The American Psychiatric Association (APA) has updated its Privacy Policy and Terms of Use, including with new information specifically addressed to individuals in the European Economic Area. As described in the Privacy Policy and Terms of Use, this website utilizes cookies, including for the purpose of offering an optimal online experience and services tailored to your preferences.

Please read the entire Privacy Policy and Terms of Use. By closing this message, browsing this website, continuing the navigation, or otherwise continuing to use the APA's websites, you confirm that you understand and accept the terms of the Privacy Policy and Terms of Use, including the utilization of cookies.

×
Published Online:

Abstract

Objective:

Given their prevalence and persuasive power in our culture, gender norms—commonly described as socially reinforced, learned expectations of what it means to be a man or a woman—likely contribute to sex differences in service utilization for depression. This study investigated whether sex differences in toughness, a gender-linked norm characterized by a desire to hide pain and maintain independence, were associated with a preference to wait for depression to resolve on its own without active professional treatment (“wait-and-see” approach).

Methods:

Participants (N=1,051) in the California Behavioral Risk Factor Surveillance System (BRFSS) survey were contacted in a follow-on survey to assess toughness, the kind of treatment they would prefer were they to receive a diagnosis of depression, and current symptoms of depression. Participants who reported ever having been diagnosed as having a depressive disorder on the BRFSS were oversampled threefold. Analyses were conducted using linear and logistic regressions.

Results:

Men and women who scored higher on toughness had a greater preference for the wait-and-see approach (OR=1.14, p<.01). Women were less likely to prefer the wait-and-see approach (OR=.58, p<.04) and scored lower on toughness (B=−.70, p<.01). Men's greater levels of toughness partially mediated the sex difference in treatment preferences (OR=.91, p<.03).

Conclusions:

Men's greater adherence to the toughness norm explained part of the sex difference observed in treatment-seeking preferences, but toughness undermined women's treatment seeking as well. Findings could be used to inform novel public health communications intended to attract both men and women to psychiatric services. (Psychiatric Services 62:740–746, 2011)

Despite the public health burden of depression (16) and the public's increased willingness (7) to seek effective treatments (2,8), many factors continue to act as significant barriers to treatment seeking (915), particularly for men (1619). Structural barriers, such as limitations on insurance coverage and availability of providers, are important obstacles to help seeking (20), but attitudinal barriers, such as stigma and social norms, are important impediments as well and are arguably more amenable to intervention. Gender role norms (21), defined as socially reinforced, learned expectations of what it means to be a man or a woman in a given culture (22), could lead to a reluctance to share personal information and admit that psychiatric services are needed.

Although many gender-based norms have been described for men and women (23,24), the toughness norm, which entails hiding pain and maintaining independence (25), is presumed to be particularly salient for men (14,23,2628) and may be especially relevant for understanding service utilization. Boys at an early age are taught to act tough and be autonomous (26,2931) and to refrain from seeking others' help to avoid signaling subordination and a loss of autonomy. Not surprisingly, men consistently have been less willing to seek help for mental disorders and more likely to prefer watchful waiting over active treatment in response to a depression diagnosis (1618, 27). Some men are believed to face “double jeopardy”—the male gender norms that dissuade help seeking simultaneously exacerbate depressive symptoms (32).

Although gender norms are commonly presumed to act as barriers to help seeking, the evidence for this position has been derived largely from small, nonrepresentative samples (14,26). We used data from the 2008 California Behavioral Risk Factor Surveillance System (BRFSS) survey of a relatively large representative sample to examine the contributions of gender norms to preferences for various psychiatric treatments, including a “wait-and-see” approach involving no treatment at all. We tested three hypotheses, of which the first two concerned sex differences. Compared with women, men were expected to endorse higher levels of toughness and to report greater willingness to manage depression without the active involvement of a health professional. Third, we hypothesized that toughness would be inversely associated with willingness to seek active treatment for depression among both men and women. We also explored whether toughness mediated any sex differences in preferences to wait and see if the depression resolved on its own.

Methods

Procedures

Between July 2, 2008, and December 11, 2008, we followed up in a telephone call with a sample of respondents to the 2008 California BRFSS survey, carried out from January 24, 2008, through June 30, 2008.The BRFSS survey contains core components about demographic characteristics as well as about current health-related perceptions, conditions, and behaviors. Optional modules are developed or acquired by participating states. A detailed description of the items included in the core component, sampling information, and the optional and state-added items specific to the California version used in 2008 is available (33). Included in the California state survey was the question, “Has a doctor or other health care provider ever told you that you have a depressive disorder (including depression, major depression, dysthymia, or minor depression)?” Responses to this item (yes or no) were used in these analyses to measure self-reported depression history.

