Complementary and alternative medicine (CAM) use in the United States (US) has increased over the last 2 decades in civilian1 and Veteran2 populations. A greater focus in the literature has been on civilian use of CAM. In the few Veteran-focused studies, it has been found that 23% to 50% of Veterans utilize CAM, which is comparable with civilian use.3–5 Research has found that a majority of Veterans not currently using CAM would be open to seeking alternative treatments6 and 40% would use additional CAM therapies7 if they were offered in Veterans Health Administration (VHA) settings.
One approach to understanding Veterans’ use and acceptability of CAM is to explore their attitudes and beliefs toward CAM. Attitudes influence an individual’s decisions and behaviors, which is particularly important in making health care decisions. In response to the absence of a comprehensive tool, one of the authors (T.D.H.) assisted in the development and testing of a measure named the Complementary, Alternative, and Conventional Medicine Attitudes Scale (CACMAS8). Prior literature has focused on medical providers’ attitudes and beliefs toward CAM,9–13 with little research on patients’ attitudes and beliefs. Most of the latter studies have been conducted outside the US,14–16 with limited sets of questions, and/or focus on populations with particular illnesses (eg, cancer). The initial study with the CACMAS8 was conducted with civilian graduate students and identified 3 factors: dissatisfaction with conventional medicine; philosophical congruence with CAM; and holistic balance. Endorsement of these factors was positively correlated with CAM use. Research exploring Veterans’ attitudes and beliefs toward CAM has been limited. A qualitative study on Veterans’ perceptions of the conventional medical care system suggested that Veterans desired a more holistic approach to health care.17 According to Veteran participants who completed a national survey, CAM use may align with their personal philosophy and lifestyle.5
Civilians have endorsed the use of CAM therapies to treat illnesses and symptoms associated with stress, depression, and anxiety.18 Other motivating factors for utilization include health conditions for which evidence-based treatments provide limited relief from chronic symptoms such as pain, allergies, fatigue, and arthritis.19–21 Reasons for CAM use in civilian populations include: dissatisfaction with conventional medical care, perhaps as a result of side effects of prescription medications22,23; and poor communication and/or limited time with medical doctors.24–26 In military populations, CAM use has been associated with high daily stress and negative perceptions of military life on physical and mental health,2 chronic illnesses, and/or higher frequency of medical conditions and symptoms,4,5 as well as a desire for alternatives to prescription medication.
As the literature has shown, Veteran populations are using CAM at increasing rates to treat a variety of conditions. Although this mirrors findings in civilian samples, it is notable that Veterans often report higher rates of physical and mental health conditions after transitioning out of active duty. Some of the “signature wounds” reported by Veterans returning from the recent conflicts include posttraumatic stress disorder (PTSD) and traumatic brain injury (TBI).27 These conditions are associated with chronic symptoms, negative health consequences, such as self-directed violence (SDV), and other negative psychiatric outcomes.27,28 Whereas some Veterans may be satisfied with conventional services for conditions such as PTSD and TBI, other Veterans have found their symptoms to be resistant to conventional therapies (eg, psychotherapy for PTSD).29 Furthermore, a notable proportion of individuals are not significantly helped by traditional treatments. In exploring nonresponse and dropout rates in outcome studies for PTSD, Schottenbauer et al30 reported both that dropout rates widely vary (0%–50%) and that it was not unusual to find nonresponse rates as high as 50%. CAM therapies may be acceptable to Veterans as alternative approaches to managing these chronic conditions. That is, increasing understanding of attitudes and beliefs about CAM may aid in the identification of treatment options for Veterans with these highly prevalent chronic conditions.27
The purpose of the present exploratory study was to: (1) determine CACMAS factors in a Veteran sample; (2) describe their attitudes and beliefs towards CAM; (3) identify associations of the attitudes and beliefs with conditions of interest (eg, history of TBI, PTSD, and history of SDV); and (4) describe patterns of CAM use.
MATERIALS AND METHODS
Participants were 97 Veterans seeking health care at a Mountain State Veterans Affairs Medical Center. All participants completed informed consent procedures, and the study was approved by the local Institutional Review Board. Veteran participants were recruited using study flyers posted throughout the Veterans Affairs Medical Center or referred from other research study staff and mental health providers. Participants were included if they were 18–89 years of age and were able to answer informed consent comprehension questions.
