Psychosomatic Medicine Faster Service from Outside North America
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrowRequest Permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Bunde, J.
Right arrow Articles by Martin, R.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Bunde, J.
Right arrow Articles by Martin, R.
Related Collections
Right arrow Depression
Right arrow Coronary Artery Disease
Right arrow Other Cardiovascular Medicine
Psychosomatic Medicine 68:51-57 (2006)
© 2006 American Psychosomatic Society

ORIGINAL ARTICLES

Depression and Prehospital Delay in the Context of Myocardial Infarction

James Bunde, PhD(c) and René Martin, PhD, RN

From the Department of Psychology (J.B., R.M.) and College of Nursing (R.M.), University of Iowa, Iowa City, IA.

Address correspondence and reprint requests to René Martin, PhD, Adult & Gerontological Nursing 374 NB, 50 Newton Road, College of Nursing, University of Iowa, Iowa City, IA 52242. E-mail: rene-martin{at}uiowa.edu.


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 
Objective: The purpose of this study was to evaluate how depression might influence treatment-seeking behaviors in the context of evolving symptoms of myocardial infarction (MI).

Methods: Post-MI patients (n = 433) completed a retrospective self-report measure of depressive symptoms with regard to the 2 weeks preceding the MI and a semistructured interview regarding their treatment-seeking behaviors.

Results: Survival analyses found that delay in seeking treatment for acute MI symptoms was observed among participants who (1) attributed their symptoms to noncardiac causes, (2) perceived their symptoms to be relatively mild, (3) experienced gastrointestinal distress, (4) did not experience sweating, and (5) reported being depressed during the 2 weeks before hospitalization. Subsidiary analyses indicated that, among depressive symptoms, sleep disturbance and fatigue predicted delay.

Conclusion: Depression warrants further attention as a variable that may influence treatment seeking for MI symptoms. Results highlight the need to adequately screen for and treat depression among persons at risk for MI.

Key Words: depression • treatment delay • myocardial infarction • common sense models of illness

Abbreviations: CHD = coronary heart disease; MI = myocardial infarction; PRIME-MD = Primary Care Evaluation of Mental Disorders; PHQ-9 = Depression module of the Patient Health Questionnaire; GI = gastrointestinal; ADL = activities of daily living; LVEF = left ventricular ejection fraction; PVD = peripheral vascular disease.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
METHODS
 RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 
Depression is a risk factor for the initial development of coronary heart disease (CHD; 1–4). Depression also is common among CHD patients recovering from myocardial infarction (MI; 5,6) and such patients are at increased risk of morbidity and mortality (7–9). Although the physiological mechanisms and psychosocial implications of the link between depression and CHD have been the subject of considerable attention (10–17), the behavioral implications of depression for the self-management of acute MI symptoms have not been explored. Little is known about how depression might affect the manner in which laypeople perceive acute MI symptoms, the common sense explanations they formulate for those symptoms, and the decisions they make about seeking emergency medical treatment. As will be discussed, there are several reasons to speculate that depression is likely to prolong prehospital delay among persons experiencing MI. However, before discussing the rationale for this prediction, we first briefly review theory and findings related to symptom perception and treatment seeking among both laypeople in general and those experiencing MI symptoms in particular.

Prehospital Delay for MI Symptoms
Prior research has identified several factors related to prolonged prehospital delay among people experiencing symptoms of an MI (18). Laypeople make the decision to seek treatment more quickly when they attribute their symptoms to cardiac as opposed to noncardiac causes (19). Women experiencing cardiac symptoms often delay longer than men in seeking treatment (20). Prolonged prehospital MI delay also is observed among elderly adults (21), people from ethnic minority backgrounds (22,23), and persons of low socioeconomic status (24). Delay is more common when cardiac symptoms are mild or moderate (versus severe) in intensity or if the symptoms begin gradually (25,26). Symptom novelty has been shown to facilitate medical treatment seeking, while familiarity impedes it (27). Delay also is especially likely when the individual does not perceive himself or herself to be vulnerable to CHD (28) or when the symptoms vary from the individual's beliefs about the typical symptoms of an MI (29). Symptom-related consultations with others are time consuming and can prolong prehospital delay, especially when the discussion involves familiar others (e.g., family members) or attempts to reach health care providers via telephone (30–32). Prior MI or a history of treatment for CHD has not been found to consistently reduce prehospital delay in the context of a subsequent MI (19,20).

Leventhal's self-regulatory perspective on health and illness behavior (33,34) provides a framework for the systematic investigation of prehospital delay and treatment-seeking decisions among persons experiencing acute symptoms. Lay decisions about symptom management can be conceptualized as three iterative stages of delay (35). The process begins with the perception of untoward physical sensations, which prompts an evaluation of whether those symptoms might mean that illness is present (i.e., appraisal delay). If the symptoms are judged to be a manifestation of illness, then the need for professional health care (versus symptom self-management) is determined (i.e., illness delay). Finally, if professional treatment is deemed to be necessary, then the costs of seeking care are weighed (i.e., utilization delay). Treatment will be sought only if benefits appear to outweigh costs (e.g., monetary expense, time, energy).

The decisions that laypeople make during the stages of appraisal, illness, and utilization delay are shaped by cognitive representations of illness, affective states and traits, and the social context. Cognitive representations of illness incorporate five types of information, including symptom labels, attributions regarding symptom causation, perceptions of seriousness, beliefs about likely consequences, and expectations regarding control and cure (36–40). Cognitive representations shape heuristics, or decision rules, that are used to increase the speed and efficiency of symptom evaluation and have been shown to predict symptom care and treatment-seeking behaviors (19,28,29,41,42). Both state (e.g., fear) and trait (e.g., neuroticism) affective states further influence the perception and self-management of symptoms (43–45). Finally, the social network plays an active role in the interpretation of symptoms and decisions to seek treatment (46).

