Screening for Vulnerability to Abuse Among Older Women: Women s Health Australia Study

Transcription

1 Journal Schofield et Applied al. / Abuse Gerontology Among Older Women Screening for Vulnerability to Abuse Among Older Women: Women s Health Australia Study Margot J. Schofield University of New England Rhonda Reynolds Gita D. Mishra Jennifer R. Powers Annette J. Dobson University of Newcastle The validity of a brief self-report screening measure for elder abuse was examined on a nationally representative sample of more than 12,000 older women in the baseline survey of the Australian Longitudinal Study on Women s Health. The screening instrument was a modification of the Hwalek-Sengstock Elder Abuse Screening Test. Construct validity was examined using factor analysis and correlation with a wide range of sociodemographic, psychological, and healthrelated variables. Four factors, each of three items, were identified representing the following domains: Vulnerability, Dependence, Dejection, and Coercion. The Vulnerability and Coercion factors had the highest face validity for abuse and demonstrated moderate to good construct validity. The six items comprising these factors may provide a simple screening tool for elder abuse. The identified correlates of abuse indicators have the potential to enhance policy development, screening, intervention, and carer support programs. Elder abuse has been recognized worldwide as an important social health issue, although it is only during the past decade that it has received serious attention as a form of family violence (Dunn, 1995; Podnieks, 1992; Sadler & Kurrle, 1993). As with other forms of family violence, elder abuse goes largely undetected by service providers (Hamberger & Ambuel, 1997; Kurrle, Sadler, Lockwood, & Cameron, 1997). The invisibility of the problem AUTHORS NOTE: The Australian Longitudinal Study on Women s Health, which was conceived and developed by groups of interdisciplinary researchers at the Universities of Newcastle and Queensland, is funded by the Commonwealth Department of Health and Aged Care. We thank Anne Young and Brendan Goodger for their valuable contribution to the article. The Journal of Applied Gerontology, Vol. 21 No. 1, March The Southern Gerontological Society 24

2 Schofield et al. / Abuse Among Older Women 25 may be in part due to a lack of consensus about a definition of elder abuse. In addition, its most common forms are less obvious than the more familiar forms of physical and sexual abuse against women. Reis and Nahmiash (1998) identified four key forms of abuse against older people: physical abuse (e.g., striking, restraining), psychosocial abuse (e.g., insulting, isolating), material/financial abuse (e.g., theft, misuse of property), and neglect (e.g., not providing medical care, lack of supervision), whether intentional or not. Psychological abuse has been identified as the most common form of elder abuse in Australia, followed by physical abuse, neglect, and financial abuse (Kurrle et al., 1997). Despite growing awareness of the magnitude of this problem, there is a paucity of methodologically sound research on risk factors for abuse or the long-term health implications of abuse. Three clusters of risk factors have been identified by Reis and Nahmiash (1998). The first relates to the personal characteristics of the abusive caregiver (e.g., alcohol or other substance abuse, depression or personality disorder, other mental health problems, behavioral problems, and inexperience or reluctance to give care). The second cluster involves the interpersonal characteristics of the abusive caregiver (e.g., poor relationships, current marital and family conflict, lack of empathy/understanding of care receiver, and financial dependence on the care recipient). The third cluster relates to characteristics of the abused care receiver (e.g., abuse in the past, lack of social support). Most screening instruments are interviewer administered rather than self-reported. They are designed to evaluate quality of caregiving rather than detect family-mediated elder mistreatment (e.g., Bravo, Girouard, Gosselin, Archambault, & Dubois, 1995), identify abusive caregivers of older people (Reis & Nahmiash, 1995), or help health professionals to detect problems (Bloom, Ansell, & Bloom, 1989; Reis & Nahmiash, 1998). The Hwalek-Sengstock Elder Abuse Screening Test (H-S/EAST) was developed in the United States to provide a brief and easily self-administered screening instrument to determine an individual s risk of elder abuse. It was designed to be completed by older people on themselves and is the only self-report measure identified in the literature. Preliminary validation of this scale has been reported (Neale, Hwalek, Scott, Sengstock, & Stahl, 1991); however, this work has not been extended beyond the original validation samples. In this article, we report the development of a screening measure for identifying older women at risk of elder abuse within the context of the Australian Longitudinal Study on Women s Health, also known as the Women s Health Australia (WHA) study. This study is designed to track the health of three age

