Printer Friendly

Factors influencing return to work after aneurysmal subarachnoid hemorrhage.


Background: Aneurysmal subarachnoid hemorrhage (aSAH) is a type of stroke that affects women and men with a mean age of 50 years. Return to work (RTW) has been cited as a strategic goal of patients after injury; however, success rates are low in multiple studies. Therefore, the purpose of this study was to investigate factors influencing RTW after aSAH. The study design was a cross-sectional design at 1-2 years after injury to assess work status in 134 patients who were treated for aSAH. Participants were recruited at one hospital setting via mailed invitations. They were interviewed over the telephone after consent was obtained for chart review and to participate in the study. Eligible participants were asked to complete the Brief Illness Perception Questionnaire and the Functional Status Questionnaire. Data analysis was performed using univariate analysis and logistic regression with Statistical Package for the Social Sciences software. Results: There was a moderate negative correlation between illness perception and RTW. Illness perception was found to significantly predict failure to RTW, whereas marital status improved the prediction model to significantly predict successful RTW. Conclusions: This study addressed a gap in the literature regarding work status after aSAH and has provided direction for further investigation. Addressing issues surrounding patients' perception of illness may serve as an important conduit to remove barriers to RTW. Recognition of these barriers to RTW in assessing a person's illness perception may be the key to the development of interventions in the recovery process.

Keywords: aneurysmal subarachnoid hemorrhage, discharge, illness perception, long-term, long-term outcomes, return to work


Aneurysmal subarachnoid hemorrhage (aSAH) is a type of stroke caused by the sudden rupture of a cerebral aneurysm affecting women and men of all ages with a mean age of 50 years (Manno, 2004). Over 30,000 new cases of aSAH are treated each year in the United States (Manno, 2004; Suarez, Tarr, & Selman, 2006). Although mortality rates associated with aSAH are reported as high as 30% before reaching medical care (Cesarini, Hardemark, & Persson, 1999), case fatalities in the hospital have declined over the last 2 decades presumably because of better surgical techniques and medical management (Hop, Rinkel, Algra, & van Gijn, 1997; Ingall, Whisnant, Wiebers, & O'Fallon, 1989). Patients who survive the initial injury of aSAH are reported to have physical impairments in less than 10% of cases within 1 year (Stegen & Freckmann, 1991) and are anticipated to make a complete recovery.

Despite technological advances in the treatment of aSAH and expectations of recovery, little progress has been made in enhancing the quality of survival, as patients report a litany of psychological complaints in the aftermath of injury. These complaints are conjectured to impede recovery and exert negative effects on outcomes including return to work (RTW). RTW occurs in less than half of this patient population although they are physically capable of doing so (Carter, Buckley, Ferraro, Rordorf, & Ogilvy, 2000; Hackett & Anderson, 2000; Nishino et al., 1999; Stegen & Freckmann, 1991; Wermer, Kool, Albrecht, Rinkel, & Aneurysm Screening after Treatment for Ruptured Aneurysms Study Group, 2007). The physical, psychological, social, financial, and economic consequences associated with loss of productivity after aSAH are staggering and reported to cost billions of dollars each year (Rosamond et al., 2008). With an increasing prevalence of survivors of working age after aSAH, the ability to RTW has gained significant importance as an area for further research.

In many studies, less than 50% of patients actually RTW after aSAH (Fertl et al., 1999; Hop, Rinkel, Algra, & van Gijn, 2001; Kirkness et al., 2002; Powell, Kitchen, Heslin, & Greenwood, 2004). In addition, RTW occurs on an average of 9 months after injury (Fertl et al., 1999; Hop et al., 2001; Kirkness et al., 2002; Powell et al., 2004), and many patients are unable to RTW even years after injury (Carter et al., 2000; Nishino et al., 1999; Ogden, Utley, & Mee, 1997; Wermer et al., 2007). Failure to RTW after recovery from illness is associated with negative health outcomes such as increased cardiac disease, depression, and higher rates of mortality (Gallo et al., 2006) and social consequences such as isolation and poor coping ability (Brown, Gilmour, & Macdonald, 2006; Leidner, 2006; Wermer et al., 2007).

Failure to RTW has been conjectured to be caused by residual psychological symptoms such as fatigue, personality and behavioral changes (Deruty, Pelissou-Guyotat, Mottolese, & Amat, 1994; Lindberg, Angquist, Fodstad, Fugl-Meyer, & Fugl-Meyer, 1992; Maurice-Williams, Willison, & Hatfield, 1991; Ogden, Levin, & Mee, 1990), and poor coping skills (Ljunggren, Sonesson, Saveland, & Brandt, 1985; Tomberg et al., 2001). Other factors such as education, occupation, social support, and comorbidities (Shipley & Newman, 1993) also affect RTW (Fries & Bellamy, 1991). However, there does not seem to be one variable or combination of variables that explains the variance in RTW. Every person is affected differently after aSAH, which makes RTW difficult to predict. Each case of aSAH is uniquely situated in personal, social, and environmental circumstances that influence various outcomes.

Illness perception is based on a self-regulatory model, which was used as the theoretical framework for this study. The premise of the model states that individuals have a natural desire to understand their illness to cope. In the presence of a health threat, the individual will create cognitive and emotional representations, which will in turn influence coping responses. A self-regulatory approach using illness perception as the sum of an individual's cognitive and emotional representations after aSAH was hypothesized to influence RTW.

The purpose of this study was to identify influential factors that affected RTW outcomes in patients 1-2 years after aSAH. In addition, this study will investigate the relationship between the variables severity of illness, illness perception, and RTW after aSAH. This study addresses a critical public health issue regarding loss of productivity in the workplace after illness.

