SPINAL CORD INJURY IS associated with increased prevalence

Transcription

1 1218 ORIGINAL ARTICLE Factor Structure and Predictive Validity of Somatic and Nonsomatic Symptoms From the Patient Health Questionnaire-9: A Longitudinal Study After Spinal Cord Injury James S. Krause, PhD, Karla S. Reed, MA, John J. McArdle, PhD ABSTRACT. Krause JS, Reed KS, McArdle JJ. Factor structure and predictive validity of somatic and nonsomatic symptoms from the Patient Health Questionnaire-9: a longitudinal study after spinal cord injury. Arch Phys Med Rehabil 2010;91: Objective: To investigate the factor structure and predictive validity of somatic and nonsomatic depressive symptoms over the first 2.5 years after spinal cord injury (SCI) using the Patient Health Questionnaire-9 (PHQ-9). Design: Somatic and nonsomatic symptoms were assessed at baseline during inpatient hospitalization (average of 50 days after onset) and during 2 follow-ups (average of 498 and 874 days after onset). Setting: Data were collected at a specialty hospital in the Southeastern United States and analyzed at a medical university. We performed time-lag regression between inpatient baseline and follow-up somatic and nonsomatic latent factors of the PHQ-9. Participants: Adults with traumatic SCI (N 584) entered the study during inpatient rehabilitation. Interventions: Not applicable. Main Outcome Measure: PHQ-9, a 9-item measure of depressive symptoms. Results: The inpatient baseline nonsomatic latent factor was significantly predictive of the nonsomatic (r.40; P.000) and somatic latent factors at the second follow-up (r.29; P.006), whereas the somatic factor at inpatient baseline did not significantly predict either factor. In contrast, when regressing latent factors between the 2 follow-ups, the nonsomatic factor predicted only the nonsomatic factor (r.66; P.002), and the somatic factor predicted only future somatic symptoms (r.66; P.000). In addition, the factor structure was not stable over time. Item analysis verified the instability of somatic items between inpatient baseline and follow-up and also indicated that self-harm at inpatient baseline was highly predictive of future self-harm. From the College of Health Professions, Medical University of South Carolina, Charleston, SC (Krause, Reed); College of Letters, Arts, and Sciences, University of Southern California, Los Angeles, CA (McArdle). The contents of this publication were developed under grants from the Department of Education, National Institute of Disability and Rehabilitation Research (grant nos. H133G and H133N000005). However, those contents do not necessarily represent the policy of the Department of Education, and you should not assume endorsement by the Federal Government. No commercial party having a direct financial interest in the results of the research supporting this article has or will confer a benefit on the authors or on any organization with which the authors are associated. Correspondence to James S. Krause, PhD, Dept of Health Sciences and Research, College of Health Professions, Medical University of South Carolina, 77 President St, Ste 117, MSC 700, Charleston, SC 29425, krause@musc.edu. Reprints not available from the author /10/ $36.00/0 doi: /j.apmr Conclusions: Nonsomatic symptoms are better predictors of future depressive symptoms when first assessed during inpatient rehabilitation, whereas somatic symptoms become stable predictors only after inpatient rehabilitation. Selfharm (suicidal ideation) is the most stable symptom over time. Clinicians should routinely assess for suicidal ideation and use nonsomatic symptoms when performing assessments during inpatient rehabilitation. Key Words: Depression; Rehabilitation; Spinal cord injuries by the American Congress of Rehabilitation Medicine SPINAL CORD INJURY IS associated with increased prevalence of depressive disorders and has been associated with poor outcomes in several areas, including diminished participation and lower quality of life. 1-8 However, a complicating factor is that diagnostic criteria for major depression include somatic symptoms (eg, sleep disturbance, appetite change). These symptoms could reflect either a condition related to the onset of SCI or the effects of hospitalization itself. Therefore, the presence of SCI may obscure the diagnosis of depression, interpretation of measures intended to assess depressive symptoms, and identification of the natural course of depressive symptoms after the onset of SCI. Recent studies have assessed the factor structure of depressive symptoms after SCI using the PHQ-9, 9 a 9-item self-report measure based on the DSM-IV 10 criteria for major depression, in order to determine whether the factor structure is unidimensional, as would be suggested by the DSM-IV. Most of these studies have suggested that a 2-factor structure, differentiating somatic and nonsomatic symptoms, is typical among participants with SCI. For instance, Richardson and Richards 11 performed EFA of the PHQ-9 data from the SCIMS in the United States. They performed separate analyses for each follow-up year, beginning with year 1. Additional analyses were conducted at 5 years, 15 years, and 25 years. A 2-factor solution best fit the data on each occasion, although the specific pattern of loadings was not consistent across the times of measurement. Three items consistently loaded with a nonsomatic factor (depressed mood, feeling bad about self, self-harm), and an- CFA DSM-IV EFA PHQ-9 RMSEA SCI NS SCIMS List of Abbreviations confirmatory factor analysis Diagnostic and Statistical Manual, 4th edition exploratory factor analysis Patient Health Questionnaire-9 root mean square error of approximation spinal cord injury nonsignificant Spinal Cord Injury Model Systems