3 26 Journal of Applied Gerontology cohorts of women over a period of up to 20 years (Brown et al., 1996). We examine the reliability and face and construct validity of an instrument based on the H-S/EAST with some additional items. We also document the characteristics of those women with higher risk scores for abuse. Method The WHA study began with a mailed baseline survey in The sampling frame was approximately 380,000 women in the database of Medicare, the national health insurance system that includes all residents in Australia, and is the best available sampling frame for the whole Australian population. For the oldest cohort, women aged 70 to 75 years were randomly selected, with intentional oversampling from rural and remote areas. Participants A total of 12,939 older women responded. Of these women, 12,340 (35% of those invited to participate) provided data for the main variables considered in this article. Confidentiality requirements for use of the Medicare database meant that the study team did not know the names or contact details of the women selected until they gave written informed consent to participate. Thus, many of the usual methods to encourage participation were not possible. Telephone interviews were provided for women who could not complete the survey on their own. Surveys were completed by family members, friends, or carers for some women with impairments. The demographic and social characteristics of respondents are broadly representative of all women in Australia, with some overrepresentation of women with higher levels of education (Brown et al., 1998). Measures The baseline survey was a 260-item self-report questionnaire. Selected variables were used in the analyses reported in this article. Demographic items included age; marital status; main occupation during working life for the woman and, where applicable, her spouse; highest level of education completed; country of birth; language spoken at home; area of residence (ranging from state capital city to remote area); state/territory of residence; type of housing; home ownership; and ability to manage on available income.

4 Schofield et al. / Abuse Among Older Women 27 The H-S/EAST is a 15-item measure that is reported to assess the risk of elder abuse on three dimensions: violations of personal rights or direct abuse, characteristics of vulnerability, and potentially abusive situations. The scale was developed from more than 100 items selected from various elder abuse screening instruments (Hwalek & Sengstock, 1986). Construct validity has been shown in small clinical populations in North America (Neale et al., 1991), with a score of 3 or more reflecting higher risk of being abused, neglected, or exploited. Two additional questions with high face validity were included: Has anyone close to you called you names or put you down or made you feel bad recently? (from Conflict Tactics Scale by Straus, 1979) and Are you afraid of anyone in your family? (McFarlane, Parker, Soeken, & Bullock, 1992). Participants were also asked, Have you ever been in a violent relationship with a spouse/partner? Participants were asked if a doctor had ever told them that they had any of 15 chronic health problems, such as diabetes or asthma. Affirmative responses were summed to give a total score for the number of chronic conditions. Acute symptoms were assessed by asking participants if, in the past 12 months, they had had any of 23 symptoms, such as allergies/hayfever/sinusitis, stiff or painful joints, or difficulty sleeping. Responses of sometimes or often were summed to give a total score for current symptoms. The women also completed the Medical Outcomes Study Health Survey Short-Form (SF-36) (Ware, Kosinski, & Keller, 1994), a widely used and validated measure of health-related quality of life. The physical and mental health component summary scores (PCS and MCS) calculated from the SF-36 were standardized using the cohort means for the WHA (Mishra & Schofield, 1998). Participants were asked how many times they had consulted a family doctor or various other medical or alternative health practitioners for their own health in the past 12 months. They were also asked if they had been admitted to a hospital in the past 12 months or were on a hospital waiting list and whether they had private hospital insurance. Medication use in the past 4 weeks was assessed by questions about medications that were prescribed by a doctor or bought without a prescription, and medications for specific conditions such as nerves or sleeping difficulties or for chronic illnesses. Current smoking status was categorized as smoker or nonsmoker. Current alcohol consumption was categorized as nondrinker or drinker. Self-reported weight and height were used to estimate body mass index (BMI), calculated by weight in kilograms divided by the square of height in meters, corrected for self-reporting bias (Waters, 1993). The 11-item Duke Social Support Index (DSSI) was used to assess overall support, with two subscales measuring social interaction and level of satisfaction