How Might Depression Influence Prehospital Delay for MI Symptoms?
As previously noted, prior research has not explored how depression might influence prehospital delay for symptoms of an acute MI. However, there are several potential and nonmutually exclusive reasons to expect that depressed persons are likely to delay longer in seeking treatment for MI symptoms than their nondepressed counterparts. First, depressed (versus nondepressed) people may take longer to label and accurately interpret the symptoms of an MI (i.e., prolonged appraisal delay). Depression is associated with the experience of a wide range of somatic symptoms (47–50); several of these symptoms (e.g., fatigue, weakness, gastrointestinal [GI] distress, and back pain) overlap with the various manifestations of MI (51). Thus, the depressed person who experiences concurrent cardiac symptoms may face a particularly complex scenario. Depressed (versus nondepressed) people with MI may experience a broader array of symptoms and they may be more likely to attribute their symptoms to some noncardiac cause. Along similar lines, family members and friends of the depressed person may have been witnessing frequent somatic complaints for some period of time; as a consequence, spouses and other members of the support network may be less likely to notice or accurately label the emerging MI symptoms.

Second, there also are reasons to expect that depression might affect the lay determination of whether MI symptoms necessitate medical attention (i.e., prolonged illness delay). The presence of baseline somatic complaints among depressed persons may mean that the juxtaposition of concurrent cardiac symptoms is less likely to be viewed as serious. If the depressed individual already has been lethargic, the impact of the evolving MI symptoms on the ability to perform daily activities may be less noticeable. Symptom misattributions formulated during the preceding appraisal phase are likely to translate into further delays during the illness stage. As previously discussed, people seek emergency medical services quickly when they accurately realize that their symptoms represent a cardiac threat (19). However, if depressed persons are less likely to attribute their symptoms to cardiac causes, then they also may be more likely to attempt to manage their symptoms at home rather than seeking medical evaluation. Along related lines, if members of the support network believe the depressed person's symptoms are due to noncardiac causes, they may be unlikely to advise seeking medical intervention.

Finally, depression also may prolong utilization delay (i.e., the analysis of the costs and benefits of seeking medical care) in the context of an evolving MI. The costs of seeking care involve not only financial expenses but also the expenditure of energy, effort, and time. The depressed person experiencing MI might lack both the motivation and energy to seek medical attention. Utilization delay usually is quite brief among persons suffering MI (18,19); however, the behavioral inertia that characterizes depression might prolong utilization delay even if the individual is aware that the symptoms might be cardiac in origin and potentially life threatening.

The Present Study
The purpose of the present study was to explore how depression might affect aspects of treatment-seeking delay among persons experiencing symptoms of an MI. It must be noted, however, that it is challenging to optimally measure depression in the population of interest. Ideally, the associations among depression and prehospital delay for MI would be measured prospectively in an initially healthy sample. However, given the lack of prior empirical investigations and the exploratory nature of the research questions, we opted instead to utilize a retrospective measure of depression among a sample of patients known to have suffered an MI.


   METHODS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 
Sample
All study procedures and materials were reviewed and approved by the relevant institutional review boards. Adult post-MI inpatients at two university hospitals were eligible to participate unless they were (a) unable to recall their decision to seek treatment (e.g., due to loss of consciousness), (b) disoriented, (c) unable to converse in English, or (d) without telephone access. The present study is the initial report from a larger project studying common sense models of illness (52); only those data related to the associations among depression and prehospital delay are reported. Most participants (n = 433) were male (n = 307, 71%), of European descent (n = 387, 89%), had a high school education (n = 392, 91%), and lived with others (n = 343, 79%). The average age was 59.85 (SD = 11.87); women (M = 64.06, SD = 12.64) were significantly older than men (M = 58.13, SD = 11.11), t(431) = –4.85, p < .001, d = 0.35. Participants in the present study represented 35% of the 1,248 eligible in patients identified during the recruitment period. Participants were younger (M = 59.85, SD = 11.87) than nonparticipants (M = 65.17, SD = 13.86), t(1161) = –6.66, p < .001, d = 0.29. A smaller proportion of participants (n = 126, 29%) versus nonparticipants (n = 276, 38%) were female, {chi}2(1, n = 1169) = 8.53, p = .003, w = 0.09.

Self-Report Questionnaires
Neuroticism
The 8-item neuroticism scale from the Big Five Inventory (53) was administered because individual differences in trait negative affect sometimes bias retrospective symptom reports (54). Participants' responses were internally consistent ({alpha} = 0.84). Neuroticism scores ranged from 8 to 39 (M = 22.63, SD = 7.13) and were similar to those previously reported in a sample of post-MI patients (19).

Depression
Participants' retrospective accounts of depressive symptoms during the 2 weeks preceding the present hospitalization were assessed using the depression module of the Primary Care Evaluation of Mental Disorders (PRIME-MD) Patient Health Questionnaire (PHQ-9, Depression module). The PHQ-9 is a self-report version of the PRIME-MD depression scale (55); the PHQ-9 is reliable and valid in patient samples, with Cronbach's {alpha} ≥0.86 and sensitivity and specificity of 88% relative to clinician ratings from diagnostic interviews (56). Responses to the PHQ-9 were internally reliable in the present sample ({alpha} = 0.87). Consistent with PHQ-9 validation data (56), a threshold score of 10 was used to differentiate between depressed and nondepressed participants; 113 (26%) participants were identified as depressed during the 2 weeks preceding hospitalization for MI. Women (n = 42, 33%) were significantly more likely to be depressed than men (n = 71, 23%), {chi}2(1, n = 433) = 4.83, p = .03, w = 0.11.