Participants and Methods Design

A retrospective design was used to examine factors associated with RTW after aSAH 1-2 years after injury. This study included 1,023 consecutive patients admitted for aSAH between January 2008 and September 2010 at an academic facility in the Northeastern United States. All patients aged 18-65 years with the primary diagnosis of subarachnoid hemorrhage, as specified by the International Classification of Diseases, Ninth Revision (code 430), were identified as potential participants for the study. Inclusion criteria were all participants with a Hunt and Hess (HH) score of 1-3 diagnosed upon admission after aSAH, the ability to speak and understand English, the ability to be understood in English over the telephone, and ages between 18 and 65 years; who had treatment of aSAH with endovascular or surgical techniques; who scored 0-1 on the modified Rankin scale (mRS) at the time of interview; who scored >30 on the Telephone Interview for Cognitive Status (TICS) questionnaire at the time of interview; and who were employed at the time of aSAH. The key exclusion criteria were definitive treatment of aSAH completed at an outside hospital or no endovascular or surgical treatment done during hospitalization and participants who were unemployed before injury. Participants had to be unambiguous cases of aSAH secondary to an aneurysm that are treated during hospitalization. An invitation to participate was mailed to all potential participants. If there was no response within 1 month, a second mailing was sent, and then a third. Finally, random telephone calling was utilized.

Data Collection

Data were collected from chart reviews and from patients after hospitalization via telephone. Consent was obtained to participate in the study and to screen the participants for eligibility. The TICS and mRS questionnaires were used to verify cognitive status and physical ability at the time of consent. If the participant qualified to participate in the study, he or she were asked questions over the telephone designed to assess RTW, preinjury work status, and educational level and the demographic variables age, gender, and race. In addition, the Brief Illness Perception Questionnaire (BIPQ) and the Functional Status Questionnaire (FSQ) were administered. Chart review provided information for the Charlson Comorbidity Index, the HH score, the modified Fisher score, and aneurysm size and location and verified the presence of intracranial hemorrhages, seizures, or strokes.

This study was approved by the institutional review board of an academic hospital. Potential participants were informed that participation in the study was entirely voluntary and that they could withdraw from the study at any given time. Informed consent was obtained from each participant before administrating the questionnaire.


Medical and Hospital Variables

The hospital variables were collected during chart review. Reports from radiographical images of admission computed tomography scan provided the information needed to score the modified Fisher and to verify the presence of an intracranial hemorrhage. Computed tomography scans are read and dictated by neuroradiologists during hospitalization. The last available report before discharge was used to verify the presence of strokes. Reports from angiography films established aneurysm size and location. These reports were read and dictated by the attending neurovascular surgeon. Presence of seizures at the onset of aSAH and/or anytime during hospitalization was obtained during chart review. The Charlson Comorbidity Index was obtained from ICD-9 (International Classification of Diseases, 9th edition) codes in the medical record (Katz et al., 1996). Information on age, gender, marital status, race, occupation, and educational level were collected from each participant during the telephone interview. Severity of injury was determined using the HH scale obtained through chart review. The use of the HH as a tool to predict morbidity has not been extensively studied, yet is shown in several studies to independently predict clinical outcomes including neuropsychiatric outcomes (Koivisto et al., 2000; Kreiter et al., 2002), physical functioning (Lagares et al., 2001; Ogilvy & Carter, 1998), and RTW (Carter et al., 2000; Nishino et al., 1999).

RTW Outcomes

All patients in this study were employed at the time of injury. RTW was determined by asking the following questions: which of the following statements best describes your work situation now? (a) Full-time; (b) part-time; or (c) unemployed, unable, or retired? This question was followed by the following: Are you working now in the same job or a different job from before your injury? Are you working now more hours, less hours, or the same number of hours from before your injury? The variable was recorded as three separate responses: RTW full time, RTW part time, and did not RTW. Because most respondents were in either the first or last category, this variable was changed to a dichotomous variable whereby the patient returned to work or did not RTW.

Quality-of-Life Variables

The BIPQ was used to measure illness perception to provide a measure of health perceptions. The BIPQ is an eight-item quantitative measure of the five domains of illness representations theoretically derived from Leventhal's self-regulatory model (Broadbent, Petrie, Main, & Weinman, 2006). The Brief Questionnaire is derived from the larger questionnaire the Illness Perception Questionnaire-Revised. All items are rated using a 0-to-10 scale. An overall score from the eight items was computed to represent the degree to which the illness was perceived as threatening or benign. A higher value was reflective of a more threatening view of the illness. Test-retest reliability was found to be stable in 132 renal patients over 3- and 6-week periods with correlations ranging from 0.42 to 0.75, all significant at p < .01 (Broadbent et al., 2006). There was a ninth optional item on the BIPQ, which was a causal question. This was an open-ended question that asked participants to rank in order the three most important factors that they believed caused his or her illness. Their responses were summarized.

The FSQ contains a psychological and social function scale to assess mental health and the participant's social role performance and affective quality of interactions with others. The subscales include items to assess mental and social health during the past month. Responses were recorded on a Likert scale from all of the time to none of the time and scored from 0 to 100, with 100 indicating maximum functioning. The scale provides a "warning zone" devised to help interpret individual scores and important functional disabilities. Internal consistency for the mental health scale was found by the authors with a reliability estimate of .81 (Jette et al., 1986). The warning zone for the social health subscale was determined by a panel of experts (Jette et al., 1986). Internal consistency for the social function scale was found by the authors with a reliability estimate of .65 (Jette et al., 1986).