2 DEPRESSIVE SYMPTOMS AFTER SPINAL CORD INJURY, Krause 1219 other 3 items consistently loaded with the somatic factor (sleep disturbance, appetite change, fatigue). However, the remaining items did not load with either factor. Both factors were negatively correlated with life satisfaction. Also using EFA, Kalpakjian et al 12 examined the factor structure of the PHQ-9 across sex. After randomly splitting the sample, they found both 1-factor and 2-factor models as acceptable solutions. For the combined sample and for men, congruence was high; however, for women, congruence was variable, leading the authors to suggest that women and men may experience or interpret certain symptoms differently. The authors concluded the 1-factor solution represented a better fit because of sex congruence. 12 Whereas the previous studies used EFA, CFA is more appropriate for evaluating a hypothesized structure. Graves and Bombardier 13 used CFA to verify the presence of a single factor and concluded it was a fair fit based on the RMSEA of.091. However, they tested only a single unidimensional model and used a liberal rule-of-thumb of.10 for the RMSEA (an RMSEA of less than.05 indicates excellent fit, is acceptable, and.08 or higher is a poor fit). 14 Krause et al 15 compared 4 alternative structures of the PHQ-9 using CFA among participants during their initial inpatient rehabilitation. The model that produced the best fit had 3 somatic items (sleep disturbance, fatigue, appetite change) and 6 nonsomatic items. Because the 3 somatic items also had the highest endorsement rates, concerns were raised that the high endorsement rates and the distinct factor may reflect hospitalization or the symptoms of SCI rather than depressive symptomatology. If indeed the endorsement of somatic items was compromised by the presence of SCI, then screening of potential depressive disorders would also be compromised. Inpatient rehabilitation is the time when somatic concerns may be greatest, given the recency of SCI and the additional consequences of the hospitalization. The factor structure of the PHQ-9 has also been evaluated in other populations. Using a sample of 5053 primary care patients, Huang et al 16 examined the utility of the PHQ-9 across racially and ethnically diverse groups. EFA resulted in a single 9-item factor that held across 4 racial/ethnic groups: non- Hispanic white, black, Chinese American, and Latino. The authors concluded that, because it is based on DSM-IV criteria, the PHQ-9 is an effective screening tool for depression among diverse populations. A single factor was found by Cameron et al 17 when comparing the psychometric properties of the PHQ-9 with those of the Hospital Anxiety and Depression Scale in a study of 1063 primary care patients. Dum et al 18 also found a single factor for the PHQ-9 using a sample of 108 substance abusers. Both studies concluded the PHQ-9 demonstrated good internal consistency, reliability, convergent validity, and strong factor structure. A longitudinal study 19 of the natural course of depressive symptoms over about 17 months postinjury indicated that the nonsomatic latent factor observed during inpatient hospitalization was highly predictive of both nonsomatic and somatic factors on follow-up. However, the somatic latent factor during inpatient rehabilitation was not significantly related to either somatic or nonsomatic factors at follow-up. Furthermore, other changes were observed between inpatient hospitalization and follow-up, including the tendency for more participants to gravitate toward higher or lower extremes in terms of total symptoms (ie, fewer participants with intermediate scores). When comparing changes in endorsement rates over time, somatic items were also endorsed significantly less on followup. Taken together, these findings question the utility of somatic items and the somatic factor in predicting future depressive symptoms when first measured during inpatient hospitalization. However, these findings do not address stability or efficacy of the somatic factor in predicting future depressive symptoms when first measured after the inpatient rehabilitation hospitalization. Purpose Our purpose was to investigate the factor structure and predictive validity of somatic and nonsomatic depressive symptoms over the first 2.5 years after SCI using the PHQ-9. We identified the stability of symptoms first measured at baseline during inpatient hospitalization with future symptoms an average of about 29 months postinjury using structural equation modeling. This study builds on 2 earlier stages of data collection (summarized in the literature review) including baseline data collection during inpatient rehabilitation, in which the factor structure of the PHQ-9 was first established, 15 and an analysis of the natural course of depressive symptoms between inpatient baseline and follow-up approximately 17 months after SCI. 19 In the current study, we identified (1) the extent to which somatic and nonsomatic latent factors observed during inpatient rehabilitation were predictive of similar factors at followup, (2) the stability of the latent factor structure itself, (3) the extent to which the presence of a particular symptom during inpatient rehabilitation was predictive of endorsement of the same symptom at follow-up, and (4) changes in the overall endorsement rates of symptoms over time. This extends existing research (limited to the first year and a half postinjury) 19 by identifying the stability of symptoms over an extended period of follow-up. Additional item analyses were conducted over each of 3 times of assessment. Research Hypotheses The hypotheses are derived from previous research. This study builds on previous data collection, with baseline observations obtained during inpatient rehabilitation, and the first follow-up an average of 17 months postinjury. The second follow-up, on which the current study is based, was conducted an average of 29 months postinjury. 