- Email: [email protected]
Life change and hospitalization—a heretical view
Journal of Psychosomatic
Research, Vol. 18, pp. 393 to 401. Pergamon Press, 1974. Printed in Great Britain
LIFE CHANGE AND HOSPITALIZATION-A HERETICAL VIEW* HAROLD
J. WERSHOW and GEORGEREINHAKT (Received 7 March 1974)
began as a didactic exercise designed to demonstrate to often recalcitrant medical students the importance of socio-psychological factors in the etiology of illness. The failure of the demonstration motivated a more intensive review of the relevant literature and the conclusions to which we reluctantly came. We employed the Schedule of Recent Experiences (SRE) [4], which has been developed by Holmes, Rahe and their associates through various minor modifications as the Social Readjustment Rating Scale (SRRS) [l], Recent Life Changes Questionnaire (RLCQ) [lo] and Life Change Inventory (LCI) [9]. This short communication need not review the literature employing that instrument; representative papers can be found in refs. 7-13 of Rubin et al. [5]. A more extensive literature discussing the relationship between various illnesses and psycho-socially stressful situations may be found in Holmes and Rahe [l] refs. 2-13. The didactic effort alluded to was an unsuccessful attempt to employ the SRE to quantify the relationship between social factors and illness; in this case, psycho-social factors (changes in life situation, which are assumed to be associated with the onset of illness) were the independent variables, The SRE notes 43 representative changes in one’s life situation and assigns to each a value in Life Change Units (LCU), ranging from receiving a traffic-ticket (11 LCU’s) to death of a spouse (100 LCU’s). Changes need not be undesirable or involuntary (e.g. marriage, promotions and less in-law troubles are all included). It is claimed that “the greater the individual’s yearly LCU total, the higher becomes his risk of a major health change in the following year”. (3 :355). THIS STUDY
METHODOLOGY In view of the above-noted literature, it was hypothesized that a high proportion of the newly admitted patients to the medical wards of the Birmingham Veterans’ Administration Hospital (BVAH), where the medical school juniors perform some of their clinical clerkships, would have high LCU scores based on the SRE and that the scores would be higher in the 6 months immediately preceding hospitalization than in the 7-12 months prior to hospita1ization.t An attempt was made to interview all male patients admitted to the BVAH, who had not been inpatients in any hospital for the preceding 24 months, that time span being selected as providing a basal period of normal living and relative good health. The SRE was administered to all patients who met the criteria (admission to the medical service and no previous hospitalization in any hospital within the nrecedina 2 vr) on 2 of the 5 (excludina the Intensive Care Unit) medical wards. In addition. the demographic backgrounds of patients were obtained. Employed as interviewers were undergraduate students of sociology, either volunteers or work-study students. The students were trained by one of us (H.J.W.) who had graduate training in and had practiced as a social worker for 15 yr. He also conducted a number of interviews and his results were congruent with those of the students. In addition, a number of the student interviews were taped for verification of interviewing techniques and scoring. There were lapses in the consecutivity of admissions screened for eligibility for the study *From the Department of Sociology and Anthropology, University College, University of Alabama in Birmingham, Birmingham, Alabama 35294, U.S.A. tThe definition of “high” LCU scores will be discussed at a later point. 393
HAROLD J. WERSHOW and GEORGE REINHART
394
and interviewed, due to student examination and holiday periods. Some patients were missed due to discharge after an admission too short to be contacted, illness too severe to permit an interview, obtundedness and death. Upon the advice of the Chief of Service, patients in isolation (usually suspected tuberculars) were excluded, as were the insigniticant number of female patients. There is no reason to believe that the lapses in (interviewing) the consecutivity of admissions or the choice of wards biased the study in any systematic manner. Medical Service patients are admitted to the 5 wards more or less consecutively, keeping the census about even, without regard to age, residence or other discernible factors, and with no selection of diagnoses within the broad area of medicine, as distinguished from psychiatry and surgery. A departure from the usual procedure employing the SRE was in using it as a highly-structured interview schedule and not as a self-administered questionnaire; many patients were barely, if at all, literate and unaccustomed to answering long and relatively complex questionnaires and this choice was forced upon us. RESULTS Between November 1970 and April 1971, 88 patients were interviewed. Some striking impressions were garnered: since these were unanticipated and no records were kept of these data, they are unfor&nately not substantiated with hard numbers. The patients seem to be, however, typical of Veterans’ Administration Hosnital (VAH) natients in any VA General Hospital anywhere in the country. Most are middle aged-and older men (90 per cent-over 40); many had not worked regularly in years. If these long-term chronically-ill men, marginally employed, unemployed or out of the labor force were sufficiently fortunate to have served in the armed forces, they “percolated down” to the VAH system rather than the “charity” medical care system as they become ineligible for, or could not afford, hospitalization insurance. A large proportion of admissions was accounted for by chronic obstructive lung disease, diseases of the circulatory system, kidney disease and diseases associated with ethanol abuse. Also noted were large numbers of gastro-intestinal bleeders, who presented themselves in periodic waves (or so it seemed), yet who came with no evidence of stress-induced disease beyond ethanol abuse. Indeed, only one GI bleeder was encountered who presented with the “classical” pattern. He was a retired senior noncommissioned officer who had begun a second career as a secondary school teacher, which he enjoyed and at which he considered himself successful. One would surmise that his classes were loaded with “tough kids”, for whom his military experience, in the eyes of his superiors, had obviously prepared him to properly control. He was called in to the school superintendent’s office one Friday afternoon and was told in no uncertain terms that his teaching ability was irrelevant and of no concern. His job was to maintain order and if he couldn’t do better at that task, he could submit his resignation on Monday. He presented on Sunday with a massive bleed. No remotely similar situation occurred during the study period. Most striking to note was the very small proportion of patients who had not been hospitalized in the 2 yr period immediately preceding admission. On several occasions, 10 or more weekend admissions to the wards studied yielded not one patient who met the criteria. A large proportion of those interviewed (19 per cent) had had absolutely no life changes in the past year, beyond the minimal 25 LCU’s which the passing of Christmas and perhaps a vacation incurred.
35 30
. h
L.C. U.
Fro. I.-Distribution
scores
of patients’ LCU scores for 6 months prior to admission.