The follow-on survey consisted of a 20-minute telephone interview designed to assess participants' current depression symptoms, attitudes toward depression and depression treatment, and adherence to the gender-linked norm of toughness. The study protocol was reviewed and approved by the institutional review board at the University of California, Davis.

Because depression was the focus of the follow-on survey, participants who reported a history of depression were oversampled approximately threefold. These respondents (N=391) constituted 38% of the entire study sample of 1,054 individuals. Sampling rates for the follow-on survey were calculated on the basis of standard definitions of the American Association of Public Opinion Research (34). The response rate was 49%, excluding households whose eligibility could not be determined. The cooperation rate (responding households generating a complete interview) was 61%, excluding households in which the eligible party was physically or mentally unable to be interviewed. More information about sampling procedures is available elsewhere (35).

Measures

Toughness was assessed using a modified version of the tough-image subscale from an update by Fischer and others of the Male Role Norms Scale, originally created by Thompson and Pleck (25,36). Participants respond on a scale of 1 (strongly agree) to 5 (strongly disagree) to four items related to the need to look tough: “People should always try to project an air of confidence even if they really do not feel confident inside”; “A good motto to live by is, ‘When the going gets tough, the tough get going’ ”; “When people are feeling a little pain, they should try not to let it show very much”; and “People must stand on their own two feet and never depend on other people to help them do things.” Although the scale was originally designed for use with men, items were rewritten in gender-neutral language so that they could be answered by both men and women. The scale was shown to be internally consistent (Cronbach's α=.63 for both men and women). Responses were reverse-scored and summed so that higher scores (from a possible range of 4 to 20) indicate greater desire to project a tough image.

Treatment preference was determined by asking participants to indicate which of four options they would prefer if they had depression—taking antidepressant medication daily for at least six to nine months, going to counseling every week for at least two months, taking medication and going to counseling, or waiting to see what happens without treatment. For the analysis, the first three responses were collapsed into one active-treatment category and compared with the wait-and-see approach.

Current level of depression was assessed using the Patient Health Questionnaire nine-item depression scale (PHQ-9), which has been shown to be a valid measure of depression symptoms in the general population (Cronbach's α=.86) (37). Participants are asked to what extent they had experienced nine symptoms over the past two weeks. Possible responses are 0, not at all; 1, on several days; 2, on more than half the days; or 3, on nearly every day. Possible scores range from 0 to 27, with higher scores indicating greater depression severity.

In the BRFSS survey, participants were asked to provide their sex, age, race, ethnicity, and highest level of education. They were also asked to indicate if at any time in the past 12 months they needed to see a doctor but could not because of cost.

Analyses

All analyses were conducted using Stata, version 11.0, and accounted for the complex survey design of both the BRFSS and the subsample of the current survey (which oversampled persons with a depression history) to yield appropriate standard errors and population parameter estimates. Participants for the analyses reported here were sampled from two strata—those with and those without a self-reported history of depression diagnosis. California BRFSS weights were used and were adjusted for the oversampling of participants with a history of a depression diagnosis. Two participants did not provide a preference for treatment, and one did not indicate level of education. Thus analyses are based on a final sample of 1,051 participants.

The dichotomous dependent variable identified as preference to wait and see without seeking active treatment was analyzed using logistic regression. Toughness was analyzed using linear regression. Variable inflation factors were examined in all models to assess risk of multicollinearity and were found to be within acceptable levels (<6). To determine whether toughness mediated any sex differences in treatment preference, an approach conceptually similar to that proposed by Baron and Kenny (38,39) was used. The “suest” command in Stata was used to test whether the product of the coefficients relating sex to toughness and toughness to treatment preferences was significantly different from zero.