After completing an in-person or telephone screening, eligible participants provided informed consent and completed clinical interviews and self-report measures.
Demographic Questionnaire: Demographic and military data were obtained through interview format and included sex, race/ethnicity, education, income, branch of service, service component, military pay grade, deployment information, and current medications/supplements.
CACMAS8: The CACMAS includes 27 items and is designed to assess attitudes and beliefs about conventional and CAM approaches to care. A full description of the CACMAS can be found in a recent paper by McFadden et al.8 Items are rated on a 7-point Likert scale, ranging from 1 (strongly disagree) to 7 (strongly agree). Sample questions include “Most complementary therapies stimulate the body’s natural therapeutic powers,” “I believe complementary medicine enables me to take a more active part in maintaining my health,” “I don’t trust medical doctors and hospitals, so I use them as little as possible.”
CAM Use Survey: Participants completed a self-report survey regarding any and all past, present, and future use of 19 specific CAM modalities, and the option to specify any other CAM modalities of interest. This survey was adapted from a larger questionnaire regarding CAM.8 CAM modalities were selected from those identified in published work1,20 as well as those referenced by the National Center for Complementary and Alternative Medicine.31
Ohio State University Traumatic Brain Injury Identification Method (OSU TBI-ID)32: The OSU TBI-ID is a clinician-administered structured interview used to assess self-report of TBI(s) occurring over a person’s lifetime and focuses on: (1) injuries caused by a blow to the head or high velocity forces; (2) altered consciousness; (3) treatment received; and (4) sequelae. The OSU TBI-ID is considered the gold standard interview for TBI diagnosis. Studies using the OSU TBI-ID in populations potentially at risk for TBI have demonstrated test-retest reliability and interrater reliability.32–34 This interview was used to obtain information on the participant’s reported lifetime history of most severe TBI. Categories of TBI severity included no TBI, mild TBI (mTBI; alteration in consciousness or loss of consciousness ≤30 min), and moderate/severe TBI (loss of consciousness of >30 min).33
Lifetime Suicide Attempt Self-Injury Interview (L-SASI)35: The L-SASI was developed as a brief survey of lifetime intentional SDV, including suicide attempts and nonsuicidal acts.35 Characteristics of SDV including method, treatment received, and lethality can also be obtained. Psychometric properties have been established including good interrater reliability and adequate validity.36 The L-SASI was used to gather information regarding the participant’s history of SDV behaviors.
Posttraumatic Stress Disorder Checklist—Civilian (PCL-C)37: The PCL-C is a 17-item self-report measure of PTSD symptoms experienced over the last 30 days. Items on the PCL-C parallel diagnostic criteria for PTSD in the DSM-IV. A 5-point scale is used to rate each item (1=not at all, 5=extremely).The PCL-C has, excellent reliability (α=0.97, test-retest r=0.96) among Vietnam Veterans, and had good sensitivity (0.82) and specificity (0.83) as compared with a diagnosis of PTSD obtained via structured clinical interview.37 There were <10% of items missing from the PCL-C for 8 participants, therefore the total score was included in analyses.38 This study used the total PCL-C score to assess participant’s PTSD symptom severity.
All analyses assumed a 2-sided test of hypothesis, an α level of 0.05 and were conducted using SAS version 9.3.39 Details of the factor analysis are described below and required that all 27 items on the CACMAS be answered, resulting in a factor analysis sample of 80 participants. Coefficient α’s were calculated to assess reliability of the emerging factors. CACMAS factor scores from the full sample were compared between those with a history of SDV and those without using a t test and across lifetime most severe TBI categories using Kruskal-Wallis and Wilcoxon rank-sum tests. Linear regression was used to assess the association between factor scores and PCL-C total scores.
Characteristics of Study Sample
Participant characteristics are presents in Table 1. The sample was primarily male Veterans (86%), with 48% self-identifying as white. Veterans reported an average age of 49.6 years (SD=10.4), with an average of 14.1 years of education (SD=2.0). The majority of the participants were unemployed (64%), and approximately one third had an annual household income of <$10,000. Over half of the sample had served in the Army (56%), 35% had engaged in combat, and 24% had served in support of the conflicts in Iraq and/or Afghanistan. Sixty-nine participants reported mTBI (71%) and 35 reported a history of SDV behavior (36%). Most of the sample reported taking medications (88%) and 32% of the sample reported taking vitamins.