Interview Assessment of Treatment-Seeking Behavior
Participants' retrospective accounts of prehospitalization symptoms, social interactions, and treatment-seeking behaviors were assessed by telephone using a semistructured interview previously developed and used by Martin and colleagues (19).1 Interviews were conducted by trained graduate assistants; on average, interviews occurred 8.5 days (SD = 6.16) after hospital admission for MI.2 The interview was designed to help participants accurately reconstruct their experience of having an MI. This was done by dividing the episode into a series of event sequences, evoking contextual factors, and asking questions regarding cognitive and emotional processing during the time period of interest. These techniques for minimizing recall bias are similar to those characterizing the Day Reconstruction Method (DRM) described by Kahneman and colleagues (57).

All variables identified participants' recall of events and experiences before hospitalization for MI. The following variables were assessed: (a) presence (versus absence) of 10 common cardiac symptoms, including chest pain, sweating, arm/shoulder pain, back pain, jaw pain, fatigue, GI distress, palpitations, shortness of breath, and abrupt episodes of difficulty breathing at night (i.e., paroxysmal nocturnal dyspnea); (b) total number of symptoms experienced; (c) elapsed time in minutes between symptom onset and decision to seek treatment (i.e., delay); (d) participants' symptom attributions (cardiac versus noncardiac); (e) confidence in symptom attributions (rated from 1, not at all, to 5, extremely); (f) perceived seriousness of symptoms (rated from 1, not at all, to 5, extremely); (g) impact of symptoms on ability to perform activities of daily living (ADL; rated from 1, complete bedrest, to 5, normal activities); (h) whether (yes/no) participant had discussed symptoms with others (i.e., lay consultation); (i) number of lay consultants; (j) lay consultants' symptom attributions (cardiac versus noncardiac); (k) lay consultants' advice (seek medical care versus other); (l) elapsed minutes between decision to seek care and hospital arrival (transportation time) and whether (yes/no) participants traveled to the hospital via ambulance.

Interviews were tape recorded, transcribed verbatim, rendered gender-neutral, and coded by teams of independent raters who were blind to study hypotheses and participant gender. Perfect interrater agreement was observed for participants' responses to all quantitative variables. Three narrative variables (participants' symptom attributions, lay consultants' symptom attributions, and lay consultants' advice) required content-analysis using a procedure previously developed by Martin et al. (19). Cohen's {kappa} was ≥0.90 for all content analyses.

Medical History
Records from the current hospitalization were reviewed for the following variables: (a) prior MI, (b) CHD severity, (c) coronary angiography results, (d) history of congestive heart failure (CHF), (e) left ventricular ejection fraction (LVEF), (f) history of any cardiac treatment, (g) peripheral vascular disease (PVD), (h) hypertension, (i) diabetes, (j) renal insufficiency or failure, and (k) hyperlipidemia. CHD severity was scored as low, medium, or high based on a composite of guidelines from the American College of Physicians (58), the American Association of Cardiovascular and Pulmonary Rehabilitation (59), and the American College of Sports Medicine (60). The evaluation of cardiac disease severity was based on the following factors: estimated preadmission functional capacity, history of four cardiovascular conditions (prior MI, CHF, PVD, and resuscitation from one or more episodes of cardiac arrest), current LVEF, and episodes of post-MI ischemia during the present hospitalization. Coronary angiography results were scored to represent the number of coronary arteries with atherosclerotic lesions producing ≥70% blockage (i.e., one-, two-, three-, or four-vessel disease).3


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
DISCUSSION
 NOTES
 REFERENCES
 
We begin by reporting associations among neuroticism and key study variables. Variables predicting delay then are presented. We conclude with subsidiary analyses of the effects of specific PHQ-9 items on delay. Sample sizes shift slightly across analyses due to missing data. Cohen's d is the reported effect size for all t tests; guidelines for the interpretation of d suggest that values of 0.2, 0.5, and 0.8 represent small, medium, and large effect sizes, respectively (61). The w statistic is reported for {chi}2 tests; values of 0.1, 0.3, and 0.5 reflect small, medium, and large effects, respectively (62).

Neuroticism
Neuroticism was not significantly correlated with treatment delay, participant symptom attributions, confidence in symptom attributions, ability to perform ADLs, number of lay consultants, or layconsultant attributions, all p values >.10. Small but significant positive correlations were observed between neuroticism and the total number of symptoms reported, r(429) = 0.12, p = .01, the perceived symptom seriousness, r(426) = 0.12, p = .01, and advice to seek medical attention, r(353) = 0.16, p = .003.

Treatment Delay
Consistent with our hypothesis, depressed participants (M = 968.78 minutes, SD = 2141.97) delayed longer before seeking treatment than their nondepressed counterparts (M = 534.67 minutes, SD = 1170.57), t(412) = 2.62, p = .009, d = 0.18. A survival analysis using the Cox proportional hazards model was conducted to further examine this association. Depression was found to be a significant predictor of delay when entered alone into the model, such that depressed (versus nondepressed) participants exhibited longer treatment delays, b = 0.27, {chi}2(1, n = 414) = 5.79, p = .02.

Additional, independent survival analyses were conducted on all study variables to identify those that predicted delay. Participants who reported profuse sweating with their MI (versus those who did not) were significantly faster in seeking treatment, b = –0.22, {chi}2(1, n = 433) = 5.04, p = .03, and those who experienced GI distress (versus those without) were slower to seek treatment, b = 0.36, {chi}2(1, n = 433) = 13.06, p < .01. Participants with (versus without) a history of prior MI sought care more quickly, b = –0.25, {chi}2(1, n = 412) = 4.09, p = .04. Treatment seeking was more rapid among those who attributed their symptoms to cardiac (versus noncardiac) causes, b = –0.31, {chi}2(1, n = 405) = 9.31, p = .002. Finally, perceptions of symptom seriousness predicted more rapid care seeking behavior, b = 0.16, {chi}2(1, n = 410) = 9.92, p = .002. No other variables—including CHF, history of any cardiac treatment, CHD severity, LVEF, or angiography results—predicted delay.