The magnitude of mediation of toughness in sex difference in treatment preference was found by factoring into direct and indirect effects the ratio of the expected odds of treatment preference when the participant was female to the expected odds when the participant was male; the expected odds were calculated on the basis of expectations of the conditional distributions of toughness among female participants and male participants, respectively. The ratio of expected odds reflects both the effect of sex directly on treatment preference as well as the difference in the distribution of toughness due to sex. In terms of the models used here it is represented by exponentiating the sum of the sex-treatment preference regression coefficient with the product of the sex-toughness and toughness-treatment preference regression coefficients. The indirect effect was calculated by multiplying the sex-toughness and toughness-treatment preference regression coefficients and exponentiating the product. Given the directional hypotheses, one-tailed significance tests were used for hypothesis testing analyses; otherwise, two-tailed tests were used.

Results

Table 1 presents descriptive data for the 1,051 respondents. A total of 115 (11%) indicated that if they had depression they would prefer to wait and see what happens without seeking treatment. Table 2 presents the correlations among all variables.

Table 3 provides the results of the multivariate linear regression analysis of variables that predicted toughness. Table 4 presents the multivariate logistic regression analyses of variables that predicted a preference to wait and see if the depression resolves without treatment. Toughness is included as a predictor in panel two but excluded in panel one.

In support of the first two hypotheses, men scored higher on toughness (B=−.70, p<.01) (Table 3) and showed a greater preference to wait and see if symptoms would resolve without treatment (OR=.58, p<.04) (Table 4). In support of the third hypothesis, toughness was related to a greater preference to wait and see among both men and women (OR=1.14, p<.01) (Table 4). When toughness was included in the treatment preference analysis, sex no longer significantly predicted treatment preference. The mediational analysis revealed that toughness partially mediated the sex difference in help seeking, modifying the ratio of expected odds by a factor of .91 (95% confidence interval [CI]=.82–.99, df =1,049, p<.03), explaining 18% of the original sex difference in help-seeking preference.

Discussion

This study tested a priori hypotheses about sex differences in toughness, in treatment preferences, and in the relationship between toughness and treatment preferences. In support of these hypotheses, men scored higher on toughness and showed a greater preference to wait and see whether symptoms resolved before seeking treatment. As expected, an inverse relationship between toughness and preference for active treatment was confirmed.

These results support suggestions that toughness is a more salient norm for men and could explain their greater resistance to traditional or formal mental health treatment (28,32,40,41). The toughness norm teaches children that asking for help implies weakness and leads to a loss of independence (25,29,30).

To the best of our knowledge, this study is the first to investigate the role of the toughness norm in women's treatment preferences. It is noteworthy that like men, women who scored higher on toughness were also less interested in seeking active treatment for depression. Nonetheless, 18% of the sex difference observed in preference to wait and see was mediated by toughness. Although other factors are likely at play, these findings support the position that sex differences in mental health help-seeking behavior can be explained, in part, by gender norms.

Notably, reporting symptoms of depression was positively related to toughness. Those who present themselves as relatively tough may possess certain psychological characteristics that exacerbate depression and, perhaps, other mental disorders. Restricted emotional expression has consistently been linked with depression (4244) as well as other disorders such as alcohol and drug abuse that may mask depression (45,46). “Tougher” individuals may also refrain from or delay seeking help and as a result may be expected to experience more severe symptoms because they are not receiving help. Having a greater likelihood of experiencing depression and an increased resistance to seeking treatment can place people at added risk (29). Those most in need of treatment are often the least likely to seek help.

Clinicians, public health officials, and policy makers interested in encouraging treatment-resistant populations to seek help for mental disorders ought to address gender norms. Attempts to bring depressed people to services could address toughness in one of two ways—through cultural interventions designed to modify gender norms, thereby decreasing the level of “toughness” in society, or through social marketing interventions designed to frame help seeking either as an act of toughness or at least as a behavior that is not inconsistent with being tough.

Attempts to change norms would require an extensive, prolonged social investment and policy changes. In such an approach, public health messages could focus on prompting people to question whether they need to act tough. Schools could also implement programs to encourage children to be more open with their emotions and more comfortable seeking help. This goal may be attainable in the longer term but is unlikely to have immediate effects on health services utilization for depression. Moreover, just as any community intervention may have unintended consequences (47), iatrogenic consequences are possible.

A more pragmatic approach that could pay off in the shorter term involves developing targeted messages that represent help seeking as an act of toughness or at least an act that is not inconsistent with being tough (27,48). For example, the “Real Men. Real Depression” campaign communicated that it takes courage to seek help for depression (49). The U.S. Air Force suicide prevention program also involved changes in norms of help seeking (50). Recently, a public education campaign was launched to improve understanding among black women that the pressure they face to always appear strong to others does not preclude seeking help (51).