Statistical Analysis

Data were collected over the telephone and entered directly into a dedicated computer database secured with a password. Descriptive statistics are presented for hospital variables, individual variables, the FSQ, and RTW. Statistical Package for the Social Sciences version 12.0 (SPSS, Inc., Chicago, IL) was used to run the data analysis. Univariate analysis was performed to identify factors associated with RTW. These factors were then used as independent variables with RTW as the dependent variable in a multivariate analysis using logistic regression. Odds ratios were computed to measure the association of each factor with RTW.


One thousand twenty-three patients were admitted to the hospital during the study period. Six hundred thirty-five (62%) patients died, were older than 65 years, were miscoded, or could not be found. That left 388 (38%) patients as the sample. Of these, 146 (38%) patients agreed to participate; however, 12 (8%) patients were excluded for not meeting the inclusion criteria. This left 134 patients, which served as the study sample for analysis. Because of constraints on patient information, participants and nonparticipants could only be obtained on the variables age, gender, and race. There were no differences between the groups.

Description of Participants

Characteristics of participants are provided in Table 1. Of the 134 participants, the mean age was 52 (SD = 8.5) years, with a range of 25-65 years. Most participants were women and Caucasian and had at least a college level degree of 80. The mean (SD) follow-up period was 19 (5) months. All participants were able to independently perform activities of daily living as measured by mRS and were cognitively intact as measured by TICS. Clinical characteristics of the participants can be seen in Table 2. No differences were seen between men and women.

Participants were divided into grades of severity: group 1 was classified as mild injury correlating to an HH grade 1 or 2. There were 51 participants who were categorized as group 1, with 19 men (50%) and 32 women (33.3%). Group 2 was classified as moderate injury correlating to an HH grade 3. There were 83 participants who were categorized as group 2, including 19 men (50%) and 64 women (66.6%). Significantly more women had a moderate injury than men: [chi square] = 3.208, df = p = .056.

Overall, the depression rate was 41.8%, measured by the FSQ. Social support was determined to be at low levels in 36% of the participants. There were no statistical differences between men and women. However, participants with a moderate injury were twice as likely to be depressed (Table 3).


Fifty-nine patients (44%) had not returned to work at the time of interview. Half of the men did not RTW, and 39 women (40%) did not RTW. Fifteen percent of the women returned to work with reduced hours, whereas only 10% of the men returned to work with a reduction in work hours. There were no statistical differences between men and women. Tables 4 and 5 show the result of preliminary analyses of participant, medical and hospital, and quality-of-life variables of participants who returned to work within the interim period versus those who did not. Participants were less likely to RTW if they were not married and if they did not identify high levels of social support. No relationship could be found between HH grade and RTW. When tested against illness perception, a moderate correlation was found [r.sub.pb] = -.30, p < .00, indicating that there is a statistically significant relationship.

Illness Perception

The BIPQ was composed of eight subcategories that each represented a different aspect of illness perception. Subcategory 1 represents consequences (how much illness has affected a person's life); subcategory 2 represents timeline (how long the illness will last); subcategory 3 represents personal control (how much control the person has over the illness); subcategory 4 represents treatment control (how effective treatment controls the illness); subcategory 5 represents identity (how much does a person experience symptoms related to the illness); subcategory 6 represents concern (how concerned is a person about the illness); subcategory 7 represents coherence (how well the illness is understood); and finally, subcategory 8 represents emotional representation (how much does the illness affect a person emotionally). In this study, the subcategories were summed to represent a total score. The total illness perception scores ranged from 0 to 69.00 (M = 35.34, SD = 16.91).

Multivariate Model

A logistic regression was run on the variables that demonstrated significance in the preliminary analysis including illness perception, marital status, education, and low levels of social support. The Hosmer and Lemeshow test was performed to test goodness of fit. The results indicate a p value of greater than .05; therefore, the model fits the data. The data were also examined for the absence of multicollinearity, which assumes that predictor variables are not closely related, and were assessed using variance inflation factors. The results of the logistic regression were significant, [chi square] = 20.07, df = 2, p = .00, suggesting that the model with marital status and illness perception was statistically significant. The variables social support and education were both dropped from the equation. The model with marital status and illness perception accounted for 12.5% of the variance in RTW, and overall, the regression correctly predicted 66.7% of the outcomes for RTW. The beta coefficients and odds ratios are presented in Table 6 and show that marital status and illness perception significantly contributed to the prediction of RTW.

In addition to the quantitative data collected during the interviews, question 9 of the BIPQ asked participants to provide three reasons as to why they thought the injury happened. Of the 134 participants, 122 responded to question 9. Not all participants provided three reasons, which resulted in 302 responses. The most common answer was that stress (77, 25.4%) had a role in the injury occurring. Hereditary or genetic factors were perceived to play a role in the injury as the second most common answer (n = 67, 22.1%). The third most common answer that participants gave was that they were not sure what caused the injury (n = 62, 20.4%). Hypertension (13%) and smoking (9%) combined accounted for 23% (n = 69) of the responses. Other causes accounted for 9% of the responses.


The sample consisted of 134 participants who were predominately female, aged 25-65 years, mostly white, married, and well educated.

Demographic and Clinical Characteristics The sample in this study was similar to the composition of other studies. Comparison of demographics was obtained from the five major subarachnoid hemorrhage trials: the International Subarachnoid Aneurysm Trial (Molyneux et al., 2002), Mild Intraoperative

Hypothermia during Surgery for Intracranial Aneurysm (Todd, Hindman, Clarke, Tomer, & Intraoperative Hypothermia for Aneurysm Surgery Trial (IHAST) Investigators, 2005), Prophylactic Transluminal Balloon Angioplasty (Zwienenberg-Lee et al., 2008), Clazosentan to Overcome Neurological Ischemia and Infarction Occurring after Subarachnoid Hemorrhage (Macdonald et al., 2008), and Cognitive Function after Aneurysm Surgery Trial (Samra et al., 2007). This current study had the advantage of recruiting more non-Caucasian participants. African Americans represented 28.8% of this sample. However, in this current study as well as the major studies mentioned, Asian and Hispanic participation was noticeably lacking.