A principal factor analysis with a varimax (orthogonal) rotation of 27 items from the CACMAS measure was conducted on those with complete data. An examination of the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy suggested that the sample was factorable (KMO=0.78). Four factors emerged from an initial analysis of the Eigenvalues that exceeded Kaiser’s criterion of 1, and which explained 81.8% of the variance. Examination of the screen plot also yielded 4 factors. Three investigators (L.M.B., T.D.H., L.A.B.) reviewed the rotated factor loadings and separated items into the 4 factors. All of the items had a loading of at least 0.46 and each factor contained items that theoretically contributed to the identified factor. Three items were excluded from the final factors due to low factor loading (I have a more equal relationship with my complementary practitioner than with my doctor), did not theoretically hang with the other items in the factor (I prefer to deal with health issues myself), or due to both previous reasons (I am often concerned that orthodox medical treatments recommended by my doctor will be associated with negative side effects). A total of 24 items (of 27) were included in the final 4 factors. Results are displayed in Table 2.
Factors Related to Veterans’ Attitudes and Belief Toward CAM
Description of attitude and beliefs based on these factors was examined for the total sample (N=97). The factor scores were calculated by taking the average score of the items in the given factor. If more than half the items in a given factor were missing then the factor score was not calculated.
Acceptability of CAM
The first pattern that emerged, explaining 38.8% of the variance, with 7 items, was acceptability of CAM. This factor represented Veterans’ perspective that CAM is an effective and appropriate treatment approach to maintaining health. High scores indicated acceptability, with a mean score in this sample of 4.2 (1.6). Acceptability of CAM demonstrated a high reliability, α=0.90.
Acceptability of Conventional Medicine
The second factor (8 items) represented acceptability of conventional medicine; that is, Veterans were satisfied with and receptive to conventional medicine. The factor explained 2.9% of the variance. Low scores indicate acceptability of conventional medicine with a mean score of 2.5 (1.3). This factor demonstrated high reliability, α=0.86.
Six items comprised the third factor, mind-body integration. High scores indicated a belief that the mind and body are related and affect holistic health. As such, treatments should address both systems. This factor explained 11.2% of the variance and had a sample mean of 5.2 (1.2). Mind-Body integration demonstrated sufficient reliability, α=0.78.
Belief in CAM
The final factor Belief in CAM (3 items), explained 8.9% of the variance. This factor represented the perspective that CAM treatments were credible and produce a real and desired effect. All the items in this factor are reverse scored, such that high scores are indicative of a belief in CAM and low scores, a nonbelief in CAM. The sample mean was 5.1 (1.2). This factor demonstrated the lowest reliability, α=0.49.
Associations Between 4 Factors and History of SDV, TBI, and PTSD
An exploratory analysis examined the associations between the factors identified above and SDV, TBI, and PTSD symptom severity. There were no significant differences in comparisons of the means across the factors and history of SDV (Table 3). That is, Veterans with a history of SDV did not differ on their attitudes and beliefs toward the acceptability of CAM, acceptability of conventional medicine, mind-body integration, and belief in CAM. Associations between the CACMAS factors and lifetime history of most severe TBI (No TBI, mTBI, and Moderate/Severe TBI) were conducted (Table 3). Participants reporting no history of TBI were significantly different from participants with a history of mTBI on the acceptability of CAM factor (P=0.02). There were no significant differences in the other areas of comparison. Acceptability of CAM was significantly associated with PCL-C total score (t(91)=4.06, P<0.001, R2=0.15) (Table 4). For every 10-unit increase on the PCL-C total score, there is a 0.34 increase in an individual’s acceptability of CAM. There were no significant findings between PCL-C total score and the other factors. However, the association between PCL-C total score and mind-body integration trended towards significant.
Patterns of CAM Use
Of the participants who indicated current use of CAM modalities, they endorsed using spirituality/prayer (39%), meditation/yoga/relaxation/imagery (21%), herbal/botanical supplements (19%), and dietary intervention (19%). Higher frequency for a wider variety of CAM modalities was reported regarding past use, for those who responded. The most frequent past use of CAM included massage (61%), spirituality/prayer (48%), chiropractic services (46%), and meditation/yoga/relaxation/imagery (43%). Given that in the past spirituality/prayer has accounted for a significant proportion of CAM use,1 we also assessed what percentage of CAM use is attributed to spirituality/prayer only. For the 43 Veterans who endorsed current CAM use, 21% (N=9) endorsed using only spirituality/prayer. The majority of these individuals reported they would use CAM modalities in the future if the occasion arose; with particular interest in future use of massage (77%), meditation/yoga/relaxation/imagery (68%), chiropractic care (63%), and acupuncture/acupressure (63%).