5 28 Journal of Applied Gerontology with support (Koenig et al., 1993). Respondents were also asked who lived with them (including partner/spouse, children, other relatives, and nonfamily members). They were asked if they regularly provided care or assistance to other people because of their long-term illness, disability, or frailty. In addition, they were asked if they themselves needed regular help with daily tasks because of long-term illness, disability, or frailty. Those who needed help were asked about their level of satisfaction with the help they received. The women were asked how stressed they had felt over the past 12 months about various aspects of their lives, and a mean stress score was calculated for each respondent. They were asked to identify, from a list of 24 life events, those they had experienced in the past 12 months; their responses were summed to give a life events score. The women were also asked to rate their satisfaction with various aspects of life, such as work, family relationships, and friendships and their responses were averaged to provide a mean life satisfaction score between 1 and 4. Statistical Analysis Exploratory factor analysis using the method of principal components and varimax rotation was performed on the 17 items measuring aspects of elder abuse. Items that cross-loaded on several factors were subsequently eliminated. Interitem reliability for each factor was assessed using Cronbach s alpha coefficients for standardized variables. Kaiser s measure of sampling adequacy (MSA) was used to quantify the degree of intercorrelations among the items. The appropriateness of the factor analysis was assessed by the percentage of variance explained and by communalities that show the amount of variance each item shares with all other items (Hair, Anderson, Tatham, & Black, 1997). To assess construct validity, scores on each of the identified factors were compared with other variables plausibly related to vulnerability to elder abuse. It was hypothesized that each of the factors would be negatively correlated with the MCS of the SF-36, two dimensions of the DSSI and life satisfaction scores. Positive correlations were hypothesized between abuse related factors and the need for help with daily tasks, dissatisfaction with the help received, mean stress score, and the number of life events experienced. In contrast, it was hypothesized that there would be no associations with BMI or height. Pearson correlation coefficients were used to determine association. To reduce the effects of inflated Type 1 errors due to multiple comparisons and the large sample size, the level of statistical significance was set at.005 (Neter, Kutner, Nachtsheim, & Wasserman, 1996). All analyses were performed using SAS (SAS Institute Inc., 1989).

6 Schofield et al. / Abuse Among Older Women 29 Results Exploratory factor analysis led to the deletion of 5 of the 17 items, all from the original H-S/EAST. Who makes decisions about your life? ( someone else, prevalence 4.8%) was deleted due to a relatively high proportion of missing data (5.1% vs. 1.6% to 2.6% for other items). Do you have anyone who spends time with you, taking you shopping or to a doctor? ( yes, 45.8%), Are you helping to support someone? ( yes, 9.1%), Does anyone in your family drink a lot of alcohol? ( yes, 9.8%), and Does anyone tell you that you give them too much trouble? ( yes, 2.1%) were deleted due to cross loading on different factors. Table 1 shows the resulting four factors, each of three items, interpreted as Vulnerability, Dependence, Dejection, and Coercion. They accounted for 50% of the total variance. The overall sampling adequacy for the analysis of the four scales was reasonable with MSA = The Cronbach coefficients ranged from 0.39 to 0.55, indicating moderate internal reliability appropriate for a brief screening instrument, because higher coefficients can be obtained simply by using more items in each factor (Streiner & Norman, 1995). The communalities ranged from 0.35 to 0.61, indicating that items shared a reasonable amount of variance with all the other items. The percentages of positive responses to each item are also provided in Table 1. For the first factor, Vulnerability, 1% to 6% of older women reported having experienced the single item indicators. Prevalence was 6% to 9%, 3% to 15%, and 1% to 4% for Dependence, Dejection, and Coercion factor items, respectively. Construct validity was assessed by correlations between the factor scores and other variables hypothesized to be associated with abuse. Table 2 presents the statistically significant correlations, which were all in the direction hypothesized except for the negative correlation between the factor Vulnerability and needing help with daily tasks. The factor Dejection was correlated with all the postulated variables, whereas associations for the other three factors were more specific. Dependence was associated with needing help and dissatisfaction with help received but was not consistently associated with any demographic or health status characteristics or use of health services. Both Vulnerability and Coercion were positively correlated with stress and number of life events and negatively correlated with the DSSI subscale for satisfaction with support. Variables that were not associated with any of the four factors are not included in the table. The number of life events was significantly associated with Vulnerability, Dejection, and Coercion. All life events were significantly associated with