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heretical view
395
The LCU scores of the BVAH sample all tended to be low. The mean LCU score for 1 yr prior to admission was 103 and the median score was 87. These scores are much lower than those reported for any other U.S. hospitalized sample by Holmes, Rahe and their colleagues. There was however, a statistically significant increase of 19 LCU score points between 7-12 and O-6 months prior to admission. Examination of Figs. 1 and 2 shows that while the distribution of
L C U.
FIG. 2.-Distribution
scores
of patients’ LCU scores for 7-12 months prior to admission.
LCU scores for the O-6 and 7-12 month periods prior to admission are essentially exponentially distributed, Fig. 3, the distribution of LCU scores for the year prior to admission is not. This suggests that there were many changes in opposite directions. In fact, of the 88 BVAH patients, 53 (60 per cent) had higher LCU scores in the 6 months preceding admission. However, 33 (38 per cent) patients had lower LCU scores in the 6 months preceding admission and 2 (2 per cent) had no change. Figure 4 shows the distribution of the change in LOU scores between the six months preceding admission and 7-12 months preceding admission of the BVAH sample. The mean of this distribution is +19 but the standard deviation is 70. While the change is statistically significant and in the predicted direction, it is a meaningless number. The standard error of the mean (a = 0.05) covers a range of 275 units running from -118.2 to 157 LCU units. This interval shows that the probability of having a high, positive change in LCU scores immediately prior to admission (say 90 LCU units) is only 0.16. In addition, one could with equal probability say that the mean LCU change immediately preceding admission would be a decrease of 51 LCU units, which would indicate a substantial reduction in life change immediately preceding hospital admission. Chi square tests were run to see if any contingent relationship existed between the variables of color, residence, age, and marital states, and the incidence of high LCU scores for the year prior to admission. High and low LCU scores were defined as above and below the median. No significant relationship was found in any case.
030060
So
I20
150 180 210 240 270 300 3CO+ L.C.
FIG. 3.-Distribution
u. scores
of patients’ LCU scores for 1 yr prior to admission.
HAROLD J. WER~HOWand GEORGE REINHART
396
Medidn value
: _1 I I I
3530-
f 25.g z zo5 2 15g IO2
-t
I II
120 160 200 L.C.U. score* FIG. 4.-Distribution
of the change in patients’ LCU scores between 6 and 7-12 months prior to admission.
We, therefore, must conclude that the BVAH sample, a sample of hospitalized patients, had small magnitudes of life change and no meaningful increase of life change immediately prior to admission. While there is a range of LCU scores of 408 points for the 1 yr period prior to admission, this variation cannot be accounted for on the basis of age, color, residence or marital states. Probably the most surprising fact found in the survey results was the number of subjects who had little or no change in life patterns for the year prior to admission.
DISCUSSION
The various papers employing the SRE use various definitions of high LCU scores. Two papers are in marked disagreement in that respect. Rahe et al. [3] state that “the mean LCU level for the entire sample (a sample of 50 out of 200 Navy and Marine Corps personnel discharged in 1958 because of psychiatric illness diagnosed while on active duty, selected to obtain those with the greatest adjudged disability) was 72 LCU’s per year”.* Rahe and Arthur [4] report “85 LCU’s . . . to give the best approximation of a ‘baseline’ 6-month LCU total that was reportedly concomitant with excellent health status”. This latter is probably an underestimate, as it derives from an equal division of the yearly rate, and one would expect fuller remembrance of recent events than of more distal happenings. The forgetting curve is probably sharpened because the SRE includes many seemingly trivial events: e.g. traffic tickets, family get-togethers, buying an appliance on the instalment plan. In another paper employing the SRE, Wyler et al. [S] claim a “highly significant correlation with chronic illness” and “a negative but insigificant correlation with acute illness”. Yet the BVAH sample, a largely chronically ill population, hospitalized for the first time in 2 yr, had few life changes. Thirty-eight (43 per cent) had less than 72 LCU’s for the year and 63 (72 per cent) had less than 85 LCU’s for the 6 months immediately proximate to hospitalization. Rahe et al. [3] elsewhere claim that the LCU value for serious illness (though all s’s in that study had been discharged from the service for serious psychiatric disability) was 164 units in the prior year. Another study [lo] cites even higher LCU-values. *The distribution of illness in Rahe’s sample [3] proved to be similar to that of the general population, in that a few people have most of the illnesses.