When men and women believe that being tough and seeking help for depression are not mutually exclusive, they may be more willing to seek treatment. Public figures who are often considered tough (sports figures, stars of action movies, military personnel) could be used as spokespersons in social marketing campaigns encouraging help seeking for depression (52,53). The effects of such public admissions on treatment uptake now and in the future could be examined.

Seeking help for depression could be positioned as aggressive action that represents taking control of one's life and going on the offense—in other words, as a way to defeat depression. If depression treatment is able to be reframed in that way, adherence to the toughness norm may actually prove to help people overcome depression. Finally, the theme of tough people, women and men, getting help for depression could be introduced into popular art forms such as television and movies through the strategy of “infotainment” (54). These examples serve as templates for interventions to increase the acceptance of depression care. Again, we would be remiss if we did not acknowledge that this approach could have unintended adverse consequences (47).

This study has four noteworthy limitations. First, the research design required participants to imagine they were depressed, but differences in capacity to imagine depression were not assessed; we do not have the data necessary to determine whether findings attributed to toughness are better explained by other variables, including individual differences in the capacity to imagine what it is like to live with depression (55), in mental health literacy (56), or in emotional intelligence (57). Second, participants were asked to imagine having been diagnosed with depression but not told how long the depression might have lasted. It is possible that those preferring a wait-and-see approach simply imagined that they had been suffering for less time and, therefore, felt less concerned about their depression.

Third, this study reports analysis of cross-sectional data. As with any cross-sectional study, no firm causal conclusions can be reached. Finally, this study presents secondary analysis of an existing data set. The population and measures were not specifically selected to assess the questions asked in this investigation. Therefore, further research with a study designed to specifically test the hypotheses are needed before firm conclusions can be reached.

Future research should determine whether gender norms explain sex differences in other stages of health service usage, including symptom awareness (14) and treatment adherence (58). Research should also continue to explore the role of the toughness norm in women's behavior, especially in relation to treatment-seeking behavior. From a public health perspective, the relationship between toughness and help seeking is perhaps best addressed among symptomatic people who have not previously been diagnosed as having depression or among those who had received a diagnosis of depression but had not been treated for it.

Conclusions

We believe this is the first study to investigate the role of the toughness norm in women's help-seeking preferences. Men's greater adherence to the toughness norm explains a part of the observed sex difference in treatment-seeking preferences, but the toughness norm undermines women's treatment seeking as well. Findings could be used to inform novel public health communications intended to attract both men and women to psychiatric services.

Dr. O'Loughlin and Dr. Duberstein are affiliated with the Department of Psychiatry, and Dr. Veazie is with the Department of Community and Preventive Medicine, University of Rochester Medical Center (URMC), Rochester, New York, where they are also with the Rochester Health Decision Making Group.
Dr. Bell is with the Department of Communication, University of California, Davis.
Dr. Bell, Dr. Fernandez y Garcia, and Dr. Kravitz are with the University of California Davis School of Medicine, Sacramento, where Dr. Bell and Dr. Kravitz are with the Center for Healthcare Policy and Research, Dr. Fernandez y Garcia is with the Department of Pediatrics, and Dr. Kravitz is also with the Department of Internal Medicine, Division of General Medicine.
Dr. Rochlen is with the Department of Educational Psychology, University of Texas at Austin, Austin.
Send correspondence to Dr. O'Loughlin at the Department of Psychology, Nazareth College, 4245 East Ave., Rochester, NY 14618 (e-mail: ).

Acknowledgments and disclosures

Dr. O'Loughlin's work on the manuscript was funded with support from a grant from the Agency for Healthcare Research and Quality (T32HS000044) (Bruce Friedman, Ph.D., M.P.H., principal investigator); Dr. Bell, Dr. Rochlen, and Dr. Kravitz were supported by grant R01MH079387 from the National Institute of Mental Health (NIMH) and Dr. Duberstein by NIMH grant K24MH072712. The sponsors were not involved in the collection, analysis, or interpretation of data; writing of the report; or decision to submit the paper for publication. The authors gratefully acknowledge the assistance of Christina Slee, M.P.H.

Dr. Kravitz has received research grant funding from Pfizer unrelated to depression care. The remaining authors report no competing interests.