7 30 Table 1. Factor Loadings, Factor Scores Coefficients, Cumulative Percentage of Variation and Internal Reliability Estimated From Responses From 12,340 Women Aged 70 to 75 Years Factor Loadings Item Percentage b Vulnerability Dependence Dejection Coercion Communality Are you afraid of anyone in your family? (0.52) Has anyone close to you tried to hurt you or harm you recently? (0.48) Has anyone close to you called you names or put you down or made you feel bad recently? (0.39) Do you have enough privacy at home? a (0.49) Do you trust most of the people in your family? a (0.49) Can you take your own medication and get around by yourself? a (0.38) Are you sad or lonely often? (0.61) Do you feel that nobody wants you around? (0.42) Do you feel uncomfortable with anyone in your family? (0.37) Does someone in your family make you stay in bed or tell you you re sick when you know you re not? (0.60) Has anyone forced you to do things you didn t want to do? (0.51)

8 Has anyone taken things that belong to you without your OK? (0.40) Cumulative percentage of variation explained (in percentages) Cronbach s alpha NOTE: The items that contribute most to each factor are shown in bold, and factor scores (in parentheses) are given for these items only. a. Item responses reversed for coding. b. Results are given as unweighted percentages. 31

9 32 Journal of Applied Gerontology Table 2. Construct Validity: Correlations and p Values for Factor Scores and Other Variables Hypothesized to be Associated (or Not Associated a ) With Factors for 12,340 Women Aged 70 to 75 Years Item Vulnerability Dependence Dejection Coercion SF-36 physical health 0.13 component score (< 0.001) SF-36 mental health 0.43 component score (< 0.001) Life event summary score (< 0.001) (< 0.001) (< 0.001) Stress score 0.12 (< 0.001) 0.42 (< 0.001) 0.04 (< 0.001) Life satisfaction score (< 0.001) (< 0.001) Duke Social Support Index Social interaction 0.16 (< 0.001) Satisfied with support (< 0.001) (< 0.001) (< 0.001) (0.001) Dissatisfied with available help (< 0.001) (< 0.001) Need help with daily tasks (0.003) (< 0.001) (< 0.001) Height a Body mass index a NOTE: SF-36 = Medical Outcomes Study Health Survey Short-Form. Only statistically significant results with p <.005 are shown. a. Hypothesized to be unrelated. Dejection, but both Vulnerability and Coercion demonstrated more specific relationships to life events. Table 3 summarizes the statistically significant differences in scores for Vulnerability and Coercion among women who experienced each life event and those who did not. The results provide evidence of the content validity of these factors. The relationships of Vulnerability to other demographic and healthrelated variables are summarized in Table 4. Vulnerability was related to country of birth, marital status, living arrangements, providing care for others, having ever been in a violent relationship, and more visits to medical specialists. Table 5 shows that women who had higher scores on Dejection had lower socioeconomic status and experienced more adverse life events in the past 12 months. Coercion showed similar, although weaker, associations to those for

10 Schofield et al. / Abuse Among Older Women 33 Table 3. Relationship Between Factors and Life Events Occurring During the Last 12 Months In the last 12 months, have you experienced any of the following events? Vulnerability Coercion Major personal illness Major personal injury Major surgery (not including dental work) Major decline in health of spouse or partner Major decline in health of other close family member or close friend yes > no** Starting a new, close personal relationship yes > no* Break-up of a close personal relationship yes > no** Major conflict with children yes > no** Death of spouse or partner no > yes** Death of child Death of other close family member Death of close friend yes > no* Major personal achievement yes > no* Decreased income yes > no** Moving house Natural disaster (fire, flood, drought, earthquake, etc.) or house fire Major loss or damage to personal property yes > no** Being robbed yes > no** Involvement in a serious accident A fall that caused serious injury Being pushed, grabbed, shoved, kicked, or hit yes > no** yes > no* Being forced to take part in unwanted sexual activity yes > no* Legal troubles or involved in a court case yes > no** yes > no** Family member/close friend being arrested/in jail yes > no** NOTE: The factor Dejection was statistically significantly related to each life event; the factor Dependence was not statistically significantly related to any life event; yes > no means the factor scores were statistically significantly higher among women who experienced the life event than those who did not. *.001 < p <.005. **p <.001. Dejection and so the results are not reported here. Dependence was unrelated to any of these variables. Discussion Methodological strengths of this study include the magnitude, diversity, and demographic representativeness of the sample; use of sound statistical

