1. YUE CAO, PHD, MSPH MEDICAL UNIVERSITY OF SOUTH CAROLINA Unmet Expectations of Adjustment: Impact on Depression and Life Satisfaction among People with Chronic TSCI

2. Disclosures  The contents of this presentation were developed under a grant from the Department of Education, NIDRR grant numbers H133B090005, and funding from the South Carolina Spinal Cord Injury Research Fund (SCSCIRF), grant number SCIRF 11-006. However, those contents do not necessarily represent the policy of the Department of Education or the SCSCIRF, and you should not assume endorsement by the Federal Government or the state of South Carolina.

3. Learning Objectives  Gain a better understanding of overall adjustment among people with chronic traumatic spinal cord injury (TSCI) by identifying participants who experienced unmet expectations of adjustment.  Examine the relationship between unmet expectations of adjustment and depressive symptoms.  Examine the relationship between unmet expectations of adjustment and life satisfaction.

4. Background  People with TSCI experience a major life event and some of them have permanent sensory and/or motor loss which causes dysfunction and deteriorates quality of life.  After people survive from the acute stage of TSCI, they hope to adjust to this major life event as quickly as possible, and it is natural for some to have high expectations or even unrealistic expectations about future outcomes.

5. Background  One study found patients’ expectations regarding independence with self-care one year post SCI were substantially higher than those of their therapists. 70% of the patients had expectations of gaining independence with feeding, but only 20% of the therapists shared those expectations (Lysack et al., 2001).  In another study comparing patients and therapists expectations about walking one year post injury, patient expectations were much higher than those of therapists at the time of admission to rehabilitation. Patients’ real performance of walking was measured at one year post injury, and the results showed the therapists’ expectations were more accurate (Harvey et al., 2012).

6. Background  Unrealistic expectation is negatively associated with subjective well-being. Unrealistic expectations for walking in a functional electrical stimulation exercise program resulted in increased depression and hostility (Bradley, 1994). A recent study suggests expecting ambulation when it is improbable could detract persons with SCI from the time and effort that might be spent learning functional independence on a wheelchair, which may result in lower quality of life and higher depression scores (Riggins, Kankipati, Oyster, Cooper, & Boninger, 2011).  It is also highly possible that unrealistic expectations can lead to unmet expectations, which may negatively affect subjective well-being.

7. Background  Self-discrepancy theory is a useful tool to understand consequences of unmet expectations. Maintains that the inconsistencies between actual self and ideal self are more likely to cause depressive states, while the inconsistencies between actual self and ought self are more likely to cause anxious states (Higgins, Bond, Klein, and Strauman, 1986; Higgins, 1987 ).  Literature exists on the negative consequences of unmet expectations on well-being across different fields of research (Xi & Hwang, 2011; Carr, 1997; Nelson & Sutton, 1991).  However, there is no empirical study to assess the role of unmet expectations as a predictor of subjective well-being among persons with chronic disability.

8. Hypothesis & Significance  In this study, we hypothesized that unmet expectations, as defined by the discrepancies between individuals’ expected achievement of their overall adjustment to TSCI and their actual self-perceived overall adjustment 10 years later, may contribute to increased risk of depressive symptoms and decreased life satisfaction.  Understanding unmet expectations of adjustment in persons with chronic disability is important for three reasons. 1. We need to know whether unmet expectations of adjustment are prevalent in this population. 2. The possible association between unmet expectations and subjective well- being needs to be empirically examined in this population. 3. Our study can expand the self-discrepancy theory to include the discrepancy between expected and actual adjustment to chronic disability.

9. Methods: Procedures  Design: Prospective cohort study  Setting: 1,929 potential participants identified from records of a rehabilitation specialty hospital in the Southeastern United States.  Procedures: IRB approval before data collection. Preliminary letters sent to all participants. Initial packet of survey materials mailed to participants. A second set of materials sent to all non-respondents, as well as a follow-up phone call. A third set of materials sent to participants who consented to participate in the phone call.

10. Methods: Participants  Time 1 survey completed in 1997 (n=1386)  Inclusion criteria Residual effects resulting from TSCI At least 1-year post-injury At least 18 years old at time of survey  Time 2 follow-up completed in 2008  863 of the original 1386 were followed up successfully (Follow-up rate = 62%)  Final sample size used in this study= 863 who completed both Time 1 and Time 2 survey

11. Methods: Outcome Measures  Outcome 1 Total score of 22-item Older Adult Health and Mood Questionnaire (OAHMQ)  Outcome 2 Probable Major Depression (PMD): OAHMQ scores of 11 and higher (Yes vs. No)  Outcome 3 Life satisfaction measured by the 20 satisfaction items within the Life Situation Questionnaire-Revised (LSQ-R).

12. Methods: Predictor of Interest  Predictor of interest: Unmet expectation (yes vs. no) At time 1, we used a 10-point ladder (10=best adjustment, 1=worst) to measure expected future adjustment. At time 2, the same 10-point ladder was used to measure current overall adjustment in the follow-up survey. Then we compared the two 10-point ratings. We considered expectations to be unmet when actual adjustment ratings at Time 2 were lower than expected adjustment at Time 1.

