in this study.
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caregiver; instrument development; psychometrics; stroke; unmet needs
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