11 34 Journal of Applied Gerontology Table 4. Demographic and Health-Related Characteristics Consistently and Statistically Significantly Associated With the Factor Vulnerability Lower to Higher Scores a p Value b Country of birth Australia Asia, Europe <.001 Marital status Widowed, never De facto, <.001 married separated Home ownership Self, other family; Spouse/partner, <.001 self and others joint self and spouse/partner Living arrangements Live alone Live with spouse/ <.001 partner Provide care for others No Yes <.001 Ever in a violent relationship No Yes <.001 Visits to specialists None, few Five or more.004 a. Women with characteristics in the left column had lower scores for Vulnerability than those in the right column. b. p value for ANOVA or t test. methods to examine the reliability; and validity of the screening instrument and inclusion of a variety of demographic, social, psychological, and healthrelated variables in the analysis. Furthermore, WHA is a longitudinal study allowing this cohort of older women to be followed prospectively to determine longer term health outcomes for women at risk of abuse as well as detecting changes in risk over time. This is important because previous research suggests that elder abuse increases dramatically with age above 80 years (National Center on Elder Abuse at the American Public Human Services Association [NCEA], 1998). A major limitation of the current study is the lack of a gold standard to test the sensitivity and specificity of the screening instrument. Despite this limitation, the development of a self-report measure was considered important because objective measures of abuse are difficult to obtain, except in the case of severe physical abuse resulting in the need for medical treatment. Even then, familial abuse may not be recognized by medical practitioners or hospital staff (Roberts, Lawrence, O Toole, & Raphael, 1997). Limitations of the self-report methodology include the possibility of discrepant perceptions, faulty recall, and respondent unwillingness to report abuse in the face of social desirability pressures (Rosenbaum, 1988). The potential for misperceptions was reduced by the use of questions focusing on specific and concrete behaviors, such as being pushed, shoved, hit, or kicked.

12 Schofield et al. / Abuse Among Older Women 35 Table 5. Demographic and Health Related Characteristics Consistently and Statistically Significantly Associated With the Dejection Factor Lower to Higher Scores a Country of birth Australia Europe Language English Non-English Marital status Married, never married Separated Occupation and spouse s Professional, manager Manual worker/ occupation machine operator Housing House Flat/unit/other Home ownership Spouse/partner joint, Self, other family, self self and spouse/ and others, and partner others Manage on income Easy Difficult/impossible Life events score No Drink alcohol No Yes Current smoker No Yes Ever in a violent relationship No Yes Have private health insurance Yes No Visits to doctors and other None, few More health care providers Prescription and over-the- None Two or more counter medicine Medications used for nerves, No Yes sleep, chronic illness Number of chronic conditions None, few Four or more Number of symptoms None, few Seven or more NOTE: All p values for ANOVA, t test, or Pearson correlation coefficient <.001. a. Women with characteristics in the left column had lower scores for Dejection than those in the right column. A further limitation of the study is the low response rate. However, comparisons with the Australian 1996 census data show that the sample was largely representative of Australian women in this age group, with some bias toward lower representation of less educated women. Education level was not associated with any of the four factors identified; therefore, this sampling error is unlikely to have a major impact on the findings. The four factors we identified through exploratory factor analysis had three items each. The three items comprising Vulnerability, singularly or together, provide face validity as a measure of susceptibility to elder abuse. This factor includes one of the original H-S/EAST abuse items, Has anyone close to you tried to hurt you or harm you recently? and two new items, Are