References

1 Strine TW , Mokdad AH , Balluz LS , et al.: Depression and anxiety in the United States: findings from the 2006 Behavioral Risk Factor Surveillance System. Psychiatric Services 59:1383–1390, 2008 LinkGoogle Scholar

2 Young AS , Klap RK , Shoai R , et al.: Persistent depression and anxiety in the United States: prevalence and quality of care. Psychiatric Services 59:1391–1398, 2008 LinkGoogle Scholar

3 Chapman DP , Perry GS , Strine TW : The vital link between chronic disease and depressive disorders. Preventing Chronic Disease 2(1), 2005 MedlineGoogle Scholar

4 Lecrubier Y : The influence of comorbidity on the prevalence of suicidal behaviour. European Psychiatry 16:395–399, 2001 Crossref, MedlineGoogle Scholar

5 Nock MK , Borges G , Bromet EJ , et al.: Cross-national prevalence and risk factors for suicidal ideation, plans, and attempts. British Journal of Psychiatry 192:98–105, 2008 Crossref, MedlineGoogle Scholar

6 Lurie IZ , Manheim LM , Dunlop DD : Differences in medical care expenditures for adults with depression compared to adults with major chronic conditions. Journal of Mental Health Policy Economics 12:87–95, 2009 MedlineGoogle Scholar

7 Mojtabai R : Americans' attitudes towards mental health treatment seeking: 1990–2003. Psychiatric Services 58:642–651, 2008 CrossrefGoogle Scholar

8 Keller MB , McCullough JP , Klein DN , et al.: A comparison of nefazodone, the cognitive behavioral-analysis system of psychotherapy, and their combination for the treatment of chronic depression. New England Journal of Medicine 342:1462–1470, 2000 Crossref, MedlineGoogle Scholar

9 Epstein RM , Duberstein PR , Feldman MD , et al.: “I didn't know what was wrong”: how people with undiagnosed depression recognize, name, and explain their distress. Journal of General Internal Medicine 25:954–961, 2010 Crossref, MedlineGoogle Scholar

10 Bell RA , Paterniti DA , Azari R , et al.: Encouraging patients with depressive symptoms to seek care: a mixed methods approach to message development. Patient Education and Counseling 78:198–205, 2010 Crossref, MedlineGoogle Scholar

11 Dwight-Johnson M , Sherbourne CD , Liao D , et al.: Treatment preferences among depressed primary care patients. Journal of General Internal Medicine 15:527–534, 2000 Crossref, MedlineGoogle Scholar

12 Barney LJ , Griffiths KM , Christensen H , et al.: Exploring the nature of stigmatising beliefs about depression and help-seeking: implications for reducing stigma. BMC Public Health 9:61, 2009 Crossref, MedlineGoogle Scholar

13 Cooper-Patrick L , Powe NR , Jenckes MW , et al.: Identification of patient attitudes and preferences regarding treatment of depression. Journal of General Internal Medicine 12:431–438, 1997 Crossref, MedlineGoogle Scholar

14 Möller-Leimkühler AM : Barriers to help-seeking by men: a review of sociocultural and clinical literature with particular reference to depression. Journal of Affective Disorders 71:1–9, 2002 Crossref, MedlineGoogle Scholar

15 Mohr DC , Hart SL , Howard I , et al.: Barriers to psychotherapy among depressed and nondepressed primary care patients. Annals of Behavioral Medicine 32:254–258, 2006 Crossref, MedlineGoogle Scholar

16 Oliver MI : Help-seeking behaviour in men and women with common mental health problems: cross-sectional study. British Journal of Psychiatry 186:297–301, 2005 Crossref, MedlineGoogle Scholar

17 Jaycox LH , Asarnow JR , Sherbourne CD : Adolescent primary care patient's preferences for depression treatment. Administration and Policy in Mental Health and Mental Health Services Research 33:198–207, 2006 Crossref, MedlineGoogle Scholar

18 Elhai JD , Patrick SL , Anderson S , et al.: Gender- and trauma-related predictors of use of mental health treatment services among primary care patients. Psychiatric Services 57:1505–1509, 2006 LinkGoogle Scholar

19 Wade JC , Good GE : Moving toward the mainstream: perspectives on enhancing therapy with men. Psychotherapy: Theory, Research and Practice 47:273–275, 2010 CrossrefGoogle Scholar

20 Sareen J , Jagdeo A , Cox BJ , et al.: Perceived barriers to mental health service utilization in the United States, Ontario, and the Netherlands. Psychiatric Services 58:357–367, 2007 LinkGoogle Scholar