Severity of Illness

Severity of illness was reported differently in the studies; however, most who participated were categorized as mild injury. In this current study, only 38% were mild injury, similar to the Prophylactic Transluminal Balloon Angioplasty study, which found 39% with mild injury (Zwienenberg-Lee et al., 2008). Strategies in this current study, including multiple mailings, telephone calls, and word of mouth, may have contributed to the recruitment of more patients with moderate severity of injury. However, in light of the number of participants with moderate injury, it therefore remains surprising that severity of injury and RTW did not have a statistically significant relationship as found in other studies (Carter et al., 2000; Nishino et al., 1999). No correlation between severity of injury and RTW was found in one other study (Cedzich & Roth, 2005). The authors hypothesized and concluded that severity of injury would not predict outcome. This current study corroborates those findings and can conclude that severity of injury does not predict RTW. An interesting finding in this study is the statistical significance of the number of women having moderate versus mild injury. This finding cannot be corroborated with another study, because most studies report gender as a total but, however, do not further elaborate on its association with objective measures such as severity of injury. Having more women with moderate injury may explain the higher rate of individuals with moderate injury participating in this study as compared with the major studies.

Another statistically significant, albeit not surprising, finding was that individuals who were determined to be depressed by the FSQ were more likely to have a moderate injury versus a mild injury. Individuals with moderate injury would likely have more cognitive difficulties to overcome, have spent time in rehabilitation, and overall, experienced a slower return to premorbid baseline.

Illness Perception

The findings of this study regarding a person's illness perception and RTW corroborated with previous research findings (Post, Krol, & Groothoff, 2006; Schulz & Williamson, 1993; Sluiter & Frings-Dresen, 2008; van der Giezen, Bouter, & Nijhuis, 2000). In this current study, illness perception was the most significant predictor of RTW. Illness perception had a weak association with severity of injury. This was consistent with other studies, which found that severity of injury is not as relevant to outcomes as is the patient's perception of how the injury will affect their life (Bergman, Jacobsson, Herrstrom, & Petersson, 2004; Petrie et al., 1996; Post et al., 2006; Reynolds, Gardner, & Lee, 2004; Scharloo et al., 2000).


RTW was recorded as a dichotomous variable in this current study. When compared with demographic and clinical variables, marital status, education, and social support were statistically significant. Marital status was a strong predictor of RTW; however, marital status was found to be less of a predictor for those who failed to RTW. Being married may provide the support and means needed to get to work and maintain the position but not necessarily explains why they did not RTW. Financial responsibility to one's family is also a strong motivator for a spouse to RTW. There have been mixed results in the literature regarding marital status and RTW, as it is a complex relationship. Many studies found no correlation (Bhattacharyya, Perkins-Porras, Whitehead, & Steptoe, 2007; DeVivo, Rutt, Stover, & Fine, 1987; Eaker et al., 2011). Regardless, because of the strong influence of marital status in this current study, further investigation is needed.

Lack of social support has been associated with increased risks of morbidity and mortality (Cacioppo & Hawkley, 2003); therefore, it was conjectured that it may also contribute to RTW or failure to RTW. Social isolation is known to occur more frequently after brain injury (Fertl et al., 1999; Hop et al., 2001; Kirkness et al., 2002; Powell et al., 2004) than in the general population. In this current study, although most of the participants reported having a high level of social support, a lack of social support had a profound effect on RTW. The group was also highly educated with a mean of 13 years. Those without a college degree may be disadvantaged by not having jobs, which would invest resources to maintain that individual's employment. This highlights the need for individuals with aSAH to have more access to higher education and, possibly, vocational training that would make them more suitable for employment after injury. Vocational training has been very effective in assisting patients with finding employment opportunities (Jang, Wang, & Wang, 2005). Vocational training could also provide a social support network for individuals experiencing similar symptoms. Despite the significance of social support and education, they were dropped from the multivariate model; yet, further research is still warranted on these variables.

Strengths and Limitations

There were many strengths to this study. This study supported other research studies utilizing illness perception to predict RTW (Jang, Bergman, Schonfeld, & Molinari, 2007; Pinquart, 2001; Schulz & Williamson, 1993; Vendrig, 1999). The use of illness perception, which turned out to be the strongest predictor of RTW, has not been used in previous studies of aSAH. The sample size provided adequate power to evaluate for a moderate-sized relationship. Because of the nature of the study as a cross-sectional study, there was no loss to follow-up and a minimal lack of missing data. The hospital used in this study was a referral center, receiving patients from a wide geographical area. The length of interview (under 30 minutes) was also a strength in this study, reducing the research burden on participants.

Limitations of the study design were that it was retrospective and cross-sectional, which does not allow for causal inferences to be made. This study only presented a static relationship between variables. Further elaboration may have revealed if attempts to RTW were made, how many times, and reasons for failure. This study also did not take into account if patients went to rehabilitation after hospitalization, which may have provided additional resources and vocational training. Finally, this study consisted of individuals who spoke English, who were well educated, working before injury, and were cognitively and functionally intact after injury; hence, the results can only be generalized to that type of population.