13. Methods: Other Variables  Age  Gender (male vs. female)  Race (white vs. others)  Years of education,  Marital status (married vs. others)  Years since injury  Injury origin (violence vs. others)  Injury severity: C1-C4, non-ambulatory C5-C8, non-ambulatory Non-cervical, non-ambulatory Ambulatory  Self-perceived health (5- point scale)  Hours out of bed per day  Social support (Reciprocal Social Support Scale)  Household income( 75K) All measured at Time 1.

14. Bivariate Analyses  Compared the group followed successfully with the group lost in terms of demographics and injury characteristics.  Compared the group with unmet expectations with the other group in terms of demographics and injury characteristics, and three outcomes.

15. Multivariate Analyses For each of the 3 outcome variables, we built two multivariate regression models. The first model had all the independent variables except for the unmet expectation variable. Then we added the unmet expectation variable in the second model to see the contribution of unmet expectations to the overall model fit. We implemented lagged-Y-regressor analysis for all the regression models (Johnson, 2005; Putzke, Richards, Hicken, & DeVivo, 2002). This method added the lagged-Y-regressor (i.e., the outcome’s values measured at the Time 1) as a controlling variable in the regression models to eliminate autocorrelation in the residuals. That means we used the depression and life satisfaction measured at time 1 in the regression models to estimate more specifically the unique explanatory power of unmet expectations.

16. Multivariate Analyses  Model 1a: OLS regression model; outcome is depression total scores measured at Time 2; without unmet expectation in the model.  Model 1b: Added unmet expectation to Model 1a.  Model 2a: Logistic regression model; outcome is PMD measured at Time 2; without unmet expectation in the model.  Model 2b: Added unmet expectation to Model 2a.  Model 3a: OLS regression model; outcome is life satisfaction scores measured at Time 2; without unmet expectation in the model.  Model 3b: Added unmet expectation to Model 3a.

17. Results Among the 863 participants, 840 had a valid value of the unmet expectation variable. We found 421 participants (50.1%) experienced unmet expectations of adjustment to TSCI.

18. Study SampleLost to Follow-Up p-value (n=863) (n=523) Mean age ± SD38.86±11.8246.04±15.56<.01 Male (%)71.9677.25 0.03 White (%)24.825.62 0.73 Married (%)36.0439.58 0.19 Average years of education ± SD13.37±2.6912.7±3.15<.01 Average years since injury ± SD9.4±6.3110.14±7.660.05 Violence Origin (%)11.714.34 0.15 Injury Severity (%) Non-ambulatory C1-411.6715.95 0.08 Non-ambulatory C5-830.2230.74 Non-ambulatory non-cervical35.3634.24 Ambulatory22.7519.07 Demographic and Injury Characteristics Comparison between Successfully Followed Participants and Lost Participants

19. Comparison between People with Unmet Expectation and Those without Expectation Unmet p-value No (n=419)Yes (n=421) Mean age ± SD39±11.2838.6±12.150.62 Male (%)69.2174.580.22 White (%)79.0072.210.02 Married (%)36.9935.39 0.76 Average years of education ± SD13.58±2.7213.23±2.640.06 Average years since injury ± SD9.96±6.558.87±6.080.01 Violence Origin (%)10.512.590.44 Injury Severity (%) Non-ambulatory C1-49.1114.35 0.02 Non-ambulatory C5-834.2926.56 Non-ambulatory non-cervical35.7334.69 Ambulatory20.8624.40

20. Depression Total Score Comparison between Two Groups across Time

21. PMD Percentage Comparison between Two Groups across Time

22. Life Satisfaction Total Score Comparison between Two Groups across Time

23. Model 1a and 1b OLS Regression Analysis: Predicting Time 2 OAHMQ Score

24. Variables Excluding Unmet Expectation Including Unmet Expectation Standardized βp-value Standardized βp-value Expectation unmet (vs. No)--0.20<.01 Age-0.100.01-0.090.02 Male (vs. Female)0.000.92-0.010.79 White (vs. Others)0.080.040.090.01 Years of education-0.050.18-0.050.15 Married (vs. Others)0.11<.010.090.01 Years since injury0.070.040.090.01 Injury severity (vs. Ambulatory) Non-ambulatory C1-4-0.070.07-0.080.04 Non-ambulatory C5-8-0.110.01-0.100.02 Non-ambulatory non-cervical-0.030.49-0.020.67 Violence origin (vs. Others)0.040.290.030.38 Self-perceived health-0.080.04-0.070.04 Hours out bed-0.030.45-0.020.62 Social support-0.050.17-0.040.23 Household income(vs. >75K) <$35K0.120.020.090.06 $35-75K0.020.670.020.74 OAHMQ at time 10.41<.010.42<.01 Adj R 2 0.26 0.30 (15.4% increase)