Next, a multivariate survival analysis was performed. Depression was entered into the equation with prior MI, participants' symptom attributions, perceptions of symptom seriousness, symptom reports of sweating, and symptom reports of GI distress as covariates.4 Depression continued to predict delay, despite the inclusion of covariates, b = 0.32, {chi}2(1, n = 399) = 7.40, p = .007. Cardiac symptom attributions, b = –0.24, {chi}2(1, n = 399) = 5.12, p = .02, perceived symptom seriousness, b = 0.12, {chi}2(1, n = 399) = 7.95, p = .03, GI distress, b = 0.37, {chi}2(1, n = 399) = 12.71, p < .001, and sweating, b = –0.23, {chi}2(1, n = 399) = 4.68, p = .03, also remained significant predictors of delay. History of prior MI did not predict delay when the other variables were included in the equation, b = –0.21, {chi}2(1, n = 399) = 2.49, p = .12.

We next examined variables influencing specific aspects of delay, including the initial appraisal of symptoms, decisions related to whether one is ill, and the utilization of health care services. Depressed participants reported a greater number of symptoms (M = 5.23, SD = 2.05) than those who were not depressed (M = 4.11, SD = 1.85), t(427) = 5.37, p < .001, d = 0.41. With regard to specific symptoms, depressed (versus nondepressed) participants were more likely to suffer from paroxysmal nocturnal dyspnea, {chi}2(1, n = 432) = 9.49, p = .003, w = 0.15; jaw pain, {chi}2(1, n = 432) = 6.56, p = .01, w = 0.12; back pain, {chi}2(1, n = 431) = 10.32, p = .002, w = 0.15; shoulder pain, {chi}2(1, n = 432) = 12.38, p < .001, w = 0.17; and fatigue, {chi}2(1, n = 432) = 15.28, p < .001, w = 0.19. Depressed (versus nondepressed) participants tended to report more palpitations, {chi}2(1, n = 431) = 3.92, p = .07, w = 0.10; shortness of breath, {chi}2(1, n = 431) = 3.55, p = .06, w = 0.09; and GI distress, {chi}2(1, n = 432) = 3.33, p < .08, w = 0.09; however, these contrasts were nonsignificant. Likelihood of having experienced chest pain, {chi}2(1, n = 432) < 1, and sweating, {chi}2(1, n = 432) < 1, did not vary as a function of depression. Depressed (n = 57, 50%) and nondepressed (n = 151, 49%) participants were equally likely to recall that they had attributed their symptoms to cardiac (versus noncardiac) causes before hospitalization, {chi}2(1, n = 423) < 1.

Most participants engaged in lay consultation before seeking medical attention (n = 353, 82%). Depressed participants (n = 101, 90%) were more likely to engage in lay consultation, {chi}2(1, n = 429) = 6.48, p = .01, w = 0.12, than their nondepressed counterparts (n = 252, 80%) but spoke to a similar number of lay consultants on average, t(350) < 1. Depressed (n = 29, 29%) and nondepressed (n = 72, 29%) participants were equally likely to recall that a lay consultant had attributed their symptoms to cardiac (versus noncardiac) causes, {chi}2(1, n = 353) < 1.

Depressed participants (M = 3.85, SD = 1.02) believed their symptoms to be as serious as their nondepressed counterparts (M = 3.68, SD = 1.09), t(424) = 1.41, p = .16, d = 0.11. No differences were observed in ratings of confidence in symptom attributions between depressed (M = 3.70, SD = 1.19) and nondepressed (M = 3.67, SD = 1.29) participants before entry into the medical care delivery system, t(420) < 1. Similarly, depressed (M = 2.81, SD = 1.16) and nondepressed (M = 2.83, SD = 1.10) participants reported no differences in their ability to perform ADLs during their prehospital symptomatic period, t(429) < 1.

We also examined whether participants received specific advice during lay consultations that may have affected their decision to seek care. Of the participants who engaged in lay consultation, most (n = 237, 67%) received symptom-related advice from a lay consultant. Depressed participants (n = 75, 75%) were more likely than their nondepressed counterparts (n = 162, 64%) to report having received advice, {chi}2(1, n = 352) = 3.74, p = .05, w = 0.10. Depressed participants (n = 77, 77%) also were more likely than those who were not depressed (n = 156, 62%) to report that their lay consultants advised them to seek medical care, {chi}2(1, n = 351) = 7.07, p = .008, w = 0.14.

Transportation time did not differ between depressed (M = 19.18, SD = 21.99) and nondepressed participants (M = 17.34, SD = 28.15), t(425) < 1. Depressed (n = 60, 53%) and nondepressed (n = 176, 55%) participants were equally likely to have traveled to the hospital by ambulance, {chi}2(1, n = 432) < 1.

Subsidiary Analyses of PHQ-9 Items
A subsidiary survival analysis was conducted for each PHQ-9 item in an attempt to determine whether specific items might be uniquely predictive of delay. As shown in Table 1, only two items, "sleep disturbance" and "fatigue," emerged as significant predictors of delay.


View this table:
[in this window]
[in a new window]
  		TABLE 1. Survival Analyses for the Associations Among Specific PHQ-9 Items and Delay

 


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
NOTES
 REFERENCES
 
Five variables—cardiac attributions, perceived seriousness of symptoms, symptom reports of GI distress, symptom reports of profuse sweating, and depression—predicted treatment-seeking behavior in the context of acute cardiac symptoms. Consistent with previous research, heuristic processes played an important role in participants' responses to acute cardiac symptoms. The decision to seek medical intervention was made more quickly by individuals who believed that their symptoms might be due to cardiac causes (19) or perceived their symptoms as being more (versus less) serious (26). This study also replicates previous findings that symptom reports of sweating predict shorter delay times in the context of acute MI (63). This result is consistent with research highlighting the importance of symptom novelty (27); profuse sweating in the context of minimal exertion is probably perceived to be quite unusual and a clear indication of illness. In contrast, GI distress is relatively commonplace and rarely necessitates immediate medical attention; thus, it is not surprising that those experiencing this symptom were slower in seeking care.