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397
heretical view
Visual inspection of graphs l-3 also evidence that the increase in LCU units in the months immediately preceding hospitalization may be statistically significant, but is obviously of little clinical significance. Further, the graph of changes in LCU’s between O-6 months and 7-12 approaches normality, and large changes (e.g. over 164 yearly LCU units noted above) occur so infrequently that the hypothesis of LCU changes related to illness cannot be confirmed. If it were true that changes in life experience were a major source of stress-induced illness, some common situations would be quite life threatening. Take, for example, a young man or woman who graduates from college, marries, leaves a part-time job waiting on tables for full-time lower-rung professional work, buys a heavily mortgaged home and the wife becomes pregnant, all in one year. Tables 1 and 2 show that TABLET.-LCU’s BUYS A
GAINED BYAYOUNGPERSONWHOGRADUATES,MARRIES, HOME,ANDBECOMESPREGNANTINONB YEAR
LCU’S
Event (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)
Marriage Major change in sleeping habits Major change in eating habits Revision of personal habits Major change in number of family Major change in financial state Change in residence Major change in working hours or Changes to a different line of work Major change in usual type and/or Taking on a mortgage greater than Taking on a mortgage or loan less Major change in social activities Vacation (honeymoon) Christmas
get-togethers
conditions amount of recreation $10,000 than %lO,OOO
Total
50 16 15 24 15 38 ;: 36 19 31 17 18 13 12 344
TABLE2.-INCREASE IN LCU’s ASSOCIATED WITH A YOUNGPERSON Event (16) (17) (18) (19) (20) (21)
LCU’S
Total from Table 1 Sexual difficulties In-law troubles Minor law violations Death of a close friend (e.g. accident or Vietnam war) Trouble with the boss Wife leaving to work outside home Total
344 39 29 11 37 23 26 509
these young people could easily amass from 344-509 LCU’s in one year. Similarly, a young person graduating from high school and going into military service would earn at least 202 LCU’s. Yet one sees no great morbidity figures for young people so situated. A careful review of the relevant literature verifies that the results herein reported are not aberrant, but indeed are quite consistent with previous findings, which when examined critically demonstrate nothing at all. The previous findings contain errors which may be classified into two general categories : improper analysis,
398
HAROLD J. WERSHOWand GEORGEF&INHART
including statistical analysis, and failure to separate very disparate groups within the samples chosen. If we ,add some events not unusual in these circumstances, the total rises dramatically (see Table 2). (1) Improper analysis Many studies are seemingly unaware that in data used, the standard deviations (SD.) are larger than the means (M), sometimes three- and four-times larger; i.e., the data lack central tendency and are randomly distributed. In addition, small coefficients of correlation, which may be statistically significant but which account for only a small proportion of the variance and are of little clinical significance, are blown up entirely out of proportion to their value. Other gaucheries and sins of omission and commission will be commented upon. Rubin et al. [7] (Table 3) comparing illness rates under normal patrol conditions with those during periods when a carrier crew was in active combat off Vietnam, cite S.D.‘s ranging from 2.5 to 7 times the M’s, compared with S.D. about equal to the means while cruising about but without enemy contact. We will later comment on certain special circumstances of the military situation and the myopias exhibited by the papers using military populations. Rubin’s paper does not employ the SRE, but is typical of the school’s neglect of the social structure of military institutions. Nelson et al. [lo] using a modification of the SRE (RLCQ) also report S.D.‘s about equal to or greater than M’s [IO] (Tables 1 and 2) and mentions the significance of “wide variations in crisis levels reported, with 12 of the 20 S.D.‘s larger than the mean values and the remaining distributions demonstrating a large scatter of life changes, with some respondents reporting no changes and others within the same sample reporting numerous changes in significant areas of their lives”. (Does that mean that the data are distributed randomly?) The authors are not thereby deterred from their customary practice of calculating various correlations which account for only a small proportion of the variance. Nonetheless, they are reported as significant to probabilities of O-05, 0.01 or O-001; correlations of O-35, O-40, 0.043 [IO], which account for no more than 12, 16 and 19 per cent, respectively, of the variance are similarly reported as significant. Some of the correlations in Rubin’s paper approach meaningfulness (O-69 and O-74, accounting for 48 and 55 per cent of the variance) but all are indiscriminately taken together. Similarly, Casey et al. [6], seemingly unaware that a sample of 88 physician-residents in a university hospital are a highly selected group from which one cannot generalize without caution, cite Pearson’s r correlations of O-669, 0.638 and 0.744 (which are incidentally in error and should be 0.45, 0.41 and O-55, respectively), accounting for less than 30 per cent of the variance. Correlations are reported to three significant figures in this and several other studies, though the data upon which they are based have only two significant figures. This is a not infrequent error. This paper also confuses reliability of recall with validity. “Consistency of recall” is not necessarily an indirect “reflection of its validity” [6]. Memories may be retained, but are reinterpreted to fit one’s needs at that stage of development. The similarity of memories for events 10 yr earlier with a retest 10 months later tells us only that the forgetting curve drops rapidly to a plateau, rather than “time may not affect the consistency of recall” [6]. Wyler et al. [8] demonstrate the shortcomings of “overly” significant correlations (both as to number of significant
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figures and the usefulness of the numbers), the highest of which is 0.356, accounting for less than 13 per cent of the variance. Spelken and Jacobs [9] use a battery of scales to “predict future illness behavior in college students” in seeking a physician’s care and claim 71 per cent accuracy, though they missed 43 per cent of the students who sought medical care. It must be pointed out that correlation coefficients cannot demonstrate causal relationships; they only reveal patterns of association of data. If causal analysis is to be properly made, then regression analysis or some other additive model must be utilized. Finally all authors have taken an over-simplistic univariate outlook in what is obviously a multi-variate situation. There are many more reactions to stress and life changes than illness and there are many more precedents to illness than stress resulting from life changes. When and only when the gestalt view of the interrelationship between structure and behavior is examined can the true, causal relationship between illness and life changes be understood. In addition to these problems common to several studies, one can cite post-hoc interpretations of results [9, 111, citing “typical” cases [3, 91 which are obviously dramatic, but, from the data presented, hardly modal and going on to make the point that one is more likely to remember the death of a spouse, divorce, separation or having served a term in jail (the study was of 88 resident physicians, and one would marvel at even 40 per cent of those few who were in the calaboose “forgetting” about it) than one would remember a traffic ticket, vacation or change in recreational habits [6]. In addition great persuasiveness is not necessary to establish (in this same paper) that one is more likely to remember life-threatening illnesses than trivial ones. (2) Failure to disaggregate groups Directing one’s efforts to research design, S’s are admittedly often chosen because they