The goal of this study was to examine variables related to aSAH and how they affect RTW. RTW is a dynamic process that is influenced by many aspects of a person's environment. In this study, illness perception and marital status were found to be statistically significant in determining whether a person returns to work.

Implications for Nurses

Despite having the outward appearance of recovery, many individuals after aSAH are unable to RTW. Nurses care for these patients not only in the hospital setting but also in primary care offices and rehabilitation centers, and they can provide knowledge and insight and teach skills that may be necessary to RTW. Nurses work closely with patients and their families in all healthcare settings and are very frequently the main point of contact. This position provides nursing the opportunity to have an impact on outcomes through identification of an issue, teaching, and interventional therapies. Nurses and other healthcare professionals can play an important role in assisting patients after aSAH to RTW through screening and interventional strategies. However, programs can only be developed and implemented when there is a solid understanding of the issues, specifically how some people manage to successfully RTW versus others who are unable to RTW. With little available research in aSAH patients and current medical treatments being limited, it is important to explore variables that have an association between aSAH and RTW.


Bergman, S., Jacobsson, L. T., Herrstrom, P., & Petersson, I. F. (2004). Health status as measured by SF-36 reflects changes and predicts outcome in chronic musculoskeletal pain: A 3-year follow up study in the general population. Pain, 108(1-2), 115-123. doi: 10.1016/j.pain.2003.12.013

Bhattacharyya, M., Perkins-Porras, L., Whitehead, D. L., & Steptoe, A. (2007). Psychological and clinical predictors of return to work after acute coronary syndrome. European Heart Journal, 28, 160-165.

Broadbent, E., Petrie, K. J., Main, J., & Weinman, J. (2006). The brief illness perception questionnaire. Journal of Psychosomatic Research, 60(6), 631-637. doi:10.1016/j.jpsychores.2005.10.020

Brown, J., Gilmour, W. Fl., & Macdonald, E. B. (2006). Return to work after ill-health retirement in Scottish NFIS staff and teachers. Occupational Medicine (Oxford, England), 56(7), 480-484. doi:10.1093/occmed/kq1075

Cacioppo, J. T., & Hawkley, L. C. (2003). Social isolation and health, with an emphasis on underlying mechanisms. Perspectives in Biology and Medicine, 46(3), S39-S52.

Carter, B. S., Buckley, D., Ferraro, R., Rordorf, G., & Ogilvy, C. S. (2000). Factors associated with reintegration to normal living after subarachnoid hemorrhage. Neurosurgery, 46(6), 1326-1333.

Cedzich, C., & Roth, A. (2005). Neurological and psychosocial outcome after subarachnoid haemorrhage, and the hunt and hess scale as a predictor of clinical outcome. Zentralblatt Fur Neurochirurgie, 66(3), 112-118. doi: 10.1055/S-2005-836477

Cesarini, K. G., Hardemark, H. G., & Persson, L. (1999). Improved survival after aneurysmal subarachnoid hemorrhage: Review of case management during a 12-year period. Journal of Neurosurgery, 90(4), 664-672.

Deruty, R., Pelissou-Guyotat, I., Mottolese, C., & Amat, D. (1994). Long term outcome after treatment of the ruptured intracranial aneurysm: 73 cases admitted from day 0 to day 3 after subarachnoid haemorrhage. Neurological Research, 16(2), 83-88.

DeVivo, M., Rutt, R., Stover, S., & Fine, P. (1987). Employment after spinal cord injury. Archives of Physical Medicine Rehabilitation, 68, 494-498.

Eaker, S., Wigertz, A., Lambert, P. C., Bergkvist, L., Ahlgren, J., & Lambe, M. (2011). Breast cancer, sickness absence, income and marital status. A study on life situation 1 year prior diagnosis compared to 3 and 5 year after diagnosis. PLoS ONE, 6(3), e18040. doi: 10.1371/journal.pone.0018040

Fertl, E., Killer, M., Eder, FI., Linzmayer, L., Richling, B., & Auff, E. (1999). Long-term functional effects of aneurysmal subarachnoid haemorrhage with special emphasis on the patient's view. Acta Neurochirurgica, 141(6), 571-577.

Fries, J. F., & Bellamy, N. (1991). Introduction. In N. Bellamy (Ed.), Prognosis in the Rheumatic Disease (pp. 1-10). London, UK: Kluwer.

Gallo, W. T., Bradley, E., Dubin, J., Jones, R., Falba, T., Teng, H., & Kasl, S. (2006). The persistence of depressive symptoms in older workers who experience involuntary job loss: Results from the health and retirement survey. Journal of Gerontology, 61B(4), S221-S228.

Hackett, M. L., & Anderson, C. S. (2000). Health outcomes 1 year after subarachnoid hemorrhage: An international population-based study, the australian cooperative research on subarachnoid hemorrhage study group. Neurology, 55(5), 658-662.

Hop, J. W., Rinkel, G. J., Algra, A., & van Gijn, J. (1997). Case-fatality rates and functional outcome after subarachnoid hemorrhage: A systematic review. Stroke: A Journal of Cerebral Circulation, 28(3), 660-664.

Hop, J. W., Rinkel, G. J., Algra, A., & van Gijn, J. (2001). Changes in functional outcome and quality of life in patients and caregivers after aneurysmal subarachnoid hemorrhage. Journal of Neurosurgery, 95(6), 957-963. doi: 10.3171/jns.2001.95.6.0957

Ingall, T. J., Whisnant, J. P., Wiebers, D. O., & O'Fallon, W. M. (1989). Has there been a decline in subarachnoid hemorrhage mortality? Stroke: A Journal of Cerebral Circulation, 20(6), 718-724.