In this Veteran sample, 4 CACMAS factors emerged: acceptability of CAM, belief in CAM, belief in a mind-body integration approach to health care, and acceptability of conventional medicine. These findings are supported by previous literature in Veteran samples; that is, Veterans appear to be drawn to alternative services because of a philosophical congruence with CAM,5,17 while continuing to accept and consume conventional medicine.17 These results are comparable with the initial factor analysis of the CACMAS8 with one notable difference. McFadden et al8 found 3 factors (ie, philosophical congruence with CAM, dissatisfaction with traditional medicine, and holistic balance); findings from the current study support 4 factors (ie, acceptability of CAM, acceptability of conventional medicine, mind-body integration, and belief in CAM). Our third factor, mind-body integration, included 3 out of 4 items found in the original holistic balance factor identified by McFadden and colleagues.8 Because the current factor analysis revealed additional items that conveyed a sense that the mind and body are related and affect holistic health, the factor was labeled differently. Even though labeled differently, the factor still identified the importance of holistic health in the Veteran population, as was previously found in a civilian population. As such, a larger factor analysis and validation study of the CACMAS may be beneficial in determining the utility of this scale as a clinical tool by which attitude domains could potentially identify optimal CAM interventions.
The exploratory analysis of associations between the factors and conditions of interest found that acceptability of CAM was significantly different for Veterans who did not report a history of TBI, as compared with Veterans who did report a history of mTBI. Acceptability of CAM was also significantly associated with PTSD symptom severity. That is, as PTSD symptom severity increased, acceptability of CAM also increased. It may be that Veterans who struggle with these chronic conditions may not be fully satisfied with conventional care, and may be more willing to integrate alternative approaches to care to manage their symptoms.
No significant differences were found for associations between the additional 3 factors and SDV, TBI, and PTSD symptom severity. At the same time, it is important to note that regardless of the Veteran’s reported history they endorsed belief in CAM, held a mind-body view of health, and were overall accepting of conventional medicine. This supports the need to further investigate what CAM services are acceptable to this population, efficacious for treating chronic conditions, as well as strategies for integrating identified evidence-based treatments with the conventional care they are currently receiving.
Overall, Veterans in this sample were open to using CAM in the future, and reported frequent use of CAM in the past, with less use currently. For example, of the Veterans who responded to use of CAM, 77% would use massage in the future, 61% reported using massage in the past, and only 7% currently endorsed using massage. Although this study did not assess reasons for changes in use of CAM, this may be an area for future investigation. The endorsement of future use of CAM reflects Veterans’ openness and desire for alternative or adjunctive treatments, which is important to consider when offering services to this population.
Although this study provides novel information on Veteran’s attitudes towards CAM, it does have limitations. This sample was relatively small (N=97) and included 1 site. This sample was predominantly male and unemployed. Thus, the results may not be generalizable to the larger Veteran population. At the same time, over a third of the sample self-identified as African American, which is a strength considering prior studies have reported use of and attitudes toward CAM in a predominantly white sample. Data from 80 participants were used in the factor analysis of the CACMAS; therefore, a larger exploratory factor analysis study of the measure may yield different factors. Yet, 3 of the 4 factors yielded high internal reliability, indicating that these items conceptually represent the Veteran’s attitudes and beliefs. The belief in CAM factor did have lower reliability; however, this may be reflective of the smaller sample size. A larger sample may provide additional information as to the strength of this factor in the Veteran population. Not all participants responded to the form regarding use of CAM. This may have been due to self-report administration of the measure. At the same time, the results did find similar patterns of use as found in a large, multisite study of Veterans.5 Although there were no significant differences among Veterans reporting a history of SDV compared with those without a history of SDV, a larger sample size may provide more robust conclusions on possible differences.