1. The factor structure of the PHQ-9 during inpatient baseline will be different from that observed during follow-up. 2. A latent factor composed of 6 nonsomatic symptoms measured during inpatient baseline will be significantly predictive of both nonsomatic and somatic latent factors at follow-up. 3. A second latent factor composed of 3 somatic items measured during inpatient baseline will not be significantly related to either the somatic and nonsomatic factor measured at 29 months postinjury. 4. The nonsomatic latent factor measured at first follow-up (approximately 17 months postinjury) will be predictive of both nonsomatic and somatic latent factors at second follow-up (29 months postinjury). 5. The somatic latent factor measured at first follow-up (approximately 17 months postinjury) will be significantly predictive of both somatic and nonsomatic factors measured at second follow-up (29 months postinjury). 6. Item analysis will indicate declines in the endorsement rate of the 3 somatic items composing the latent factor. (No hypothesis is forwarded about endorsement rates of nonsomatic items). The first hypothesis of a different latent factor structure from that observed during inpatient rehabilitation 15 is based on preliminary studies identifying different structures at different times postinjury, with each change appearing as early as 1 year

3 1220 DEPRESSIVE SYMPTOMS AFTER SPINAL CORD INJURY, Krause after the onset of SCI The remaining hypotheses are based on the preliminary study of changes in depressive symptoms between inpatient rehabilitation and approximately 17 months postinjury. 19 In the absence of evidence to the contrary, the working hypothesis remains that somatic content is a poor predictor of future depressive symptoms, even when first measured 17 months postinjury. METHODS Participants Participants were recruited from the inpatient census of a specialty hospital in the Southeastern United States between December 2001 and June Subsequent follow-ups were conducted on 2 occasions. The first was initiated via mailed survey about 12 months after discharge (responses were an average of 17 months postinjury), and the second an average of 29 months postinjury. At the time of enrollment, all participants had traumatic SCI, were currently hospitalized for initial rehabilitation, and were at least 16 years of age. A total of 584 completed the research materials prior to discharge (82.6% of those who were consented). The median number of days between the onset of SCI and time of interview was 50. Procedures The preliminary contact with participants was made by the peer support coordinator who meets with all newly injured patients early during the inpatient hospitalization. At the time of the first meeting, the peer supporter described the study and obtained informed consent. An appointment was then made with a staff member who brought the actual materials and either left them for the participant to complete or assisted the participant in completing the materials (as needed). Participants received $25 remuneration for completing the materials. Assessments were completed an average of 50 days after SCI (range, 2 153). Two subsequent follow-up assessments were conducted, both via mailed survey. The first was initiated 12 months after discharge and responses were received at an average of 17 months (an average of 498 days; range, ). Preliminary findings from the inpatient baseline assessment and the first follow-up have been reported elsewhere. 15,19 In the first follow-up, materials were sent to participants just after the first anniversary of their discharge from inpatient rehabilitation. The packet of materials included a cover letter describing the study and a follow-up questionnaire. Nonrespondents received a follow-up call answering questions and encouraging them to participate. Participants were again offered $25 remuneration. Not all participants were contacted for the first follow-up. A total of 410 of the 584 participants were asked to participate in the first follow-up. A total of 377 of the 410 cases received both a follow-up mailing and phone call because of time restrictions and termination of the funding cycle. Of these, 227 participants returned completed materials (55%). The current (or second) follow-up was an average of 12 months after the first follow-up at 29 months postinjury (an average of 874 days; range, ) and coincided with the second anniversary of SCI. We followed the typical data collection standards within the SCIMS by allowing a 6-month window of data collection prior to the second anniversary (ie, data collection was implemented as early as 18 months postinjury). Those cases with less than a 100-day interval between follow-ups were eliminated. All participants who completed the original inpatient baseline assessment were sent materials during the second follow-up (rather than only the subset of 410 for whom participation was elicited during the first follow-up). There were 316 respondents (an overall response rate 54%). However, after the data collection and for the purpose of this article, we eliminated 14 persons from the total for 1 or more of the following: their inpatient baseline response was not within 6 months of SCI onset, they reported a complete recovery, or the interval between follow-ups was less than 100 days. Measures The PHQ-9 9 is a 9-item screening tool of depressive symptoms. Each of the 9 items corresponds to a symptom of major depressive disorder based on DSM-IV criteria. 