Jang, Y., Bergman, E., Schonfeld, L., & Molinari, V. (2007). The mediating role of health perceptions in the relation between physical and mental health: A study of older residents in assisted living facilities. Journal of Aging and Health, 19(3), 439-452. doi: 10.1177/0898264307300969

Jang, Y., Wang, Y., & Wang, J. (2005). Return to work after spinal cord injury in Taiwan: The contribution of functional independence. Archives of Physical Medicine and Rehabilitation, 86(4), 681-686.

Jette, A. M., Davies, A. R., Cleary, P. D., Calkins, D. R., Rubenstein, L. V., Fink, A., ... Delbanco, T. L. (1986). The functional status questionnaire: Reliability and validity when used in primary care. Journal of General Internal Medicine, 1(3), 143-149.

Katz, J. N., Chang, L. C., Sangha, O., Fossel, A. H., & Bates, D. W. (1996). Can comorbidity be measured by questionnaire rather than medical record review? Medical Care, 34(1), 73-84.

Kirkness, C. J., Thompson, J. M., Ricker, B. A., Buzaitis, A., Newell, D. W., Dikmen, S., & Mitchell, P. H. (2002). The impact of aneurysmal subarachnoid hemorrhage on functional outcome. The Journal of Neuroscience Nursing: Journal of the American Association of Neuroscience Nurses, 34(3), 134-141.

Koivisto, T., Vanninen, R., Hurskainen, H., Saari, T., Hemesniemi, J., & Vapalahti, M. (2000). Outcomes of early endovascular versus surgical treatment of ruptured cerebral aneurysms. A prospective randomized study. Stroke: A Journal of Cerebral Circulation, 37(10), 2369-2377.

Kreiter, K. T., Copeland, D., Bemardini, G. L., Bates, J. E., Peery, S., Claassen, J., ... Mayer, S. A. (2002). Predictors of cognitive dysfunction after subarachnoid hemorrhage. Stroke: A Journal of Cerebral Circulation, 33(1), 200-208.

Lagares, A., Gomez, P. A., Lobato, R. D., Alen, J. F., Alday, R., & Campollo, J. (2001). Prognostic factors on hospital admission after spontaneous subarachnoid haemorrhage. Acta Neurochirurgica, 143(1), 665-672.

Leidner, R. (2006). Identity and work. London, UK: Oxford University Press.

Lindberg, M., Angquist, K. A., Fodstad, H., Fugl-Meyer, K., & Fugl-Meyer, A. R. (1992). Self-reported prevalence of disability after subarachnoid haemorrhage, with special emphasis on return to leisure and work. British Journal of Neurosurgery, 6(4), 297-304.

Ljunggren, B., Sonesson, B., Saveland, H., & Brandt, L. (1985). Cognitive impairment and adjustment in patients without neurological deficits after aneurysmal SAH and early operation. Journal of Neurosurgery, 62(5), 673-679. doi: 10 .3171/jns. 1985.62.5.0673

Macdonald, R. L., Kassell, N. F., Mayer, S., Ruefenacht, D., Schmiedek, P. Weidauer, S., & CONSCIOUS-1 Investigators. (2008). Clazosentan to overcome neurological ischemia and infarction occurring after subarachnoid hemorrhage (CONSCIOUS-1): Randomized, double-blind, placebo-controlled phase 2 dose-finding trial. Stroke: A Journal of Cerebral Circulation, 39(11), 3015-3021. doi: 10.1161/STROKEAHA. 108.519942

Manno, E. M. (2004). Subarachnoid hemorrhage. Neurologic Clinics, 22(2), 347-366. doi: 10.1016/j.ncl.2003.12.002

Maurice-Williams, R. S., Willison, J. R., & Hatfield, R. (1991). The cognitive and psychological sequelae of uncomplicated aneurysm surgery. Journal of Neurology, Neurosurgery, and Psychiatiy, 54(A), 335-340.

Molyneux, A., Kerr, R., Stratton, I., Sandercock, R, Clarke, M., Shrimpton, J., ... International Subarachnoid Aneurysm Trial (ISAT) Collaborative Group. (2002). International subarachnoid aneurysm trial (ISAT) of neurosurgical clipping versus endovascular coiling in 2143 patients with ruptured intracranial aneurysms: A randomised trial. Lancet, 360(9342), 1267-1274.

Nishino, A., Sakurai, Y., Tsuji, I., Arai, H., Uenohara, H., Suzuki, S., & Li, J. H. (1999). Resumption of work after aneurysmal subarachnoid hemorrhage in middle-aged Japanese patients. Journal of Neurosurgery, 90(1), 59-64. doi: 10.3171/ jns. 1999.90.1.0059

Ogden, J. A., Levin, P., & Mee, E. W. (1990). Long-term neuro-psychological and psychosocial effects of subarachnoid hemorrhage. Neuropsychiatry, Neuropsychology and Behavioral Neurology, 3, 260-274.

Ogden, J. A., Utley, T., & Mee, E. W. (1997). Neurological and psychosocial outcome 4 to 7 years after subarachnoid hemorrhage. Neurosurgery, 4/(1), 25-34.

Ogilvy, C. S., & Carter, B. S. (1998). A proposed comprehensive grading system to predict outcome for surgical management of intracranial aneurysms. Neurosurgery, 42(5), 959-968.

Petrie, K. J., Weinman, J., Sharpe, N., & Buckley, J. (1996). Role of patients' view of their illness in predicting return to work and functioning after myocardial infarction: Longitudinal study. BMJ (Clinical Research Ed.), 3/2(7040), 1191-1194.

Pinquart, M. (2001). Correlates of subjective health in older adults: A meta-analysis. Psychology and Aging, 16(3), 414-426.