Even with these limitations, the CACMAS provided a comprehensive tool with which to assess attitudes/beliefs in a Veteran population, and potentially link these attitudes to other chronic health issues. In these ways, the CACMAS has the potential to provide an additional level of information from which to approach patient-centered care. Results from this study support the need for identifying and implementing evidence-based CAM practices to improve wellness, prevent illness, and manage chronic conditions. With this information it may be possible to tailor treatments that best fit the individual. This is particularly important to consider in the treatment of mental health conditions, given the literature shows greater CAM use for these. For those conditions that are associated with increased risk for negative psychiatric outcomes, including TBI, PTSD, and SDV, understanding attitudes about medical care in general may aid in the identification of potentially effective treatments that reduce such risk and may help make such treatments more accessible to those individuals most likely to benefit from them.
The findings from this study support previous research conducted in both civilian and military populations, with the addition of providing knowledge about Veterans’ attitudes and beliefs of CAM using an existing measure. Veterans may be more accepting of and may utilize CAM to complement their current medical care, particularly Veterans dealing with chronic health conditions such as TBI and PTSD, and associated negative outcomes. Understanding Veterans’ beliefs and attitudes regarding CAM may help promote investigation of the efficacy and effectiveness of CAM treatments, particularly among those with conditions for which evidence-based interventions are limited (eg, mTBI).
1. Barnes PM, Bloom B, Nahin RL. Complementary and alternative medicine use among adults and children: United States, 2007. Natl Health Stat Report. 2008;12:1–23.
2. Baldwin CM, Long K, Kroesen K, et al.. A profile of military veterans in the southwestern United States who use complementary and alternative medicine. Arch Intern. 2002;162:1697–1704.
3. Smith TC, Ryan MA, Smith B, et al.. Complementary and alternative medicine use among US Navy and Marine Corps personnel. BMC Complement Altern Med. 2007;7:16.
4. Jacobson IG, White MR, Smith TC, et al.. Self-reported health symptoms and conditions among complementary and alternative medicine users in a large military cohort. Ann Epidemiol. 2009;19:613–622.
5. Micek MA, Bradley KA, BraddockIII CH, et al.. Complementary and alternative medicine use among Veterans Affairs outpatients [letter to editor]. J Altern Complement Med. 2007;13:190–193.
6. McEachrane-Gross FP, Liebschutz JM, Berlowitz D. Use of selected complementary and alternative (CAM) treatments in veterans with cancer or chronic pain: a cross-sectional survey. BMC Complement Altern Med. 2006;6:34–40.
7. Campbell DG, Turner AP, Williams RM, et al.. Complementary and alternative medicine use in veterans with multiple sclerosis: prevalence and demographic associations. J Rehabil Res Dev. 2006;43:99–109.
8. McFadden KL, Hernández TD, Ito TA. Attitudes toward complementary and alternative medicine influence its use. Explore. 2010;6:380–388.
9. Lie D, Boker J. Development and validation of the CAM Health Belief Questionnaire (CHBQ) and CAM use and attitudes amongst medical students. BMC Med Educ. 2004;4:2.
10. Lie DA, Boker J. Comparative survey of complementary and alternative medicine (CAM) attitudes, use, and information-seeking behaviour among medical students, residents & faculty. BMC Med Educ. 2006;6:58doi: 10.1186/1472-6920-6-58.
11. Pettersen S, Olsen RV. Exploring predictors of health sciences students’ attitudes towards complementary-alternative medicine. Adv Health Sci Edu Theory Pract. 2007;12:35–53.
12. Chaterji R, Tractenberg RE, Amri H, et al.. A large-sample survey of first- and second-year medical student attitudes toward complementary and alternative medicine in the curriculum and in practice. Altern Ther Health Med. 2007;13:30–35.
13. Desylvia D, Stuber M, Fung CC, et al.. The knowledge, attitudes and usage of complementary and alternative medicine of medical students. Evid Based Complement Alternat Med. 2011728–902.
14. Hyland ME, Lewith GT, Westoby C. Developing a measure of attitudes: the holistic complementary and alternative medicine questionnaire. Complement Ther Med. 2003;11:33–38.
15. Kersten P, White PJ, Tennant A. Construct validity of the Holistic Complementary and Alternative Medicines Questionnaire (HCAMQ)—an investigation using modern psychometric approaches. Evid Based Complement Alternat Med. 2011
16. Robinson A, Chesters J, Cooper S, et al.. The PUC-CAM-Q: a new questionnaire for delving into the use of complmentary and alternative medicines. J Altern Complement Med. 2007;13:207–216.