10 The format requires those completing the instrument to identify how each symptom has been a problem over the past 2 weeks. There are 4 response options: (1) not at all, (2) several days, (3) more than half the days, or (4) nearly every day. The PHQ-9 is both reliable and valid as a brief measure of depression. Kroenke et al 9 found.89 internal consistency and.84 test-retest reliability. Data Analysis SPSS a was used to generate descriptive statistics to summarize the characteristics of the participants and to identify the extent to which selective attrition may have affected the results. Specifically, we classified participants into 2 groups based on their response status at the most recent follow-up and then compared respondents and nonrespondents on biographic and injury characteristics. The chi-square statistic was used for categoric variables, such as sex or race-ethnicity, and a t test was used for continuous variables, such as age. We used Mplus, 20 specialized software for a wide range of structural equation models, to conduct a combination of factor analysis and time-lagged regression analysis. Mplus was selected because it offers a diverse selection of models, estimators, and algorithms and has explicit features for missing data, complex survey data, and multilevel data. It allows for estimation of parameters in the presence of missing data using the assumption of missing at random. The missing at random assumption applies only to variables not incorporated in the analysis (ie, the pattern of responses to the items accounted for in the analysis). We used the previously reported factor analysis identified during inpatient hospitalization in order to quantify somatic and nonsomatic latent factor scores dimensions. 15 We performed a CFA of the structure obtained during inpatient hospitalization using maximum likelihood. Based on these results, we also conducted an EFA of the data during the second follow-up to identify whether an alternative structure better fit the data, and we added similar EFA for the inpatient baseline and first follow-up. The RMSEA was used to evaluate model fit with both CFA and EFA. The RMSEA is a function of N, the chi-square, and the degrees of freedom and is determined by the discrepancy per degrees of freedom and corrects for model complexity. RMSEA of less than.05 represents an excellent fit, with less than.08 representing acceptable fit, and.08 or higher is a poor fit. 14 We added EFA from the first 2 assessments, inpatient baseline, and the first follow-up in order to present direct comparisons. We then performed time-lagged regression analyses. For this analysis, we generated each dimension with 3 somatic items composing 1 factor (sleep disturbance, appetite change, fatigue) and the other 6 items composing the nonsomatic factor (the factor structure observed during inpatient rehabilitation). Scores were generated in this manner for inpatient baseline and for each of the 2 follow-ups. The first regression analysis regressed latent factors from the second follow-up on inpatient baseline scores. The second regression analysis regressed latent factor scores from the

4 DEPRESSIVE SYMPTOMS AFTER SPINAL CORD INJURY, Krause 1221 second follow-up on the same factors obtained during the first follow-up. Because regression of the first follow-up scores on inpatient baseline scores has already been reported in the literature, we did not repeat this analysis. 19 Standardized regression coefficients are reported for each comparison. We also conducted item analysis by repeating the regression analysis for each item. As with the latent factors, we first regressed the most recent follow-up scores on inpatient baseline and then regressed the most recent follow-up scores on those obtained during the first follow-up. In the final analysis, we used SPSS to identify changes in portion of people endorsing each of the 9 items. We first dichotomized items based on whether the individual reported the symptom on at least half of the days. The 1 exception was for self-harm, because we dichotomized based on whether the individual reported the symptom on any days. We then used the chi-square statistic with the McNemar tests to identify changes between inpatient baseline and the second follow-up (changes in item responses between inpatient baseline and first follow-up have been reported elsewhere). 