Independent of heuristic processes associated with symptom attribution and interpretation, participants who characterized themselves as having been depressed during the 2 weeks preceding hospitalization were significantly slower in seeking treatment for their cardiac symptoms. This finding extends the literature on the physiological and psychosocial consequences of depression and CHD to incorporate the novel idea that the depressed person having an MI is prone to maladaptive treatment-seeking behaviors. Our finding that heuristic processes and depression were independently related to treatment-seeking is consistent with Leventhal's self-regulatory perspective, which assumes that cognitive and affective systems make independent contributions to health and illness behavior (33,34).

We used the Safer et al. (35) model of treatment-seeking behavior, with its stages of appraisal, illness, and utilization delay, to identify similarities and differences as a function of depression. As previously discussed, somatic complaints are common in depression. Consistent with this perspective, depressed (versus nondepressed) participants recalled more overall symptoms; they also were more likely to report several specific symptoms (e.g., difficulty breathing at night). However, depressed and nondepressed participants were equally likely to recall that they had experienced chest pain, the prototypic symptom of MI. Comparable chest pain between the two groups may explain why depressed participants were just as likely as their nondepressed counterparts to attribute their symptoms to potential cardiac causes. Similarly, participants were equally likely, irrespective of depressive status, to recall that a family member or friend had voiced a cardiac attribution. Thus, despite some differences in symptom presentation, depression did not appear to influence the manner in which participants and their lay consultants interpreted those symptoms.

Depression had no effect on ratings of perceived seriousness of symptoms or on ratings of the impact of symptoms on the ability to perform ADLs. In fact, depressed (versus nondepressed) participants actually were more likely to recall that a family member or friend had advised them to seek medical intervention. It is particularly worrisome that depressed individuals delayed in seeking treatment despite receiving sound advice from members of their support network. Important variables related to health care utilization also did not vary by depressive status. Depressed and nondepressed participants were equally likely to summon an ambulance for transportation to the hospital. In addition, no differences were observed in the time it took for depressed and nondepressed participants to travel to the emergency room.

In sum, heuristic and social processes suggest that depressed participants should have exhibited similar (or shorter) delay times than their nondepressed counterparts. What factors, then, might account for the prolonged delay among depressed participants? Our exploratory analyses of the PHQ-9 items offer some basis for post hoc speculation. Most PHQ-9 items, including those related to depressed mood, feelings of failure, and thoughts of being better off dead, were unrelated to delay. This suggests that participants probably were not engaging in "suicide by MI." The depressed participants who were most likely to delay in seeking treatment were those who endorsed PHQ-9 items related to sleep disturbance and fatigue. This pattern of findings suggests that behavioral inertia and lethargy may be powerful inhibitors in executing care-seeking behaviors. Comparable rates of cardiac attributions across groups and the positive effect of cardiac attributions on overall treatment seeking suggests that the association between depression and delay could be a consequence of difficulties in mobilizing the energy necessary to seek care.

We are cautious in making these speculations, however; this was an initial study of the domain, and our findings raise as many questions as they answer. As such, a number of important limitations of the present study should be noted. We used a predominantly male and ethnically homogenous sample, thereby limiting the generalizability of our findings. Reactions of individuals in the lay support network were reported by study participants, and convergent data coming directly from lay consultants would strengthen our conclusions regarding the nature of social influence in treatment-seeking for MI. We relied on post-MI patients' retrospective reports of their symptoms, attributions, and care-seeking behavior. Although previous studies report adequate convergent validity between information recorded in medical records on the day of the MI and subsequent retrospective self-reports (64), it remains possible that the accounts of our participants were biased in some important way, especially with regard to variables that are unlikely to be acknowledged and recorded at the time of the MI (i.e., patient attributions).

Our measure of depression was suboptimal. The PHQ-9 has demonstrated adequate reliability and validity in medical settings, but a more established measure of depression, such as the Beck Depression Inventory (65) or a diagnostic interview, may be more appropriate in future studies. It is unclear what effect the experience of having an MI might have on recollections of mood in the 2 weeks before the cardiac event. Depression is common among post-MI patients, and some evidence suggests that current depressive status may influence reporting of past depressive episodes and traumatic events (66). Unfortunately, a measure of current depression was not included in the present study. In future research, information from family members regarding patients' depressive symptoms before hospitalization would increase confidence in participants' retrospective symptom self-reports.

Depressed and nondepressed participants had fairly similar medical and cardiac histories. Diabetes and renal insufficiency/failure were more common among depressed participants, but neither condition was associated with delay. Nonetheless, we cannot definitively determine whether our results might reflect the effects of CHD severity, perhaps resulting in functional disability and prolonged delay. However, prior MI, CHF, CHD severity, angiography results, LVEF, and history of any cardiac treatment failed to predict delay and the effects of depression on delay persisted after controlling for these variables. It also is important to acknowledge that the present study does not distinguish between the effects of depression and those of vital exhaustion, which is common in the weeks preceding an MI (67). Although the PHQ-9 is not suitable to differentiate between the two constructs, future studies might include a measure of vital exhaustion, such as the Maastricht Questionnaire (68), to determine which is most closely associated with delay.

In conclusion, depression was found to independently influence treatment seeking for MI in our sample. Should depression prove to be a robust predictor of MI treatment delay in future studies, that association would have important implications for practice in both the physical and mental health domains. Our findings may add even greater urgency to adequately screening for and treating depression among patients at risk of CHD or reinfarction. Given the documented overlap among negative affective dispositions (17), future research should address the potential impact of emotional states other than depression (e.g., anxiety) on treatment delay for acute MI.