17. Kroesen K, Baldwin CM, Brooks AJ, et al.. US military veterans’ perceptions of the conventional medical care system and their use of complementary and alternative medicine. Fam Pract. 2002;19:57–64.
18. Eisenberg DM, Davis RB, Ettner SL, et al.. Trends in alternative medicine use in the United States, 1990-1997: results of a follow-up national survey. J Am Med Assoc. 1998;280:1569–1575.
19. Barnes PM, Powell-Griner E, McFann K, et al.. National Center for Complementary and Alternative Medicine, National Institutes of Health. Complementary and alternative medicine use among adults: United States, 2002. Adv Data Vital Health Stat. 2004;343:1–20.
20. Astin JA. Why patients use alternative medicine. J Am Med Assoc. 1998;279:1548–1553.
21. Astin JA, Pelletier KR, Marie A, et al.. Complementary and alternative medicine use among elderly persons: one-year analysis of a Blue Shield Medicare supplement. J Gerontol. 2000;55:M4–M9.
22. Barrett B, Marchand L, Scheder J, et al.. Bridging the gap between conventional and alternative medicine. J Fam Pract. 2000;49:234–239.
23. White MR, Jacobson IG, Smith B, et al.. Health care utilization among complementary and alternative medicine users in a large military cohort. BMC Complement Altern Med. 2011;11:27–38.
24. George S, Jackson JL, Passamonti M. Complementary and alternative medicine in a military primary care clinic: a 5-year cohort study. Mil Med. 2011;176:685–688.
25. Sirois FM, Gick ML. An investigation of the health beliefs and motivation of complementary medicine clients. Soc Sci Med. 2002;55:1025–1037.
26. Furnham A, Smith C. Choosing alternative medicine: a comparison of the beliefs of patients visiting a general practitioner and a homoeopath. Soc Sci Med. 1988;26:685–689.
27. Tanelian T, Jaycox LH. Invisible Wounds of War: Psychological and Cognitive Injuries, Their Consequences, and Services to Assist Recovery. 2008.California: RAND Corporation.
28. Karch DL, Lubell KM, Friday J, et al.. Surveillance for Violent Deaths—National Violent Death Reporting System, 16 States, 2005
. Centers for Disease Control and Prevention MMWR Surveillance Summaries. Available at: http://www.cdc.gov/mmwr/preview/mmwrhtml/ss5703a1.htm
. Accessed March 1, 2014.
30. Schottenbauer MA, Glass CR, Amkoff DB, et al.. Nonresponse and dropout rates in outcome studies on PTSD: review and methodological considerations. Psychiatry. 2008;71:134–168.
31. Complementary, alternative, or integrative health: what’s in a name? National Center for Complementary and Alternative Medicine (NCCAM) Web site. Available at: http://nccam.nih.gov/health/whatiscam
. Accessed July 28, 2014.
32. Corrigan JD, Bogner J. Initial reliability and validity of the Ohio State University TBI identification method. J Head Trauma Rehab. 2007;22:318–329.
33. Bogner JA, Corrigan JD. Reliability and validity of the OSU TBI Identification Method with prisoners. J Head Trauma Rehab. 2009;24:279–291.
34. The Management of Concussion/mTBI Working Group. VA/DoD Clinical Practice Guideline for Management of Concussion/mTBI. 2009.Washington, DC: Department of Veterans Affairs and Department of Defense.
35. Linehan MM, Comtois KA. Lifetime Parasuicide History. 1996.Seattle, WA: University of Washington.
36. Linehan MM, Comtois KA, Brown MZ, et al.. Suicide Attempt Self-Injury Interview (SASII): development, reliability, and validity of a scale to assess suicide attempts and intentional self-injury. Psychol Assess. 2006;18:303–312.
37. Weathers FW, Litz B, Herman D, et al.. The PTSD Checklist (PCL): Reliability, Validity, and Diagnostic Utility. 1993.San Antonio, TX: Paper presented at: Annual Convention of the International Society for Traumatic Stress Studies.
38. Keen SM, Kutter CJ, Niles BL, et al.. Psychometric properties of PTSD Checklist in a sample of male veterans. J Rehabil Res Dev. 2008;45:465–474.
39. SAS [computer program]. 2002-2012.Cary, NC: SAS Institute Inc..
Keywords:© 2014 by Lippincott Williams & Wilkins.
Veterans; CAM; attitudes