Post, M., Krol, B., & Groothofif, J. W. (2006). Self-rated health as a predictor of return to work among employees on long-term sickness absence. Disability and Rehabilitation, 28(5), 289-297. doi: 10.1080/09638280500160303

Powell, J., Kitchen, N., Heslin, J., & Greenwood, R. (2004). Psychosocial outcomes at 18 months after good neurological recovery from aneurysmal subarachnoid haemorrhage. Journal of Neurology, Neurosurgery & Psychiatry, 75(8), 1119-1124.

Reynolds, P., Gardner, D., & Lee, R. (2004). Tinnitus and psychological morbidity: A cross-sectional study to investigate psychological morbidity in tinnitus patients and its relationship with severity of symptoms and illness perceptions. Clinical Otolaryngology and Allied Sciences, 29(6), 628-634. doi: 10.1111/j.1365-2273.2004.00879.X

Rosamond, W., Flegal, K., Furie, K., Go, A., Greenlund, K., Haase, N., ... American Heart Association Statistics Committee and Stroke Statistics Subcommittee. (2008). Heart disease and stroke statistics--2008 update: A report from the American Heart Association statistics committee and stroke statistics subcommittee. Circulation, 117(A), e25-e146. doi: 10.1161/CIRCULATIONAHA.107.187998

Samra, S. K., Giordani, B., Caveney, A. F., Clarke, W. R., Scott, P. A., Anderson, S., ... Todd, M. M. (2007). Recovery of cognitive function after surgery for aneurysmal subarachnoid hemorrhage. Stroke: A Journal of Cerebral Circulation, 38(6), 1864-1872. doi: 10.1161/STROKEAHA.106.477448

Scharloo, M., Kaptein, A. A., Weinman, J., Bergman, W., Vermeer, B. J., & Rooijmans, H. G. (2000). Patients' illness perceptions and coping as predictors of functional status in psoriasis: A 1-year follow-up. The British Journal of Dermatology, 142(5), 899-907.

Schulz, R., & Williamson, G. M. (1993). Psychosocial and behavioral dimensions of physical frailty. Journal of Gerontology, 48, 39-43.

Shipley, M., & Newman, S. P. (1993). Psychological aspects of rheumatic diseases. Bailliere's Clinical Rheumatology, 7, 215-219.

Sluiter, J. K., & Frings-Dresen, M. H. (2008). Quality of life and illness perception in working and sick-listed chronic RSI patients. International Archives of Occupational and Environmental Health, 81(4), 495-501. doi:10.1007/s00420-007-0222-z

Stegen, G., & Freckmann, N. (1991). Outcome and rehabilitation after aneurysmal subarachnoid haemorrhage. Zentralblatt Fur Neurochirurgie, 52(1), 37-39.

Suarez, J. I., Tarr, R. W., & Selman, W. R. (2006). Aneurysmal subarachnoid hemorrhage. The New England Journal of Medicine, 354(4), 387-396. doi:10.1056/NEJMra052732

Todd, M. M., Hindman, B. J., Clarke, W. R., Tomer, J. C., & Intraoperative Flypothermia for Aneurysm Surgery Trial (IHAST) Investigators. (2005). Mild intraoperative hypothermia during surgery for intracranial aneurysm. The New England Journal of Medicine, 352(2), 135-145. doi: 10.1056/ NEJMoa040975

Tomberg, T., Orasson, A., Linnamagi, U., Toomela, A., Pulver, A., & Asser, T. (2001). Coping strategies in patients following subarachnoid haemorrhage. Acta Neurologica Scandinavica, 104(3), 148-155.

van der Giezen, A. M., Bouter, L. M., & Nijhuis, F. J. (2000). Prediction of return-to-work of low back pain patients sick-listed for 3-4 months. Pain, 87(3), 285-294.

Vendrig, A. A. (1999). Prognostic factors and treatment-related changes associated with return to work in the multimodal treatment of chronic back pain. Journal of Behavioral Medicine, 22(3), 217-232.

Wermer, M. J., Kool, H., Albrecht, K. W., Rinkel, G. J., & Aneurysm Screening after Treatment for Ruptured Aneurysms Study Group. (2007). Subarachnoid hemorrhage treated with clipping: Long-term effects on employment, relationships, personality, and mood. Neurosurgery, 60(1), 91-97. doi: 10 .1227/01.NEU.0000249215.19591.86

Zwienenberg-Lee, M., Hartman, J., Rudisill, N., Madden, L. K., Smith, K., Eskridge, J., & Balloon Prophylaxis for Aneurysmal Vasospasm (BPAV) Study Group. (2008). Effect of prophylactic transluminal balloon angioplasty on cerebral vasospasm and outcome in patients with fisher grade III subarachnoid hemorrhage: Results of a phase II multicenter, randomized, clinical trial. Stroke: A Journal of Cerebral Circulation, 59(6), 1759-1765. doi:10.1161/STROKEAHA.107.502666

Questions or comments about this article may be directed to Catherine Harris, PhD MBA CRNP, at She is an Assistant Professor of Graduate Programs at Jefferson School of Nursing, Philadelphia, PA.

The author declares no conflicts of interest.