19 RESULTS Participant Characteristics At the time of follow-up, 75.7% of the participants were white, non-hispanic; 72.8% were men (table 1). The average age at onset was 32.7 years. Nearly half of the participants (48%) had cervical injuries. The primary etiology of injury was motor vehicle collision (54.3%), followed by falls/falling objects (16.6%), sporting injuries (12.9%), and acts of violence (7.9%) The average number of years of education was Table 1: Participant Characteristics at Each Time of Measurement Variables Baseline 1st Follow-Up 2nd Follow-Up (N 584) (n 227) (n 316) Mean SD Mean SD Mean SD Age at injury (y) Age at survey (y) Days since injury Years of education ND % % % Sex Male Female Race White Nonwhite Injury level Cervical Thoracic Lumbar Sacral Etiology Motor vehicle Fall/flying object Sporting Violence Medical/surgical Other NOTE. Sample sizes reflect all available cases. Values are mean SD or percentages. Abbreviation: ND, no data. Sex, race-ethnicity, and years of education were significantly related to differential response, whereas age, years since injury, injury severity, and etiology of SCI were not. Whereas only 50.2% of men participated at the most recent follow-up, 70.8% of women did so. In terms of race-ethnicity, 57.3% of white subjects participated at the follow-up, compared with 44% for nonwhite subjects. The average number of years of education of participants (12.8y) was higher than that of nonparticipants (12.4y). Factor Analysis (Hypothesis 1) The CFA using the latent factors observed at inpatient baseline with 6 nonsomatic and 3 somatic items resulted in an unacceptable model fit (RMSEA.110). Therefore, we ran an EFA and reported this for each of the 3 times of measurement (inpatient baseline, follow-up 1, follow-up 2). The solution with 2 factors produced an acceptable fit, with an RMSEA of.074. Table 2 summarizes the rotated loadings (those from inpatient baseline and the first follow-up are reported in table 2 for comparison). For the second follow-up, 5 items loaded with the first factor, including the 3 somatic items that composed the unique factor during inpatient rehabilitation (sleep disturbance, appetite change, fatigue). The other 2 items loading with the first factor were loss of interest and difficulty concentrating. The second factor was composed of 3 items: depressed mood, feeling bad about self, and self-harm. Psychomotor disturbance did not clearly fit with either factor. This pattern is different than those observed during inpatient baseline and the first follow-up (previously reported in the literature). 15,19 Regression (Hypotheses 2 5) Figure 1 summarizes the model regressing nonsomatic and somatic latent scores from the second follow-up on inpatient baseline latent scores. The nonsomatic factor at inpatient baseline was significantly related to both the nonsomatic (.40; P.000) and somatic factors (.29; P.006) at follow-up. In contrast, the somatic factor during inpatient baseline was not significantly related to either the somatic (.07; NS) or nonsomatic (.01; NS) factors at follow-up. Both latent factors were significantly correlated at follow-up (.34; P.000). We also regressed latent scores during the second follow-up on those from the first follow-up (fig 2). The nonsomatic factor at the first follow-up was predictive of the nonsomatic factor during the second follow-up ( 0.66; P.000); however, it was not predictive of the somatic factor (.09; NS). The somatic factor during the first follow-up was significantly predictive of the somatic factor at the second follow-up (.66; P.000) but not significantly predictive of the nonsomatic factor (.10; NS). The coefficient between the 2 latent factors at follow-up was.11 (P.000). Table 3 summarizes the strength of the prediction across items, which varies between the 3 times of measurement. The coefficients from inpatient baseline to the first follow-up ranged from.16 to.51, with an average coefficient of.27. The coefficients between inpatient baseline and the second follow-up were smaller, ranging between.09 and.44. The average coefficient was.23, or a drop of about.04 over the additional time between the 2 follow-ups. Whereas all the coefficients were significant between inpatient baseline and the first followup, 8 of the 9 coefficients were significant between inpatient baseline and the second follow-up. By far the highest coefficients were between the first and second follow-up, with a range of.31 to.70 and an average coefficient of.55. Self-harm was the symptom with the strongest association over time. Other items with coefficients exceeding.20 for regression equations between inpatient baseline and each follow-up included

5 1222 DEPRESSIVE SYMPTOMS AFTER SPINAL CORD INJURY, Krause Table 2: Factor Loadings at Baseline, First Follow-Up, and Second Follow-Up PHQ-9 Item Baseline 1st Follow-Up 2nd Follow-Up (n 554) (RMSEA 0.07) (n 211) (RMSEA 0.09) (n 302) (RMSEA 0.08) Loss of interest (anhedonia) 0.37* * * 0.29 Depressed mood 0.66* * * Sleep disturbance * * 0.90* 0.16 Fatigue * * 0.75* 0.01 Appetite change * * 0.65* 0.10 Feeling bad about self 0.84* * * Difficulty concentrating 0.50* * 0.42* 0.27 Psychomotor disturbance 0.36* * 0.34* 0.26 Self harm 0.53* * * *Items that loaded with each factor. depressed mood, feeling bad about self, and difficulty concentrating. Items with the lowest coefficients between inpatient baseline and the first follow-up included psychomotor disturbance, fatigue, loss of interest, and appetite change. These symptoms also had the lowest coefficients between inpatient baseline and second followup, with the coefficient for sleep disturbance nonsignificant. The coefficients for loss of interest, appetite change, psychomotor disturbance, and fatigue were all.18 or less. The coefficients between the first and second follow-ups were much higher