21 Danielsson U , Johansson EE : Beyond weeping and crying: a gender analysis of expressions of depression. Scandinavian Journal of Primary Health Care 23:171–177, 2005 Crossref, MedlineGoogle Scholar

22 Mischel W : Sex-typing and socialization; in Carmichael's Manual of Child Psychology, vol 2. Edited by Mussen PH. New York, Wiley, 1970 Google Scholar

23 Mahalik JR , Locke BD , Ludlow LH , et al.: Development of the Conformity to Masculine Norms Inventory. Psychology of Men and Masculinity 4:3–25, 2003 CrossrefGoogle Scholar

24 Mahalik JR , Morray EB , Coonerty-Femiano A , et al.: Development of the Conformity to Feminine Norms Inventory. Sex Roles 52:417–435, 2005 CrossrefGoogle Scholar

25 Fischer AR , Tokar DM , Good GE , et al.: More on the structure of male role norms: exploratory and multiple sample confirmatory analyses. Psychology of Women Quarterly 22:135–155, 1998 CrossrefGoogle Scholar

26 Addis ME , Mahalik JR : Men, masculinity, and the contexts of help seeking. American Psychologist 58:5–14, 2003 Crossref, MedlineGoogle Scholar

27 Rochlen AB , McKelley RA , Pituch KA : A preliminary examination of the “Real Men. Real Depression” campaign. Psychology of Men and Masculinity 7:1–13, 2006 CrossrefGoogle Scholar

28 Mahalik JR , Rochlen AB : Men's likely responses to clinical depression: what are they and do masculinity norms predict them? Sex Roles 55:659–667, 2006 CrossrefGoogle Scholar

29 David DSBrannon R (eds): The Forty-Nine Percent Majority. Reading, Mass, Addison-Wesley, 1976 Google Scholar

30 O'Neil JM : Patterns of gender role conflict and strain: the fear of femininity in men's lives. Personnel and Guidance Journal 60:203–210, 1981 Crossref, MedlineGoogle Scholar

31 Pollack W : Real Boys: Rescuing Our Sons From the Myths of Boyhood. New York, Random House, 1998 Google Scholar

32 Good GE , Wood WP : Male gender role conflict, depression, and help seeking: do college men face double jeopardy? Journal of Counseling and Development 74:70–75, 1995 CrossrefGoogle Scholar

33 Centers for Disease Control and Prevention: Behavioral Risk Factor Surveillance System Survey Questionnaire. Atlanta Ga, US Department of Health and Human Services, Centers for Disease Control and Prevention, 2008. Available online at www.cdc.gov/brfss/ Google Scholar

34 American Association for Public Opinion Research. Standard Definitions: Final Dispositions of Case Codes and Outcome Rates for Surveys (6th ed), 2009. Available at www.aapor.org/Standard_Definitions/1818.htm Google Scholar

35 Fernandez y Garcia E , Franks P , Jerant A , et al.: Depression treatment preferences of Hispanic individuals: exploring the influence of ethnicity, language, and explanatory models. Journal of the American Board of Family Medicine 24:39–50, 2011 Crossref, MedlineGoogle Scholar

36 Thompson EH , Pleck JH : The structure of male role norms. American Behavioral Scientist 29:531–543, 1986 CrossrefGoogle Scholar

37 Kroenke K , Spitzer RL , Williams JBW : The PHQ-9: validity of a brief depression severity measure. Journal of General Internal Medicine 16:606–613, 2001 Crossref, MedlineGoogle Scholar

38 Baron RM , Kenny DA : The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology 51:1173–1182, 1986 Crossref, MedlineGoogle Scholar

39 Frazier PA , Tix AP , Barron KE : Testing moderator and mediator effects in counseling psychology research. Journal of Counseling Psychology 51:115–134, 2004 CrossrefGoogle Scholar

40 Mahalik JR , Good GE , Englar-Carlson M : Masculinity scripts, presenting concerns, and help seeking: implications for practice and training. Professional Psychology: Research and Practice 34:123–132, 2003 CrossrefGoogle Scholar

41 Mansfield AK , Addis ME , Mahalik JR : “Why won't he go to the doctor?”: the psychology of men's help seeking. International Journal of Men's Health 2:93–109, 2003 CrossrefGoogle Scholar