   NOTES
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 NOTES
REFERENCES
 
1Additional information regarding development, administration, and coding of the interview can be found in Martin et al. (19). The interview script is available from the second author upon request. Back

2Number of days between hospital admission and interview completion was not significantly related to depression scores or any dependent variables (r values <.15, p values ≥.10). Back

3Depressed participants were more likely than nondepressed participants to suffer from diabetes (40% versus 27%, {chi}2(1, N = 431) = 6.10, p = .02, w = .12) and renal insufficiency or failure (15% versus 6%, {chi}2(1, N = 431) = 8.14, p = .01, w = .14). No other medical history variables differed by depressive status, including prior MI, CHD severity, angiography results, history of CHF, LVEF, history of cardiac treatment, hypertension, hyperlipidemia, and PVD. Back

4An additional multivariate survival analysis was conducted with depression, symptom attributions, perceived seriousness, and all cardiac-related variables—including prior MI, CHD severity, angiography results, history of CHF, LVEF, and history of any cardiac treatment—included. Only depression (p = .003) and symptom attributions (p = .006) predicted delay. Back

This research was supported, in part, by a grant from the National Institute of Nursing Research (NR04886) to René Martin. We appreciate the efforts of Ellen Gordon, Elaine Leventhal, Howard Leventhal, Nan Rothrock, Erica Johnsen, S. Beth Bellman, and Aliza Weinrib for their assistance with this study.