overall, with the highest again for self-harm (.70) and the lowest for psychomotor disturbance (.31). Although the 3 somatic items composing the latent factor used in the previous analysis (sleep disturbance, appetite change, fatigue) had relatively low coefficients between inpatient baseline and the first follow-up (.17.22) and inpatient baseline and the second follow-up (.09.17), the coefficients between the first and second follow-ups were substantially higher (.58.67), and the average coefficient for these 3 items (.61) was higher than the average coefficient for the other 6 (.51). Symptom Endorsement (Hypothesis 6) Table 4 summarizes the item endorsement percentages between inpatient baseline and the second follow-up. Of the 9 symptoms, the percentage of participants endorsing appetite change decreased, and the portion endorsing feeling bad about self increased between inpatient baseline and the second follow-up. The other 7 symptoms did not significantly change in terms of portion of endorsement. None of the endorsement rates changed between inpatient baseline and the second follow-up. DISCUSSION The study findings help clarify the natural course of depressive symptoms beginning from baseline at inpatient hospitalization and continuing through 29 months postinjury, well after the individual has returned to the community. Consistent with previous research, there is considerable instability in depressive symptoms over the 29 months, 19 as indicated by lack of factor stability over time and the pattern of regression coefficients between latent factors over time. The first hypothesis was confirmed because we were unable to validate the factor structure first identified during inpatient rehabilitation, with a distinctive somatic factor consisting of the following 3 items: sleep disturbance, appetite change, and fatigue. This is not surprising, because the factor structure during the first follow-up (psychomotor retardation and difficulty concentrating loading with sleep disturbance, appetite change, and fatigue) 19 also differed from that observed during inpatient rehabilitation, and other research has identified differing factor structures. 11 However, the factor structure observed during the current follow-up was different from any of those previously noted by Richardson and Richards. 11 The EFA conducted from responses to the second follow-up had some striking differences from that of the other times of measurement. Although the same 3 items (sleep Fig 1. Model regressing second follow-up somatic and nonsomatic latent scores on baseline latent scores. (Standardized regression coefficients, n 553). Abbreviations: N_B, nonsomatic factor at inpatient baseline; N_2 nonsomatic factor at 2nd follow-up; S_B, somatic factor at inpatient baseline; S_2, somatic factor at 2nd follow-up. Fig 2. Model regressing second follow-up somatic and nonsomatic latent scores on first follow-up latent scores. (Standardized regression coefficients, n 364.) Abbreviations: N_1, nonsomatic factor at 1st follow-up; N_2 nonsomatic factor at 2nd follow-up; S_1, somatic factor at 1st follow-up; S_2, somatic factor at 2nd follow-up.

6 DEPRESSIVE SYMPTOMS AFTER SPINAL CORD INJURY, Krause 1223 Table 3: Time-Lag Regression of Each PHQ-9 Item Across Itself at Each Time of Measurement PHQ-9 Item Baseline 1st Follow-Up Baseline 2nd Follow-Up 1st Follow-Up 2nd Follow-Up Difference High-Low Loss of interest (anhedonia).17*.12* Depressed mood Sleep disturbance.22.09, NS Fatigue Appetite change Feeling bad about self Difficulty concentrating Psychomotor disturbance.16* Self-harm NOTE. Standardized regression coefficients are shown (n 562). *P.05; P.01; P.001. disturbance, appetite change, fatigue) continued to load together along with a fourth item (difficulty concentrating), consistent with somatic complaints, loss of interest also loaded with this factor. Observing this, many changes to the factor structure over time, using the same participants, is of concern. This concern is heightened because the factor structure during the second follow-up differed from all those previously reported in the literature, including that reported by Richardson and Richards, 11 who did a cross-sectional study at 4 different points in time using data from the National SCI Statistical Center. Therefore, this study adds to the body of literature that indicates a highly variable factor structure of depressive symptoms after SCI onset, at least using the PHQ-9. Because this instrument is based on DSM-IV diagnostic criteria, one might question whether the changing nature of the factor structure relates to the depressive symptoms themselves. Hypotheses 2 and 3 were confirmed. The nonsomatic latent factor, measured during inpatient rehabilitation, was significantly predictive of both somatic and nonsomatic latent factors during the second follow-up, whereas the somatic latent factor was not predictive of either somatic or nonsomatic factors at the second follow-up. This is further evidence that the somatic latent factor identified during inpatient rehabilitation is not particularly helpful in predicting depressive symptoms after hospital discharge. Furthermore, there is ambiguity over the meaning of the symptoms composing this factor and the extent to which they reflect true depressive symptomatology during inpatient rehabilitation. These symptoms could also be in response to the SCI and hospitalization. Nonsomatic symptoms first identified during inpatient rehabilitation, particularly