42 Mahalik JR , Cournoyer RJ : Identifying gender role conflict measures that distinguish mildly depressed from non-depressed men. Psychology of Men and Masculinity 1:109–115, 2000 CrossrefGoogle Scholar

43 Syzdek MR , Addis ME : Adherence to masculine norms and attributional processes predict depressive symptoms in recently unemployed men. Cognitive Therapy and Research 34:533–543, 2010 CrossrefGoogle Scholar

44 Bamonti PM , Heisel MJ , Topciu RA , et al.: Association of alexithymia and depression symptom severity in adults aged 50 years and older. American Journal of Geriatric Psychiatry 18:51–56, 2010 Crossref, MedlineGoogle Scholar

45 Monk DD , Ricciardelli LA : Three dimensions of the male gender roles as correlates of alcohol and cannabis involvement in young Australian men. Psychology of Men and Masculinity 4:57–69, 2003 CrossrefGoogle Scholar

46 Brooks GR : Beyond the Crisis of Masculinity: A Transtheoretical Model for Male-Friendly Therapy. Washington, DC, American Psychological Association, 2010 CrossrefGoogle Scholar

47 Sarason SB : If it can be studied or developed, should it be? American Psychologist 39:477–485, 1984 CrossrefGoogle Scholar

48 Hammer JH , Vogel DL : Men's help seeking for depression: the efficacy of a male-sensitive brochure about counseling. Counseling Psychologist 38:296–313, 2010 CrossrefGoogle Scholar

49 Rochlen A , Whilde MR , Hoyer WD : Real Men. Real Depression: overview, theoretical implications, and research considerations. Psychology of Men and Masculinity 6:186–194, 2005 CrossrefGoogle Scholar

50 Knox KL , Litts DA , Talcott GW , et al.: Risk of suicide and related adverse outcomes after exposure to a suicide prevention programme in the US Air Force: cohort study. British Medical Journal 13:1376–1380, 2003 CrossrefGoogle Scholar

51 Nicolaidis C , Timmons V , Thomas MJ , et al.: “You Don't Go Tell White People Nothing”: African American women's perspectives on the influence of violence and race on depression and depression care. American Journal of Public Health 100:1470–1476, 2010 Crossref, MedlineGoogle Scholar

52 Associated Press: A-Rod: Therapy helps avoid “train wreck.” NBC Sports, May 25, 2005. Available at nbcsports.msnbc.com/id/7978062 Google Scholar

53 Pisani F : Fernando Pisani: Battling back from ulcerative colitis. Hockey News May 6, 2008. Available at www.thehockeynews.com/articles/15821-Fernando-Pisanis-Blog-Battling-back-from-ulcerative-colitis.html Google Scholar

54 Emergency Contraception: Is the Secret Getting Out? National Surveys of Americans and Health Care Providers on Emergency Contraception. Menlo Park, Calif, Kaiser Family Foundation, 1997. Available at www.kff.org/womenshealth/1352-contraception.cfm Google Scholar

55 Ubel PA , Lowenstein G , Schwarz N , et al.: Misimagining the unimaginable: the disability paradox and health care decision making. Health Psychology 24:S57–S62, 2005 Crossref, MedlineGoogle Scholar

56 Jorm AF : Mental health literacy: public knowledge and beliefs about mental disorders. British Journal of Psychiatry 177:396–401, 2000 Crossref, MedlineGoogle Scholar

57 Mayer JD , Salovey P , Caruso DR : Emotional intelligence: new ability or eclectic traits? American Psychologist 63:503–517, 2008 Crossref, MedlineGoogle Scholar

58 Vik SA , Maxwell CJ , Hogan DB : Measurement, correlates, and health outcomes of medication adherence among seniors. Annals of Pharmacotherapy 38:303–312, 2004 Crossref, MedlineGoogle Scholar

Figures and Tables

Table 1

Table 1 Descriptive data for 1,051 participants in the California Behavioral Risk Factor Surveillance System survey

Table 2

Table 2 Correlations among study variables for 1,051 participants in the California Behavioral Risk Factor Surveillance System survey

Table 3

Table 3 Multivariate linear regression predicting toughness among 1,051 participants in the California Behavioral Risk Factor Surveillance System survey

Table 4

Table 4 Multivariate logistic regression analyses predicting preference for wait-and-see approach among 1,051 survey respondents, by panel including or not including toughness as a predictor