happen to be available, and for no other discernible reasons. Spilken and Jacobs [9] state a positive relationship between chronicity of illness and greater life change. It is somewhat ridiculous to include dandruff, eczema and psoriasis as chronic illnesses, along with heart attack, stroke and meningitis, but there were dermatology clinic outpatients around, and their illnesses had to be classified somehow. These are the decisions into which one is almost forced when using “convenience samples” which include both “apples” and “watermelons”, and is stuck with mounds of data gathered with some effort and less thought. Wyler et al. [8] employed 232 s’s, 212 from medical, surgical and psychiatric inpatient services and the outpatient dermatology clinic of a University Hospital, 10 Veterans’ Hospital medical service inpatients (all Caucasian), and 10 gynaecological inpatients from another hospital, 9 of whom were black (the last 10 are then dropped, when they refuse to confirm the hypothesis). Nelson et al. [IO] used 50 V.A. Extended Care Facility patients (i.e. seriously, chronically ill, middle-aged men) 28 veterans in Residential status (i.e., we would have to guess, relatively healthy, destitute men, many with a drinking problem) (mean age 54*7), 6 “Vietnam” patients (mean age 27.17) in a Veteran’s Hospital and 33 female veteran patients (mean age 61.4). Rahe and Arthur [4] used the entire ship’s company of 3 cruisers: draftees, “lifers”, petty officers, lower ranks and officers together with 365 presumably highly motivated officers and men enrolled in a “frogman” training program. One would expect investigators employing military populations as their subjects
400
HAROLD J. WERSHOW and GEORGE REINHART
to be aware of the secondary gains peculiar to the military situation, in which some participants perceive that they must willy-nilly serve a period of time in a setting in which medical care is freely available. Some in this setting prefer hospitalization (or at least medically prescribed “light duty”) to their usual duties, if only as a respite from time to time. In such settings [2, 4, 71, it would be of interest to investigate differences between presumably more and less-motivated groups, to ensure that illness-onset is truly being investigated, rather than “riding the sick book”. One searches in vain for differences between “first-hitch” recruits and frogmen trainees, between lower ranking Enlisted Men and Petty and Commissioned Officers; between older and younger men in lower ranks, between those striking for promotions and the less motivated. Indeed, several studies [2, 7, 91 investigated, not illness behavior, but “official” medical-care seeking behavior. In addition, there are variations in reported illness due to the danger inherent in certain jobs. In a recent report on the mortality of servicemen [13], above-average mortality from accidents and belowaverage from non-accident causes was reported for non-combat servicemen in all branches for all ages, 1966-1971. Thus the danger of injury faced by people in certain jobs is a major factor in determining both the number of physician visits reported and the nature of the illness. If the hypothesis by Rahe, Holmes and their associates was correct, little difference in reported illnesses by type of job should be reported. Examination of data collected by Rubin et al. [7] shows that high accident-risk jobs, deck hands and boiler workers, have much higher illness rates than low accident-risk jobs, medical-dental workers and radio and electronics operators. In fact only high risk jobs had illness rates above the ship’s company mean. However the variable of exposure to accident risk is not considered as a predictor variable by the authors. CONCLUSIONS
This area of psychosomatic when Mendelson noted :
medicine has not advanced significantly since 1956
“there has too long existed among psychosomatic writers an attitude that more clearly resembles the devout believer’s than the sceptical scientist’s. [14] . . . disinterested presentation of all the data available is not always to be found. . . instead, random isolated supporting evidence is sometimes quoted, while the solid mass of experimental and clinical data that contravenes the thesis is ignored [14]“. A decade later, another review of the literature concluded that: “As far as well-substantiated fact can tell us, about all that can be concluded from the various studies is that which was originally assumed: that there is some relationship between psychological stress and physical illness and that the specific relationship between the two depends upon various constitutional, environmental and personality factors which interact in a highly complex and as yet little understood manner [l,]“. One might suggest a moratorium on papers employing the SRE and similar instruments. The point has been amply made that some relationship exists between change in life-ways, let alone stress, and illness. However, the relationship is a weak one. Some people become ill or are hospitalized, and as we have demonstrated, no discernible changes in their life have occurred. Others meet life changes in other ways, some withdraw into sleep, or leave the field in other ways; some may even find
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constructive ways of dealing with change. We would suggest that, among other steps, deviant cases be sought out, those who handle life changes well and those who break down on what seems to be little provocation, to learn more about coping mechanisms. When the mechanisms of successful and unsuccessful coping are known, they can perhaps be taught and then we can really get on to some elements of primary prevention in medicine. Trying to force data into a stronger position than our favorite hypotheses warrant will only lead us further down the current cul-de-sac. Acknowledgemenrs-The authors wish to acknowledge the co-operation of the Birmingham Veterans’ Administration Hospital, Dr. Thomas Sheehy, Chief of Medicine, and the assistance of Mmes Lee Anne Shuler and Nancy Hillman and Mr Keith Marshall who acted as interviewers. REFERENCES 1. HOLMEST. H. and
RAHE
R. H. The social readjustment
rating scale. J. Psychosom. Res. 11, 213
(1967). 2. DOLL R. E., RUBIN R. T. and GVNDERSONE. K. E. Life stress and illness patterns
3. 4. 5.
6. 7.
8. 9. 10.
11. 12. 13. 14. 15.
in the U.S. Navy: II. Demographic variables and illness onset in an attack carrier’s crew. Archs Environ. Hlth 19, 748 (1969). RAHE R. H., MCKEAN J. D. and ARTHURR. J. A longitudinal study of life change and illness. J. Psychosom. Res. 10, 355 (1967). RAHER. H. and ARTHURR. J. Life change patterns surrounding illness experience. J. Psychosom. Res. 11, 341 (1968). Rwr~ R. T., GUNDER~ONE. K. E. and RANSOM J. A. Life stresses and illness patterns in the U.S. Navy-III. Prior life change and illness onset in an attack carrier’s crew. Archs Environ. Hlth. 19,735 (1969). CASEYR. L., MA~UDAM. and HOLMEST. H. Quantitive study of recall of life events. J. Psychosom. Res. 11, 239 (1967). RU~IN R. T., GUNDER~~NE. K. E. and DOLL R. E. Life stress and illness patterns in the U.S. Navy-I. Environmental variables and illness onset in an attack carrier’s crew. Archs Environ. Hlth. 19,740 (1969). WYLERA. R., MA~UDAM. and HOLMEST. H. Magnitude of life events and seriousness of illness. Psychosom. Med. 33, 115 (1971). SPOKEN A. Z. and JACOBSM. A. Prediction of illness behavior from measures of life crisis, manifest distress and maladaptive coping. Psychosom. Med. 33, 251 (1971). NELWN P., MENSCH I. N., HECHT E. and SCHWARTZA. N. Variables in the reporting of recent life changes. J. Psychosom. Res. 16,465 (1972). DOHREMVANDB. S. Life events as stressors: A methodological inquiry, J. Hlth. & Sot. Behav. 14, 167 (1973). MERTONR. K. Social Theory and Social Structure. Free Press, Glencoe, Ill. (1957). Metropolitan Life Insurance Co. Sfntisticul Bulletin 54, 6 (1973). MENDELSONM., HIRXH H. and WEBBERC. S. A critical examination of some recent theoretical models in psychosomatic medicine. Psychosom. Med. 18, 363 (1956). WERSHOWH. J. The balance of mental health and regression, as expressed in the literature of chronic disease and disability. Sot. Serv. Rev. 37, 193 (1963).