25. Model 2a and 2b Logistic Regression Analysis: Predicting Time 2 PMD

26. Variables Excluding Unmet Expectation Including Unmet Expectation OR (95% CI)p-value OR (95% CI)p-value Expectation unmet (vs. No)--2.8(1.8-4.35)<.01 Age0.97(0.95-0.99)0.010.98(0.96-1)0.02 Male (vs. Female)1.09(0.68-1.75)0.721.06(0.66-1.71)0.80 White (vs. Others)1.79(1.04-3.08)0.031.94(1.12-3.36)0.02 Years of education0.99(0.91-1.08)0.850.99(0.9-1.08)0.80 Married (vs. Others)1.7(1.02-2.81)0.041.57(0.94-2.64)0.09 Years since injury1.02(0.99-1.06)0.231.03(0.99-1.06)0.18 Injury severity (vs. Ambulatory) Non-ambulatory C1-40.35(0.15-0.81)0.010.32(0.14-0.75)0.01 Non-ambulatory C5-80.5(0.28-0.9)0.020.53(0.29-0.96)0.04 Non-ambulatory non-cervical0.75(0.45-1.28)0.290.8(0.47-1.37)0.41 Violence origin (vs. Others)1.5(0.76-2.96)0.241.41(0.71-2.79)0.32 Self-perceived health0.71(0.56-0.9)<.010.7(0.55-0.89)<.01 Hours out bed1(0.94-1.07)0.991(0.94-1.07)0.95 Social support0.98(0.94-1.02)0.300.98(0.95-1.02)0.37 Household income(vs. >75K) <$35K2.72(1.22-6.07)0.012.6(1.14-5.93)0.02 $35-75K1.18(0.49-2.85)0.711.19(0.48-2.96)0.71 PMD at time 14.67(2.9-7.53)<.015.35(3.27-8.76)<.01 -2 Log L603.11580.86 Rescaled R 2 0.23 0.27 (17.4% increase)

27. Model 3a and 3b OLS Regression Analysis: Predicting Time 2 Life Satisfaction score

28. Variables Excluding Unmet Expectation Including Unmet Expectation Standardized βp-value Standardized βp-value Expectation unmet (vs. No)---0.28<.01 Age0.040.310.030.35 Male (vs. Female)0.000.980.010.77 White (vs. Others)-0.10<.01-0.12<.01 Years of education0.040.230.040.19 Married (vs. Others)0.060.110.070.04 Years since injury-0.050.17-0.070.03 Injury severity (vs. Ambulatory) Non-ambulatory C1-4-0.050.18-0.040.20 Non-ambulatory C5-80.000.97-0.020.57 Non-ambulatory non-cervical-0.040.38-0.050.19 Violence origin (vs. Others)-0.010.80-0.010.87 Self-perceived health0.080.020.080.01 Hours out bed0.010.750.000.99 Depression-0.15<.01-0.18<.01 Social support0.080.020.080.01 Household income(vs. >75K) <$35K-0.110.03-0.080.09 $35-75K-0.030.49-0.020.55 LSQ-R at time 10.30<.010.27<.01 Adj R 2 0.31 0.39 (26% increase)

29. Discussion  Our study confirms that unmet expectations are of concern among people with chronic TSCI, as more than half of our sample experienced unmet expectations of adjustment.  Although unmet expectations were associated with increased risk of depressive symptoms and decreased life satisfaction among people with chronic TSCI, we should not necessarily discourage high expectations at the acute stage of injury.  Hope is particularly important for people who traumatically acquired physical disabilities to maintain a sense of optimism and capability of coping in spite of their losses.

30. Discussion  From hope theory perspective (Elliott, Witty, Herrick, & Hoffman, 1991; Snyder, 1989; Snyder, 2002), high expectations provide motivation and energy to meet the rehabilitation goals and are beneficial to short-term psychological adjustment soon after TSCI. However, they will lose momentum at the chronic stage, and the feasible strategies and means to achieve the goals are the key to the successful long-term adjustment.  For those having high expectations without realistic planning and strategies at the chronic stage, it is highly possible unmet expectations may occur and may contribute to a discrepancy between actual and ideal self, which may lead to deterioration of subjective well-being.

31. Implications  For clinicians, it is understandable to provide more positive feedback as a way to engender patients’ hope at the acute stage of TSCI. However, it becomes more important at the chronic stage to reinforce reasonable expectations with realistic pathways to achieve goals.  Unmet expectations may be prevented at an early stage through monitoring and identifying individuals who have unrealistic expectations and through an educational program to build a more realistic understanding of the rehabilitation process and living with TSCI.  If people are suffering from depression caused by unmet expectations, clinicians may consider some interventions program designed to reduce self- discrepancy.  Our study raises an interesting and significant research question for future study: How do we make patients more reasonable in their expectations while not hurting their hope?

32. Limitations  Selection bias due to 38% follow-up attrition.  The measurement of unmet expectations is a rough and general item, did not distinguish between different perspectives of the expectations after TSCI: for example, functional and psychosocial expectations.  Under- or over-reporting problems on self-report measures.  Our findings can not be generalized to people with acute TSCI.

33. Conclusion  Despite limitations, this is the first empirical research in the rehabilitation field to focus on the effects of unmet expectations on subject well-beings.  Our findings suggest unmet expectations of adjustment are common among people with chronic TSCI.  Unmet expectations are associated with increased risk of depressive symptoms and decreased life satisfaction among people with chronic TSCI.

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