13 36 Journal of Applied Gerontology you afraid of anyone in your family? and Has anyone close to you called you names or put you down or made you feel bad recently? The factor showed good construct validity, being related to a wide range of hypothesized variables, and it had good discriminant validity for life events. Vulnerability was also associated with having ever been in a violent relationship, supporting earlier findings that past history of domestic abuse was related to elder abuse (Reis & Nahmiash, 1998). This factor is a clear indicator of risk of abuse (covering physical, verbal, and emotional abuse). Coercion, like Vulnerability, appears to measure physical and psychological abuse. It was related to fewer variables, but it did demonstrate reasonably good discrimination. The items forming these two factors might be the basis for a brief measure for clinicians and aged-care providers to screen for risk of abuse. Dependence does not represent abuse in any direct sense. Rather, it seems to measure a lack of autonomy. This factor was weakly negatively related to social variables such as satisfaction with social support and satisfaction with help and positively associated with lack of social support at meals times (eating alone) and needing help with daily tasks. Dependence relates most clearly to the neglect dimension of elder abuse, which has not been adequately measured previously. It appears to be less useful as a screening measure for abuse. Dejection seems to represent depression or social isolation, which may be associated with higher risk of abuse (NCEA, 1998). It was significantly related to all hypothesized variables and was not related to those variables hypothesized to be unrelated. The high correlations with mental health and stress suggest that it may be more a measure of depression. Alternatively, it may be an outcome of elder abuse because severe mental or physical impairment among older people has been associated with elder abuse in clinical studies (NCEA, 1998). There are many implications of our findings for health service policy and service delivery. First, Australian women in their early 70s report experiencing a range of indicators of abuse (e.g., physical: 2% to 3%; psychological: 3% to 8%). This rate is likely to increase as they age over the next 10 years (NCEA, 1998), suggesting the need to plan for this substantial public health issue. Second, we identify a number of sociodemographic correlates of risk of abuse among older Australian women that have the potential to enhance detection and facilitate more targeted intervention. Our findings suggest higher vulnerability among women from non-english-speaking backgrounds, women who were separated or in de facto relationships, and women who have ever been in a violent relationship.

14 Schofield et al. / Abuse Among Older Women 37 Third, we found that women making more visits to medical specialists had higher vulnerability scores. Such findings highlight the importance of improving the training of health and welfare providers to adequately prepare them for their role in screening and intervention with women at risk of elder abuse. Finally, our finding that women who provide care for others are at higher risk of experiencing physical abuse highlights the need for policies and programs to support carers, such as provision of counseling, home care support, and respite care. In summary, the original three factors of the H-S/EAST were not supported by this study, but four plausible factors were identified. Responses to the six items that comprise the factors Vulnerability and Coercion could provide a simple screening tool for elder abuse. Improving the detection of elder abuse by service providers is an important step toward developing and implementing interventions to improve the quality of life of older people in the community. References Bloom, J. B., Ansell, P., & Bloom, M. N. (1989). Detecting elder abuse: A guide for physicians. Geriatrics, 44, Bravo, G., Girouard, D., Gosselin, S., Archambault, C., & Dubois, M. (1995). Further validation of the QUALCARE scale. Journal of Elder Abuse & Neglect, 7(4), Brown, W., Bryson, L., Byles, J., Dobson, A., Lee, C., Mishra, G., et al. (1998). Women s health Australia: Recruitment for a national longitudinal cohort study. Women & Health, 28, Brown, W., Bryson, L., Byles, J., Dobson, A., Manderson, L., Schofield, M., et al. (1996). Establishment of the Australian Longitudinal Study on Women s Health. Journal of Women s Health, 5, Dunn, P. F. (1995). Elder abuse as an innovation to Australia: A critical overview. Journal of Elder Abuse & Neglect, 6(3/4), Hair, J. F., Jr., Anderson R. E., Tatham R. L., & Black, W. C. (1997). Multivariate data analysis with readings (4th ed.). Englewood Cliffs, NJ: Prentice Hall International Editions. Hamberger, L. K., & Ambuel, B. (1997). Training psychology students and professionals to recognise and intervene into partner violence: Borrowing a page from medicine. Psychotherapy, 34, Hwalek, M., & Sengstock, M. (1986). Assessing the probability of abuse of the elderly: Toward development of a clinical screening instrument. Journal of Applied Gerontology, 5, Koenig, H. G., Weslund, R. E., George, L. K., Hughes, D. C., Blazer, D. G., & Hybels, C. (1993). Abbreviating the Duke Social Support Index for use in chronically ill elderly individuals. Psychosomatics, 34, Kurrle, S. E., Sadler, P. M., Lockwood, K., & Cameron, I. D. (1997). Elder abuse: Prevalence, intervention and outcomes in patients referred to four aged care assessment teams. Medical Journal of Australia, 166, McFarlane, J., Parker, B., Soeken, K., & Bullock, L. (1992). Assessing for abuse during pregnancy. Journal of the American Medical Association, 267(23),