self-harm, do predict future depressive Table 4: Changes in Endorsement Rates Between Baseline and the Second Follow-Up Among Those Responding on Both Occasions PHQ-9 Item Baseline Percent 2nd Follow-up Percent McNemar Test Loss of interest (anhedonia) Depressed mood Sleep disturbance Fatigue Appetite change Feeling bad about self Difficulty concentrating Psychomotor disturbance Self-harm NOTE. The McNemar test is between baseline and the second follow-up (n 302). Self-harm is based on endorsement during any number of days, whereas the other symptoms are based on endorsement on at least half of the days. symptoms. The presence of self-harm at any point in time should be taken very seriously, not only for the present evaluation but also for the long-term implications. In contrast, neither hypotheses 4 or 5 were confirmed. Rather than the nonsomatic factor at the first follow-up predicting both latent factors at the second follow-up, each latent factor predicted future status on the same factor. In essence, the somatic factor, when measured during the first follow-up, was a strong predictor of future scores on the somatic factor. This suggests that somatic symptoms may become more meaningful when first obtained more than a year after discharge from the inpatient rehabilitation. Furthermore, the hospitalization itself or the recency of the SCI, rather than the long-term physiologic sequelae of SCI, appears to be the primary factor in the failure of the latent somatic factor obtained during inpatient rehabilitation to predict any future depressive symptoms. If so, then the PHQ-9 is more appropriate when used after the inpatient rehabilitation. The item analysis supports the conclusions drawn from the analysis of latent factors in that somatic symptoms first taken during inpatient rehabilitation (the 3 that composed the inpatient somatic factor) were not highly predictive of the same symptom during either follow-up. Analysis of the other items provides insight about the importance of the other symptoms during inpatient rehabilitation and beyond. Of the 2 cardinal symptoms of a depressive order, as outlined in the DSM-IV, 10 depressed mood tended to be one of the better predictors across time (.30 from inpatient to the second follow-up) and had a relatively low range between coefficients (.30.53). Therefore, it is a symptom that tends to be stable over time and perhaps less affected by the SCI or hospitalization. On the other hand, loss of interest was a poor predictor when first measured during inpatient rehabilitation and was minimally related to loss of interest during the second follow-up. This is not to say it is not a valid indicator of a depressive disorder during inpatient rehabilitation (the findings are not definitive), but it is not likely to be a good predictor of future depressive disorders. The 2 other symptoms, self-harm and feeling bad about self, were both good predictors from inpatient baseline to the follow-ups. Although this is helpful in terms of predicting future outcomes based on responses during inpatient rehabilitation, it must be of grave concern to rehabilitation psychologists. One would hope that thoughts of self-harm would diminish after the inpatient rehabilitation, yet the strength of coefficients suggests that the same persons who present at risk during inpatient rehabilitation are more likely to be at risk at follow-up even 29 months postinjury. Even more dramatic findings were observed between the 2 follow-ups, because the coefficient for self-harm was.70. This suggests that the observance of self-harm should be taken very seriously, not only for its importance at a given point in time but also because it may be a chronic indicator of future risk.

7 1224 DEPRESSIVE SYMPTOMS AFTER SPINAL CORD INJURY, Krause Hypothesis 6 received minimal support, because only 1 of the 3 somatic items (appetite change) witnessed a decline in endorsement rates between inpatient baseline and the second follow-up. Therefore, the latent somatic factor was of questionable validity in predicting future somatic symptoms even though the overall endorsement of somatic items between inpatient baseline and the second follow-up indicated only limited change. Taken together, the findings suggest that somatic items may be misinterpreted during inpatient rehabilitation as part of a depressive disorder when they may not be, and that they may not be cause for alarm in and of themselves. On the other hand, other symptoms of a depressive disorder, particularly self-harm, must be taken very seriously. They not only may be indicative of a depressive disorder at the time but also are highly predictive of similar future issues. In short, these symptoms are likely to persist. Study Limitations There are several study limitations. First, the data are limited to self-report. It would be interesting to have external data that could be used to differentiate further the extent to which depressive symptoms during inpatient rehabilitation are associated with other important outcomes or independent diagnostic assessments. Second, we used only a single measure of depressive symptoms. There is no guarantee that other measures would have the same results, and there have not been many studies using other measures. This limitation relates, in part, to use of the PHQ-9 as the criterion standard for SCI and its incorporation into the SCIMS data collection, which has been widely used in studies of depression and SCI Third, we do not have data on