DOI:10.1097/01.psy.0000195724.58085.f0


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 

  1. Barefoot JC, Schroll M. Symptoms of depression, acute myocardial infarction, and total mortality in a community sample. Circulation 1996;93:1976–80.[Abstract/Free Full Text]
  2. Ford DE, Mead LA, Chang PP, Cooper-Patrick L, Wang NY, Klag MJ. Depression is a risk factor for coronary artery disease in men: the precursors study. Arch Intern Med 1998;158:1422–6.[Abstract/Free Full Text]
  3. Penninx BW, Beekman AT, Honig A, Deeg DJ, Schoevers RA, van Eijk JT, van Tilburg W. Depression and cardiac mortality: results from a community-based longitudinal study. Arch Gen Psychiatry 2001;58:221–7.[Abstract/Free Full Text]
  4. Wulsin LR, Singal BM. Do depressive symptoms increase the risk for onset of coronary disease? a systematic quantitative review. Psychosom Med 2003;65:201–10.[Abstract/Free Full Text]
  5. Frasure-Smith N, Lespérance F, Talajic M. Depression and 18-month prognosis after myocardial infarction. Circulation 1995;91:999–1005.[Abstract/Free Full Text]
  6. Ladwig KH, Kieser M, König J, Breithardt G, Borggrefe M. Affective disorders and survival after acute myocardial infarction. Eur Heart J 1991;12:959–64.[Medline]
  7. Bush DE, Ziegelstein RC, Tayback M, Richter D, Stevens S, Zahalsky H, Rauerback JA. Even minimal symptoms of depression increase mortality risk after acute myocardial infarction. Am J Cardiol 2001;88:337–41.[CrossRef][Medline]
  8. Frasure-Smith N, Lespérance F. Depression and other psychological risks following myocardial infarction. Arch Gen Psychiatry 2003;60:627–36.[Abstract/Free Full Text]
  9. Frasure-Smith N, Lespérance F, Talajic M. Depression following myocardial infarction: impact on 6-month survival. JAMA 1993;270:1819–25.[Abstract/Free Full Text]
  10. Lett HS, Blumenthal JA, Babyak MA, Sherwood A, Strauman T, Robins C, Newman MF. Depression as a risk factor for coronary artery disease: evidence, mechanisms, and treatment. Psychosom Med 2004;66:305–15.[Abstract/Free Full Text]
  11. Musselman DL, Evans DL, Nemeroff CB. The relationship of depression to cardiovascular disease: epidemiology, biology, and treatment. Arch Gen Psychiatry 1998;55:580–92.[Abstract/Free Full Text]
  12. Rozanski A, Blumenthal JA, Kaplan J. Impact of psychological factors on the pathogenesis of cardiovascular disease and implications for therapy. Circulation 1999;99:2191–217.
  13. Sheps DS, Rosanski A. From feeling blue to clinical depression: exploring the pathogenicity of depressive symptoms and their management in cardiac practice. Psychosom Med 2005;67:S2–5.[Free Full Text]
  14. Davidson KW, Rieckmann N, Rapp MA. Definitions and distinctions among depressive syndromes and symptoms: implications for a better understanding of the depression-cardiovascular disease association. Psychosom Med 2005;67:S6–9.[Abstract/Free Full Text]
  15. Frasure-Smith N, Lespérance F. Reflections on depression as a cardiac risk factor. Psychosom Med 2005;67:S19–25.[Abstract/Free Full Text]
  16. Freedland KE, Carney RM, Skala JA. Depression and smoking in coronary heart disease. Psychosom Med 2005;67:S42–6.[Abstract/Free Full Text]
  17. Suls J, Bunde J. Anger, anxiety, and depression as risk factors for cardiovascular disease: the problems and implications of overlapping affective dispositions. Psychol Bull 131:260–300.
  18. Dracup K, Alonzo AA, Atkins JM, Bennett NM, Braslow A, Clark LT, Eisenberg M, Ferdinand K, Frye R, Green L, Hill MM, Kennedy JW, Kline-Rogers E, Moser DK, Ornate JP, Pitt B, Scott JD, Selker HP, Silva SJ, Thies W, Weaver WD, Wenger NK, White SK. The physician's role in minimizing prehospital delay in patients at high risk of acute myocardial infarction: recommendations from the National Heart Attack Alert Program. Ann Intern Med 1997;126:645–51.[Abstract/Free Full Text]
  19. Martin R, Lemos K, Rothrock N, Bellman SB, Russell D, Tripp-Reimer T, Lounsbury P, Gordon E. Gender disparities in common sense models of illness among myocardial infarction victims. Health Psychol 2004;23:345–53.[CrossRef][Medline]
  20. Meischke H, Eisenberg MS, Larsen M. Prehospital delay interval for patients who use emergency medical services: the effect of heart-related medical conditions and demographic variables. Ann Emerg Med 1993;22:1597–601.[CrossRef][Medline]
  21. Yarzebski J, Goldberg RJ, Gore JM, Alpert JS. Temporal trends and factors associated with extent of delay to hospital arrival in patients with acute myocardial infarction: the Worcester Heart Study. Am Heart J 1994;128:255–63.[CrossRef][Medline]
  22. Clark LT, Bellam SV, Shah AH, Feldman JG. Analysis of prehospital delay among inner-city patients with symptoms of myocardial infarction: implications for therapeutic intervention. J Natl Med Assoc 1992;84:931.[Medline]
  23. Dracup K, Moser DK, Eisenberg M, Meischke H, Alonzo A, Branslow A. Causes of delay in seeking treatment for symptoms of acute myocardial infarction. Soc Sci Med 1995;40:379–92.
  24. Ell K, Haywood J, Sobel E, deGuzman M, Blumfield D, Ning J. Acute chest pain in African Americans: factors in the delay in seeking emergency care. Am J Public Health 1994;84:965–70.[Abstract/Free Full Text]
  25. Maynard C, Althouse R, Olsufka M, Ritchie JL, Davis KB, Kennedy JW. Early versus late hospital arrival for acute myocardial infarction in the western Washington thrombolytic therapy trials. Am J Cardiol 1989;63:1296–300.[CrossRef][Medline]
  26. Schmidt SB, Borsch MA. The prehospital phase of acute myocardial infarction in the era of thrombolysis. Am J Cardiol 1990;65:1411–5.[CrossRef][Medline]
  27. Mora PA, Robitaille C, Leventhal H, Swigar M, Leventhal EA. Trait negative affect relates to prior-week symptoms, but not to reports of illness episodes, illness symptoms, and care seeking among older persons. Psychosom Med 2002;64:436–49.[Abstract/Free Full Text]
  28. Rushton A, Clayton J, Calnan M. Patients' action during their cardiac event: qualitative study exploring differences and modifiable factors. BMJ 1998;316:1060–4.[Abstract/Free Full Text]
  29. Johnson JA, King KB. Influence of expectations about symptoms on delay in seeking treatment during a myocardial infarction. Am J Crit Care 1995;4:29–35.
  30. Alonzo AA. The impact of the family and lay others on care-seeking during life-threatening episodes of suspected coronary artery disease. Soc Sci Med 1986;22:1297–311.
  31. Gray D, Keating NA, Murdock J, Skene AM, Hampton JR. Impact of hospital thrombolysis policy on out-of-hospital response to suspected myocardial infarction. Lancet 1993;341:654.[CrossRef][Medline]
  32. Reilly A, Dracup K, Dattolo J. Factors influencing prehospital delay in patients experiencing chest pain. Am J Crit Care 1994;3:300–6.
  33. Brownlee S, Leventhal H, Leventhal E. Regulation, self-regulation, and the construction of the self in the maintenance of physical health. In: Boekaerts M, Pintrich PR, eds. Handbook of Self-regulation. San Diego, CA: Academic Press; 2000:369–416.
  34. Leventhal H, Diefenbach M. The active side of illness cognition. In: Skelton JA, Croyle RT, eds. Mental Representation in Health and Illness. New York: Springer-Verlag; 1991:247–72.
  35. Safer MA, Tharps QJ, Jackson TC, Leventhal H. Determinants of three stages of delay in seeking care at a medical clinic. Med Care 1979;17:11–29.[Medline]
  36. Baumann LJ, Cameron LD, Zimmerman RS, Leventhal H. Illness representations and matching labels with symptoms. Health Psychol 1989;8:449–69.[CrossRef][Medline]
  37. Lau RR. Cognitive representations of health and illness. In: Gochman DS, ed. Handbook of Health Behavior Research I: Personal and Social Determinants. New York: Plenum; 1997:51–69.
  38. Meyer D, Leventhal H, Gutman M. Common-sense models of illness: the example of hypertension. Health Psychol 1985;4:115–35.[CrossRef][Medline]
  39. Sharloo M, Kaptein A. Measurement of illness perceptions in patients with chronic somatic illness: a review. In: Petrie KJ, Weinman JA, eds. Perceptions of Health and Illness: Current Research and Applications. Amsterdam, Netherlands: Harwood Academic Publishers; 1997:103–54.
  40. Skelton JA, Croyle RT, eds. Mental Representations in Health and Illness. New York: Springer-Verlag; 1991.
  41. Leventhal H, Meyer D, Nerenz D. The common sense representation of illness danger. In: Rachman S, ed. Contributions of Medical Psychology. Vol. 2. New York: Pergamon Press; 1980:17–30.
  42. Leventhal H, Nerenz D, Steele D. Illness representations and coping with health threats. In: Baum A, Singer J, eds. A Handbook of Psychology and Health. Vol 4. Hillsdale, NJ: Erlbaum; 1984:219–52.
  43. Contrada RJ, Guyll M. On who gets sick and why: the role of personality and stress. In: Baum A, Revenson TA, Singer JE, eds. Handbook of Health Psychology. Mahwah, NJ: Lawrence Erlbaum; 2001:59–84.
  44. Diefenbach MA, Miller SM, Daly MB. Specific worry about breast cancer predicts mammography use in women at risk for breast and ovarian cancer. Health Psychol 1999;18:532–6.[CrossRef][Medline]
  45. McCaul KD, Branstetter AD, O'Donnell SM, Jacobson K, Quinlan KB. A descriptive study of breast cancer worry. J Behav Med 1998;21:565–79.[CrossRef][Medline]
  46. Suls J, Martin R, Leventhal H. Social comparison, lay referral, and the decision to seek medical care. In: Buunk BP, Gibbons FX, eds. Health, Coping, and Well-being: Perspectives from Social Comparison Theory. Mahwah, NJ: Erlbaum; 1997:195–226.
  47. Kroenke K. Patients presenting with somatic complaints: epidemiology, psychiatric co-morbidity and management. Int J Methods Psychiatry Res 2003;12:34–43.
  48. Simon GE, VonKorff M, Piccinelli M, Fullerton C, Ormel J. An international study of the relation between somatic symptoms and depression. N Engl J Med 1999;341:1329–35.[Abstract/Free Full Text]
  49. Goldberg DP, Bridges RN. Somatic presentation of DSM-III psychiatric disorder in primary care. J Psychosom Res 1988;32:563–9.
  50. Salzman C, Shader RI. Depression in the elderly, I: relationship between depression, psychologic defense mechanisms and physical illness. J Am Geriatr Soc 1978;26:253–60.[Medline]
  51. Lee H, Bahler R, Park OJ, Kim CJ, Lee HY, Kim YJ. Typical and atypical symptoms of myocardial infarction among African-Americans. Crit Care Nurs Clin North Am 2001;13:531–9.[Medline]
  52. Martin R. Lay CHD representations and women's self-referral for MI. NIH Grant NR04886; 2000.
  53. John OP, Donahue EM, Kentle RL. The Big Five Inventory: Versions 4a and 5 (Tech. Rep.). Berkeley, CA: University of California, Institute of Personality and Social Research; 1991.
  54. Watson D, Pennebaker JW. Health complaints, stress, and distress: exploring the central role of negative affectivity. Psychol Rev 1989;96:234–54.[CrossRef][Medline]
  55. Spitzer RL, Williams JB, Kroenke K, Linzer M, deGruy FV 3rd, Hahn SR, Brody D, Johnson JG. Utility of a new procedure for diagnosing mental disorders in primary care: the PRIME-MD 1000 study. JAMA 1994;272:1749–56.[Abstract/Free Full Text]
  56. Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med 2001;16:606–13.[CrossRef][Medline]
  57. Kahneman D, Krueger AB, Schkade DA, Schwarz N, Stone AA. A survey method for characterizing daily life experience: the day reconstruction method. Science 2004;306:1776–80.[Abstract/Free Full Text]
  58. American College of Physicians. Position: cardiac rehabilitation services. Ann Intern Med 1988;109:650–63.
  59. American Association of Cardiovascular and Pulmonary Rehabilitation. Guidelines for Cardiac Rehabilitation Programs. Champaign, IL: Human Kinetics Books; 1991.
  60. American College of Sports Medicine. Guidelines for Exercise Testing and Prescription. 4th ed. Philadelphia, PA: Lea & Febiger; 1991.
  61. Cohen J. Statistical Power Analysis for the Behavioral Sciences. 2nd ed. Hillsdale, NJ: Lawrence Earlbaum Associates; 1988.
  62. Cohen J. Statistical Power Analysis for the Behavioral Sciences, Revised Edition. New York: Academic Press; 1977.
  63. Zerwic JJ, Ryan CJ, DeVon HA, Drell MJ. Treatment seeking for acute myocardial infarction symptoms: differences in delay across sex and races. Nurs Res 2003;52:159–67.[CrossRef][Medline]
  64. Goldberg RJ, McCormick D, Gurwitz JH, Yarzebski J, Lessard D, Gore JM. Age-related trends in short- and long-term survival after acute myocardial infarction: a 20-year population-based perspective (1975–1995). Am J Cardiol 1998;82:1311–7.[CrossRef][Medline]
  65. Beck AT, Steer RA, Brown GK. The Beck Depression Inventory: Second Edition (Manual). San Antonio, TX: The Psychological Corporation, Harcourt Brace & Company; 1996.
  66. Schraedley PK, Turner RJ, Gotlib IH. Stability of retrospective reports in depression: traumatic events, past depressive episodes, and parental psychopathology. J Health Soc Behav 2002;43:307–16.[CrossRef][Medline]
  67. Appels A, Kop WJ, Schouten E. The nature of the depressive symptomatology preceding myocardial infarction. Behav Med 2000;26:86–9.[Medline]
  68. Appels A, Mulder P. Excess fatigue as a precursor of myocardial infarction. Eur Heart J 1988;9:758–64.[Abstract/Free Full Text]