DOI: 10.1097/JNN.0000000000000067
TABLE 1. Characteristics of 134
Participants With Aneurysmal
Subarachnoid Hemorrhage

Demographic                                      Value

Age, mean (SD)                                 52.2 (8.8)
  Median                                           54
  Range                                          25-65
Education, mean (SD)                          13.53 (2.4)
  Median                                           12
  Range                                          10-25
Brief Illness Perception
  Questionnaire, mean (SD)                     36.02 (16)
  Median                                           38
  Range                                           1-69
Psychological health, mean (SD)                70.7 (21)
  Median                                           76
  Range                                          4-100
Quality of social interaction, mean (SD)      75.42 (20.6)
  Median                                           80
  Range                                          16-100
Social support, mean (SD)                      75.38 (31)
  Median                                          100
  Range                                          0-100
Characteristic, n (%)
    Male                                        38 (28)
    Female                                      96 (72)
  Marital status
    Married                                     84 (63)
    Single                                      22 (17)
    Divorced                                    20 (14)
    Other                                        8 (6)
    Caucasian                                   89 (67)
    Black                                       38 (28)
    Asian                                        5 (4)
    Other                                        2 (1)

TABLE 2. Frequencies and Percentage of Participants' Clinical
Characteristics Upon Admission or Discharge: Total and by Gender (a)

Clinical Characteristic          N (%)       Men,        Women,
                                             n (%)       n (%)

On admission
  Modified Fisher grade
    0-1                          31 (23.2)    8 (21)     23 (23.9)
    2-3                          52 (38.8)   19 (50)     33 (34.3)
    4                            51 (38)     11 (28.9)   40 (41.6)
  Intraparenchymal hemorrhage    18 (13.4)    9 (23.6)    9 (9.3)
  Seizure                        10 (7.5)     3 (7.8)     7 (7.2)
  Comorbidities (>2)             13 (9.7)     4 (10.5)    9 (9.3)
On discharge
  Ischemic stroke                43 (32.1)   14 (36.8)   29 (30.2)

(a) No significant differences among variables and gender.

TABLE 3. Depressed Participants Compared
With Not Depressed: Total and
by Severity of Injury

                               Mild Injury,   Moderate
Characteristic     N (%)       n (%)          Injury, n (%)

Depressed          56 (41.8)   16 (31)        40 (48) (a)
Not depressed      78 (58.2)   35 (69)        43 (51)

(a) [chi square] = 3.67, df = 1, p = .04, and OR = 2.06.

TABLE 4. Comparison of Nominal Demographic and Clinical Variables
on Return to Work!

Demographic Variables           Return to     [chi     df     P
                               Work, n (%)   square]

Gender                                        0.767    1     .44
  Male                           19 (50)
  Female                         56 (58)
Marital status                                8.39     1    .00 *
  Married/significant other      55 (65)
  Not involved                   19 (44)
Ethnicity                                     3.181    2     .20
  Caucasian                      55 (61)
  Black                          17 (44)
  Asian/Hispanic                 3 (60)

Clinical Variables

Severity of injury                            1.53     1     .14
  Mild injury                    43 (52)
  Moderate injury                32 (63)
Fisher grade                                  3.269    4     .51
  0                              4 (67)
  1                              13 (52)
  2                              24 (67)
  3                              7 (44)
  4                              27 (53)
Intraparenchymal hemorrhage                   0.301    1     .38
  Yes                            9 (50)
  No                             66 (57)
Seizure                                       1.118    1     .23
  Yes                            4 (40)
  No                             71 (57)
Ischemic stroke                               0.519    1     .29
  Yes                            26 (60)
  No                             49 (54)
Size of aneurysm, mm                          2.282    2     .32
  <5                             22 (54)
  5-10                           49 (60)
  >10                            4 (36)
Location of aneurysm                          0.963    1     .22
  Anterior                       60 (54)
  Posterior                      15 (65)
Treatment                                     0.397    1     .33
  Endovascular                   57 (57)
  Open surgery                   18 (51)
Comorbidities                                 0.563    1     .32
  <2                             69 (57)
  [greater than or equal to] 2   6 (46)

* p < .05.

TABLE 5. Comparison of Means Between RTW and non-RTW Participants on
Demographic, Clinical, and Predictor Variables

Demographic Variables         N      M      SD       t        P

Age, years                                         -0.943   .34
  RTW                         75   51.67   8.47
  Non-RTW                     59   53.07   8.68
Education, years                                    2.42    .01 *
  RTW                         75   14.01   2.77
  Non-RTW                     59   13.03   1.87

Clinical Variables            N      M      SD       t        P

Depression                                          1.32    .18
  RTW                         75   73.84   17.83
  Non-RTW                     59   69.14   23.23
Low-quality social support                          3.05    .00 *
  RTW                         75   83.21   28.36
  Non-RTW                     59   66.03   35.06
Illness perception                                 -4.03    .00 *
  RTW                         75   30.39   16.65
  Non-RTW                     59   41.63   15.17

Note. RTW = return to work.

* p < .05.

TABLE 6. Logistic Regression With Marital Status and Illness
Perception Predicting Return to Work

Variable                B       SE       Wald    df    P     Exp(B)

Illness perception    0.037    0.012     9.48    1    .00    1.038
Marital Status        1.052    0.391     7.24    1    .00     2.86

Variable                  95% Confidence
                       Interval for Exp(B)

                        Lower        Upper

Illness perception      1.014        1.063
Marital Status          1.331        6.616

Note, [chi square] = 20.07, df = 2, and p = .00.
COPYRIGHT 2014 American Association of Neuroscience Nurses
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2014 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Author:Harris, Catherine
Publication:Journal of Neuroscience Nursing
Article Type:Report
Date:Aug 1, 2014
Previous Article:Peripheral immune response and infection in first-time and recurrent ischemic stroke or transient ischemic attack.
Next Article:The effectiveness of four translation strategies on nurses' adoption of an evidence-based bladder protocol.

Terms of use | Copyright © 2018 Farlex, Inc. | Feedback | For webmasters