the extent to which participants were receiving treatment for depression. Any pattern of medication could affect the extent to which participants report somatic symptoms. Fourth, we do not have data on additional associated conditions that could be affecting responses to the PHQ-9. For instance, we cannot determine whether additional complications could be triggering sleep disturbance, fatigue, appetite change, or other symptoms. Last, there is a substantial amount of attrition, as is the case with all longitudinal studies. Because women, white subjects, and those with more education were more likely to remain in the study, there is less potential for bias among these groups. Future Research Additional research is needed that continues to unravel the natural course of depression after the onset of SCI. Identifying differential changes in symptoms over time as a function of biographic and injury characteristics would help to identify the generalizability of the findings. This research should seek to identify appropriate instruments to measure depressive symptoms, including during inpatient hospitalization, or to provide alternative scoring strategies that maximize fluidity. Whereas the current study was restricted to a single measure of depression, future research would benefit from use of alternative measures. Investigators must challenge and go beyond data available through the SCIMS alone and collect additional types of data relevant to the measurement, diagnosis, and natural course of depression. Additional research is needed beyond the length of the current follow-up. It is also important for future research to identify other factors related to postdischarge depression scores in order to help us better understand the natural course of depression and to implement preventative measures as early as possible. CONCLUSIONS The factor structure of the PHQ-9 shifts over time. Somatic symptoms during inpatient rehabilitation tend to be poor predictors of future depressive symptoms, making them unreliable diagnostically when used shortly after SCI. The results suggest that the PHQ-9 should be used cautiously during inpatient rehabilitation, avoiding overreliance on somatic items. However, the PHQ-9 is more valid when first measured well after the inpatient hospitalization. Regardless of the time of measurement, reports of self-harm should be taken very seriously, because they are likely to be stable over time. References 1. Dryden DM, Saunders LD, Rowe BH, et al. Depression following traumatic spinal cord injury. Neuroepidemiology 2005;25: Price GL, Kendall M, Amsters DI, Pershouse KJ. Perceived causes of change in function and quality of life for people with long duration spinal cord injury. Clin Rehabil 2004;18: Tate DG, Kalpakjian CZ, Forchheimer MB. Quality of life issues in individuals with spinal cord injury. Arch Phys Med Rehabil 2002;83(12 Suppl 2):S Charlifue S, Gerhart K. Community integration in spinal cord injury of long duration. NeuroRehabilitation 2004;19: Elliott TR, Frank RG. Depression following spinal cord injury. Arch Phys Med Rehabil 1996;77: Fuhrer MJ, Rintala DH, Hart KA, Clearman R, Young ME. Depressive symptomatology in persons with spinal cord injury who reside in the community. Arch Phys Med Rehabil 1993;74: Krause JS. Dimensions of subjective well-being after spinal cord injury: an empirical analysis by gender and race/ethnicity. Arch Phys Med Rehabil 1998;79: Krause JS, Rohe DE. Personality and life adjustment after spinal cord injury: an exploratory study. Rehabil Psychol 1998;43: Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med 2001;16: APA. Diagnostic and statistical manual of mental disorders. 4th ed. Washington (DC): American Psychiatric Association; Richardson EJ, Richards JS. Factor structure of the PHQ-9 screen for depression across time since injury among persons with spinal cord injury. Rehabil Psychol 2008;53: Kalpakjian CZ, Toussaint LL, Albright KJ, Bombardier CH, Krause JK, Tate DG. Patient health Questionnaire-9 in spinal cord injury: an examination of factor structure as related to gender. J Spinal Cord Med 2009;32: Graves DE, Bombardier CH. Improving the efficiency of screening for major depression in people with spinal cord injury. J Spinal Cord Med 2008;31: Browne M, Cudeck R. Alternative ways of assessing model fit. In: Bollen K, Long S, editors. Testing structural equation models. Beverly Hills: Sage; p Krause JS, Bombardier CH, Carter RE. Assessment of depressive symptoms during inpatient rehabilitation for spinal cord injury: is there an underlying somatic factor when using the PHQ? Rehabil Psychol 2008;53: Huang FY, Chung H, Kroenke K, Delucchi KL, Spitzer RL. Using the Patient Health Questionnaire-9 to measure depression among racially and ethnically diverse primary care patients. J Gen Intern Med 2006;21: Cameron IM, Crawford JR, Lawton K, Reid IC. Psychometric comparison of PHQ-9 and HADS for measuring depression severity in primary care. Br J Gen Pract 2008;58: Dum M, Pickren J, Sobell LC, Sobell MB. Comparing the BDI-II and the PHQ-9 with outpatient substance abusers. Addict Behav 2008;33: Krause JS, Reed KS, McArdle JJ. Prediction of somatic and nonsomatic depressive symptoms between inpatient rehabilitation and follow-up. Spinal Cord. E-pub ahead of print: doi: /sc Muthén L, Muthén B. Mplus, the comprehensive modeling program for applied researchers: user s guide. 4th ed. Los Angeles: Muthen & Muthen; Supplier a. SPSS Inc, 233 S Wacker Dr, 11th Fl, Chicago, IL