Research, Vol. 18, pp. 393 to 401. Pergamon Press, 1974. Printed in Great Britain
LIFE CHANGE AND HOSPITALIZATION-A HERETICAL VIEW* HAROLD
J. WERSHOW and GEORGEREINHAKT (Received 7 March 1974)
began as a didactic exercise designed to demonstrate to often recalcitrant medical students the importance of socio-psychological factors in the etiology of illness. The failure of the demonstration motivated a more intensive review of the relevant literature and the conclusions to which we reluctantly came. We employed the Schedule of Recent Experiences (SRE) [4], which has been developed by Holmes, Rahe and their associates through various minor modifications as the Social Readjustment Rating Scale (SRRS) [l], Recent Life Changes Questionnaire (RLCQ) [lo] and Life Change Inventory (LCI) [9]. This short communication need not review the literature employing that instrument; representative papers can be found in refs. 7-13 of Rubin et al. [5]. A more extensive literature discussing the relationship between various illnesses and psycho-socially stressful situations may be found in Holmes and Rahe [l] refs. 2-13. The didactic effort alluded to was an unsuccessful attempt to employ the SRE to quantify the relationship between social factors and illness; in this case, psycho-social factors (changes in life situation, which are assumed to be associated with the onset of illness) were the independent variables, The SRE notes 43 representative changes in one’s life situation and assigns to each a value in Life Change Units (LCU), ranging from receiving a traffic-ticket (11 LCU’s) to death of a spouse (100 LCU’s). Changes need not be undesirable or involuntary (e.g. marriage, promotions and less in-law troubles are all included). It is claimed that “the greater the individual’s yearly LCU total, the higher becomes his risk of a major health change in the following year”. (3 :355). THIS STUDY
METHODOLOGY In view of the above-noted literature, it was hypothesized that a high proportion of the newly admitted patients to the medical wards of the Birmingham Veterans’ Administration Hospital (BVAH), where the medical school juniors perform some of their clinical clerkships, would have high LCU scores based on the SRE and that the scores would be higher in the 6 months immediately preceding hospitalization than in the 7-12 months prior to hospita1ization.t An attempt was made to interview all male patients admitted to the BVAH, who had not been inpatients in any hospital for the preceding 24 months, that time span being selected as providing a basal period of normal living and relative good health. The SRE was administered to all patients who met the criteria (admission to the medical service and no previous hospitalization in any hospital within the nrecedina 2 vr) on 2 of the 5 (excludina the Intensive Care Unit) medical wards. In addition. the demographic backgrounds of patients were obtained. Employed as interviewers were undergraduate students of sociology, either volunteers or work-study students. The students were trained by one of us (H.J.W.) who had graduate training in and had practiced as a social worker for 15 yr. He also conducted a number of interviews and his results were congruent with those of the students. In addition, a number of the student interviews were taped for verification of interviewing techniques and scoring. There were lapses in the consecutivity of admissions screened for eligibility for the study *From the Department of Sociology and Anthropology, University College, University of Alabama in Birmingham, Birmingham, Alabama 35294, U.S.A. tThe definition of “high” LCU scores will be discussed at a later point. 393
HAROLD J. WERSHOW and GEORGE REINHART
394
and interviewed, due to student examination and holiday periods. Some patients were missed due to discharge after an admission too short to be contacted, illness too severe to permit an interview, obtundedness and death. Upon the advice of the Chief of Service, patients in isolation (usually suspected tuberculars) were excluded, as were the insigniticant number of female patients. There is no reason to believe that the lapses in (interviewing) the consecutivity of admissions or the choice of wards biased the study in any systematic manner. Medical Service patients are admitted to the 5 wards more or less consecutively, keeping the census about even, without regard to age, residence or other discernible factors, and with no selection of diagnoses within the broad area of medicine, as distinguished from psychiatry and surgery. A departure from the usual procedure employing the SRE was in using it as a highly-structured interview schedule and not as a self-administered questionnaire; many patients were barely, if at all, literate and unaccustomed to answering long and relatively complex questionnaires and this choice was forced upon us. RESULTS Between November 1970 and April 1971, 88 patients were interviewed. Some striking impressions were garnered: since these were unanticipated and no records were kept of these data, they are unfor&nately not substantiated with hard numbers. The patients seem to be, however, typical of Veterans’ Administration Hosnital (VAH) natients in any VA General Hospital anywhere in the country. Most are middle aged-and older men (90 per cent-over 40); many had not worked regularly in years. If these long-term chronically-ill men, marginally employed, unemployed or out of the labor force were sufficiently fortunate to have served in the armed forces, they “percolated down” to the VAH system rather than the “charity” medical care system as they become ineligible for, or could not afford, hospitalization insurance. A large proportion of admissions was accounted for by chronic obstructive lung disease, diseases of the circulatory system, kidney disease and diseases associated with ethanol abuse. Also noted were large numbers of gastro-intestinal bleeders, who presented themselves in periodic waves (or so it seemed), yet who came with no evidence of stress-induced disease beyond ethanol abuse. Indeed, only one GI bleeder was encountered who presented with the “classical” pattern. He was a retired senior noncommissioned officer who had begun a second career as a secondary school teacher, which he enjoyed and at which he considered himself successful. One would surmise that his classes were loaded with “tough kids”, for whom his military experience, in the eyes of his superiors, had obviously prepared him to properly control. He was called in to the school superintendent’s office one Friday afternoon and was told in no uncertain terms that his teaching ability was irrelevant and of no concern. His job was to maintain order and if he couldn’t do better at that task, he could submit his resignation on Monday. He presented on Sunday with a massive bleed. No remotely similar situation occurred during the study period. Most striking to note was the very small proportion of patients who had not been hospitalized in the 2 yr period immediately preceding admission. On several occasions, 10 or more weekend admissions to the wards studied yielded not one patient who met the criteria. A large proportion of those interviewed (19 per cent) had had absolutely no life changes in the past year, beyond the minimal 25 LCU’s which the passing of Christmas and perhaps a vacation incurred.
35 30
. h
L.C. U.
Fro. I.-Distribution
scores
of patients’ LCU scores for 6 months prior to admission.
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395
The LCU scores of the BVAH sample all tended to be low. The mean LCU score for 1 yr prior to admission was 103 and the median score was 87. These scores are much lower than those reported for any other U.S. hospitalized sample by Holmes, Rahe and their colleagues. There was however, a statistically significant increase of 19 LCU score points between 7-12 and O-6 months prior to admission. Examination of Figs. 1 and 2 shows that while the distribution of
L C U.
FIG. 2.-Distribution
scores
of patients’ LCU scores for 7-12 months prior to admission.
LCU scores for the O-6 and 7-12 month periods prior to admission are essentially exponentially distributed, Fig. 3, the distribution of LCU scores for the year prior to admission is not. This suggests that there were many changes in opposite directions. In fact, of the 88 BVAH patients, 53 (60 per cent) had higher LCU scores in the 6 months preceding admission. However, 33 (38 per cent) patients had lower LCU scores in the 6 months preceding admission and 2 (2 per cent) had no change. Figure 4 shows the distribution of the change in LOU scores between the six months preceding admission and 7-12 months preceding admission of the BVAH sample. The mean of this distribution is +19 but the standard deviation is 70. While the change is statistically significant and in the predicted direction, it is a meaningless number. The standard error of the mean (a = 0.05) covers a range of 275 units running from -118.2 to 157 LCU units. This interval shows that the probability of having a high, positive change in LCU scores immediately prior to admission (say 90 LCU units) is only 0.16. In addition, one could with equal probability say that the mean LCU change immediately preceding admission would be a decrease of 51 LCU units, which would indicate a substantial reduction in life change immediately preceding hospital admission. Chi square tests were run to see if any contingent relationship existed between the variables of color, residence, age, and marital states, and the incidence of high LCU scores for the year prior to admission. High and low LCU scores were defined as above and below the median. No significant relationship was found in any case.
030060
So
I20
150 180 210 240 270 300 3CO+ L.C.
FIG. 3.-Distribution
u. scores
of patients’ LCU scores for 1 yr prior to admission.
HAROLD J. WER~HOWand GEORGE REINHART
396
Medidn value
: _1 I I I
3530-
f 25.g z zo5 2 15g IO2
-t
I II
120 160 200 L.C.U. score* FIG. 4.-Distribution
of the change in patients’ LCU scores between 6 and 7-12 months prior to admission.
We, therefore, must conclude that the BVAH sample, a sample of hospitalized patients, had small magnitudes of life change and no meaningful increase of life change immediately prior to admission. While there is a range of LCU scores of 408 points for the 1 yr period prior to admission, this variation cannot be accounted for on the basis of age, color, residence or marital states. Probably the most surprising fact found in the survey results was the number of subjects who had little or no change in life patterns for the year prior to admission.
DISCUSSION
The various papers employing the SRE use various definitions of high LCU scores. Two papers are in marked disagreement in that respect. Rahe et al. [3] state that “the mean LCU level for the entire sample (a sample of 50 out of 200 Navy and Marine Corps personnel discharged in 1958 because of psychiatric illness diagnosed while on active duty, selected to obtain those with the greatest adjudged disability) was 72 LCU’s per year”.* Rahe and Arthur [4] report “85 LCU’s . . . to give the best approximation of a ‘baseline’ 6-month LCU total that was reportedly concomitant with excellent health status”. This latter is probably an underestimate, as it derives from an equal division of the yearly rate, and one would expect fuller remembrance of recent events than of more distal happenings. The forgetting curve is probably sharpened because the SRE includes many seemingly trivial events: e.g. traffic tickets, family get-togethers, buying an appliance on the instalment plan. In another paper employing the SRE, Wyler et al. [S] claim a “highly significant correlation with chronic illness” and “a negative but insigificant correlation with acute illness”. Yet the BVAH sample, a largely chronically ill population, hospitalized for the first time in 2 yr, had few life changes. Thirty-eight (43 per cent) had less than 72 LCU’s for the year and 63 (72 per cent) had less than 85 LCU’s for the 6 months immediately proximate to hospitalization. Rahe et al. [3] elsewhere claim that the LCU value for serious illness (though all s’s in that study had been discharged from the service for serious psychiatric disability) was 164 units in the prior year. Another study [lo] cites even higher LCU-values. *The distribution of illness in Rahe’s sample [3] proved to be similar to that of the general population, in that a few people have most of the illnesses.
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heretical view
Visual inspection of graphs l-3 also evidence that the increase in LCU units in the months immediately preceding hospitalization may be statistically significant, but is obviously of little clinical significance. Further, the graph of changes in LCU’s between O-6 months and 7-12 approaches normality, and large changes (e.g. over 164 yearly LCU units noted above) occur so infrequently that the hypothesis of LCU changes related to illness cannot be confirmed. If it were true that changes in life experience were a major source of stress-induced illness, some common situations would be quite life threatening. Take, for example, a young man or woman who graduates from college, marries, leaves a part-time job waiting on tables for full-time lower-rung professional work, buys a heavily mortgaged home and the wife becomes pregnant, all in one year. Tables 1 and 2 show that TABLET.-LCU’s BUYS A
GAINED BYAYOUNGPERSONWHOGRADUATES,MARRIES, HOME,ANDBECOMESPREGNANTINONB YEAR
LCU’S
Event (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)
Marriage Major change in sleeping habits Major change in eating habits Revision of personal habits Major change in number of family Major change in financial state Change in residence Major change in working hours or Changes to a different line of work Major change in usual type and/or Taking on a mortgage greater than Taking on a mortgage or loan less Major change in social activities Vacation (honeymoon) Christmas
get-togethers
conditions amount of recreation $10,000 than %lO,OOO
Total
50 16 15 24 15 38 ;: 36 19 31 17 18 13 12 344
TABLE2.-INCREASE IN LCU’s ASSOCIATED WITH A YOUNGPERSON Event (16) (17) (18) (19) (20) (21)
LCU’S
Total from Table 1 Sexual difficulties In-law troubles Minor law violations Death of a close friend (e.g. accident or Vietnam war) Trouble with the boss Wife leaving to work outside home Total
344 39 29 11 37 23 26 509
these young people could easily amass from 344-509 LCU’s in one year. Similarly, a young person graduating from high school and going into military service would earn at least 202 LCU’s. Yet one sees no great morbidity figures for young people so situated. A careful review of the relevant literature verifies that the results herein reported are not aberrant, but indeed are quite consistent with previous findings, which when examined critically demonstrate nothing at all. The previous findings contain errors which may be classified into two general categories : improper analysis,
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HAROLD J. WERSHOWand GEORGEF&INHART
including statistical analysis, and failure to separate very disparate groups within the samples chosen. If we ,add some events not unusual in these circumstances, the total rises dramatically (see Table 2). (1) Improper analysis Many studies are seemingly unaware that in data used, the standard deviations (SD.) are larger than the means (M), sometimes three- and four-times larger; i.e., the data lack central tendency and are randomly distributed. In addition, small coefficients of correlation, which may be statistically significant but which account for only a small proportion of the variance and are of little clinical significance, are blown up entirely out of proportion to their value. Other gaucheries and sins of omission and commission will be commented upon. Rubin et al. [7] (Table 3) comparing illness rates under normal patrol conditions with those during periods when a carrier crew was in active combat off Vietnam, cite S.D.‘s ranging from 2.5 to 7 times the M’s, compared with S.D. about equal to the means while cruising about but without enemy contact. We will later comment on certain special circumstances of the military situation and the myopias exhibited by the papers using military populations. Rubin’s paper does not employ the SRE, but is typical of the school’s neglect of the social structure of military institutions. Nelson et al. [lo] using a modification of the SRE (RLCQ) also report S.D.‘s about equal to or greater than M’s [IO] (Tables 1 and 2) and mentions the significance of “wide variations in crisis levels reported, with 12 of the 20 S.D.‘s larger than the mean values and the remaining distributions demonstrating a large scatter of life changes, with some respondents reporting no changes and others within the same sample reporting numerous changes in significant areas of their lives”. (Does that mean that the data are distributed randomly?) The authors are not thereby deterred from their customary practice of calculating various correlations which account for only a small proportion of the variance. Nonetheless, they are reported as significant to probabilities of O-05, 0.01 or O-001; correlations of O-35, O-40, 0.043 [IO], which account for no more than 12, 16 and 19 per cent, respectively, of the variance are similarly reported as significant. Some of the correlations in Rubin’s paper approach meaningfulness (O-69 and O-74, accounting for 48 and 55 per cent of the variance) but all are indiscriminately taken together. Similarly, Casey et al. [6], seemingly unaware that a sample of 88 physician-residents in a university hospital are a highly selected group from which one cannot generalize without caution, cite Pearson’s r correlations of O-669, 0.638 and 0.744 (which are incidentally in error and should be 0.45, 0.41 and O-55, respectively), accounting for less than 30 per cent of the variance. Correlations are reported to three significant figures in this and several other studies, though the data upon which they are based have only two significant figures. This is a not infrequent error. This paper also confuses reliability of recall with validity. “Consistency of recall” is not necessarily an indirect “reflection of its validity” [6]. Memories may be retained, but are reinterpreted to fit one’s needs at that stage of development. The similarity of memories for events 10 yr earlier with a retest 10 months later tells us only that the forgetting curve drops rapidly to a plateau, rather than “time may not affect the consistency of recall” [6]. Wyler et al. [8] demonstrate the shortcomings of “overly” significant correlations (both as to number of significant
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399
figures and the usefulness of the numbers), the highest of which is 0.356, accounting for less than 13 per cent of the variance. Spelken and Jacobs [9] use a battery of scales to “predict future illness behavior in college students” in seeking a physician’s care and claim 71 per cent accuracy, though they missed 43 per cent of the students who sought medical care. It must be pointed out that correlation coefficients cannot demonstrate causal relationships; they only reveal patterns of association of data. If causal analysis is to be properly made, then regression analysis or some other additive model must be utilized. Finally all authors have taken an over-simplistic univariate outlook in what is obviously a multi-variate situation. There are many more reactions to stress and life changes than illness and there are many more precedents to illness than stress resulting from life changes. When and only when the gestalt view of the interrelationship between structure and behavior is examined can the true, causal relationship between illness and life changes be understood. In addition to these problems common to several studies, one can cite post-hoc interpretations of results [9, 111, citing “typical” cases [3, 91 which are obviously dramatic, but, from the data presented, hardly modal and going on to make the point that one is more likely to remember the death of a spouse, divorce, separation or having served a term in jail (the study was of 88 resident physicians, and one would marvel at even 40 per cent of those few who were in the calaboose “forgetting” about it) than one would remember a traffic ticket, vacation or change in recreational habits [6]. In addition great persuasiveness is not necessary to establish (in this same paper) that one is more likely to remember life-threatening illnesses than trivial ones. (2) Failure to disaggregate groups Directing one’s efforts to research design, S’s are admittedly often chosen because they happen to be available, and for no other discernible reasons. Spilken and Jacobs [9] state a positive relationship between chronicity of illness and greater life change. It is somewhat ridiculous to include dandruff, eczema and psoriasis as chronic illnesses, along with heart attack, stroke and meningitis, but there were dermatology clinic outpatients around, and their illnesses had to be classified somehow. These are the decisions into which one is almost forced when using “convenience samples” which include both “apples” and “watermelons”, and is stuck with mounds of data gathered with some effort and less thought. Wyler et al. [8] employed 232 s’s, 212 from medical, surgical and psychiatric inpatient services and the outpatient dermatology clinic of a University Hospital, 10 Veterans’ Hospital medical service inpatients (all Caucasian), and 10 gynaecological inpatients from another hospital, 9 of whom were black (the last 10 are then dropped, when they refuse to confirm the hypothesis). Nelson et al. [IO] used 50 V.A. Extended Care Facility patients (i.e. seriously, chronically ill, middle-aged men) 28 veterans in Residential status (i.e., we would have to guess, relatively healthy, destitute men, many with a drinking problem) (mean age 54*7), 6 “Vietnam” patients (mean age 27.17) in a Veteran’s Hospital and 33 female veteran patients (mean age 61.4). Rahe and Arthur [4] used the entire ship’s company of 3 cruisers: draftees, “lifers”, petty officers, lower ranks and officers together with 365 presumably highly motivated officers and men enrolled in a “frogman” training program. One would expect investigators employing military populations as their subjects
400
HAROLD J. WERSHOW and GEORGE REINHART
to be aware of the secondary gains peculiar to the military situation, in which some participants perceive that they must willy-nilly serve a period of time in a setting in which medical care is freely available. Some in this setting prefer hospitalization (or at least medically prescribed “light duty”) to their usual duties, if only as a respite from time to time. In such settings [2, 4, 71, it would be of interest to investigate differences between presumably more and less-motivated groups, to ensure that illness-onset is truly being investigated, rather than “riding the sick book”. One searches in vain for differences between “first-hitch” recruits and frogmen trainees, between lower ranking Enlisted Men and Petty and Commissioned Officers; between older and younger men in lower ranks, between those striking for promotions and the less motivated. Indeed, several studies [2, 7, 91 investigated, not illness behavior, but “official” medical-care seeking behavior. In addition, there are variations in reported illness due to the danger inherent in certain jobs. In a recent report on the mortality of servicemen [13], above-average mortality from accidents and belowaverage from non-accident causes was reported for non-combat servicemen in all branches for all ages, 1966-1971. Thus the danger of injury faced by people in certain jobs is a major factor in determining both the number of physician visits reported and the nature of the illness. If the hypothesis by Rahe, Holmes and their associates was correct, little difference in reported illnesses by type of job should be reported. Examination of data collected by Rubin et al. [7] shows that high accident-risk jobs, deck hands and boiler workers, have much higher illness rates than low accident-risk jobs, medical-dental workers and radio and electronics operators. In fact only high risk jobs had illness rates above the ship’s company mean. However the variable of exposure to accident risk is not considered as a predictor variable by the authors. CONCLUSIONS
This area of psychosomatic when Mendelson noted :
medicine has not advanced significantly since 1956
“there has too long existed among psychosomatic writers an attitude that more clearly resembles the devout believer’s than the sceptical scientist’s. [14] . . . disinterested presentation of all the data available is not always to be found. . . instead, random isolated supporting evidence is sometimes quoted, while the solid mass of experimental and clinical data that contravenes the thesis is ignored [14]“. A decade later, another review of the literature concluded that: “As far as well-substantiated fact can tell us, about all that can be concluded from the various studies is that which was originally assumed: that there is some relationship between psychological stress and physical illness and that the specific relationship between the two depends upon various constitutional, environmental and personality factors which interact in a highly complex and as yet little understood manner [l,]“. One might suggest a moratorium on papers employing the SRE and similar instruments. The point has been amply made that some relationship exists between change in life-ways, let alone stress, and illness. However, the relationship is a weak one. Some people become ill or are hospitalized, and as we have demonstrated, no discernible changes in their life have occurred. Others meet life changes in other ways, some withdraw into sleep, or leave the field in other ways; some may even find
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constructive ways of dealing with change. We would suggest that, among other steps, deviant cases be sought out, those who handle life changes well and those who break down on what seems to be little provocation, to learn more about coping mechanisms. When the mechanisms of successful and unsuccessful coping are known, they can perhaps be taught and then we can really get on to some elements of primary prevention in medicine. Trying to force data into a stronger position than our favorite hypotheses warrant will only lead us further down the current cul-de-sac. Acknowledgemenrs-The authors wish to acknowledge the co-operation of the Birmingham Veterans’ Administration Hospital, Dr. Thomas Sheehy, Chief of Medicine, and the assistance of Mmes Lee Anne Shuler and Nancy Hillman and Mr Keith Marshall who acted as interviewers. REFERENCES 1. HOLMEST. H. and
RAHE
R. H. The social readjustment
rating scale. J. Psychosom. Res. 11, 213
(1967). 2. DOLL R. E., RUBIN R. T. and GVNDERSONE. K. E. Life stress and illness patterns
3. 4. 5.
6. 7.
8. 9. 10.
11. 12. 13. 14. 15.
in the U.S. Navy: II. Demographic variables and illness onset in an attack carrier’s crew. Archs Environ. Hlth 19, 748 (1969). RAHE R. H., MCKEAN J. D. and ARTHURR. J. A longitudinal study of life change and illness. J. Psychosom. Res. 10, 355 (1967). RAHER. H. and ARTHURR. J. Life change patterns surrounding illness experience. J. Psychosom. Res. 11, 341 (1968). Rwr~ R. T., GUNDER~ONE. K. E. and RANSOM J. A. Life stresses and illness patterns in the U.S. Navy-III. Prior life change and illness onset in an attack carrier’s crew. Archs Environ. Hlth. 19,735 (1969). CASEYR. L., MA~UDAM. and HOLMEST. H. Quantitive study of recall of life events. J. Psychosom. Res. 11, 239 (1967). RU~IN R. T., GUNDER~~NE. K. E. and DOLL R. E. Life stress and illness patterns in the U.S. Navy-I. Environmental variables and illness onset in an attack carrier’s crew. Archs Environ. Hlth. 19,740 (1969). WYLERA. R., MA~UDAM. and HOLMEST. H. Magnitude of life events and seriousness of illness. Psychosom. Med. 33, 115 (1971). SPOKEN A. Z. and JACOBSM. A. Prediction of illness behavior from measures of life crisis, manifest distress and maladaptive coping. Psychosom. Med. 33, 251 (1971). NELWN P., MENSCH I. N., HECHT E. and SCHWARTZA. N. Variables in the reporting of recent life changes. J. Psychosom. Res. 16,465 (1972). DOHREMVANDB. S. Life events as stressors: A methodological inquiry, J. Hlth. & Sot. Behav. 14, 167 (1973). MERTONR. K. Social Theory and Social Structure. Free Press, Glencoe, Ill. (1957). Metropolitan Life Insurance Co. Sfntisticul Bulletin 54, 6 (1973). MENDELSONM., HIRXH H. and WEBBERC. S. A critical examination of some recent theoretical models in psychosomatic medicine. Psychosom. Med. 18, 363 (1956). WERSHOWH. J. The balance of mental health and regression, as expressed in the literature of chronic disease and disability. Sot. Serv. Rev. 37, 193 (1963).