15 38 Journal of Applied Gerontology Mishra, G., & Schofield, M. (1998). Norms for the physical and mental component summary scores of the SF-36 for young, middle and older Australian women. Quality of Life Research, 7(3), National Center on Elder Abuse at the American Public Human Services Association. (1998). The national elder abuse incidence study: Final report. Retrieved from dhhs.gov/abuse/report/default.htm Neale, A. V., Hwalek, M. A., Scott, R. O., Sengstock, M. C., & Stahl, C. (1991). Validation of the Hwalek-Sengstock Elder Abuse Screening Test. Journal of Applied Gerontology, 10(4), Neter, J., Kutner, M. H., Nachtsheim, C. J., & Wasserman, W. (1996). Applied Linear Statistical Model (4th ed.). Chicago: Irwin. Podnieks, E. (1992). National survey on abuse of the elderly in Canada. Journal of Elder Abuse & Neglect, 4, Reis, M., & Nahmiash, D. (1995). Validation of the caregiver abuse screen (CASE). Canadian Journal on Aging, 14, Reis, M., & Nahmiash, D. (1998). Validation of the indicators of abuse (IOA) screen. The Gerontologist, 38, Roberts, G., Lawrence, J., O Toole, B., & Raphael, B. (1997). Domestic violence in the emergency department: 2. Detection by doctors and nurses. General Hospital Psychiatry, 19, Rosenbaum, A. (1988). Methodological issues in marital violence research. Journal of Family Violence, 3, Sadler, P. M., & Kurrle, S. E. (1993). Australian service providers responses to elder abuse. Journal of Elder Abuse & Neglect, 5(1), SAS Institute Inc. (1989). SAS/STAT user s guide (Version 6, 4th ed., Vol. 2). Cary, NC: Author. Straus, M. A. (1979). Measuring intrafamily conflict and violence: The Conflict Tactics (CT) Scales. Journal of Marriage and the Family, 41, Streiner, D. L., & Norman, G. R. (1995). Health measurement scales: A practical guide to their development and use (2nd ed.). Oxford, UK: Oxford University Press. Ware, J. E., Kosinski, M., & Keller, S. D. (1994). SF-36 Physical and Mental Health Summary Scales: A user s manual. Boston: New England Medical Center, The Health Institute. Waters, A-M. (1993). Assessment of self-reported height and weight and their use in the determination of body mass index. Canberra: Australian Institute of Health & Welfare. Article accepted January 4, Margot J. Schofield, M.Clin.Psych., Ph.D., is an associate professor in counseling in the School of Health at the University of New England in Armidale, Australia. She is a principal investigator on the Australian Longitudinal Study on Women s Health and has published on its methodology and recruitment methods, validity and Australian norms for the SF-36, and smoking and miscarriage. A recent title is Sexually Transmitted Infections and Use of Sexual Health Services Among Young Australian Women, published in the International Journal of STDs and AIDS in Rhonda Reynolds, Ph.D., is an associate investigator on the Australian Longitudinal Study on Women s Health and is associated with the Research Centre for Gender and

16 Schofield et al. / Abuse Among Older Women 39 Health at the University of Newcastle in New South Wales, Australia. A recent publication is Food Habits of Young and Middle-Aged Women Living Outside the Capital Cities of Australia (with A. Dobson, G. Mishra, W. Brown, and R. Reynolds) in Australian and New Zealand Journal of Public Health, 21(7). Gita D. Mishra, Ph.D., is a senior biostatistician at MRC Human Nutrition Research at the University of Cambridge, United Kingdom. She is an investigator on Australian Longitudinal Study on Women s Health and has published in the areas of epidemiology, public health, and statistical methodology. A recent title is Cigarette Smoking, Menstrual Symptoms and Miscarriage Among Young Women, published in the Australian and New Zealand Journal of Public Health in Jennifer R. Powers, MMedStats, is a statistician with the Australian Longitudinal Study on Women s Health and has published in the areas of epidemiology and public health, with particular emphasis on aboriginal health and women s health. Recent articles were on women drivers behavior in Accident Analysis and Prevention (1999) and the National Death Index in the Australian and New Zealand Journal of Public Health (2000). Annette J. Dobson, Ph.D., is a professor of biostatistics at the University of Queensland and Emeritus professor at the University of Newcastle. She is the director of the Australian Longitudinal Study on Women s Health (ALSWH) and has published widely in the areas of epidemiology, public health, and methodology, including generalized linear statistical models. Recent publications include descriptions of the methodology for ALSWH in the Australian and New Zealand Journal of Public Health (2000) and the Journal of Women s Health and Gender-based Medicine (1999).