This article has been cited by other articles:


Home page
 West J Nurs ResHome page
Ju Young Shin, R. Martin, and M. Bryant Howren
Influence of Assessment Methods on Reports of Gender Differences in AMI Symptoms
West J Nurs Res, August 1, 2009; 31(5): 553 - 568.
[Abstract] [PDF]

Home page
 Qual Health ResHome page
S. A. Turris and J. L. Johnson
Maintaining Integrity: Women and Treatment Seeking for the Symptoms of Potential Cardiac Illness
Qual Health Res, November 1, 2008; 18(11): 1461 - 1476.
[Abstract] [PDF]

Home page
 QJMHome page
C.-K. Wong, E.W. Tang, P. Herbison, B. Birmingham, L. Barclay, and S.Y.F. Fu
Pre-existent depression in the 2 weeks before an acute coronary syndrome can be associated with delayed presentation of the heart attack
QJM, February 1, 2008; 101(2): 137 - 144.
[Abstract] [Full Text] [PDF]

Home page
 Psychosom. Med.Home page
A. M. Nezu, C. M. Nezu, D. Jain, M. S. Xanthopoulos, T. A. Cos, J. Friedman, and M. Lee
Social Problem Solving and Noncardiac Chest Pain
Psychosom Med, November 1, 2007; 69(9): 944 - 951.
[Abstract] [Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrowRequest Permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Bunde, J.
Right arrow Articles by Martin, R.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Bunde, J.
Right arrow Articles by Martin, R.
Related Collections
Right arrow Depression
Right arrow Coronary Artery Disease
Right arrow Other Cardiovascular Medicine

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS